the effect of corporate governance on the …

THE EFFECT OF CORPORATE GOVERNANCE ON THE

ORGANIZATIONAL PERFORMANCE OF DAIRY

CO-OPERATIVES IN KENYA

BY

JOSHUA WATHANGA

UNITED STATES INTERNATIONAL UNIVERSITY – AFRICA

FALL 2016

ii

THE EFFECT OF CORPORATE GOVERNANCE ON THE

ORGANIZATIONAL PERFORMANCE OF DAIRY

CO-OPERATIVES IN KENYA

BY

JOSHUA WATHANGA

A Dissertation Report Submitted to the Chandaria School of

Business in Partial Fulfillment of the Requirements for the

Degree of Doctorate in Business Administration (DBA)

UNITED STATES INTERNATIONAL UNIVERSITY – AFRICA

FALL 2016

iii

STUDENT’S DECLARATION

I, the undersigned, declare that this is my original work and has not been submitted to any

other college, institution or university other than the United States International

University - Africa in Nairobi for academic credit.

Signed: ________________________ Date: _________________________

Joshua Wathanga (ID 640168)

This dissertation has been presented for examination with our approval as the appointed

supervisors.

Signed: ________________________ Date: _________________________

Prof. George O. K’Aol

Signed: _______________________ Date: _________________________

Dr Joseph Ngugi Kamau

Signed: _______________________ Date: _________________________

Dean, Chandaria School of Business

Signed: _______________________ Date: _________________________

Deputy Vice Chancellor Academic and Students Affairs

iv

COPYRIGHT

All rights reserved. No part of this dissertation report may be photocopied, recorded or

otherwise reproduced, stored in retrieval system or transmitted in any electronic or

mechanical means without prior permission of USIU-A or the author.

Joshua Wathanga © 2016

v

ABSTRACT

The purpose of this study was to investigate the effect of corporate governance on the

organizational performance of dairy co-operatives in Kenya. The study assessed five

research questions: How does comprehensive strategic decision-making affect the

organizational performance of dairy co-operatives in Kenya? How does participative

governance affect the organizational performance? How does human capital affect the

organizational performance? How does long-term orientation affect the organizational

performance? To what extent does market orientation moderate the effect of corporate

governance on the organizational performance of dairy co-operatives in Kenya?

The study was guided by positivist research philosophy and descriptive correlational

research design. The population of the study consisted of 198 executive

directors/managers of active dairy co-operatives in eight counties in the Mt. Kenya

region. A sample size of 184 was drawn using stratified random sampling, and data was

collected using self-administered questionnaires. The data was then analyzed using

descriptive statistics of frequency, distribution, mean, and standard deviation.

Additionally, inferential data analysis methods of Pearson’s correlation, ANOVA, and

multiple linear regression were used to test the hypotheses. Data was presented in tables

and figures.

Regarding the effect of comprehensive strategic decision making on organizational

performance, the results of the multiple regression analysis showed that revenue per

customer explained 49.7% of the variance, (R2=.497, F(9,121)= 73.938, p <.05, while

ROA explained 29.4%, and product innovation explained 41.2%. It was found that

comprehensive strategic decision-making was not significant in predicting revenue per

customer, ROA, or product innovation and the null hypothesis was accepted. In relation

to the effect of participative governance on organizational performance, the results of the

regression indicated that revenue per customer explained 50% of the variance, (R2 = .50,

F(5, 125) = 20.10, p < .05), while ROA explained 26.9%, and product innovation

explained 41.2%. It was found that participative governance was not significant in

predicting revenue per customer, ROA, or product innovation and the null hypothesis was

accepted. Human capital was found not significant in predicting revenue per customer

vi

and ROA but significantly predicted product innovation, = .94, t(141) = 2.01, p <.05.

Product innovation also explained 41.2% of the variance, (R2 = 0.412, F(9, 120) = 9.35, p

< .05. This result led to accepting the hypothesis that human capital significantly affected

organizational performance.

The results of the regression indicated that long-term orientation significantly predicted

revenue per customer, = 1.04, t(141) = 3.35, p <.05 and product innovation, = 1.56,

t(141) = 1.43, p < .05. It was also found that revenue per customer explained 49.7% of the

variance, (R2 = .497, F(5, 125) = 20.10, p < .05, while ROA explained 29.4 %, (R

2 =

.294, F(5, 123) = 9.06, p < .05. Product innovation explained 41.2% of the variance, (R2 =

0.412, F(9, 120) = 9.35, p < .05. In relation to the moderating variable, the regression

results revealed that market orientation significantly predicted revenue per customer, =

-2.85, t(141) = -2.24, p < .05; ROA, = 2.14, t(141) = 5.9, p < .05; and product

innovation, =1.89, t(141) = 5.77, p < .05. It was also found that revenue per customer

explained 49.7% of the variance, (R2 = .497, F(5, 125) = 20.10, p < .05, while ROA

explained 29.4 %, and product innovation explained 41.2%. However, the results showed

that market orientation did not significantly moderate the relationship between corporate

governance and organizational performance.

This study concluded that keeping the respective roles of governance and management in

the co-operatives distinct allowed the board to prioritize organizational ends and leaving

the implementation to the management. This study recommends that a governance code

should be developed for co-operatives based on the stewardship theory as it is better

aligned to co-operative principles, which are predicated on democracy and inclusive

participation. This study further recommends the inclusion of board members other than

the CEO, as respondents for future research into the corporate governance of dairy co-

operatives.

vii

ACKNOWLEDGEMENTS

My heartfelt gratitude and appreciation goes to the following individuals who encouraged

and supported me on this tough journey to completing this research. First, I wish to thank

Prof. George K’Aol, who would have had many reasons for giving up on me, but did not;

rather, he continuously challenged me to improve my research abilities. I owe him deep

gratitude. Whenever I was on the verge of giving up, I sought solace with my second

supervisor, Dr Joseph Ngugi, who was often more confident than I, that I would see the

successful end to this journey. I would not have completed this journey, and in one piece,

without his patient encouragement.

Prof. George Achoki and Prof. Amos Njuguna, Dean and Associate Dean of Chandaria

Business School, respectfully, were a great source of encouragement right from the start

of the course. They cast the vision for us and kept alerting us to the roadblocks ahead,

steering us safely to our destination; I am greatly indebted to them. Along with them, I

wish to also thank the excellent faculty and support staff of the Chandaria Business

School, for making my time at the USIU-A such a wonderful experience for me; I learned

much from each of you. I would wish to also thank my classmates in DBA2, and

especially those in Group 4. We had memorable times in those brainstorming and review

meetings. I not only learned a lot from you, but also had lots of fun.

I also wish to acknowledge, with deep gratitude, the support of Joseph Muriithi Ndegwa,

Senior Training and Development Consultant, Future Focus Development, for managing

the collection of data for this research. Mr. Ndegwa took this research project as his own

and went beyond the call of duty to offer an excellent service. Through him, I also

appreciate all the leaders of the nearly two hundred co-operatives who were respondents

in this study.

I thank God for giving me the opportunity to know and work with all these wonderful

people, and for enabling me to complete this research. To Him be the Glory.

viii

DEDICATION

I dedicate this dissertation to all those who suffered and labored with me without having

to step into class, especially my wife, Gladys Muya Wathanga. My sons, Wathanga Muya

and Wahome Muya, put up with a dad who was always studying into his old age, and I

thank them for their love and moral support during this period. I also dedicate this work

to my mother, and to my siblings and relatives, for their part in encouraging me and

putting up with my absences. Finally, this study is dedicated to the co-operative sector in

Kenya; if I will have made even a small contribution to their performance as a result of

this study, then my labors will not have been in vain.

ix

TABLE OF CONTENTS

STUDENT’S DECLARATION ..............................................................................................iii

COPYRIGHT ...........................................................................................................................iii

ABSTRACT ............................................................................................................................... v

TABLE OF CONTENTS ........................................................................................................ ix

LIST OF TABLES ................................................................................................................... xi

LIST OF FIGURES ............................................................................................................... xvi

ABBREVIATIONS/ACRONYMS ...................................................................................... xvii

CHAPTER ONE ....................................................................................................................... 1

1.0. INTRODUCTION......................................................................................................... 1

1.1. Background of the Study ................................................................................................ 1

1.2. Statement of the Problem ................................................................................................ 8

1.3. Purpose of the Study ..................................................................................................... 10

1.4. Research Questions ....................................................................................................... 10

1.5. Research Hypotheses .................................................................................................... 10

1.6. Significance of the Study .............................................................................................. 11

1.7. Scope of the Study ........................................................................................................ 12

1.8. Definition of Terms....................................................................................................... 12

1.9. Chapter Summary ......................................................................................................... 14

CHAPTER TWO .................................................................................................................... 15

2.0. LITERATURE REVIEW .......................................................................................... 15

2.1. Introduction ................................................................................................................... 15

2.2. Theoretical Review ....................................................................................................... 15

2.3. Conceptual Framework ................................................................................................. 21

2.4. Empirical Review of Literature .................................................................................... 36

2.5. Chapter Summary ....................................................................................................... 113

CHAPTER THREE .............................................................................................................. 114

3.0. RESEARCH METHODOLOGY ............................................................................ 114

3.1. Introduction ................................................................................................................. 114

3.2. Research Philosophy ................................................................................................... 114

3.3. Research Design.......................................................................................................... 116

3.4. Target Population ........................................................................................................ 117

3.5. Sampling Design ......................................................................................................... 118

x

3.6. Data Collection Methods ............................................................................................ 122

3.7. Research Procedure ..................................................................................................... 123

3.8. Data Analysis Methods ............................................................................................... 128

3.9. Chapter Summary ....................................................................................................... 134

CHAPTER FOUR ................................................................................................................. 135

4.0 RESULTS AND FINDINGS .................................................................................... 135

4.1 Introduction ................................................................................................................. 135

4.2. Demographic Information ........................................................................................... 135

4.3 Comprehensive Strategic Decision-Making and Organizational Performance .......... 141

4.4 Participative Governance on Organizational Performance ......................................... 157

4.5 Human Capital and Organizational Performance ....................................................... 173

4.6 Long-Term Orientation on Organizational Performance ............................................ 189

4.7 Market Orientation and Organizational Performance ................................................. 205

4.8 Chapter Summary ....................................................................................................... 222

CHAPTER FIVE .................................................................................................................. 226

5.0 SUMMARY, DISCUSSION, CONCLUSION AND RECOMMENDATIONS .. 226

5.1 Introduction ................................................................................................................. 226

5.2 Summary ..................................................................................................................... 226

5.3 Discussion ................................................................................................................... 229

5.4 Conclusion .................................................................................................................. 240

5.5 Recommendations ....................................................................................................... 242

REFERENCES ...................................................................................................................... 245

APPENDIX A: Letter of Introduction to the Respondents ............................................ 320

APPENDIX B: The Survey Questionnaire ......................................................................... 321

APPENDIX C: List of Dairy Co-operatives in the Mt Kenya Region ............................. 335

APPENDIX D: University’s Permission to Conduct Research ........................................ 340

APPENDIX E: Research Clearance Permit ....................................................................... 341

APPENDIX E: Research Authorization ............................................................................. 342

xi

LIST OF TABLES

Table 2.1: Operationalization of Variables and Hypothesis Testing ........................................ 36

Table 3.1: Dairy Co-operatives in Mt Kenya region of Kenya ............................................... 118

Table 3.2: Distribution of the Sample Size ............................................................................. 122

Table 3.3: Results of Cronbach’s Alpha Measurements for the Pilot Study .......................... 125

Table 4.1: Year of Registration ............................................................................................... 136

Table 4.2: Position Held ......................................................................................................... 136

Table 4.3: Professional Qualification ..................................................................................... 139

Table 4.4: Distribution of Daily Milk Production .................................................................. 141

Table 4.5: Frequency and Percentage Distribution for Strategic Decision-Making ............... 142

Table 4.6: Frequency and Percentage Distribution of the Effect of Strategic Decision-

Making on Revenue per customer .......................................................................................... 142

Table 4.7: Frequency and Percentage Distribution of the Effect of Comprehensive

Strategic Decision-Making on ROA ....................................................................................... 143

Table 4.8: Frequency and Percentage Distribution of the Effect of Strategic Decision-

Making on Product Innovation ............................................................................................... 144

Table 4.9: Descriptive Statistics for Comprehensive Strategic Decision-Making ................. 145

Table 4.10: KMO and Bartlett's Test for Comprehensive Strategic Decision-Making .......... 146

Table 4.11: Total Variance Explained for Comprehensive Strategic Decision-Making ........ 146

Table 4.12: Component Matrix for Comprehensive Strategic Decision-Making ................... 147

Table 4.13: Correlation between Comprehensive Strategic Decision-Making and

Organizational Performance ................................................................................................... 148

Table 4.14: Correlation between Strategic Decision-Making and Organizational

Performance ............................................................................................................................ 149

Table 4.15: One Way ANOVA for Strategic Decision-Making and Gender ......................... 149

Table 4.16: One Way ANOVA for Strategic Decision-Making Index and Level of

Education ................................................................................................................................ 149

Table 4.17: Bonferroni Test for Strategic Decision-Making Index and Level of Education . 150

Table 4.18: Test of Linearity for Comprehensive Strategic Decision-Making and

Organizational Performance ................................................................................................... 151

Table 4.19: Multicollinearity test for Comprehensive Strategic Decision-Making ................ 152

Table 4.20: Normality test for Comprehensive Strategic Decision-Making .......................... 152

Table 4.21a: Model Summary ................................................................................................. 153

xii

Table 4.21b: ANOVA ............................................................................................................. 153

Table 4.21c: Coefficients ........................................................................................................ 154


Table 4.22b: ANOVA ............................................................................................................. 155



Table 4.23b: ANOVA ............................................................................................................. 156


Table 4.24: Frequency and Percentage Distribution for Participative Governance ................ 157

Table 4.25: Frequency and Percentage Distribution of the Effect of Participative

Governance on Revenue per Customer................................................................................... 158

Table 4.26: Frequency and Percentage Distribution of Effect of Participative Governance

on ROA ................................................................................................................................... 159


Governance on Product Innovation ........................................................................................ 160

Table 4.28: Descriptive Statistics for Participative Governance ............................................ 161

Table 4.29: KMO and Bartlett's Test for Participative Governance ....................................... 162

Table 4.30: Total Variance Explained for Participative Governance ..................................... 162

Table 4.31: Component Matrix for Participative Governance ................................................ 163

Table 4.32: Correlation between Participative Governance and Organizational

Performance ............................................................................................................................ 164


Performance ............................................................................................................................ 165

Table 4.34: One Way ANOVA for Participative Governance and Gender ............................ 165

Table 4.35: One Way ANOVA for Participative Governance and Education ....................... 165

Table 4.36: Bonferroni Test for Participative Governance and Education ............................. 166

Table 4.37: Test of Linearity for Participative Governance and Organizational

Performance ............................................................................................................................ 167

Table 4.38: Multicollinearity test for Participative Governance ............................................ 167

Table 4.39: Normality test for Participative Governance ....................................................... 168


Table 4.40b: ANOVA ............................................................................................................. 169



xiii

Table 4.41 b: ANOVA ............................................................................................................ 170



Table 4.42b: ANOVA ............................................................................................................. 172


Table 4.43: Frequency and Percentage Distribution for Human Capital ................................ 173

Table 4.44: Frequency and Percentage Distribution of the Effect of Human Capital on

Revenue per Customer ............................................................................................................ 174

Table 4.45: Effect of Human Capital on ROA ....................................................................... 175

Table 4.46: Effect of Human Capital on Product Innovation ................................................. 176

Table 4.47: Descriptive Statistics for Human Capital ............................................................ 177

Table 4.48: KMO and Bartlett's Test for Human Capital ....................................................... 178

Table 4.49: Total Variance Explained for Human Capital ..................................................... 178

Table 4.50: Component Matrix for Human Capital ................................................................ 180

Table 4.51: Correlation between Human Capital and Organizational Performance .............. 180

Table 4.52: Correlation between Human Capital and Organizational Performance .............. 181

Table 4.53: One Way ANOVA for Human Capital and Gender ............................................ 181

Table 4.54: One Way ANOVA for Human Capital and Education ........................................ 181

Table 4.55: Bonferroni Test for Human Capital and Education ............................................. 182

Table 4.56: Test of Linearity for Human Capital and Organizational Performance .............. 183

Table 4.57: Multicollinearity Test for Human Capital ........................................................... 183

Table 4.58: Normality test for Human Capital ....................................................................... 184


Table 4.59b: ANOVA ............................................................................................................. 185



Table 4.60b: ANOVA ............................................................................................................. 186



Table 4.61b: ANOVA ............................................................................................................. 188


Table 4.62: Frequency and Percentage Distribution for Long-term Orientation .................... 189

Table 4.63: Frequency and Percentage Distribution of the Effect of Long-Term

Orientation on Revenue per Customer .................................................................................... 190

xiv


Orientation on ROA ................................................................................................................ 191


Orientation on Product Innovation.......................................................................................... 192

Table 4.66: Descriptive Statistics for Long-Term Orientation ............................................... 193

Table 4.67: KMO and Bartlett's Test for Long-Term Orientation .......................................... 194

Table 4.68: Total Variance Explained for Long-Term Orientation ........................................ 194

Table 4.69: Component Matrix for Long-Term Orientation .................................................. 195

Table 4.70: Correlation between Long-Term Orientation and Organizational Performance . 196

Table 4.71: Correlation between Long-Term Orientation and Organizational Performance . 197

Table 4.72: One Way ANOVA for Long-Term Orientation and Gender ............................... 197

Table 4.73: One Way ANOVA for Long-Term Orientation and Education .......................... 197

Table 4.74: Bonferroni Test for Long-Term Orientation and Education ................................ 198

Table 4.75: Test of Linearity for Long-Term Orientation and Organizational Performance . 199

Table 4.76: Multicollinearity test for Long-Term Orientation ............................................... 199

Table 4.77: Normality test for Long-Term Orientation .......................................................... 200


Table 4.78b: ANOVA ............................................................................................................. 201



Table 4.79b: ANOVA ............................................................................................................. 202



Table 4.80b: ANOVA ............................................................................................................. 204


Table 4.81: Frequency and Percentage Distribution for Assessment of Market Orientation . 205

Table 4.82: Frequency and Percentage Distribution for the Effect of Market Orientation

on Revenue per Customer ....................................................................................................... 206


on ROA ................................................................................................................................... 207


on Product Innovation ............................................................................................................. 208

Table 4.85: Descriptive Statistics for Market Orientation ...................................................... 210

xv

Table 4.86: KMO and Bartlett's Test for Market Orientation ................................................. 210

Table 4.87: Total Variance Explained for Market Orientation ............................................... 210

Table 4.88: Component Matrix for Market Orientation ......................................................... 211

Table 4.89: Correlation between Market Orientation and Organizational Performance ........ 212

Table 4.90: Correlation between Market Orientation and Organizational Performance ........ 213

Table 4.91: One Way ANOVA for Market Orientation and Gender ...................................... 213

Table 4.92: One Way ANOVA for Market Orientation and Education ................................. 213

Table 4.93: Bonferroni Test for Market Orientation and Education ...................................... 214

Table 4.94: Test of Linearity for Market Orientation and Organizational Performance ........ 215

Table 4.95: Multicollinearity test for Market Orientation ...................................................... 216

Table 4.96: Normality test for Market Orientation ................................................................. 216


Table 4.97b: ANOVA ............................................................................................................. 217



Table 4.98b: ANOVA ............................................................................................................. 219


Table 4.199a: Model Summary............................................................................................... 221

Table 4.99b: ANOVA ............................................................................................................. 221


xvi

LIST OF FIGURES

Figure 2.1: Stewardship Theory Determinants. ........................................................................ 16

Figure 2.2: Conceptual Framework of Effect of Co-operative Governance on the

Organizational performance of Dairy Co-operatives. ............................................................... 22

Figure 4.1: Gender of the Respondents................................................................................... 137

Figure 4.2: Age of the Respondents ........................................................................................ 138

Figure 4.3: Highest Level of Education .................................................................................. 138

Figure 4.4: Work Experience .................................................................................................. 140

Figure 4.5: Scree Plot for Comprehensive Strategic Decision-Making .................................. 147

Figure 4.6: Scree Plot for Participative Governance .............................................................. 163

Figure 4.7: Scree Plot for Human Capital ............................................................................... 179

Figure 4.8: Scree Plot for Long-Term Orientation ................................................................. 195

Figure 4.9: Scree Plot for Market Orientation ........................................................................ 211

xvii

ABBREVIATIONS/ACRONYMS

BSC Balanced Scorecard

CAK Co-operative Alliance of Kenya

CEO Chief Executive Officer

CSFI Center for the Study of Financial Innovation

EACB European Association of Co-operative Banks

ECCOS Ethics Commission for Co-operative Societies

EURICSE European Research Institute on Co-operative and Social Enterprises

GCC Gulf Cooperation Council

GOK Government of Kenya

ILO International Labor Organization

IPGA International Policy Governance Association

KCC Kenya Co-operative Creameries

MFI Micro Finance Institutions

MNCs Multi-national Corporations

OCAI Organizational Culture Assessment Instrument

OLS Ordinary Least Squares

ROA Return on Assets

ROCE Return on Capital Employed

ROE Return on Equity

SACCO Savings and Credit Co-operative Organization

SOX Sarbanes–Oxley Act

SPSS Statistical Package for Social Sciences

S&P Standard & Poor’s

UAE United Arab Emirates

UNCTAD United Nations Conference on Trade and Development

UNDESA United Nations Department of Economic and Social Affairs

1

CHAPTER ONE

1.0. INTRODUCTION

1.1. Background of the Study

The origins of corporate governance movement started in earnest in North America

(Cheffins, 2011; Wells, 2010). The preoccupation of corporate governance in the USA

had to do with making sure directors were independent from management domination,

ensuring that audit committees are in place to monitor, and raising the standards of

corporate behavior in relation to the investors and the public (Mees, 2015). European, and

particularly British, corporations were, at first, influenced by the American economic

theorists and their considerations of agency theory and control (Fama & Jensen, 1983;

Jensen & Meckling, 1976). However, the deregulatory and hard-nosed business climate of

the 1980s along with many ethical and corporate failures such as the Bank of Credit and

Commerce collapse and the Robert Maxwell/Mirror Group fraud produced perhaps the

greatest reform in British corporate governance (Mees, 2015).

The evolution of corporate governance coincided with the retreat of government in

modern times while at the same time borrowing from the latter the framework of checks

and balances on the one hand, and democracy on the other. The agency theory and the

principal-agent model introduced by Jensen and Meckling (1976) is an important

cornerstone of corporate governance research. The expression ‘corporate governance'

only entered the normal parlance as late as 1970s and is now associated with balance of

power, organizational structure and decision-making processes within the corporation

(Pargendler, 2015). Dubbed the origin of the ‘code of conduct movement’, the Cadbury

Report moved from the agency theory in their bid to restore confidence in British capital

markets (Cadbury, 1992). The Cadbury Report and the development of the governance

code set in train a number of similar bodies, first in South Africa (with the King Report),

then in Canada, France, Japan, The Netherlands, India and Germany and even influenced

the USA Business Roundtable (Spira & Slinn, 2013).

Corporate governance, at its broadest, covers all rules and constraints on corporate

decision-making, the need to constrain managers to act in the shareholders’ best interests

(Novkovic, 2013, Aggarwal, 2013). At its most basic level, corporate governance is a

2

response to the agency problems created by the separation of ownership and control. It is

the balance of power between what officers and directors do, on the one hand, and what

shareholders desire, on the other (Wells, 2010). It refers to the oversight exercised over

the delegated tasks of running the venture, how the owners’ interests are protected, setting

direction for the enterprise and ensuring accountability and the exercise of legitimate

power over the corporation (Cornforth, 2011; Tricker, 2012a).

The 2007 global financial crisis and the corporate scandals a few years earlier, which

nearly brought the international financial systems to a halt, has catapulted corporate

governance to the fore (Erkens, Hung, & Matos, 2011; Essen, Engelen, & Carney, 2013).

The financial crisis was attributed to various aspects of failure, of which corporate

governance was major (Sun, Stewart, & Pollard, 2012; UNCTAD, 2010). In explaining

the crisis, literature highlights that the way risk was created, engaged and managed,

widening gaps in remunerations, transparency or information use and misuse, disclosure

norms, and internal controls were all found wanting (Abid & Ahmed, 2014; Clarke,

2015). In addition, the pressures within international financial markets further distanced

the most common forms of capitalism from the concerns of the community and the

welfare and participation of employees in decision-making (Cheney, Cruz, Peredo, &

Nazareno, 2014).

These crises have brought corporate governance into sharper focus with a renewed call

for strengthening board oversight of management, positioning risk management as a key

board responsibility, and encouraging remuneration practices that balance risk and long-

term performance criteria (Bekiaris, Efthymiou, & Koutoupis, 2013; Berger,

Imbierowicz, & Rauch, 2014). In addition, there has been a call for stronger shareholder

and stakeholder rights in order to hold boards to account, strengthening internal audit, and

an emphasis on sustainability and long-term strategic considerations (CSFI, 2015; Kumar

& Singh, 2013). The impact of corporate governance on organizational performance has

been seen to affect all industries (Abid & Ahmed, 2014; Mori, Golesorkhi, Randoy, &

Hermes, 2015) and in every part of the world (Al-Tamini, 2012; Nyamongo & Temesgen,

2013).

3

Although corporate governance has been associated with better organizational

performance, exactly how it affects performance and how to measure it has not been as

easy (Wessels, Wansbeek, & Dam, 2015). According to Hassan and Halbouni (2013), the

importance of governance is diminished in the eyes of managers and shareholders if the

level of corporate governance does not affect organizational performance. Katchova and

Enlow (2013) arrived at a similar conclusion. They opined that investor and manager

perceptions of firm performance are highly related to financial success. The enquiry into

the impact of boards of directors on the performance of organizations has been studied for

more than 50 years and primarily applying the agency theory (Charas, 2015; Minichilli,

Zattoni, Nielsen, & Huse, 2012). Due to the primary use of the agency theory, the most

favored pathways to explain the impact of boards on organizational performance are those

that mitigate conflicts between agents and principals (Clarke, 2015; Donaldson, 2012;

Tricker, 2012a).

One of the significant studies to demonstrate the effect of corporate governance on

organizational performance is that of the Association of British Insurers (ABI) in 2008,

which showed a robust causal relationship between good corporate governance, superior

company performance and value creation (Selvaggi & Upton, 2008). In that study, using a

dataset comprising 654 companies, the authors demonstrated that, over a five year period,

the shares of the well governed companies delivered an extra return of 37 basis points a

month and outperformed the poorly governed firms by 4 basis points, after allowing for

risk. A similar huge study comprising data from 100 Fortune 500 companies, with 800

observations for each of the 11 variables over a eight-year period between 2005-2012,

found a strong positive relationship between corporate governance and firm performance

(Malik & Makhdoom, 2016). In the study, Malik and Makhdoom found that smaller

board sizes and board independence generated better firm performance while the

frequency of meetings and CEO compensation were found to have an inverse relationship

with firm performance.

Similarly, a study using panel data of 50 top companies of the New Zealand Securities

Commission over the period, 1999-2007, found that establishing audit and remuneration

committees, and having majority independent non-executive directors all had a positive

influence on firm performance (Reddy, Locke, & Scrimgeour, 2010). In a broad based US

4

research to study the effect on organizational performance of top rated governed firms,

Shank, Hill, and Stang (2013) incorporated 61 factors in corporate governance (17 Board,

4 Audit, 11 Charter/bylaws, 8 State of Incorporation, 10 Executive and Director

Remuneration, 6 Qualitative Factors, 4 Ownership, 1 Director Education). The findings

showed evidence of better risk-adjusted stock perfomance over a 10 year period. In

another US study, Berger, et al. (2014) analyzed a sample of 341 US commercial banks

during the financial crisis 2007-2010 and found that the ownership structure of a bank is

an important predictor of default probability. Interestingly, the study also found out that

the shareholdings of outside directors and that of the chief officers had no direct impact

on a bank’s default probability.

In a study of Indian listed firms, Roy (2016) used panel data of 58 top Indian listed

companies in terms of market capitalization over a five-year period using 25 structural

indicators of corporate governance. The study concluded that five factors were positively

correlated to firm performance. Cheema and Din (2013) used panel data of 15 cement

companies in Pakistan and showed a positive relationship between corporate governance

and firms’ performance as measured by return on assets, return on equity, earnings per

share, debt to equity ratio, and current ratio. In another study, Al-Haddad, Alzurqan, and

Al-Sufy (2011) researched 96 industrial firms listed on the Amman Stock Exchange and

found that there was a direct positive relationship between profitability and corporate

governance.

Some studies are inconclusive and do not demonstrate positive relationship between

corporate governance variables and firm performance. For example, in a study of 86 non-

financial firms in the Egyptian Exchange, Shahwan (2014) found no positive association

between disclosure and transparency, composition of the board of directors, shareholders’

rights and investor relations, and ownership/control structure with organizational

performance. In another study in India by Arora and Sharma (2016) covering 20

industries over a decade revealed mixed findings. On the one hand, larger boards, which

are associated with greater intellectual depth improved decision-making, but there was no

positive effect on financial and profitability measures. In a research study of US

investment banks over the 2000-2012 period, Mamatzakis and Bermpei (2015) noted a

5

negative effect of board size, operational complexity, and increase in bank ownership by

the board on performance.

As a result of the financial crises that developed in the United States in 2007 and which

spread worldwide, corporate governance has been better understood and strengthened

globally. However, the aftermath of the crisis revealed structural problems and

assumptions in the global financial and market systems (Cheney et al., 2014). The

American economist and recipient of the Nobel Memorial Prize in Economic Sciences,

Joseph Stigliz, had raised these concerns at the time of the financial crisis. In his paper,

“Moving beyond Market Fundamentalism to a More Balanced Economy”, Stigliz (2009)

argued that one of the flaws of market fundamentalism was that it paid no attention to the

distribution of incomes or the notion of a good, fair and sustainable society. He called for

socially oriented enterprises that are less inclined to exploit those with whom they

interact. He further argued that it is crucial to broaden our notions of productivity beyond

formal measures such as gross domestic product and incorporate aspects of well-being

and connections to the community and the environment.

What Stigliz (2009) and other researchers were calling for was an alternate form of

market organization that is more socially oriented, less exploitative, more democratic and

prioritizes labor over capital, and co-operatives fit that bill (Alperovitz & Hanna, 2013;

Cheney et al., 2014; Flecha & Ngai, 2014). Stigliz went on to opine that from his

research, the East Asia Miracle would not have been possible without the role played by

the co-operatives in the region’s development in the nineties. Ban Ki-moon (2012), the

United Nations General Secretary, underlined this paradigmatic finding that co-operatives

are a model for inclusive growth, which is defined as growth that creates opportunity for

all segments of the society (MacPherson, 2012; OECD, 2014). According to Ban Ki-

moon, with an egalitarian ethos, participatory decision-making, common ownership, and

commitment to goals beyond the profit motive, co-operatives are a reminder to the

international community that it is possible to pursue both economic viability and social

responsibility.

Cheney et al. (2014) underlined the same point that co-operatives have an important role

in reimagining and reconfiguring the economy as a whole by bringing to the fore another

6

alternative economic and corporate governance system. Cheney gives the illustration of

Mondragon Corporation, which is an 80,000 person grouping of over 100 worker-owned

co-operatives based in the Basque region of Spain. Mondragon has revenues of 12 billion

euro, has 125 subsidiary companies, present in one form or the other in 41 countries, and

trades in more than 150 countries (Mondragon Corporation, 2016). The sustainability of

the Mondragon Corporation as a co-operative can be traced in its adaptation to changing

markets since its beginning in the 1950s when Spain was a closed economy, through the

challenges of Spain joining the European Union, to its growth to become a global

corporation today (Restakis, 2010; Cheney et al, 2014).

The new questions about the health of corporate governance were as a result of an

unexpected observation during the economic crisis. While huge financial institutions in

Europe and North America filed for bankruptcies or were on life-support from their

central banks due to their reckless lending and unethical behavior, another sector in the

economy went about its work seemingly unaffected (CETS, 2012b). Surprisingly to

analysts, policy makers and researchers, the co-operative institutions, that dominated

agriculture, housing finance, banking and life assurance markets, escaped relatively

unscathed from the financial crisis (Delbono & Reggiani, 2013; Narvaiza, Aragon-

Amonarizz, Iturrioz-Landart, Bayle-Cordier, & Stervinou, 2016). This was attributed to

the co-operative model and its unique characteristics of member ownership, long-term

and risk averse stance, high level of reserves and capitalization, and transparency

(Altman, 2015; Birchall, 2012; EACB, 2010).

The conception of governance based on control of organizations by external shareholder

interests (Berry, Broadbent, & Otley, 1995) has been challenged by a number of authors,

over the last three decades, who see the need for a refocus of the control of the board by

internal interests in order to advance social and economic democracy (Ellerman, 2009;

Ridley-Duff, 2010). The dominance of agency theory, a product of the Anglo-American

corporation, and the resultant pursuit of the shareholder value and short-term profits, has

damaged the corporation, distracted managers and, most paradoxically, neglected the

long-term interests of shareholders (Clarke, 2015; Lazonik, 2014; Stout, 2012).

Consequently, there has been a renewed interest in understanding how governance of

democratically and controlled businesses such as co-operatives differs from conventional

7

investor-owned businesses (Alperovitz, 2013; Sherwood, 2012). Evidence is growing that

the difference between co-operatives and corporations is not in performance as the former

can do everything the latter does (Thompson, 2015), but with a democratic structure, an

equitable sharing of income and a commitment to the common good of the community

and future generations (Hightower, 2012; King, Adler, & Grieves, 2013). Thus, co-

operatives and other worker-owned enterprises are being seen to be playing an important

role in reimagining and reconfiguring the economy as well as bringing to the table

alternative forms of corporate governance (Cheney et al., 2014; Paranque & Willmott,

2014).

In the African scene, a number of studies have also contributed to corporate governance

and its effect on organizational performance. Focusing on 20 out of 34 listed companies

on the Ghana Stock Exchange, a study by Darko, Aribi, and Uzonwanne (2016)

established the relationship between corporate governance (board structure, ownership

structure and corporate control) on firm performance (return on assets, return on equity,

net profit margin and Tobin’s Q). In Nigeria, a study by Alalade, Onadeko, and Okezie

(2014) using panel data of 10 companies over eight years, showed a positive relationship

between of adoption of best practices in governance with performance. Regionally, the

most advanced code of corporate governance is that of South Africa where the Institute of

Directors in Southern Africa and the King Committee on Governance has issued a series

of reports and governance principles, which have been the basis of their company laws.

For example, the South Africa Companies Act of 2008 is based on King III report

(Institute of Directors of South Africa, 2009). The King IV report has been recently

released, for public comment, to supersede the previous versions. According to the

Institute of Directors of South Africa, King IV has been made necessary due to some

developments such as focus on executive remuneration, the key role of social and ethics

committees and the continuing development of integrated reporting (Institute of Directors

of South Africa, 2016a; 2016b).

Corporate governance has received prominence in Kenya in the last 15 years mostly due

to failure or poor performance of public and private companies (Elkadah & Mboya, 2011;

Mang’unyi, 2011; Wanyama & Olweny, 2013). Kenya has suffered its fair share of bad

corporate governance incidents and this has inspired the proposed Kenya Stewardship

8

Code, which is a voluntary mechanism meant to assist the institutional investors in the

monitoring and compliance of companies in which they have stake (Gakeri, 2013;

Hussein, 2015). In a study to investigate the effect of corporate governance on the

occurrence of fraud in commercial banks in Kenya, Ogola, K’Aol and Linge (2016) found

significant correlations between the various corporate governance variables (top

leadership’s tone, prudential control systems, top leadership’s compensation structure,

and robust fraud strategy) and the frequency and amount of fraud loss. In a similar study

on the banking industry in Kenya, Manini and Abdillahi (2015) found out that audit

committee size, board gender diversity and bank capital have no significant effect on

bank profitability, and that board size negatively influences organizational performance.

For state corporations, Kenya has recently developed a code of governance by the name

‘Mwongozo’, which seeks to reform and improve performance of government bodies

(PSC & SCAC, 2015). Until recently, the management and corporate governance of

Kenya’s companies was guided by the 1948 Companies Act (Cap 486). In September

2015, the President of Kenya assented to the Companies Act 2015 to repeal the 1948 Act

(Nduati-Mutero & Nyakieka, 2015; GOK, 2015). For co-operative societies, a revised

edition in 2012 of the 2005 Co-operative Socitieties Act, Cap 490, of 2005 (Kenya Law

Reports, 2012) was gazetted.

1.2. Statement of the Problem

Agency theory, a product of the Anglo-American corporation and capital markets, has

become the cornerstone of corporate governance (Lan & Heracleous, 2010). However,

according to Clarke (2015), corporate governance is overwhelmed by the intellectual

constrictions of agency theory and pre-occupation with compliance and regulation, and is

unaware of its contribution to inequality in both corporation and wider society (Clarke,

2014; Piketty, 2014; Weinstein, 2012). Specifically, the pursuit of shareholder value has

damaged and shrunk corporations, deviated and undermined resources, and,

paradoxically, neglected the very thing agency theory set out to do: the long-term

interests of shareholders (Stout, 2012; Lazonick, 2014). Contrasted to the agency theory,

which assumes that the interests of the principal and agent in the exchange relationship

are not aligned, in stewardship theory, the interests are not only aligned, but lead to long-

term goals and investment (Hernandez, 2012).

9

Increasingly, corporate governance research in socio-enterprises such as co-operatives are

focusing on stewardship theory in appreciation of broader objectives for member-owned

enterprises beyond the profit motive (Cheney et al., 2014; L’Hullier, 2014; Liang,

Hendrikse, Huang, & Xu, 2015). A stewardship approach in corporate governance has

been shown to lead organizations to greater investment in research and development

(Hitt, Ireland, & Hoskisson, 2012), long-term orientation (Hernandez, 2012; Hiebl, 2015),

and greater trust and transparency (Choi, Choi, Jang, & Park, 2014). The importance of

co-operatives in employment creation has been underlined by the ILO (2016), which

estimated that, globally, co-operatives provide 100 million jobs, which is twenty percent

more than multinational corporations. Further, the report noted that co-operatives are the

largest employers in many countries and states such as Switzerland, Colombia, Quebec in

Canada, and Wisconsin in the USA.

In Kenya, the co-operative movement has played a big role in economic empowerment

and financial inclusion of rural communities as over forty percent of all licensed SACCOs

are farmer based and offer loans to more than ninety percent of their 1.5 million members

(Kuria, 2014). Co-operatives generate employment for over 555,000 people directly and a

total of 2 million indirectly, and savings of 250 billion Kenya shillings or thirty percent of

the national savings (Co-operative Alliance of Kenya, 2015; Gicheru, 2012). Despite this

potential, co-operatives, especially those in agricultural production and marketing are

characterized by poor performance (Wanyama, 2014); poor governance and management

(KNBS, 2016; Mumanyi, 2014; Nkuru, 2015); and extensive government and political

interference (Hannan, 2014).

While there has been a growing interest in the research of corporate governance and the

effect on the performance of co-operatives in Kenya, nearly all of them are in the

SACCOs (Mumanyi, 2014; Mwanja, Marangu, Wanjere, & Thuo, 2014; Nkuru, 2015).

Other studies of co-operatives in the agricultural sector in Kenya are not related to

corporate governance (Muriithi, Huka, & Njati, 2014; Musuya, 2014; Mwamuye, Nyamu,

& Mrope, 2012). Additionally, even in the few studies cited on corporate governance of

SACCOS, the models used are predominantly based on agency theory, focusing mainly

on profit maximization and none on other theories, such as stewardship, whose principles

are closer to co-operatives as member owned societies. Therefore, in recognition of the

10

contribution of co-operatives to the global and the Kenyan economy, their under-

performance due to poor governance, this study investigated the effect of corporate

governance on the organizational performance of dairy co-operatives in Kenya and was

based on stewardship theory.

1.3. Purpose of the Study


organizational performance of dairy co-operatives in Kenya.

1.4. Research Questions

This study was based on the following research questions:

1.4.1. How does comprehensive strategic decision-making affect the organizational

performance of dairy co-operatives in Kenya?

1.4.2. How does participative governance affect the organizational performance of dairy

co-operatives in Kenya?

1.4.3. How does human capital affect the organizational performance of dairy co-

operatives in Kenya?

1.4.4. How does long-term orientation affect the organizational performance of dairy co-

operatives in Kenya?

1.4.5. To what extent does market orientation moderate the effect of corporate

governance on the organizational performance of dairy co-operatives in Kenya?

1.5. Research Hypotheses

The following five null hypotheses were used to test the effect of corporate governance

on the performance of dairy co-operatives in Kenya.

1.5.1. H01: Comprehensive strategic decision-making does not significantly affect the


1.5.2. H02: Participative governance does not significantly affect the organizational

performance of dairy co-operatives in Kenya.

1.5.3. H03: Human capital does not significantly affect the organizational performance

of dairy co-operatives in Kenya.

1.5.4. H04: Long-term orientation does not significantly affect the organizational


11

1.5.5. H05: Market orientation has no significant moderating effect on the relationship

between corporate governance and organizational performance of dairy co-

operatives in Kenya.

1.6. Significance of the Study

This research will contribute to both theoretical knowledge as well as development

practice to the co-operatives sector, the policy makers in Kenya, and the academia.

1.6.1. Co-operative Societies

Members and leaders of co-operative societies will benefit from this study in identifying

the corporate governance factors that affect the performance of their enterprises and, by

so doing, improve their practices and the value that will accrue to their members. This

study was based on stewardship theory whose dimensions of strategic decision-making,

participative governance, human capital, and long-term orientation are better aligned to

co-operative principles and values than the traditional agency theory.

1.6.2. Policy Makers

The co-operative sector, other social enterprises and the government of Kenya will

benefit from this study as its results can help identify the areas for governance policy

development as well as regulatory legislation needed by the sector so as to improve dairy

farming for the farmers and the national economy as a whole.

1.6.3. Academia

This study contributes to research on corporate governance in co-operatives. While

previous studies have relied largely on agency theory and shareholder wealth

maximization, this study was based on stewardship theory to show its effect on the

organizational performance of dairy co-operatives. The inclusion of market orientation as

a moderating variable is of great interest to academia in establishing a better link between

corporate governance of co-operatives and other agricultural enterprises, and their

performance.

12

1.7. Scope of the Study

The study examined the effect of corporate governance on the organizational performance

of dairy co-operatives in Kenya using a positivistic epistemology and descriptive

correlational research design. The target population for this study was 198 executive

directors/managers of the dairy co-operatives from eight counties in the Mt. Kenya

region. The choice was made given that the dairy co-operatives in this region have the

most variety in organizational size. This variety in organizational size of the co-operatives

is expected to provide further insights in their corporate governance and the effect on

organizational performance. In each of the 198 co-operative societies, the executive

director/manager was targeted. Data was collected between December 2016 and January

2017.

1.8. Definition of Terms

1.8.1. Corporate Governance

Corporate governance refers to the organizational governance of a corporation (McGrath

& Whitty, 2015), or the way in which companies are directed and controlled in the

interest of shareholders and other stakeholders (Agyei-Mensah, 2016).

1.8.2. Strategic Decision-making

Comprehensive strategic decision-making is the diligent and in-depth analysis of strategic

options by organizational leadership, and aims at maximizing organizational performance

(Eddleston et al., 2010).

1.8.3. Participative Governance

Participative governance refers to organization stakeholders participating in decision-

making which engenders a sense of psychological ownership and belongingness and

which results in their productivity and higher performance (Cheney et al., 2014; Liang et

al., 2015).

1.8.4. Human Capital

Human capital is the resource that an organization has in the workforce and refers to the

education, skills, and experience of the staff and board of directors (Gottesman & Morey,

2010; Kirca, Hult, Deligonul, Perryy, & Cavusgil, 2010; N. Kim & Kim, 2015).

13

1.8.5. Long-term Orientation

A long-term orientation refers to a culture that favors patient investment in time-

consuming activities (Davis, Schoorman, & Donaldson, 1997; Miller, Breton-Miller, &

Scholnick, 2008) or a tendency to prioritize long-range implications and impact of

decisions and actions that come to fruition after an extended time period (Hoffman &

Wulf, 2016; Lumpkin, Brigham, & Moss, 2010).

1.8.6. Market Orientation

Market orientation is the organization-wide generation, dissemination, and responsiveness

to market intelligence (Jaworski & Kohli, 1993; Kohli & Jaworski, 1990).

1.8.7. Organizational Performance

Financial performance refers to the actual output or results of an organization and is

measured either in financial and non-financial terms (Franken & Cook, 2013). In this

study, a balanced scorecard is used with both financial (ROA) and non-financial measures

(such as attendance to AGMs, Growth of the co-operative, and Innovation).

1.8.8. Balance Scorecard

Balanced scorecard is a multi-dimensional set of measures comprising financial

measures, customer satisfaction, internal processes, and the organization’s internal

learning and improvement activities (Kaplan & Norton, 1992; Kim, 2015; Ondoro, 2015).

1.8.9. Board

A board is a collective of directors and represents a suitable proxy to represent owners’

interests, and through which the activities of management can be monitored and controls

exerted on behalf of these owners (Crow & Lockhart, 2016).

1.8.10. Board of Directors

Board of Directors or corporate directors represent a group of elected individuals whose

primary responsibility is to act in the owners’ interests by formally monitoring and

controlling the corporation’s top level executives (Hitt et al., 2012). Corporate directors

have three basic fiduciary duties: duty of care, a duty of good faith, and a duty of loyalty

(Al-Tawi, 2016; Sheehy & Feaver, 2014).

14

1.8.11. Corporation

A corporation is a structure established by law to allow different parties to contribute

capital, expertise, and labor for the maximum benefit of all of them (Monks & Minow,

2011).

1.8.12. Co-operative

A co-operative refers to autonomous associations of people, usually through membership,

united voluntarily to meet their common social, economic and cultural needs and

aspirations through jointly-owned and democratically-controlled enterprises (ILO, 2014).

1.8.13. Co-operative Principles

The seven co-operative principles comprise voluntary and open membership, democratic

member control, member economic participation, autonomy and independence,

education, training and information, cooperation amongst co-operatives, and concern for

community (ICA, 2016).

1.9. Chapter Summary

This chapter provided the background of the study, stated the problem to be researched,

described the research questions and hypotheses, and concluded with the significance and

the scope of the study. Chapter two reviews the critical literature on corporate governance

and the effect on organizational performance. Chapter three presents the research

methodology used the study. Chapter four presents the results and findings of the study

from the data collected and analyzed.

Chapter five presents the summary, discussions, conclusions, and recommendations of the

study.

15

CHAPTER TWO

2.0. LITERATURE REVIEW

2.1. Introduction

This chapter reviews the theory that informs the study on corporate governance and

organizational performance. A conceptual model of the key theory and how it relates to

the study is then discussed. The chapter subsequently presents a review of empirical

literature on corporate governance and how it is linked to the research questions of this

study. The chapter closes with a summary.

2.2. Theoretical Review

A theoretical review refers to the comprehensive analysis and synthesis of literature with

a view to identifying research gaps, adopting new perspectives to test existing theories

and building new ones, and for providing a research agenda (Schryen, Wagner, &

Benlian, 2015). This section reviews stewardship theory which is the one to underpin this

study.

2.2.1. Theoretical Framework

A theoretical framework refers to how the research is guided, its assumptions and

underpinnings, and provides a structure of ideas on which the research is based (Saunders

et al, 2016). This study was based on a stewardship theoretical framework developed by

Eddleston, Kellermans, and Zellweger (2010). Drawing from previous research by Miller

et al. (2008), Eddleston et al. (2010) chose four determinants of stewardship theory

related to governance of firms in general, and one related to the specific study on family-

to-firm unity. The four stewardship determinants, which are also closely followed by

Achua and Lussier (2013) in defining the stewardship theory dimensions, are shown in

Figure 2.1 and comprise: comprehensive strategic decision-making; participative

governance; human capital; and long-term orientation.

16

Figure 2.1. Stewardship Theory Determinants. Source: Eddleston, Kellermans, and

Zellweger, (2010).

2.2.1.1. Comprehensive Strategic Decision-Making

Comprehensive strategic decision-making is characterized by diligent and in-depth

analysis of strategic options as stewards are motivated to maximize organizational

performance (Eddleston et al., 2010). According to the stewardship theory, stewards are

motivated to maximize their own utility by making decisions that are to the best interests

of the organization and, therefore, are diligent in comprehensively evaluating strategic

decisions (Davis, Schoorman, & Donaldson, 1997; Basco, 2014). Stewardship theory,

introduced by Donaldson and Davis (1991), suggests the potential for pro-organizational

motives of the directors (Donaldson, 1990; Donaldson & Davis, 1993) and acting with

altruism for the welfare of the entire organizations and the stakeholders (Swamy, 2011).

Stewardship theory was developed further by other researchers (Davis et al., 1997;

Cornforth, 2004; Donaldson, 2008) who pointed out that the executives can be good

stewards and partners of the organization and work diligently to achieve higher levels of

profits and better shareholder returns (Cornforth, 2004). The theory holds that managers

are motivated by achievement and responsibility needs and are self-directed, besides

attaching significances to their personal reputation. Thus, managers are stewards whose

motives are aligned with the objectives of the principal (Donaldson & Davis, 1991).

Comprehensive Strategic

Decision-Making

Long-term Orientation

Participative Governance

Human Capital

STEWARDSHIP

17

According to the research of Davis et al. (1997), managers are stewards and team players

who align themselves with the objectives of their principals, not a rational opportunist

bent on maximizing his or her own utility to the detriment of others, including the

principal. An underlying premise of the stewardship theory is that directors, having a

fiduciary duty, can be trusted and will act as stewards over the resources of the company.

Thus, the principals can allocate corporate power to professional managers and empower

them to maximize shareholder wealth for the private sector, or social benefit for the

public sector (L'Huillier, 2014). In effect, managers in the stewardship model are good

stewards of corporate assets and they work diligently to maximize shareholder returns

when empowering structures are put into place (Davis et al., 1997). In stewardship theory,

both the executive and the shareholder have an interest in maximizing the long-term

stewardship of the company and their interests are therefore already well aligned

(Madison, Holt, Kellermanns, & Ranft, 2016).

In stewardship theory, managers and owners collaborate and the emphasis of the board’s

role is developing strategy rather than monitoring performance (Chambers, G, Mannion,

Bond, & Marshall, 2013). Inherent in this theory is the understanding that the owners are

prepared to take risks on how managers run their business and invest their resources,

indicating a high level of trust (Viander & Espina, 2014). According to Jussila, Goel, and

Tuominen (2012), despite working collaboratively and collectively with management in

providing strategic direction, the role of the board as monitor is not compromised and

indeed increases organizational performance. In order for the board to play higher-level

roles, members should be selected on the basis of their expertise and contacts so that they

are in a position to add value to the organization’s strategies and decisions. Additionally,

boards and managers should receive proper induction and training so that they can

operate as effectively and optimally as possible (Chait, Ryan, & Taylor, 2013).

2.2.1.2. Participative Governance

Davis et al. (1997) suggest that pro-organizational actions are best facilitated when

corporate governance supports cooperation, participation and empowerment as opposed

to monitoring and control. Achua and Lussier (2013) define stewardship as an employee-

based form of leadership that empowers followers to make decisions and have control

over their jobs, while Ahn, Ettner, and Loupin (2011) associate it with value-based

18

leadership. A stewardship approach in governance has sometimes been referred to as the

moral imperative (Carver, 2007) as leaders who embody it are concerned about its

followers and their growth. Stewardship is more about facilitating than leading and an

effective steward leader creates an environment for team empowerment where decisions

are decentralized (Achua & Lussier, 2013). Also, critical to stewardship is ethical

leadership when followers perceive the leader’s behavior as trustworthy (Caldwell,

Hayes, & Long, 2010).

When workers participate in decision-making they feel a sense of psychological

ownership and belongingness and this results in increased productivity and higher

performance for the organization (Cheney et al., 2014). For co-operatives, participative

governance is usually associated with the principle of one member, one vote, which

balances managerial direction with employee-owners’ concerns (Liang et al., 2015). The

participation of members leads to cohesion as it gives them voice and authority to monitor

management (Dayanandan, 2013; Francesconi & Ruben, 2012). In the John Lewis

Partnership (JLP), one of Europe’s largest models of employee ownership and often

described as a ‘workers’ paradise’, Cathcart (2013) shows that participation can range

from information-giving to worker control. For the JLP, the degree of control employees

exercised over decision-making declined as a direct result of changes of representation in

the organization.

Stewardship theory has been used to underpin corporate governance of co-operatives

particularly because of its closeness to the co-operative values and principles. While, like

other firms, co-operatives must remain efficient, provide products and services to

customers and be financially viable, they differ from other businesses in the fundamental

respect that they are owned by a member community and not by shareholders (Sherwood,

2012). Members, who are also the owners, of a co-operative also use its services and so

are not just interested in profit-making. Co-operatives also value democracy in their

governance and operations, a fundamental difference with the for-profit sector (Sacchetti

& Tortia, 2015). Thus, co-operatives maintain a different approach to philosophy,

structure, ownership, investment and disposition of profits, which calls for a different

kind of governance (Ernst & Young, 2012). Co-operative governance that will lead to

high performance of co-operatives must, therefore, include a transparent and democratic

19

culture, member participation, strategic leadership, and accountability (Dayanandan,

2013; Scholl & Sherwood, 2014).

2.2.1.3. Human Capital

Firms that embrace a stewardship culture develop a skilled workforce as they see their

people as the greatest resource and lifeblood of their businesses (Miller, et al., 2008).

Greater educational level of directors has been shown to be associated with receptivity to

innovation and technology (N. Kim & Kim, 2015), openness to change, tolerance to

ambiguity and introducing control systems (Gottesman & Morey, 2010; Kirca, Hult,

Deligonul, Perryy, & Cavusgil, 2010). Higher levels of education lead to better ability to

process information, absorb new ideas, and find creative solutions (Barroso, Villegas, &

Perez-Calero, 2011; Dalziel, Gentry, & Bowerman, 2011). In a study of electronic firms

in Taiwan, Chen (2014) showed that directors’ educational level, CEO experience and

international experience, had a positive effect on firms’ decisions towards

internationalization.

Board capital, a construct that has been created to represent both human and social capital

of the board of directors, is a source of advice and resources to the organization (Hillman,

2014; Hillman & Dalziel, 2003; Kwon & Adler, 2014). Haynes and Hillman (2010)

differentiate between the breadth and depth of board capital. The board capital breadth

comprises the directors’ functional, occupational, social and professional experience,

while the depth refers to embeddedness of directors in the primary industry of the firm,

their intra-industry human and social capital. In their research on family social capital,

Cabrera-Suárez, Déniz-Déniz, and Martín-Santana (2015) concluded that there are three

dimensions of internal social capital: structural, cognitive, and relational. The structural

social capital refers to internal network of ties that facilitate interaction and

communication between members. The cognitive dimensions of social capital are the

shared representations, interpretations and systems of meaning. As a result of both

structural and cognitive interactions, personal relationships based on trust, norms,

obligations and identity result, which is the relational dimension of social capital.

According to Perez-Calero, Villegas, and Barroso (2016), there are three interdependent

forms of capital; human capital, external social capital, and internal social capital. Both

20

human and external social capital provide the board with knowledge, experience and

information about the environment of the firm, while the internal social capital bring in

bonding, cohesiveness and facilitates the pursuit of collective goals (Arnegger, Hofmann,

Pull, & Vetter, 2014). While previous research on human and social capital has tended to

give more prominence to how a board’s external social capital influences the performance

of the firm, there is a growing body of research showing that the relationships between

directors of the board (internal social capital) is as important (Barroso, Villegas, & Perez-

Calero, 2011; Barroso-Castro, Villegas-Perinan, & Casillas-Bueno, 2016; He & Zhi,

2011). Barroso-Castro et al. (2016) further posit that, while board’s external ties are latent

and organizations may fail to take advantage of them (Obukhova, Lan, & George, 2013),

a higher internal social capital could further deploy it. In effect, when external ties are

low, higher internal social capital will compensate by intensive co-working among

directors (Johnson, Schnatterly, & Hill, 2013).

Board size and composition have also been used as proxy for board diversity of

knowledge pool, an indicator of board capital (De Maere, Jorissen, & Uhlaner, 2014).

Studies have shown that larger boards can counter the weight of the CEO and are also

likely to have a wider range of skills, knowledge and expertise which are useful for

monitoring and service roles (Ayadi, Ojo, Ayadi, & Adetula, 2015; Fauzi & Locke,

2012). Board diversity in relation to gender is also an important aspect of human capital

and has been shown to have impact on firm performance (Ntim, 2015). There is a

substantial amount of research showing a positive relationship between percentage of

women on the board of directors and firm performance (Fidanoski, Simeonovski, &

Mateska, 2014; Gotsis & Grimani, 2016; Velte, 2016; Lenard, Yu, & York, 2014), while

others show no effect or negative relationship (Manini & Abdillahi, 2015; Wessels,

Wansbeek, & Dam, 2015).

2.2.1.4. Long-term Orientation


consuming activities and is a key component of the stewardship perspective (Davis et al.,

1997; Miller, et al., 2008). It has also been defined as a tendency to prioritize long-range

implications and impact of decisions and actions that come to fruition after an extended

time period (Hoffman & Wulf, 2016; Lumpkin, Brigham, & Moss, 2010). People with

21

long-term orientation consider the past and the future to be important, make plans in

advance and avoid impulsive decisions as their interest is in long-term rewards (Park,

Seung-Bae, Chung, & Woo, 2013). Long-term orientation (LTO) is a focus on the future

benefits of outcomes and reflects a desire to build and maintain long-term relationships

among business partners (Hwang, Chung, & Jin, 2013; Maleki & de Jong, 2014).

LTO has been operationalized across different levels of analysis. For instance, Hofstede

(2011) distinguished between short-term and long-term orientations, both related to the

choice of focus for people’s efforts: the future or the present and the past. On the other

hand, Lumpkin and Brigham (2011) have conceptualized LTO as comprising continuity,

futurity and perserverence. Family, mutual, and member-based firms tend to possess a

long range perspective as they tend to have longer tenures for their CEOs and are often

willing to be more patient in their investment decisions and risk taking (Brigham,

Lumpkin, Payne, & Zachary, 2014). Hoftede’s LTO dimension is also similar to

GLOBE’s future orientation dimension as they both refer to time orientation in terms of

the past, present and future framework (Venaik, Zhu, & Brewer, 2013).

Contrasted to long-term orientation, short term orientation is a lack of deliberation, where

consequences for choices are not planned in advance, or a lack of imagination, where the

future is not planned imaginatively (Chakhovich, 2013). LTO strengthens stewardship

effects of an arganization by enhancing goal alignment between owners and managers as

well as balancing various stakeholder interess (Hoffman & Wulf, 2016).

2.3. Conceptual Framework

A conceptual framework is a key part of research design and comprises the system of

concepts, assumptions, expectations, beliefs and theories that inform the study (Miles,

Huberman, & Saldana, 2014). It also refers to a visual or written relationship between

various variables often derived from one or more theories and traces the input-process-

output paradigm of the study (Saunders et al., 2016). This section describes a conceptual

framework of study and how the dimensions of stewardship theory will be tested. The

model (Figure 2.2), derived from Eddleston, Kellermans, and Zellweger (2010), shows

four independent variables, with the respective hypotheses shown, a mediating variable,

and a dependent variable.

22

Figure 2.2: Conceptual Framework of Effect of Co-operative Governance on the

Organizational performance of Dairy Co-operatives. Derived from Eddleston,

Kellermans, and Zellweger, (2010).

2.3.1 Independent Variables

An independent variable, so called because they are determined outside the process being

studied, is a variable that is expected to influence the dependent variable in some way

(Zikmund et al., 2013). Independent variables are those that probably cause, influence or

affect outcomes and are also called manipulated or predictor variable (Creswell, 2014) as

H01

H02

H03

H04 H05

STRATEGIC DECISION-MAKING (X1)

Board’s role in decision-making

Board empowers management

Board works as team

PARTICIPATIVE GOVERNANCE (X2)

Members have equal voting rights

Members participate in decision-making

Timely information is shared

HUMAN CAPITAL (X3)

Board/management knowledge & skills

Board/management experience

Board diversity

LONG-TERM ORIENTATION (X4)

Investment for long-term profits

Management incentivized to take risks

Management held accountable for

performance.

ORGANIZATIONAL

PERFORMANCE (Y)

Revenue per customer

ROA over 5 years

Product Innovation

MARKET ORIENTATION (Z)

Generating market intelligence

Disseminating marketing

intelligence

Responding to market intelligence

Independent Variables (X)

Corporate Governance

Dependent Variable (Y)

Organizational

Performance

Moderating Variable (Z)

Market Orientation

23

they are manipulated by the researcher to cause an effect on the dependent variable

(Cooper & Schindler, 2014). The independent variables for this study, derived from

stewardship leadership model developed by Eddleston et al. (2010) were the following:

strategic decision-making; participative governance; human capital; and long-term

orientation.

2.3.1.1. Strategic Decision-Making (X1)

Strategic decision-making refers to the responsibility that stewards have in supporting in-

depth analysis of multiple strategic options in order to make decisions that are in the best

interests of their organization (Eddleston et al., 2010; Shepherd & Rudd, 2014). The

dimensions of strategic decision-making for this study were: board’s role in decision-

making; board empowers management; and board works as a team (Achua & Lussier,

2013). Strategic orientation behaviors refer to how organizations interact with their

customers, competitors, technology and other external factors to make optimal strategic

choices which results in positive impact on performance (Li, Wei, & Liu, 2010; Liu,

Takeda, & Ko, 2014; Zhou & Li, 2010). In a study to investigate how strategic orientation

affects performance for social enterprises in the United Kingdom and Japan, Liu et al.

(2014) used variables to assess market intelligence dissemination and responsiveness,

pro-activeness, innovativeness and risk taking. The study found that the pursuit of

strategic orientation had positive effects on the performance of social enterprises in both

social and commercial aspects.

The role of the board in decision-making has been shown to be positively related to

organizational performance. In a survey of CEOs and Board Chairs of 2,000 non-profit,

for-profit and public hospitals in Germany, Buchner, Schreyogg, and Schultz (2013)

found that the strategy-setting of the board led to positive hospital performance. To

measure the performance, the researchers used data from the annual financial reports and

other reports, instead of relying on informant responses. For the independent variables,

the researchers used the 5-point Likert scale to measure the effect of the boards’ strategy-

setting role on four factors, namely market-related, employment, social, and innovation-

related objectives. The study employed a structural equation modeling approach for the

empirical analysis. In another study within the same sector, Ford-Eickoff, Plowman, and

McDaniel Jr. (2011) surveyed the top management team members of 72 hospitals in the

24

United States to explore board involvement in their strategic decision-making processes.

For the strategic decision-making variables, the study used decision-scenario

methodology to study board involvement. The method presented respondents with

realistic descriptions of typical scenarios using a 10-point scale and asked them to report

the breadth of expertise of the board in strategic decision-making. The study concluded

that boards that participate in decision-making have a greater impact in their

organization’s strategic focus and performance.

The role of the board in providing guidance to the senior management for strategy setting

is important in improving organizational performance. In an exploratory study of French

co-operatives, Allemand, Brullebaut, and Raimbault (2013) used one-to-one interviews

and observation during meetings and debates as well as semi-structured interviews. The

variables for the study were, first, the role of the board in the cooperative’s strategy, and

second, the monitoring role of the board. The aim of the study was to identify good

practices that would improve the governance of the co-operatives. This study measured

the effect of strategic decision-making on organizational performance by looking at three

variables: the board’s role in the strategic direction of the co-operative; the extent to

which the board empowers management; and the board working as a team.

2.3.1.2. Participative Governance (X2)

Eddleston et al. (2010) define participative governance as the capability of the board of

directors to participate in the development of a value-creating corporate strategy.

Participative governance is also the extent to which the principals or shareholders retain

formal and real authority and this is usually allied to the balance between residual risk

bearing and decision-making functions (Chaddad & Iliopoulos, 2013). The range of

control can be from total integration where there is no separation between residual risk-

bearing from decision-making by the owners to loss of member control in

demutualization (Berle & Means, 1932; Bijman, Hendrikse, & Oijen, 2013). The

dimensions of participative governance for this study are: all voices are heard; members

participate in decision-making; and timely information is shared (Achua & Lussier, 2013;

Barraud-Didier, Henninger, & El Akremi, 2012; Dayanandan, 2013).

25

Co-operatives and other community organizations are unique in that they have to balance

and negotiate relationships between their members in order to ensure internal democracy

and participation in decision-making (Dayanandan, 2013). Member participation in the

decision-making is an important measure of democratic member control. The attendance

of the general assembly or the annual general meeting is an important indicator of good

governance as these major events provide the opportunity of incorporating members’

voices in decision-making (Brown & Dillard, 2015). In an empirical study to survey co-

operatives in China’s Zhejiang province, Liang, Hendrikse, Huang, and Xu (2015)

investigated four characteristics of democratic member control: democratic decision-

making procedures, participation in decision-making, member exit, and profit allocation.

Other ways of measuring participation is the extent to which members are involved in the

administration of their co-operatives (Siebert & Park, 2010), participation in decision-

making fora such as the annual general meetings, as well as participating in various board

committees of the co-operative (Barraud-Didier et al., 2012).

Another way of measuring democratic participation is the level of knowledge and

management skills of the board, and also how it communicates with the members. Choi et

al. (2014) in a study of South Korean co-operatives, measured democratic participation by

the proportion of members present in educational and training courses, and economic

participation by the amount of members’ equity capital and patronage. In a study to

analyze the factors of farmers’ participation in the management of co-operatives in

Finland, Sumelius (2010) defined and measured participation in terms of frequency of

attending meetings, frequency of voting, frequency of communicating with leaders, the

will to leave, not fulfilling the obligation of members, and the will to participate in co-

operative management.

Participative governance, though indisputably has positive effect on organizational

performance, comes with what Pozzobon and Zylbersztajn (2013) call ‘democratic costs’.

According to the researchers, democratic costs are decision-making costs that result from

the need to provide incentives for members to participate in collective decision-making

processes, the costs incurred from the resulting, and managing of, conflict of interest. In a

study of 12 co-operatives in the Brazilian state of Rio Grande do Sul, the study used

26

member participation at the general assembly, and in the board of directors as variables

for member participation.

Board transparency is a fundamental pillar of good governance and one of the values of

co-operatives. It refers to the provision of essential information to stakeholders in order to

minimize information asymmetry and aid in participation and decision-making

(Agyemang, Aboagye, & Ahali, 2013; Agyei-Mensah, 2016; Bijman & van Dijk, 2009).

Transparency means that information that members need is disseminated to them and

there is a two way communication in order to ensure participation in decision-making and

involvement in the work by all (Dayanandan, 2013). In the wake of the global financial

crisis and corporate scandals of the last decade, legislations have been put into place in

many countries to limit the information asymmetry between shareholders and agents, as

well as dishonesty on the part of the management (Choi et al., 2014; Tarus & Omandi,

2013; Torchia & Calbro, 2016). In this study, participative governance was measured in

three ways: the extent to which all voices are heard; members’ participation in decision-

making; and board transparency in their sharing of information to members in order to be

held accountable.

2.3.1.3. Human Capital (X3)

Human capital refers to the intangible collective resources possessed by individuals and

groups in an organization, which includes knowledge, talents and experience needed to

accomplish the goals of the organization (Huff, 2015). Research has shown that

companies with well-educated board members are more profitable and overvalued in the

market (Fidanoski, Simeonovski, & Mateska, 2014). Further, it has been shown that the

creation of value in a firm, one of the two roles of boards (Bertoni, Meoli, & Vismara,

2014), is dependent on how they manage intellectual capital (Appuhami & Bhuyan,

2015). In this study, human capital dimensions included board composition, board and

staff skills and experience; and boad diversity (Eddleston et al., 2010). Due to the link

between human capital and innovation (López-Nicolás & Merono-Cerdán, 2011; Wang &

Wang, 2012), the measurement used for human capital in this study was product

innovation or number of new products.

27

In their study of the contribution of the board’s intellectual capital in generating the

intellectual capital of a company, Berezzinets, Garanina, and Ilina (2016) suggested that

members of the board used their knowledge, experience, and networking opportunities to

build the intellectual capital for effective monitoring, advising and providing the company

with resources. The researchers further posited that the intellectual capital from the

directors translated to value creation for the company, and concluded that the personal

characteristics of board members, therefore, influences the performance of a company.

Group diversity in general and gender in particular, and its effect on the organizational

performance has been a common variable for many studies on corporate governance

(Hillman, 2014; Kumar & Zattoni, 2016). Female members of the board have been shown

to have a positive impact on the organizational performance (Fidanoski et al., 2014;

Gotsis & Grimani, 2016; Velte, 2016). However, exactly how women representation

influences the organizational performance is contested. A case in point is the research by

Willows and van der Linde (2016) which showed positive impact of female

representation on the board when using accounting-based measures of performance such

as ROA and ROE, but negatively when using market-based measures such as Tobin’s Q.

The study by Willows and van der Linde (2016) studied the top 40 companies of the

Johannesburg Securities Exchange where female directors made up less than nineteen

percent of the board of directors, with the majority of thesee women being in non-

executive positions.

Similar results were obtained from a meta-analytical research on 140 studies by Post and

Byron (2015) who also found mixed evidence. In the latter study, the researchers found

that female representation was positively related to accounting returns and that the

relationship was more positive in countries with stronger shareholder protections. The

relationship between women representation was positively related to board’s role of

monitoring and strategy involvement but neurtral for organizational performance. On the

positive side, the board gender diversity contributes creativity and improves the quality of

decision-making as a result of increasing the alternatives considered by members (Kumar

& Zattoni, 2016).

28

In a study using a dataset of 211 European Union publicly listed companies belonging to

the construction industry from 28 different countries, Arena et al. (2015) examined the

role of women on firm performance. The study collected information on the performance

and composition of board of directors in terms of gender diversity and education. As a

proxy for gender diversity, the study used the percentage of women on the board and

considered more than three women to represent a ‘critical mass’. In a study of 103 MFIs

in East Africa, Mori et al. (2015) used the proportion of board members who are female

as an independent variable, and the attainment of a Masters, MBA and PhD for the

education level of women. In a meta-analytical study investigating the relationship

between female representation and firm organizational performance, Pletzer, Nikolova,

Kedzior, and Voelpel (2015) studied data from 20 studies on 3,097 companies. For

female representation, the study measured the percentage of females on corporate boards.

Board size, composition and diversity have a positive effect on the performance of the

organization. Using one of the largest data sets with 120 provisions from the 2010 UK

Combined Code, Elmagrhi, Ntim, and Yan (2016) studied compliance and disclosure

practices of 100 listed firms from 2008 to 2012. The firms included in the study all had to

have annual reports, financial and market performance data, and continuous listing for the

six years of the study. The dependent variable of the study, the UK Corporate Governance

Index, contained five sections, namely: board leadership; board effectiveness; board

accountability; executive pay; and relations with shareholders. The independent variables

of the study included board size, proportion of independent outside directors, board

gender diversity, board ethnic diversity and the existence of a separate compliance

committee. Using two-stage least squares and multiples regression analyses, the study

found that the firms with larger board size, more independent directors and greater board

diversity tended to practice greater transparency and disclosure.

In a study of the effect of governance of commercial banks in Kenya, Nyamongo and

Temesgen (2013) proxied governance using three variables, namely board size,

independent directors and CEO duality. The study made use of secondary data collected

from the audited financial statements in which information on board size and composition

as well as CEO duality was extracted. The study found that the bigger the board size, the

lower the return on assets, and the higher the number of independent directors, the greater

29

the return on assets. The findings on CEO duality was mixed and inconclusive. To

measure human capital, this study considered the education level of the board and

management, the composition, diversity, skills and experience of the board of directors

(Abor, 2015).

2.3.1.4. Long-Term Orientation (X4)


consuming activities, a focus on the future benefits, and reflects a desire to build and

maintain long-term relationships among business partners (Davis et al., 1997; Hwang,

Chung, & Jin, 2013; Maleki & de Jong, 2014; Miller, et al., 2008). Long-term orientation

(LTO) has also been defined as a tendency to prioritize long-range implications and

impact of decisions (Hoffman & Wulf, 2016; Lumpkin, Brigham, & Moss, 2010),

considering the past and the future in decision-making, and making plans in advance and

avoiding impulsive decisions (Park, Seung-Bae, Chung, & Woo, 2013). In this study, the

dimensions of long-term orientation used were: investment in long-term projects;

management incentivized to take risk; and management held accountable for performance

(Eddleston et al., 2010; Hoffman & Wulf, 2016). For the measurement of LTO, this study

utilized Return on Assets over five years.

Long-term orientation has been measured in a variety of ways in empirical research.

Hoffman et al. (2016) did an analysis of 201 privately owned firms from Germany and

showed that a long-term orientation helps align firm owners and organizational goals. In

order to measure long-term orientation, the researchers used a questionnaire with four

questions on a 7-point Likert-type scale to indicate the degree to which they agreed with

the statements. The constructs for long-term orientation were: The management in our

firm focuses in particular on long-term profitability; long-term goals have priority over

short-term goals among our management; the management in our firm invests deeply into

the long-term development of employees; the management in our firm emphasizes long-

term investments. In a study with similar variables, Park et al. (2013) used two scenarios

to study long-term orientation, High LTO and low LTO. Participants of the study were

asked to describe situations in which they were rewarded when they visited a restaurant

and given some questions to respond to. The four questions were: I make plans on a long-

30

term basis; I work hard for future success; I can give up today’s pleasures for future

success; Persistence and patience are important to me.

In a study of the effects of satisfaction and trust on LTO, Cho, Chung, and Hwang (2015)

studied 515 US apparel retailers using a questionnaire. The questions the study used for

LTO are as follows: I expect this supplier to be working with us for a long time; we

believe that over the long run our relationship with this supplier will be profitable;

maintaining a long-term relationship with this supplier is important to us; we focus on

long-term goals in this relationship. Other researchers have used multi-dimensional

constructs to measure LTO composed of continuity, futurity and perseverance (Brigham

et al., 2014; Lumpkin & Brigham, 2011; Lumpkin et al., 2010).

2.3.2. Dependent Variable (Y): Organizational Performance

A dependent variable is a process outcome that can be predicted or explained by other

variables (Zikmund, Babin, Carr, & Griffin, 2013). According to Cooper and Schindler

(2014), a dependent variable is measured, predicted, monitored and expected to be

affected by the manipulation of an independent variable. This study had organizational

performance as the dependent variable. Organizational performance is defined as the

actual results of an organization as measured against that organization’s intended outputs

(Choa & Dansereau, 2010), or the performance of an organization measured against its

intended outputs (Tomal & Jones, 2015).

Since the onset of corporate governance as a discipline about 30 years ago, a lot of

academic research has gone into investigating the link between governance and the

performance of the firm. A ground-breaking work in this regard was the research by

Demsetz and Lehn (1985) where they studied 511 US corporations and showed the

relationship between firm structure and value maximization. Since then there are many

studies that have shown correlation between corporate governance and organizational

performance. For example, Wessels, Wansbeek, and Dam, (2015) have shown how

exogenous changes like legislation and gender quotas have negative effect on firm

performance. In their study, Wessels et al. (2015) modeled corporate governance, firm

performance and investment opportunity as latent variables in order to account for

measurement errors inherent in use of proxy variables. For proxies of organizational

31

performance, the study noted that there is lack of consensus on how organizational

performance should be measured, but noted three types of measures: measures of firm’s

relative value such as Tobin’s Q; accounting measures of organizational performance

such as ROA; and returns on equity.

Traditionally and particularly in the industrial era, and in the light of the agency theory,

the financial ratios have been the main measures of organizational performance

(Stefanovska & Soklevski, 2014). However, most organizations now consider using one

measure, such as financial, as too one-sided and misleading given that there are other

important criteria for performance (Abdel-Maksoud, Elbanna, Mahama, & Pollanen,

2015). In their ground-breaking research, Kaplan and Norton (1992) devised a ‘balanced

scorecard’, a multi-dimensional set of measures that included financial measures,

customer satisfaction, internal processes, and the organization’s internal learning and

improvement activities (Kim, 2015; Ondoro, 2015). The balanced scorecard (BSC) was

originally introduced to deal with performance measurement issues that arose out of an

over-reliance on financial performance metrics (Khomba, 2015). Dependence on just

financial measures was thought to promote short-term decision-making at the expense of

long-term profitability (Albright, Burgess, & Davis, 2015). In this study, three measures

were employed to measure organizational performance: return on assets (ROA), revenue

per customer, and product innovation (number of new products).

2.3.2.1. Return on assets (ROA)

Return on Assets is a financial ratio and is calculated as calculated as the net income

divided by total assets (Miller, Dobbins, Boehlje, Barnard, & Olynk, 2012). The internal

perspective of the balanced scorecard responds to the question of which work processes

are important for the organization to deliver on its strategy (Hladchenko, 2015). Internal

process focuses on operational and management processes that create and deliver

business value (Lin, 2015). In this study, the internal perspective – which is aligned to

strategic decision-making variable, was measured by the use of one of the accounting-

based profitability measures, Return on assets (ROA). In order to align it with the long-

term orientation variable which also used ROA, the ratio was calculated over a period of

five years. This study used ROA as a measure of both short-term (strategic decision-

making) and long-term profitability as it is a return on all assets, including assets financed

32

with debt capital (Miller et al., 2012; Quayes & Hasan, 2014; Upadhaya, Munir, &

Blount, 2014). The other reason for preferring ROA as one of the measures of

organizational performance for dairy co-operatives is because agricultural enterprises

tend to be asset and investment heavy. Businesses that mostly rent or lease production

assets (including land) tend to generate and also require higher return on asset ratios to

remain competitive (Northwest Farm Credit Services, 2016).

2.3.2.2. Revenue per customer

Revenue per customer is a the measurement of customer satisfaction, one of the four

perspectives of the Balanced Score Card (Callado & Jack, 2015). The customer

orientation in the BSC is one of two external facing perspectives or outcome measures

and responds to the question of “how do customers see us” (Cheng & Humphreys, 2016).

It also responds to the question, “what qualitative and quantitative performance is

expected by the stakeholders” (Hladchenko, 2015)? Customer satisfaction emphasizes

the customer relationship and service delivery to the customer and includes: improving

market share growth; improving customer complainant response time; creating new

customers; and keeping current customers (Lin, 2015).

In a study of 169 corporations, Gonzalez-Padron, Chabowski, Hult, and Ketchen (2010)

found that customer performance was the only BSC outcome significantly related to

financial performance. According to Busco and Quattrone (2015), customer perspective

deals with a focus on customer needs and their satisfaction (on time delivery of products

and customer meetings, as well as quality of service (turn-around and access). Other

measures of customer perspective include: customer loyalty, new customers, market

share, brand value, profitability per customer, revenue per customer, responsiveness to

clients, and maximizing sales (Callado & Jack, 2015; Jack, Ramon-Jeronimo, & Florez-

Lopez, 2012). Perkins and Remmers (2014) opine that customers’ concerns generally fall

into four main categories of time, quality, performance, service and cost, and that this

perspective helps managers to effectively match their performance to the expectations of

the customer.

In this study, customer satisfaction was measured by the revenue received by each

customer (member of co-operative) in shillings per liter. The level of payment determines

33

the growth of the co-operative as members are not obligated to bring their milk to a

particular co-operative, which makes it competitive for the co-operatives in the vicinity.

2.3.2.3. Product innovation

The learning and growth perspective deals with the enabling factors needed to achieve

excellent results for the organization and the critical drivers are related to human capital.

It looks at the organization’s intangible assets such as employee skills and capabilities

needed to facilitate organizational growth and improvement (Lin, 2015). Learning and

growth perspective concerns itself on the activities necessary to develop the organization

and its personnel in order to guarantee the success of the organization by learning from its

failures and successes (Hladchenko, 2015). According to Baraldi and Cifalino (2015),

three critical drivers for learning and growth are: developing staff competencies by

training; implementing new technologies; and creating strong partnerships.

New product innovation has been idenfied as a critical variable of organizational

performance as it is a means by which firms grow and stay competitive over time

(Kraiczy, Hack, & Kellermanns, 2014; Schultz, Salamo, & Talke, 2013). Among the

important determinants of innovativeness, the preferences and dispositions of the top

management teams, and especially the role of the CEO, in risk-taking behaviour have

been noted (Felekoglu & Moultrie, 2014). In the study, innovation was measured in the

following ways: ‘the number of new or improved products and services launched to the

market is superior to the average in your industry’; and ‘the number of new or improved

processes is superior to the average in your industry’ (López-Nicolás & Merono-Cerdán,

2011; Khomba, 2015; Ozmantar & Gedikoglu, 2016). For dairy co-operatives, new

products and services could include processing of milk, production of yoghourt, provision

of inputs for dairy farming, artificial insemination, veterinary services, and provision of

savings and credit facilities (SACCOs).

2.3.3. Moderating Variable (Z): Market Orientation

A moderating variable is a variable that affects the direction and/or strength of the

relationship between an independent variable and a dependent variable (Creswell, 2014;

Saunders et al., 2016). The moderating variable for this study was market orientation,

34

whose dimensions were: generating market intelligence; disseminating marketing

intelligence; and responding to market intelligence.

According to Kohli and Jaworski (1990), market orientation entails (a) one of more

departments engaging in activities toward developing an understanding of customers’

current and future needs, (b) sharing of this understanding across departments, and (3) the

various departments engaging in activities designed to meet select customer needs. In

summary, market orientation refers to the organizationwide generation, dissemination,

and responsiveness to market intelligence (Jaworski & Kohli, 1993; Kohli & Jaworski,

1990). However, according to Narver and Slater (1990), market orientation is an

important organizational climate that produces behaviour necessary to generate superior

customer value and high performance The three components of the organizational climate

are customer orientation, competitor orientation, and interfunctional coordination (Weng,

Chen, Pong, Chen, & Lin, 2016).

In a study based on a nation-wide survey among senior managers of 28 banks in Ghana,

Mahmoud, Blankson, Owusu-Frimpong, Nwankwo, and Trang (2016) used the market

orientation (MARKOR) criteria proposed by Kohli, Jaworski, and Kumar (1993), which

was in turn refined and validated by Kolar (2006). Mahmoud et al. (2016) used the three

constructs of intelligence generation (of which they had three items); intelligence

dissemination (seven items); and intelligence responsiveness (six items) and measured

them using five-point Likert scale. However, Andotra and Gupta (2016), in a census

research of 150 small scale industry firms in Udhampur, India, studied the impact of

environmental turbulence on market orientation and used the Narver and Slater’s (1990)

scale which comprised customer orientation, competitor orientation and environmental

moderators. Sun and Pan (2011) used the same scale (Narver & Slater, 1990) consisting

13 items, in their study of 143 firms in China. Kazakov (2016), on the the other hand used

both the MARKOR criteria (Kohli et al., 1993) and market orientation (MKTOR) scale

(Narver & Slater, 1990) for a study of market orientation in the service industry in Russia.

2.3.3.1. Generating Market Intelligence

Generating market intelligence is an organizational process of continuous gathering,

analyzing, and monitoring information for present and future needs of customers (Pinho,

35

et al., 2014; Zebal & Goodwin, 2012). A market-oriented organization looks beyond itself

towards the environment to gather information that can then be shared, first within the

firm, and later utilized to respond to the customer needs and wants (McClure, 2010).

2.3.3.2. Disseminating Marketing Intelligence

Once the market intelligence is generated and analyzed (Jain, R., Jain, & Jain, 2013), it is

disseminated within the departments and functions of the organization Rodrigues &

Pinho, 2012; Polo-Pena et al., 2012a). Disseminating market intelligence can go beyond

the organization and involve cooperating with similar organizations in order to forming a

joint response to respond satisfy stakeholder needs and demands (Mahmoud & Yusif,

2012).

2.3.3.3. Responding to Market Intelligence

Response to market intelligence refers to the ability of a firm to serve its customers more

efficiently as a result to generating intelligence, analyzing it, and using it to improve its

internal systems (Hilman & Kaliappen, 2014). Market orientation helps an organization to

monitor its competitors and outperform them in responding to the needs and wants in the

market, thus creativing greater value for customers (Julian, Mohamad, Ahmed, &

Sefnedi, 2014).

2.3.3.4. Operationalization of Variables and Hypothesis Testing

This study set out to test the following five hypotheses: comprehensive strategic decision-

making does not significantly affect the organizational performance of dairy co-

operatives in Kenya; participative governance does not significantly affect the

organizational performance of dairy co-operatives in Kenya; human capital does not

significantly affect the organizational performance of dairy co-operatives in Kenya; long-

term orientation does not significantly affect the organizational performance of dairy co-

operatives in Kenya; and market orientation has no significant moderating effect on the

relationship between corporate governance and organizational performance of dairy co-

operatives in Kenya. The hypotheses were tested mainly multiple linear regression F-test

and coefficients, using a p value of p ≤ 0.05 for testing the significance of the independent

variables (Table 2.1).

36

Table 2.1: Operationalization of Variables and Hypothesis Testing

Variables and Measurement

Hypothesis Statistical

Test Independent

Variables

Parameters

Comprehensive

Strategic

Decision-making

(X1)

Board’s role in decision-making

Board empowers management

Board works as team

H01: Comprehensive strategic

decision-making does not

significantly affect the

organizational performance of

dairy co-operatives in Kenya

Multiple

Linear

Regression

( p < .05)

Participative

Governance (X2) Members have equal voting

rights

Members participate in

decision-making

Timely information is shared

H02: Participative governance

does not significantly affect the



Multiple

Linear

Regression

( p < .05)

Human Capital

(X3) Board/management knowledge

& skills

Board/management experience

Board diversity

H03: Human capital does not

significantly affect the



Multiple

Linear

Regression

( p < .05)

Long-term

Orientation (X4) Investment for long-term profits

Management incentivized to

take risks

Management held accountable

for performance.

H04: Long-term orientation does

not significantly affect the



Multiple

Linear

Regression

( p < .05)

Dependent Variable (Y)

Organizational

Performance Revenue per customer

ROA over 5 years

Product Innovation

Multiple

Linear

Regression

( p < .05)

Moderating Variable (Z)

Market

Orientation Generating market intelligence

Disseminating marketing

intelligence

Responding to market

intelligence

H05: Market orientation has no

significant moderating effect on

the relationship between

corporate governance and



Multiple

Linear

Regression

( p < .05)

2.4. Empirical Review of Literature

A literature review is text or part of a scholarly paper, which includes current knowledge

of a topic, findings of research into the subject along with the theoretical and

methodological contributions (Jasti & Kodali, 2014). Literature reviews use secondary

sources to validate the methodology and research models of the proposed research

questions. The review should be critical in order to interpret existing, and often

conflicting, opinions and debates on the subject (Saunders et al., 2016; Wallace & Wray,

2016). The purpose of this study was to investigate the effect of corporate governance on

the performance of the dairy co-operatives in Kenya. In this section, research work by

previous scholars concerning the effect of corporate governance of co-operatives on the

organizational performance was reviewed. Past studies, global, regional and local have

37

been reviewed along with their methodologies and scope in order to identify the research

gap.

2.4.1. Effect of Comprehensive Strategic Decision-making on Organizational

Performance

Comprehensive strategic decision-making refers to the responsibility that leaders have in

supporting in-depth analysis of multiple strategic options in order to make decisions that

are in the best interests of their organization (Eddleston et al., 2010; Shepherd & Rudd,

2014). Strategic decision-making also refers to how organizations interact with their

customers, competitors, technology and other external factors to make optimal strategic

choices which results in positive impact on performance (Li, Wei, & Liu, 2010; Liu,

Takeda, & Ko, 2014; Zhou & Li, 2010).

In business, as in the military where the concept was adopted, strategy is a general

framework that provides guidance for actions to be taken and at the same time shaped by

the actions taken. The necessary precondition for formulating strategy is clear

understanding of the ends to be obtained as it bridges the gap between policy, or high

order goals, and tactics or between ends and means (Nickols, 2016). Porter (1996)

describes strategy as an endeavor to carve out a distinct and valuable positioning and that

each firm’s strategy is reflected by the character of the unique collection of tailored

activities that it performs. The greater the “fit” among the activities the firm performs, the

greater the potential to carve out a distinct position in order to deliver a unique mix of

value. Porter posits that strategic positions have a horizon of a decade or more, unlike

operational activities which are usually a single planning cycle. On the other hand,

Mintzberg (2000) in his book, “The Rise and Fall of Strategic Planning”, points to

different meanings ‘strategy’ strategy is given: Strategy is a plan, a pattern, a position, or

perspective. Mintzberg argues that strategy emerges over time as intentions collide with

the changing reality. Thus one might start with a perspective that leads to a carefully

crafted plan, which results to a strategy reflected in patterns and actions over time.

No matter which definition of strategy one adopts, strategic decision-making is about

making choices between and among customers and markets, technologies, pricing and

geographic locations, products and services, among many others. Decision-making

38

requires a systematic, structured, and a disciplined way of making these decisions

(Nickols, 2016). According to Shivakumar (2014) differentiating between strategic and

tactical decisions determines the longevity and peformance of organizations. The

researcher provides a conceptual framework comprising two dimesions that clarifies how

strategic decisions are distinguished from the non-strategic decision, namely: the degree

of commitment and the scope of the firm. The degree of commitment is the extent to

which a decision is reversible or expense of undoing the decision, while the scope of the

firm is the effect the decisions have on organization’s architecture, people, routines and

culture (Shivakumar, 2014). The study reviewed comprehensive strategic decision-

making under three parameters, namely: the board’s role in strategic decision-making;

board empowers management; and the board works as a team.

2.4.1.1. Board’s role in strategic decision-making

The strategic decision-making of an organization refers to the fundamental choices and

directional choices an organization makes in order to maximize value (Bordean et al.,

2011). Strategic decision-making requires a strategic orientation which refers to how the

organization interacts with its customers, competitors, technology and other external

factors in order to make strategic choices (Friis, Holmgren, & Eskildsen, 2016; Kamardin

& Haron, 2011). When an organization does this, invariably there is a direct positive

impact on its performance (Li, Wei, & Liu, 2010; Zhou & Li, 2010). A governance board

is providing strategic leadership when it defines the purpose of the organization and sets

its direction. Strategic leadership is about distinguishing itself as an organization and

being clear about what the organization can achieve, its choices, priorities and the

resources it will employ (Scholl & Sherwood, 2014).

The role of strategy in an organization is in translating the vision, mission and values into

action and helping identify the identity of that organization and the business in which it

operates (Sarros, Sarros, Cooper, Santora, & Baker, 2016). There is a current debate

raging as to what is it that drives success of a firm between leadership and strategy and

there is growing recognition that the latter is the reason why the former succeeds

(Almatrooshi, Singh, & Farouk, 2016; Allio, 2015; Freedman, 2013).

39

In a study of what they describe as ‘era-defining success’ of Apple, Microsoft and Intel,

Harvard professor David Yoffie and MIT professor Michael Cusumuno (Yoffie &

Cusumuno, 2015) concluded that what made Steve Jobs, Bill Gates and Andy Grove,

CEOs of Apple, Microsoft and Intel respectively, successful, was more aligned to their

strategies than just their leadership styles. In their book, “Strategy Rules”, they deduce

five guidelines for strategy formulation that led to the success of these corporate giants.

These guidelines are: look forward, reason back; make big bets without betting the

company; build platforms and ecosystems; exploit leverage and power; shape the

organization around a personal anchor. Allio (2015) opines that it is their implementation

of these guidelines that made these leaders masters of their domains, and concludes that

successful leadership ultimately comes down to good strategy and good fortune.

The essence of strategic leadership is moving the unit of analysis from an individual

leader to re-conceptualizing leadership as a network of leaders at all levels in the

organization. In a study based on observations over many years of organizations and

reflections of leadership theories, Kriger and Zhovtobryukh (2013) developed a typology

of strategic leadership comprising single actor and shared leadership. The four

propositions and forms of leadership in the study were stars, clans, teams and leadership

networks. The researchers argue that there is ample evidence that single-actor leadership

(stars) is not fitted for complexity and when the organization is experiencing the

turbulence of competing values (Yukl, 2013). Instead of vertical, single-hero, leader-

centered style, the authors argue for distributed leadership (Bolden, 2011; Cope,

Kempster, & Parry, 2011; Currie & Locket, 2011; Gron, 2010), shared leadership

(Fitzsimons, 2011; Hmieleski & Cole, 2012; Nielsen & Daniels, 2012), and collective

leadership (Contractor, DeChurch, Carson, Carter, & Keegan, 2012; Cullen, Palus,

Chrobot-Mason, & Appaneal, 2012; Hunter, Cushenbery, & Fairchild, 2012; Mumford,

Friedrich, Vessey, & Ruark, 2012). Shared leadership is found to be more collaborative

and participatory and impacts team performance by helping build collective strategic

focus.

In a research study based on a database of 25,000 companies, Raynor and Ahmed (2013)

analyzed 344 exceptional performers based on their return on assets over a sustained

period of time and found that only two strategic decisions explained their success.

40

According to the researchers, the two strategic decisions were, first, that they emphasized

quality over low price, and second, they emphasized revenue-generation over cost

reduction. High performing corporate governance goes beyond compliance and financial

equilibrium and gives attention to fulfilling a purpose or a socially valuable mission or

impact by engaging in strategic leadership of the organization. Strategic thinking allows

the organization to exploit new opportunities and capture new markets (Chait, Ryan, &

Taylor, 2013).

A board needs to ensure that it flees board agenda so as to focus on strategic thinking and

not just looking in its rear mirror, which is its fiduciary and Type 1 governance which

concentrates on asking ‘what is wrong?’ (Chait, Ryan & Taylor, 2013). Thus a board

observing good governance practice can easily distinguish between what is strategic even

about seemingly operational matters. High performance boards spend less time on

compliance issues but accord greater priority to forward looking strategies that maximize

shareholder value, as well as in sense-making (Bordean et al., 2011). Sense-making as

decisionmaking process occurs when members confront unanticipated or non-routine

events, issues or actions (Sur, 2014). The process best happens through experiential

dialogue and engagement of complex and critical issues for the sustainability of the

organization (Caesar & Page, 2013). It is called ‘sense-making’ as it makes effort to

create order and meaning from apparent chaos or while needing to make decisions about

future events (Combe & Carrington, 2015).

Traditionally, boards have been preoccupied with compliance and fiduciary duties; that is

changing with more boards understanding their role in strategic decision-making.

According to Parsons and Feigen (2014), authors of the “The Boardroom's Quiet

Revolution”, today directors engage in a two-way learning about the organization’s

strategy. Directors are also now more fully conversant with the growth prospects of their

firms, where to invest, where to divest and where to grow as they focus less on the past

and more on the strategic topics and people (Parsons & Feigen, 2014). Modern boards are

equally in strategy development as they are in controlling the organization (Saj, 2013).

The proactive role of the board in strategic management in an organization is critical if it

is going to exert its influence beyond the boardroom (Huse, Hoskisson, Zattoni, &

Vigano, 2011). According to the work of Bordean et al. (2011), there are several benefits

41

of the board’s involvement in strategic decision-making: First, it is a precondition to

perform their fiduciary monitoring duties as their ability to fulfill legal requirements

depends on their understanding of how the management will implement the strategy.

Secondly, board members bring in huge expertise which they can make available to the

organization while developing the strategy. The role of the board in strategic decision-

making should only be high level in order not to micro-manage the administration in the

implementation of strategy (Bordean et al., 2011). The type of decisions expected of

boards are the strategic ones where there is significant and daunting complexity and

ambiguity (Sharpe, 2012). The big picture decisions of the board may include how the

management responds to dramatically changing business environment and whether to pull

out from the market or some its segments (Bukhvalov & Bukhvalova, 2011).

The predominance of agency theory and the supposed division of labor between

governance and management precluded boards from engaging in the development of

strategy and may have contributed to the corporate financial crises of early and late 2000s

(Conyon, Judge, & Useem, 2011; Soltani, 2014). The statutory reforms and codes of

practice that followed the financial crises seemingly did little to improve the quality of

corporate governance and company performance (Leblanc, 2010; Pozen, 2010) and may

have contributed to some failures (Weitzner & Peridis, 2011). Since company

performance is dependent on the selection and implementation of an appropriate strategy

in order to maximise returns, the role of the board in value creation and strategic decision-

making is paramount (Bukhvalov & Bukhvalova, 2011) especially during a period of

crisis or change (Weitzner & Peridis, 2011). While the role of the board in strategic

decision-making can be challenging as a result of lacking adequate information to make

informed choices (Lim, 2012), there is a growing recognition of the need for greater

involvement (Babic, Nikolić, & Erić, 2011; Parsons & Feigen, 2014; Bordean et al.,

2011).

While the predominance of agency theory in corporate governance has over-emphasized

the importance of monitoring the top management team as a critical function of the board,

it is not its sole function; functions of the board also include the review, development, and

monitoring of strategy (Kim & Ozdemir, 2014). Boards also play important strategic roles

such as strategy formulation, strategy choice and strategy implementation (Tarus & Aime,

42

2014). Important in influencing the board’s involvement in strategy include board

members’ knowledge, specifically board members’ firm and industry specific skills

(Machold, et al., 2011). Investigating the role of leadership in encouraging board

members to become involved in strategy, Tuwey and Tarus (2016) targeted 1200 private

firms in Kenya; The study found that board members’ knowledge, board chairman’s

leadership efficacy, board members’ personal motivation and board members’

background all have a positive and significant effect on their involvement in the

organizational strategy.

The direct observation of exactly how boards influence performance and what happens in

the boardroom is beset by access and methodological issues (Machold & Farquhar, 2013).

In order to avoid the reliability issues associated with single incursion into the boardroom

and artificial behaviour of board members due to direct observation, Crow and Lockhart

(2016), employed a multi-case study and a longitudinal approach centered on actual

boardroom observations for two organizations (Crow & Lockhart, 2014). Data was

collected from first-hand observations of the board within the boardroom over a 12-month

period in addition to use of semi-structured interviews with the chairman and CEO of

each company. In addition, secondary board data and annual reports of each company

were analyzed. The data collected from the minutes included the sequence of discussions

around the strategic and other decisions, performance and other significant discussions

over a ten year period. The findings of the study showed that the two boards studied

improved the quality of environmental scanning which, in turn, led to better selection of

strategies (Crow & Lockhart, 2016).

In a similar case study of one of the largest co-operative owned food-processing company

in Greece, Adamides (2015) shows the role and active participation of the board of

directors in the alignment of operations strategy to the corporate strategy. In a study of

social enterprises in the United Kingdom and Japan that met the criteria of generating

income from business activities and being large enough to practice sophisticated business

operations, Liu et al. (2014) measured strategic orientation, market effectiveness,

customer satisfaction and performance of social enterprises in the United Kingdom and

Japan. This study produced evidence of how a social enterprise pursuing a strategic

orientation has positive effects on its performance due to its market and entrepreneurial

43

orientations. The positive effects of the market and entrepreneurial behaviors were found

to be enhanced by the extent to which the enterprises implement institutional

arrangements and develop support structures and feedback systems.

The role of the board in monitoring the senior management and providing guidance for

strategy is important in improving organizational performance. In an exploratory study of

French co-operatives, Allemand, Brullebaut, and Raimbault (2013) concluded that the

role of the board can be enhanced by improving decision-making, choosing good

governance bodies and having an efficient interaction between the board and

management. According to their study, the role of the board in organization strategy starts

with the identification and ensuring commitment of the core mission and values of the co-

operative, and also its ability to predict the future. The role of the board in collective

decision-making was found to be enhanced by setting up committees to debate specific

issues and making the recommendations to the board to concentrate on the important.

Of all the strategic decisions a board takes in an organization, the hiring and assessment

of the chief executive is by far the most important (Adams, Hermalin, & Weisback, 2010;

Schwartz-Ziv & Weisbach, 2013). The reason for this is that the CEO is the primary

architect of the the firm’s strategy and getting the right person has a lot of bearing to the

long-term performance of the organization (Beck & Wiersema, 2013; Hyväri, 2016).

There are other important strategic decisions the board takes in addition to executive

selection. In a case study of two attempted union mergers in Germany, Behrens and

Pekarek (2016) showed the important the role of the board in the decisions of whether

and who to merge with. Boards also enhance strategic decision-making processes when

they play the role of fiduciaries in minimizing the agency costs as well as by questioning,

criticizing, advising and counselling the management (Ben-Amar, Francoeur, Hafsi, &

Labelle, 2013).

2.4.1.2. Board empowers management

Empowering leadership refers to leader behaviors that share power, delegate and allocate

more responsibility and autonomy to team members; it enables team members to

participate in decision-making and break free from inactive mindsets (Zhang & Bartol,

2010). According to Lorinkova and Perry (2014), empowering leadership fosters an

44

environment of positive exchanges with followers through equalization of power and

communication of trust and confidence. Empowerment takes place when followers are

allowed participation in decision-making and removing bureacratic constraints. Magni

and Maruping (2013) posit that empowering leadership positively moderates the

relationship between team improvization and organizational performance. Empowering

leadership has been identified as being more suitable in complex non-routine situations as

it gives team members the autonomy and confidence to take initiative in problem solving

by combining the team members’ resources (Magni & Maruping, 2013).

In both stewardship and resource dependence (Pfeffer & Salancik, 1978) theories, the

board is a human capital resource to the organization and uses its knowledge and its skills

to advise management in strategy. The board adds value through its skills and experience

by offering a wide spectrum of perspectives and strategic considerations of possible

alternatives (Tuwey & Tarus, 2016). Using survey data from 140 firms in Norway taken

over two time periods, Machold et al. (2011) showed that the board members

complemented the management by using their knowledge and skills to supplement the

organizations’ existing manangerial resources. Boards’ knowledge and skills also enable

the board to advise management on strategic choices (Nas & Kalaycioglu, 2016; Tuwey

& Tarus, 2016).

The board’s governance responsibilities include helping the organization to think

strategically about its decisions and how it allocates its resources. A quality board is one

that is competent and knowledgeable enough about the firm’s operations, customers, and

business models to have a constructive dialogue with the CEO about the firm’s business

model (Bruni-Bossio & Sheehan, 2013). The board as a whole should be actively

involved in discussing, reviewing and ultimately approving the strategic plan. Directors

can be a valuable resource by providing a fresh perspective and asking questions to

satisfy themselves that the plan is well thought out, realistic and compatible with the

organization’s mission, vision and values (Buchner, Schreyogg, & Schultz, 2013). Due to

its oversight role, it is important that the board does not get too involved in the short term

plans for the organization but instead agree on the planning parameters with the executive

(Kenny, 2012). The most important role for leadership is to define the reason for

organizational existence or the results, ends and impact to which it should aspire in the

45

lives of its stakeholders (Montgomery, 2012). Thus the board should be preoccupied with

the ends while management is responsible for the means (Fryday-Field, 2013).

An important role of the board in decision-making is empowering management, to make

operational decisions aligned to the strategic outcomes (Cui, 2016). The chief executive

of an organization is equally motivated and empowered by support from the board of

directors as other staff are by their supervisors. In two studies based on employees of

Norwegian faith-based organizations and municipal healthcare, Amundsen and Martinsen

(2015) showed that empowering leadership is an important antecedent to job satisfaction,

psychological empowerment, work effort and creativity in the workplace. The results

from structural equation modeling indicated that empowering leadership positively

affected psychological empowerment and was mediated by self-leadership. Boards can

also empower management by ensuring there is in place a performance management

system which gives accurate information about the goals that their work requires

(Swiatczak, Morner, & Finkbeiner, 2015).

However, only if clear goals are put in place can trust develop and assist managers use

them to evaluate their usefulness to make better decisions (Gonzalez-Mulé, Courtright,

DeGeest, Seong, & Hong, 2014). The communication about the goals relevant to the

managers must also be transparent and well documented in order for managers to assess

the meaning of their work (Melnyka, Bititci, Platts, Tobias, & Andersen, 2014).

Inspite of the stated benefits of empowerment, questions remain regarding its

effectiveness and whether there is a link between empowering leadership and

organizational outcomes (Lee, Cheong, Kim, & Yun, 2017; Zang & Bartol, 2010). Some

research has posited that, in given situations, too much empowerment may have

detrimental effects on organizational outcomes (Sharma & Kirkman, 2015). In their

study, Chua and Iyengar (2011) supported this view by demonstrating that a curvilinear

relationship exists between decision latitude granted by leaderss and their followers’

perceived effectiveness. They concluded that giving followers’ unfettered freedom might

backfire. According to Lee et al. (2017), too much empowerment can be “Too-Much-of-

a-Good-Thing” and that an inflection point exists when beneficial antecendents such as

leadership, personality, job design and the desired outcomes cease to be linear and

46

positive (Pierce & Aguinis, 2013). Similarly, in a study of 150 leader-follower dyads,

Wong and Giessner (2016) suggested that empowering leadership can be perceived by

followers as laissez-faire when leaders’ behaviour is not aligned with followers’

empowerment expectations (Raub & Robert, 2010).

2.4.1.3. Board works as a team

A team comprises a working group of people with a common purpose, complementary

and interdependent skills and clear roles, mutual accountability and contribution, and

realization of synergy and mutuality (Hajela, 2015). The power to cooperate and team

spirit come from an appreciation of the distinctive contribution that each member brings

to the organization (Pillai, Kumar, & Krishnadas, 2015). As O'Reilly, Caldwell, Chatman,

Lapiz, and Self (2010) opine, it is not the effectiveness of a leader as individuals that

affects organizational performance, but teamwork and alignment of leaders across all

levels that are associated with successful strategy implementation. A team is also defined

as composed of two or more individuals who exist to perform organizationally relevant

tasks, share goals, exhibit team interdependencies, or a collective which exists to provide

strategic direction to an organization (Krishnan, Barnett, McCormick, & Newcombe,

2016). Team-work involves the existence of an organizational mission that is to be

achieved through collective effort (Pais & Parente, 2015). Teamwork in a boardroom is

one of the critical determinants of board effectiveness and sometimes more important

than formal heirarchy (He & Huang, 2011).

The concept of teamwork in corporate governance and why it works has been subject to a

lot of research (Chin, 2015; Salas, Shuffler, Thayer, Bedwell, & Lazzara, 2014; Solansky,

Beck, & Travis, 2014). For example, Crowley, Payne, and Kennedy (2014) provide

evidence that supports empowerment and panopticon theories of teamwork.

Empowerment is seen as a managerial strategy aimed at solving problems of inflexibility

and resistance and engenders trust and commitment. Empowerment involves some loss of

the leader’s power or relinquishing some of their authority but this is compensated by the

competitive benefits of increase in organization’s power to accomplish its goals. On the

other hand, panopticon is the disciplinary aspect of teamwork intended to increase effort

and deter sabotage through heightened visibility and peer monitoring and control

(Crowley et al., 2014). The boardroom should be a place of fresh input and thinking,

47

where there is a right balance between challenge and teamwork, while maintaining

cohesiveness of the board (FRC, 2011). Teamwork also refers to collaboratioon and

cooperation and is associated with better judgement and problem solving, which lead to

better productivity, creativity and innovation in organizations (Sandoff & Nilsson, 2016).

Another concept of teamwork is communities of practice, in which learning is transmitted

through participating community and not simply through linear transactions (Bolisani &

Scarso, 2014). The idea of ‘situated learning’ redefines learning from acquisition of

propositional knowledge to co-participation, interactions and other group processes in the

socio-cultural practices of a community (Cordery, et al., 2015). According to Powell and

Pieczka (2016) the idea of communities of practice facilitates concept-led learning, which

is fundamental to the creation of a body of professional knowledge. Consequently, the

professional group promotes higher order thinking across constellations of practice where

uncertainty is valued thus leading to creation of new knowledge and practices (Laxton &

Applebee, 2010).

Effective boards operate as a unit and must have the ability to think and learn together as

a team (Adams, Hermalin, & Weisback, 2010). Effective boards operate as self-

responsible teams that maintain a group culture that supports their work (Carver, J.B &

Carver, 2009). The quality and effectiveness of the board teamwork will depend on the

level of trust in the group (Bailey & Peck, 2013). Recent studies have shown that board

performance is not the result of board structures alone but also director behaviors and

team processes inside and outside the boardroom (Bezemer, Nicholson, & Pugliese, 2014;

Machold & Farquhar, 2013; Machold, Huse, Minichilli, & Nordqvist, 2011).

Heterogeneity in a board encourages interaction and teamwork by promoting diverse

interpretations, different values which trigger behaviours to challenge each other’s

opionions and justify alternate approaches (Mitchell, Boyle, & Nicholas, 2011). While

boards composed of members of diverse backgrounds engage in more debate about goals

and decisions, homogeneity leads to lack of conflict in a board and groupthink (Coles,

Daniel, & Naveen, 2014; Jian, Flores, Leelawong, & Manz, 2016). In most situations,

team performance exceeds that of an average individual though not necessarily that of an

expert (Laughlin, Nelson, & Donaldson, 2011).

48

Sarros et al. (2016) have suggested that it is not the effectiveness of a leader in isolation

that affects organizational performance, but the alignment of leaders across all levels in

an organization. Alignment or misalignment of leaders in an organization may enhance or

detract from successful execution of strategy (O'Reilly et al., 2010). Boards are social

groups and share social norms and values and these lead to bonding and cohesiveness,

which are important constructs for successful group performance and strategic decision-

making (Brown, Buchholtz, Butts, & Ward, 2016). A cohesive team culture creates a

conducive environment to information exchange and the ability to engage in constructive

debate which contributes to the long-term success of the organization (Cumberland &

Githens, 2014).

In their study of 60 chairpersons of U.S publicly held companies during the enanctment

of the Sarbanes-Oxley Act of 2002 (SOX), Brown et al. (2016) hypothesized that the

lower the level of cohesiveness of the board, the lower the board task performance would

be. They further sought to investigate if the relationship between board cognitions and

board task performance was moderated by board cohesiveness. In the study, cohesiveness

was measured by use of eight items: the extent to which the board members were ready

to defend each other, help each other on the job, get along with each other, stick together

under pressure, unite in trying to reach goals of performance, have conflicting aspirations

for board performance, communicate freely about each other’s responsibilities, and take

responsibility for loss of performance. The results of their study showed that board task

performance was higher under conditions of high cohesiveness and that board

cohesiveness reduces the negative impact of affective conflict on performance (Brown et

al., 2016).

An important governance principle and practice is ensuring that the composition of

boards comprise both executives (senior managers in the company) and non-executive or

independent directors from outside the company or the management. Even more crucial,

getting board members with appropriate skills and experiences is imperative for

governance and organizational effectiveness (Spear, Cornforth, & Aiken, 2009). Finding

such qualified board members, especially for co-operatives that would be looking for

volunteers and from the membership, is one of the challenges of governance. The

problems of capacity is further exarcerbated by what Berle and Means (1932) called the

49

‘legal fiction of shareholder control’ where it’s the managers who have the main levers of

power to carry out their responsibilities, even when it the role of the board to control the

organization (Spear et al, 2009).

Transparency in governance comes about when the board organizes and manages its own

work such that it exudes confidence and trust from stakeholders and especially the

management and members of an organization (Thompson, 2015). It includes having a

common agreement about work, clear expectations of individuals and the group itself

which is as a result of effective leadership and decision-making of the board (Scholl &

Sherwood, 2014). While teams enhance the organization’s adaptability and agility to deal

with dynamic and complex environmental contexts, they rarely fully use their resources

of information, competencies and knowledge due to their deficiencies in group processes

(Boak, 2014; Pais & Parente, 2015).

According to Sur (2014), the board is a specialized strategic decision-making team whose

activities include sense-making, i.e. making decisions for crisis situations and future

events. The author uses a socio-psychological typology of our forms of sense-making

processes which assigns the board chair the role of leader and all the other participants as

team members to develop four decision-making processes: First, restricted decision-

making processes, which are characterized by high leader sensegiving and low member

sensegiving, and whose outcome is unitary one time actions. Second, guided decision-

making processes where there is high leader sensegiving, and high member sense giving.

Third, fragmented decision-making process, which is characterized by high member

sense-giving, low leader sense-giving results in high team involvement but poor leader

coordination. The last type is minimal decision-making process which is characterized by

low leader and low members sense-giving, which results in low team involvement and

low leader coordination. The outcome of this process will lead to one time compromise

action (Sur, 2014).

The UK Co-operative Group, with a history of 150 years of existence, was nearly brought

down in 2013 by losses of 1.5 billion sterling pounds (Kelly, 2014). Even after it was

rescued from this near-catastrophic capital shortfall, the group still ended the year with a

loss of 2.5 billion sterling pounds, which immediately brought damaging uncertainty for

50

its 90,000 employees and millions of its members. The report of the independent review

observed, “Failures in board oversight are inevitable if the criteria used to elect its

members do not require those elected to have the necessary skills. Sustained success

requires effective governance. Effective governance requires a high performing board.

The composition of the Co-operative Board, and the limited pool from which its members

were drawn, made a serious governance failure almost inevitable” (p. 124). Lord Myner’s

review reached similar conclusions when he observed that the Co-operative Group’s

governnance architecture and allocation of responsibilities was not fit for purpose as it

placed individuals who didn’t possess the requisite skills and experience into positions

where their lack of understanding prevents them from exercising the necessary oversight

over the Executive (Myners, 2014).

Teamwork is negatively affected by the challenges of its leadership and management and

recommend building relationships among team members by carefully selected activities

and avoiding compartmentalization (Liff & Wikstrom, 2014). According to McInnes,

Halcomb, Bonney, and Peters (2015), team can suffer from confusion around roles and

responsibilities, heierarchy, territorialism, and poor communication. McIntyre and Foti

(2013) emphasize how absolutely essential leadership is for team effectiveness and that

this leadership should be shared and not focusing on the person in charge. Sandoff and

Nilsson (2016) also highlight the role of self-managed teams, which they define as groups

of interdependent employees who have the collective authority and responsibility of

managing relatively whole tasks, but argue that even they need a leader. Siasakos, et al.

(2013) observe that a team leader’s capability and experience are more important than

seniority and hence the importance of focussing on group processes that mere heirarchy

(Sandoff & Nilsson, 2016).

2.4.2. Effect of Participative Governance on Organizational Performance

Participative governance is defined as the capability of the leaders of an organization

participating in the development of a value creating corporate strategy (Eddleston et al.,

2010), on the one hand, and the access that the shareholders and members have a role to

participate in decision-making (Bijman et al.,2013). It also refers to the processes by

which the shareholders voice their views, receive timely communication and information,

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and are involved in important decision-making fora (Achua & Lussier, 2013; Barraud-

Didier, et al., 2012; Dayanandan, 2013).

Participation is about power and how power shapes the boundaries of participatory

spaces, which are either invited or claimed. Participation in governance is access to not

only information but also the opportunity to express preferences and contribute to

decision-making (Pettit, 2012). According to Chaundhuri (2016), invited spaces are those

controlled by planners and policy-makers and which preclude alternative perspectives and

thus reinforce existing privileges. On the other hand, claimed spaces are demanded,

created or chosen by communities and social movements. Participation by itself does not

guarantee real empowerment due to power imbalances in a given context. Emancipatory

participation requires the fostering of critical consciousness within dominated groups as a

precondition to effective participation (Aasgaard, Borg, & Karlsson, 2012). Participation

is purely symbolic if the stakeholders are invited to collaborate but underlying interests

do not serve democracy and a balanced power between the leaders and participants (Borg,

Karlsson, Kim, & McCormack, 2012). This study reviewed literature on participative

governance from three perspectives, namely: members have equal rights; shareholders

participate in decision-making; and board and management share timely information.

2.4.2.1. All members have equal voting rights

Having voice and choice is a condition for participation in decision-making in an

organization (Hendriks & Ewijk, 2016). Voice is a broad rubric that encompasses

everything from information and consultation to organized unions and work-based

mechanisms like quality teams and financial participation schemes (Hendriks & Ewijk,

2016; Timming, 2015). The usage of the terms ‘voice’ and ‘participation’ overlaps and is

sometimes used interchangeably with words such as involvement, shareholder

democracy, empowerment and citizenship, among others (Budd, Gollan, & Wilkinson,

2010). Temkins (2016) observes that the ideal of equality of opportunity, which equal

voting rights exemplifies, plays an important part in contemporary social and political

discourse. Temkins (2016) argues that, although the ideal of equal opportunity would rule

out discrimination on the basis of race, religion, gender, social or economic class, in

reality the poorly educated and the poor do not have the same opportunity in social and

political life as those well educated and connected.

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Democratic member control is one of the seven principles of co-operatives. According to

the International Co-operative Alliance (ICA, 2016), ‘co-operatives are democratic

organizations controlled by their members, who actively participate in setting their

policies and making decisions. Men and women serving as elected representatives are

accountable to the membership. In primary co-operatives members have equal voting

rights (one member, one vote) and co-operatives at other levels are also organized in a

democratic manner’. The concept of participative governance, earthed in social and

political sciences, is gaining traction in public administration and public action due to the

move from hierarchy and bureaucracy towards markets and networks (Bevir, 2011).

Co-operatives are patron-owned organizations with a defining feature in their governance

of strong democratic member control. There is now strong empirical evidence that shared

ownership of means of production by all workers in a co-operative model, accompanied

by high levels of participation, has positive effects on working environment and

relationships (Cheney et al, 2014; Avey, Wensing, & Palanski, 2012). In co-operative

thought and ideology, it is now recognized that democratic principles are applicable to

economic activities and can be superior to autocratic practices in running businesses

(MacPherson, 2012).

However, research into agricultural co-operatives in North and South America, North and

South Europe and Oceania by Chaddad and Iliopoulos (2013) shows that there is a

continuum of integration from full member control or integration where principals retain

formal and real authority, to the other extreme of a complete loss of member control. In

between, there is the traditional or quasi-integration model, through to a separation model

where principals delegate authority to a board of directors, to a managerial and corporate

model where principals delegate to management both formal and real authority.

According to Yermack (2010), the rights of shareholders to choose members of the board

of directors, approve strategy, as well as amend the constitution of their organization lies

at the heart of corporate governance protections. Shareholders are the providers of risk

capital for their firms and as such they need to be able to protect their investment by

ensuring good governance practices and strategy are in place for the company’s overall

performance and sustainability (Mallin & Melis, 2010). Hamlin and Jennings, (2011)

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show that voting can be either expressive or instrumental. Instrumental voting focuses on

the expected benefits associated with the outcome of the election. On the other hand,

expressive voting is motivated, not by the outcomes expected, but by just making a point

or to express some aspect of the voter’s beliefs, values, ideology or personality regardless

of any impact the vote has on the election outcome (Blankart & Margraf, 2011; Hillman,

2010).

The John Lewis Partnership (JLP) in the United Kingdom is one of the most celebrated

successes in organizational democracy. JLP was founded by John Spendan Lewis with a

vision of a co-owned business based on the principle of sharing knowledge, gain and

power. The workers of the JLP participate in the decision-making of the business and

have equal rights irrespective of status, although the interpretation of voice and power in

decision-making has not always been unanimous between the managers and the workers.

In a study to explore the practice of employee involvement and participation at the JLP,

Cathcart (2013) found that democracy in co-operative-like organizations needs to be

understood as a contested terrain and yet an important pillar in organizational

effectiveness and performance. The study found that organizational democracy was a

moving target subject to constant challenge and reinterpretation and so required vigilance

and protection from potential degeneration.

Set in a different context in Sri Lanka, a study by Adikaram (2016) arrived at similar

conclusions as Cathcart (2013) that democracy and giving voice in an organization is a

moving target. The study by Adikaram targeted 180 employees of an IT company and

whose responses indicated that they were not properly heard and also not happy with the

communication from senior managers A decision had been to establish a Joint

Consultative Council (JCC) at the company to promote communication and employee

involvement at the company. The study found that at first the JCC was concerned only

about the ‘tea, towels, toilets’ issues as the employees believed that all they had was a

‘voice without muscle’ (Gollan & Patmore, 2013) devoid of any decision-making power.

Only after enhancing and institutionalizing the joint decision-making processes and

improving communication did the management regain the trust of the employees. The

benefits of voice by followers has also been underlined by the research of Gollan and

Patmore (2013) who observed that only by establishing mechanism that enable followes

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to have legitimate voice will managers be able to obtain productive outcomes for their

organizations.

While some scholars have argued that shareholder voting is potentially the most powerful

instrument that they can use to secure their residual claims on the firm (Mallin & Melis,

2010), the available evidence has been mixed. On the affirmative side, Yermack (2010)

argues that shareholders can vote down any proposal that they consider value decreasing,

which he describes as shareholder dissent or expressive shareholder democracy. Yermack

(2010) argues further that the rights of shareholders to elect board of directors and be

custodians of the firms governing articles and policies give them ultimate power over

corporate decisions (Celis & Mugge, 2017). Hillman et al. (2011) amplify this point

further by noting that voting rights provide shareholders with the ultimate weapon to

refuse election or re-election of directors who may be favoured by the incumbent board.

However, other scholars have observed that shareholder dissent, expressed through voting

and participation, is simply a ‘paper tiger’ rather than an effective corporate governance

practice (Cai, Garner, & Walkling, 2013). In practice, shareholders may submit proposals

for consideration by their assemblies, but these typically hardly fare better than board-

sponsored proposals (Cziraki, Renneboog, & Szilagyi, 2010).

The role of dialogue and open communication in fostering democracy in organizations

has been shown to be a sign of a gradual shift from earlier traditional forms of

communication in which heated arguments and debates settled differences (Akella, 2016).

Dialogue visualizes communication as a two-way process where participants think

together and create new perceptions or reality, build coonnections and relationships, and

which may lead to emerging ideas and consequences (Ganesh & Zoller, 2012). Dialogue

and voice by employees to express opinions have also been linked to organizational

identification (Atouba, Carlson, & Lammers, 2016). However, dialogue does not

guarantee followers’ voices being heard or participation in decision-making as it can turn

out to be a façade in which the more powerful can use as an empty rhetoric intended to

impose their preferences over the less powerful (Akella, 2016). Dialogue can also be

fragile and vulnerable to manipulation by more by more powerful agents, especially in the

context of inequality (Ganesh & Zoller, 2012). Employees are especially suspicious of

management-led process of dialogue as they are seen as inducement to reveal their

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feelings and opinions in order to avoid conflicts and indoctrinate them to management’s

way of thinking (Akella, 2016).

Critical to the health of the co-operatives is the principle of one member one vote, which

gives cooperators the ultimate control over appointed management and aims at balancing

managerial direction with employee-owner’s concerns. In a review of the Mondragon

system of co-operatives, Cheney et al. (2014) noted how members have ultimate control

over the management through the general assembly which is based on the one member

one vote principle. In addition, the Mondragon co-operatives had developed social

councils whose aims were to balance managerial direction with members’ concerns. The

principal of one member one vote in the co-operatives is contrasted with the ‘plutocracy’

in investor owned firms in which large shareholders have more voting rights than small

shareholders, which is also at odds with the foundational principle of shareholder

democracy (Sauerwald, Van Oosterhout, & Essen, 2016).

In an empirical study to survey co-operatives in China’s Zhejiang province, Liang, et al.

(2015) investigated four characteristics of participative governance, namely: democratic

decision-making procedures, participation in decision-making, member exit, and profit

allocation. The study found that the distribution of ownership rights, and even profits, in

the farmer co-operatives were skewed towards a small proportion of core members to the

exclusion of the majority. For example, while Chinese Law allows for one member one

vote, the practice was that members delegated their voting rights to core members.

Similarly, member participation in decision-making was only nominal as most decisions

(over ninety percent) were made by the board members and management, who were part

of the small core group who controlled the co-operatives.

2.4.2.2. Shareholders participate in decision-making

Defining participation is not a straightforward enquiry and it is easier to describe it with

other words such as collaboration, deliberation, involvement, engagement and co-

management (Carr, 2015). Nevertheless, the “World Bank Participation Sourcebook”

(1996) defines participation as a ‘process through which stakeholders influence and share

control over development initiatives and decisions and resources which affect them’. The

goal of participation is shareholder empowerment, which Goranova and Ryan (2015)

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define as shift in the allocation of power from corporate officers and directors to

shareholders. The shift in power, especially in emerging economies where minority

shareholders do not get sufficient protection, renders managers and directors more

accountable as shareholders’ interests receive greater attention and protection than in

purely board-centric models of governance (Goranova & Ryan, 2015).

Participatory development has been widely touted as necessary in making aid more

effective, pro-poor, domestically-driven, relevant and sustainable (O'Meally, 2014). The

World Bank has been an intellectual and financial leader in participatory development,

noting that ‘involving local communities in decisions that affect their lives is central to

making development more effective, and it has the potential to transform the role that

poor people play in development by giving them voice and agency’ (World Bank, 2012).

Focusing on the role of participatry development in combating extreme poverty, the

World Bank noted that ‘citizen voice can be pivotal in providing the demand side

pressure…that is needed to encourage full and swift response to citizen needs (Kim,

2013).

The democratic participation of the members is predicated on trust as it explains their

favorable behavior and commitment towards the co-operative. Trust is dependent on the

cooperative’s capacity to act competently, reliably and to take the right decisions while

still showing goodwill and closeness to members. In a study of 259 members of French

agricultural co-operatives, Barraud-Didier, Henninger, and El Akremi (2012) showed that

there is a positive link between trust, commitment and participation. Members participate

in the governance of their co-operative when they are attached to it affectively and this is

enhanced by better communication and sharing of information. In a study to analyze the

factors of farmers’ participation in the management of co-operatives in Finland, Sumelius

(2010) concluded that equality, fairness, trust, and managers’ personal charisma can

improve members’ willingness and participatory behaviour in co-operative management.

Additionally, the study also found that members’ education level also affects their

frequency of interaction with the more educated and likely to understand and

communicate more.

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One of the criticisms of the notion that good corporate governance, and in particular

prescriptions to ensure oversight over management lead to firm performance, is that these

assumptions may not hold during a time of crisis. Using a large sample of 1,197 firms

across 26 European countries, Essen, Engelen, and Carney (2013) showed that managerial

discretion and CEO duality might be required during a time of crisis. They concluded that

the efficacy of governance mechanisms, including member control, may be contingent

upon organizational and environmental circumstances. Shareholder participation in the

decision-making processes of a firm, especially voting, has also been shown to lead to

short-termism, profit maximization, and to favor capital over labor (Talbot, 2013).

Another criticism of co-operative democracy and participation is that it clashes with

efficiency demands and economies of scale. In order to examine this dilemma, Jones &

Kalmi (2012) studied the Mondragon Co-operative in Spain and Co-operatives in Finland

and showed that the evidence for the trade-off between efficiency and economies of scale

was not sustained.

Several theoretical frameworks conceptualize participation according to the degree of

participant involvement, position and power in decision-making. Arnstein’s ladder

(Arnstein, 1969) of participation has eight rungs which can be divided into three levels.

The bottom rungs of the ladder are manipulation and therapy which comprise ‘non-

participation’ that is contrived to substitute for genuine participation. The real objective

of this level is to enable the powerholders to ‘educate’ or ‘cure’ the participants into

silence. The middle rungs comprise informing, consultation and placation, which

comprise the ‘tokenism’ level. The main objective for this level is to allow the ‘have-

nots’ to hear but not to have a voice. Even when people at this level are informed or

consulted, they may indeed hear and be heard, but they lack the power to ensure that their

views will be heeded by the powerful as they have no ‘muscle’. Only at the highest rungs

of partnership, delegated power and citizen control, comprising citizen power does the

decision-making clout increase and participants can negotiate and engage in trade-offs

with traditional power holders (Carr, 2015).

Similar to Arnstein’s Citizen’s Ladder of Participation is Pretty’s typology (Pretty, 1995),

which was aimed at participatory methods in agriculture. According to Pretty,

participation ranges from manipulation and passive participation at the lowest levels;

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consultation, material incentives and functional at the middle levels; and interactive and

self-mobilization, at the highest levels. The various levels in Pretty’s typology refer to the

extent of involvement in activities and the control participants have over outcomes.

Another typology of participation is by Michener (1998), which classifies participation

from two extremes: whether it is planner centered or people centered. Michener’s work

was based on rural communities in Burkina Faso and highlights the apathy and reluctance

of sections of the community to get involved in participatory processes (Ng’ombe,

Keivani, Stubbs, & Mattingly, 2012).

The debate on participation has been shifting away from representative democracies

where stakeholders are represented by intermediary stakeholders to participatory models

where there is a direct link between the community and the state or organization

(Cornwall, 2011; Cornwall, Robins, & Von Lieres, 2011; O'Meally, 2014). This shift is

what some scholars have called “participatory governance” (Fung, 2002), “post-

participation” (Reed, 2008), and “empowered deliberative democracy” (Gaventa, 2002).

The shift to participatory democracy is informed by the growing loss of confidence in

state institutions and public organizations as a result of widespread reports of lack of

accountability and responsiveness (Ganuza, Nez, & Morales, 2014; Ng’ombe et al.,

2012). The appeal to participative governance in community engagement lies in the

ability to create a governance architecture that supports actively engaged and responsible

citizens on the one hand, and inclusive, open and responsive institutions, on the other

(Commonwealth Foundation, 1999). Participation can help develop credibility and trust

among the stakeholdes in an organization (Cornwall, 2011).

Participation in decision-making has been shown to enhance quality working

relationships, less conflict, better interpersonal communication and ultimately resulting in

higher organizational performance (Bernardes, et al., 2015). Yermack (2010) notes that

shareholder wealth increases with shareholder democracy expressed by voting. In

addition to director elections, shareholders also vote on other important issues such as the

strategic direction the firm is taking, as well as amendments to the corporate charter or

bylaws. Participation suggests a balanced distribution of ownership (Belle, 2016), co-

determination (Kristiansen & Bloch-Poulsen, 2011), and co-construction (Raes, Kyndt,

Decuyper, Bossche, & Dochy, 2015). Participation in itself does not necessarily lead to

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equal participation as the legitimacy of partnerships can be undermined by power

imbalance, lack of accountability and resource differentials between the various partners

(Bell & Stockdale, 2016). Equally, and as Belle (2015) posits, mere presence does not

equal participation and neither does representation, but participation must be intentional,

experiential and motivational. Meaningful engagement and participation characterizes

learning organizations as they engage in critical reflection (Matsuo, 2015; Newig,

Kochskamper, Challies, & Jagger, 2016).

In a study of 30 rural and community banks in Ghana, Aboagye and Otieku (2010) found

that when ownership incentive to monitor and control management is weak, the

association between the banks’ state of corporate governance and their organizational

performance was weak. The study found that the regulation by the Ghana Central Bank

that ownership of rural and community bank be limited to 30 percent as not being enough

incentive for the cost of management monitoring and control. In a similar study of eight

co-operatives in Ethiopia targeting a sample of 125 members, Dayanandan (2013) found

out that lack of members’ involvement in business participation, lack of transparency and

accountability led to a weak performance. In order of importance, the top three factors

that respondents identified for hindering good governance were lack of participation, lack

of accountability and lack of transparency. In the same study, the top three reasons the

respondents gave for the above factors hindering good governance were lack of

knowledge on co-operative values and principles, poor service delivery to the members

and negligence of the members by the directors. A similar study in Ethiopia comparing

individual farmers with those in dairy co-operatives showed that co-operative

membership had a positive impact on productivity (Francesconi & Ruben, 2012).

Shareholder empowerment and activism arising out of a changing external environment

can also motivate participative governance (Brown, et al., 2016; Goranova & Ryan, 2014;

Ryan, Buchholtz, & Kolb, 2010). A case in point is the changing regulation as a result of

corporate scandals in North America that led to the enactment of the Sarbanes-Oxley Act

of 2002 (SOX) which resulted to the increased shareholder power over boards and

demand for vigilance and accountability (Dah, Frye, & Hurst, 2014). Drawing on the

social cognitive theory, which describes how groups acquire certain behavioural patterns

due to ennvironmental influences, Brown et al. (2016) examined how directors reacted to

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increased pressures to be more accountable and vigilant in the wake of SOX (Pugliese,

Minichilli, & Zatton, 2014). Their study comprised of 60 board chairpersons drawn from

US publicly held companies selected from the Investor Responsibility Research Center

and ExecuComp databases and who served before and after the enanctment of SOX.

Results revealed that increased shareholder empowerment and participation led to

improvement of director oversight, activism in influencing favourable legislation and

regulation (Ryan et al., 2010), and provision of advice and counsel to management

(Joseph, Ocasio, & McDonnell, 2014).

However, while participation in decision-making is well intentioned, its practice has

mixed results for many co-operatives. Cathcart (2013) noted that while participation was

intentioned by the management of John Lewis Partnership as a means of facilitating high

employee involvement for sustained competitiveness, in practice it turned out to be a

means of cultural control of employees. In a similar study of governance of co-operatives,

Liang et al. (2015) collected data from 37 fruit and vegetable co-operatives in the

Zhejiang Province of China. The study found that the co-operatives had merged the

management and boards, thus creating a core group of members who made all the

decisions and shared most of the profits. Ribot (2011) has also cautioned that

participation can be manipulated into an indirect rule when it uses organizations or

processes to carry out externally conceived commercial projects. This kind of

participation is what Williams (2011) calls “the new tyranny of development”, which

Ribot (2011) argues that it amounts to forced labor as it is implemented without adequate

representation.

In a critique of the World Bank’s practice of participatory development, O’Meally (2014)

proffers three main arguments to show the contradictions of the pro-poor and

empowerment credentials of the approach. First, O’Meally suggests that participation is a

guise, a buzzword, one-size-fits-all development recipe, and a vacuous rhetoric that

masks ulterior motives of promoting neo-liberalism (Golooba-Mutebi & Hickey, 2010).

O’Meally’s second argument is that participation is disciplinary in that the Bank’s

participatory development model seeks to discipline behavior and regulate social and

political action down to the grassroots. This argument perceives the Bank to be a vehicle

for deepening and socializing the neo-liberal agenda by pushing the participatory

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budgeting approach (Goldfrank, 2012). The third argument, “participation as

incongruent”, suggests that the Bank’s participatory initiatives can have ameliorative and

transformative effects. According to this argument, whatever the Bank’s other credentials,

its participatory approch may have some fluid, ambigous and progressive impact

particularly through opening up spaces for debate and practice (Hickey, 2010).

2.4.2.3. Board and management share timely information

According to the UNCTAD (2010) report on “Corporate Governance in the Wake of the

Financial Crisis”, weak shareholder rights limit the ability of shareholders to hold boards

to account, while fairness and transparency in financial markets inspire confidence and

facilitate increased investment. A similar report released the same year by the European

Association of the Co-operative Banks (EACB, 2010) restated the need for a stronger

customer focus, greater integrity and ethics and improved transparency if co-operative

banks were to continue weathering the financial crisis of the late 2000s. Transparency and

disclosure have been shown to have a positive relationship to organizational performance.

On the other hand, the G20/OECD “Principles of Corporate Governance” (OECD, 2015)

state that the corporate governance framework should protect and facilitate the exercise of

shareholders’ rights, which include: the right to relevant and regular information of the

company; the right to participate and vote in shareholder meetings; the right to elect and

remove members of the board; and the right to share in the company’s profits.

The OECD (2015) principles support stakeholders’ access to information on a timely and

regular basis and their rights to obtain redress for violations of their rights. The

disclosure and transparency that the OECD principles call for include key areas such as

financial and operating results, company objectives, major share ownership,

remuneration, risk factors, among others. The notion of transparency refers to openness,

disclosure, and access of information either unsolicited or on demand (Niforou, 2014). In

order to promote shareholder participation and counter capture of decision-making by

narrow interests in an organization, accessibility of information is critical (OECD, 2014).

Some studies that have shown importance of transparency in accessing information

include a Canadian study using panel data from 289 firms over a four year period. The

results of the study suggested that publishing corporate governance rankings was related

to the firms’ market value and accounting results (Bethelot, Morris, & Morill, 2010). In a

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another study of UAE banks to investigate the importance of disclosure transparency,

executive compensation and relationship with shareholders, Al-Tamini (2012) found a

positive relationship of disclosure transparency, shareholder interests and the role of

board of directors.

In a study of agricultural co-operatives, Choi et al. (2014) surveyed 52 primary co-

operatives and collected questionnaires from 220 directors in order to study the effect of

democratic participation and economic participation on firm performance. The results

showed that the Board of Directors’ communication with the members had positive effect

on democratic participation and organizational performance of a co-operative.

Additionally, economic participation also had a positive effect on the organizational

performance of the co-operatives. The study concluded that focusing on member

participation is more than a good value for co-operatives but also tied to organizational

performance.

2.4.3. Effect of Human Capital on Organizational Performance

The Encyclopedia Britannica defines human capital as the ‘intangible collective resources

possessed by individuals and groups within a given population. These resources include

all the knowledge, talents, skills, abilities, experience, intelligence, training, judgment,

and wisdom possessed individually and collectively, the cumulative total of which

represents a form of wealth available to nations and organizations to accomplish their

goals’ (Huff, 2015). Neeliah and Seetanah (2016), on other hand, define human capital as

a set of knowledge, abilities and skills, used in activities, processes and services that

contribute to stimulate economic growth. According to Felıcio, Couto, and Caiado

(2014), the relevant characteristics of human capital are education, experience and

knowledge, all of which allow access to a broader range of opportunities. For corporate

governance, human capital characteristics include knowledge of the industry, skills and

experiences that individual board members bring to the strategic-decision process, and the

overall familiarity with the firm (Johnson, Schnatterly, & Hill, 2013).

Nkundabanyanga, Balunywa, Tauringana, and Ntayi (2014) conceptualize human capital

as including leadership, problem solving ability, work environment interaction,

recruitment and selection, employee relations, and employee welfare. The authors further

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posit that human capital includes training and development, entrepreneurial skills, equity

issues, career paths, rewards and recognition, employee satisfaction, employee safety,

employee retention, employee relations, knowledge, functional skills and experience.

This study reviewed human capital using three categories: board and senior management

knowledge and skills; board and senior management experience; and board diversity.

2.4.3.1. Board and Senior Management Knowledge and Skills

High performing organizations require board members with adequate qualifications, high

levels of intellectual ability and experience (Choi, Sul, & Min, 2012). Board members

with higher qualifications provide for their firms critical thinking and a rich source of

innovative and strategic ideas (Gaur, Bathula, & Singh, 2015). In order for firms to

effectively compete and be innovative, they rely on their strategic assets such as

knowledge and their dynamic capabilities. For this to happen, the firms need a continual

upgrading of their skills and knowledge in order to manage, share and use information

effectively (Claver-Cortés, et al., 2015). To be competitive, firms depend a lot more on

endogeneous factors - individuals’ skills and competencies, rather than simply on

effectively executed programmed activities. It is the sum of these skills and competencies

that are referred to as intellectual capital, while a subset of it – human capital, comprises

not only the knowledge, skills and capabilities, but also their capacity to generate all those

resources (Vaz, Rocha, Werutsky, Selig, & Morales, 2015).

Closely related to human capital is the concept of intellectual capital, which is defined as

a form of knowledge, intellect and brainpower activity, which uses knowledge to create

value (Shih, Chang, & Lin, 2010). Other researchers see intellectual capital to also refer

to the aggregation of all knowledge and competencies of employees that can bring

competitive advantage for their firms or any knowledge capabilities stemming from

manpower, creativity and innovation (Claver-Cortés, Zaragoza-Sáez, Molina-Manchón,

& Úbeda-García, 2015). Al-Musali and Ismail (2015) introduce yet another concept in

their definition of intellectual capital which, according to them, refers to the economic

value of two categories of intangible assets of a firm, that is, human capital, and

organizational (structural) capital. They define human capital (HC) as the knowledge,

qualifications, experiences and skills employees take with them when they leave the firm

(Zeghal & Maaloul, 2010), and structural capital as the knowledge that remains with the

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firm after employees leave or the result of HC’s past performances (Abdulsalam, Al-

Qaheri, & Al-Khayyat, 2011). Shih et al. (2010) agree with this classification and

describe human capital as employees’ competencies and human resources of external

parties accessible by companies.

Human capital is not tradable and not owned by the organization as it is generated by the

professional knowledge and skills of employees. Structural capital, on the other hand,

refers to corporate flows, software systems and supply chains and can be further

subdivided into flow capital, innovation capital, and relationship capital (Shih et al.

(2010). Nkundabanyanga, Ntayi, Ahiauzu, and Sejjaaka (2014), who define intellectual

capital as the aggregate expression of intangible assets possessed by the organization,

suggest that construct comprises human capital, relational capital and structural capital.

Intellectual capital has been shown as an indispensable business parameter in enhancing

overall organizational performance and primary source of superior competitive advantage

(Latif, Malik, & Aslam, 2012). But not all intangible assets become intellectual capital.

According to Scafarto, Ricci, and Scafarto (2016), only those intangible assets which

possess the necessary requisites of strategic resources become intellectual capital. This

school of thought opines that intellectual capital consists of knowledge that creates value

identifiable on the market or the benefits the customers pays for.

In their study to investigate the relationship between intellectual capital (IC) and business

performance, Scarfarto et al. (2016) divided IC into four subconstructs: human capital,

relational capital, innovation capital, and process capital. To measure human capital, the

proxy variables used were labour and related expenses, which included wages, salaries,

pension, etc. (Sydler, Haefliger, & Pruksa, 2014). For relation capital, the proxy variables

they used were selling, general and administrative expenses, which included expenses not

directly attributed to the production process but related to sales and administrative

functions (Gourio & Rudanko, 2014). Innovation capital referred to research and

development expenses, which included all direct and indirect costs related to the creation

and development of new processes, techniques, applications and products with marketing

possibilities (Goebel, 2015). For process capital, the proxy variables chosen were fixed

assets turnover, and this was computed as the ratio of next annual sales to average fixed

assets (Yu, Wang, & Chang, 2015).

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In another study by Claver-Cortés, et al. (2015), their multiple case studies of human

capital intangibles involving 25 international family firms, identified ten variables and 60

indicators. The ten human capital intangibles in family firms were: leadership, self-

motivation, entrepreneurship, commitment (feeling of membership, dedication and shared

identity), emotional family component, creativity, skills, capabilities and knowledge

acquired from family members, parent-child relationships and relationships between

successors, and knowledge owned by family professionals. The study underlined the

importance of not only identifying these intangibles, but for managers to become aware of

their importance and improve the management of the human capital attributes. Valuing

and developing human capital intangibles creates differentiated advantages to boost

corporate competitiveness (Shih et al., 2010).

Attempts at measuring the financial value of human capital have met with mixed results

and most scholars rely more on inferences about human capital resource (Jiang, Lepak,

Hu, & Baer, 2012; Rabl, Jayasinghe, Gerhart, & Kuhlmann, 2011). The neglect of the

issue of financial valuation of human capital gives the perception that management is a

soft science relative to accounting, finance and operations management, and other areas

that have clear and understandable financial value and terms. This lack of financial

valuation of human capital may also make it difficult to persuade others of its relative

contribution to the organization’s success which may affect the allocation of resources to

the most important asset of an organization (Fulmer & Ployhart, 2013). However, recent

scholarship has seen development of systems to test human capital constructs such as

aggregated measures of individual’s knowledge, skills, abilities, and other characteristics

(KSAOs) or indices of tenure, education or skill (Nyberg, Moliterno, Hale Jr, & Lepak,

2014).

Research has shown that higher levels of education in an organization leads to better

ability of board members and management to process information, absorb new ideas and

find creative solutions to problems. In a study of 562 board members of 45 listed Spanish

companies to investigate board influence on a firm’s internationalization, Barroso et al.

(2011) found out that directors’ managerial experience and a high academic achievement

affected the degree of international diversification. Greater education level was also

associated with receptivity to innovation and tolerance for ambiguity. Similar results were

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obtained by Dalziel et al. (2011), who demonstrated that education, entrepreneurial

finance experience, and technical experience significantly influenced R&D spending.

Greater educational level has also been shown to be associated with receptivity to

innovation and technology (N. Kim & Kim, 2015), openness to change, tolerance to

ambiguity, and ability to introduce control systems (Chen, 2014; Gottesman & Morey,

2010; Kirca et al., 2010).

Selecting the chief executive of an organization is among the most important and delicate

roles of a board (Adams, et. al, 2010; Schwartz-Ziv & Weisbach, 2013), but it is often a

difficult role as selection process is expected to evaluate such intangible areas such as

personality, integrity, technical skills and experience (Darmadi, 2013). This is the same

dilemma that confronts an organization in choosing board members. Since the

identification and measurement of such capabilities are difficult and costly, Bhagat,

Bolton, and Subramanian (2011) state that educational qualification may be used as a

proxy for knowledge and skills.

According to the study by Bhagat et al. (2011), the quality and relevanance of that

education may be debatable but the facts of its existence are verifiable. In the work by

these researchers, data from 1,800 CEOs of Standard & Poor’s Composite 1500

companies, was analyzed to determine the effect of education on CEO turnover and firm

performance. In order to measure the quality of education, rankings of different programs

were used in order to obtain various categories: Undergraduate Top 20, attainment of an

MBA, MBA from Top 20, Law degree, Law degree from Top 20, or Masters degree. The

results showed no strong evidence of a relationship between CEO education and firm

performance, but a weak evidence that a CEO having an MBA from a Top 20 business

school enables better operating performance and Tobin’s Q (Bhagat et al., 2011).

Darmadi (2013) obtained different results from a study to examine the influence of the

educational qualifications of board members, including the CEO, on the financial

performance of Indonesian listed firms. The study comprised 160 firms listed on the

Indonesian Stock Exchange from which annual reports were collected to provide

information on the educational qualifications of the members. The dependent variable,

firm performance, was measured by ROA and Tobin’s Q. In order to measure educational

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backgrounds of the CEO and board members, the study employed four measures, namely

postgaduate degrees, degrees obtained from presitigious domestic universities, degrees

from universities in developed countries, and degrees in financial fields. The results of the

study showed that postgraduate degrees and degrees from prestigious domestic

universities positively influenced firm performance. The study also found that the firms

whose CEOs hold a postgradaute or top-university degree were better performers than

their peers. Tseng and Jian (2016) also obtained similar results and found that Taiwanese

firms were more likely to be successful in brand development when their board members

were educated at top-ranked universities both domestic and abroad, and especially those

who studied top MBA programs.

2.4.3.2. Board and Senior Management Experience

The question of whether board members’ and senior management experience are

associated with productivity has been a matter of great research interest and also

controversial (Cornelius, Moyers, & Bell, 2011; Daveri & Parisi, 2015; Jones, 2010; Jung

& Ejermo, 2014). For example, Jones (2010) observed that great achievements in

knowledge are produced by older innovators now than was the case last century. He

further noted that Nobel Prize winners and great inventors were inproductive at younger

ages when they would have been engaged in undertaking education and other forms of

human capital investment. Jones (2010) further posits that innovator productivity

increases with experience as every successive generation needs to build on the last

without re-inventing the wheel.

Daveri and Parisi (2015) are in agreement with the argument that productivity of workers

depends on experience as well as other traits such as education, skills, motivation,

intellectual and physical abilities. However, Jung and Ejermo (2014) arrived at a different

finding, that the age of inventors has been falling in all areas despite levels of education

with the the average being between 40-47 years in Europe, Japan and United States.

In a national study of 3000 nonprofit executive directors entitled “Daring to Lead, 2011”,

Cornelius et al. (2011) note that one in three (32 percent) respondents reported being

either unsatisfied or only a little satisfied with board performance. For the executive

directors surveyed, newer leaders were particularly challenged in establishing effective

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partnerships with their boards and especially in regard to the input the directors provided

in strategy and resource development as well as personal support. The study underlined

the need for capable and experienced board members especially during executive

transitions and ongoing involvement and support for new executives beyond the hire.

Another concept related to human capital is social capital which Felicio, Couto, and

Caiado (2014) view as a product of of multi-complex networks through a combinations of

work and friendship relationships. It encompasses the context, stock of relationships,

interpersonal trust and norms between individuals and knowledge sharing in

organizations (Felıcio, et al., 2014; Hasan & Bagde, 2013). Andrews (2012) posits that

the concept of social capital is a latent construct that cannot be observed directly but

whose dimensions are susceptible to observation. According to Johnson, Schnatterly, and

Hill (2013), the board social capital is built by the directors’ social relationships and can

be divided into three types. First, ties to other firms in which directors have links to firms

in which they have full-time employment. Through these ties, information and resources

can flow both ways and can have both positive and negative consequences (Stuart & Yim,

2010). The second type of social capital is personal relationships or loyalty relationships

of the directors, which may facilitate more open communication or compromise their

independence (Platt & Platt, 2012). The third type of social capital is the social standing

of the directors. This comprises the directors’ status, prestige and reputation and these can

have a mixed influence on the perception others will have of the firm (Johnson,

Schnatterly, Bolton, & Tuggle, 2011).

Social capital, an important competency that leaders bring to an organization, has also

been conceptualized as a structural and attitudinal phenomenon that is the property of

communities, rather than individuals, and can be harnessed to achieve desired outcomes

for an organization (Andrews, 2012). However, other researchers see social capital as also

comprising managerial social capital, which is the top manager’s network with his or her

stakeholders through which there is a reciprocal exchange of values (Ryu, 2015). Ryu

(2015) counter-balances his position by also suggesting that even if a manager develops

social capital with reputable people for his or her own sake, the social capital may lead to

a better organizational reputation as the manager is a representative of the organization in

the community.

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The role of the board as a source of human and social capital has been shown to be more

important than its control role (Knapp, Dalziel, & Lewis, 2011). The resource dependence

theory focuses on the board as a human capital resource in using their power, knowledge

and skills to advise the senior management, thus giving the organization competitive

advantage (Neville, 2011). Externally, the board uses its human capital to bridge the gap

between the organization and its environment and serve as a source of attracting

resources, thus adding value to the firm. This external role is more aligned to stewardship

theory (Davis et al., 1997) in which the board serves and advises the senior management

(Arosa, Iturralde, & Maseda, 2010). The internal and external dimensions of social capital

have been referred to as bonding and bridging social capital, respectively (Menahem,

Doron, & Halm, 2011; Ryu, 2015). Bonding social capital consists of inward looking and

closed networks that tend to reinforce exclusive identities and homogeneous groups,

while bridging social capital is defined as open networks that are outward looking and

consist of people across diverse social groups (Menahem, 2011).

According to the study findings of Menahem (2011), groups exhibiting bonding capital

surround themselves with closed, cohesive networks and limit flow of information and

diversity of resources, thereby weakening community level collective actions. On the

other hand, groups tied with bridging capital promote access to information and diversity

engagement by others resulting in higher organizational performance (Andrew & Carr,

2012; Menahem, 2011).

Corporate governance literature highlights the two main tasks of the board are the

exercise of control and provision of advice (Cabrera-Suárez & Martín-Santana, 2015).

According to the stewardship theory (Davis et al., 1997), decision makers can show pro-

organizational behaviour and, instead of opportunistic behaviour explained in agency

theory (Clarke, 2015), support and advise the management instead of just controlling

them (Bammens, Voordeckers, & Gils, 2011). The huge need for experienced board

members has raised the demand for adults over 50 years of age who can be volunteer

directors (Walton, et al., 2017). According to the US Bureau of Labour Statistics (2015)

nearly half of all volunteers (48 percent) in 2015 were between 45-64 years. In addition,

the 56 median hours spent volunteering by the 55-64 year olds exceeded the hours

volunteered by the younger age groups and was only eclipsed by the 94 median annual

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hours volunteered by those 65 years and older. When it came to the volunteer activity for

the various age groups, about a third (28 percent) of all volunteers 45 years and older

provided professional services or management assistance including serving on a board

(US Bureau of Labor Statistics, 2015).

Volunteers in boards use their means – one’s individual assets that promote and facilitate

their contribution to a cause or organization (Walton, et al., 2017). In a study of

volunteerism in the United States, Einolf and Chambre (2011) describes three major

theoretical perspectives on volunteering: social theories stress the importance of context,

roles and integration; individual characteristic theories emphasize values, traits and

motivations; while resource theories focus on skills and free time. Einolf and Chambre

(2011) conclude that individuals with higher resources such as education, skills, free time

and wealth are more likely to volunteer and also more likely to be recruited to volunteer.

Mocan and Altindag (2011) argue that, since leisure is a normal good, then economic

theory predicts that individuals with more assets will engage more in volunteering as

leisure, a view supported by Wilson (2012) and Youssim, Hank, and Litwin (2015).

The experience of board members and senior management team is an asset for an

organization that is going through culture change (Allan, et al., 2014; Boyal & Hewison,

2016; McLarty, Highley, & Alderson, 2010). Such experience becomes a source of advice

for the CEO or other managers and become a source of competitive advantage for the

firm (Heyden, Doorn, Reimer, Bosch, & Volberda, 2013). The diverse experience that

members of the board bring to an organization is important in their role in shaping

strategic focus and performance, with the longer tenure implying greater socialization and

shared frames of reference (Tuggle, Schnatterly, & Johnson, 2010). Tuggle et al. (2010)

further assert that by bringing their functional experiences to the board, senior managers

bring histories of successfully approaching and solving problems. Conversely, boards

with heterogenous backgrounds bring greater breadth of knowledge and valuable non-

firm specific problem solving knowledge, which are equally important for enriching

strategy (Heyden, Oehmichen, Nichting, & Volberda, 2015).

In a case study research of the voluntary sector, Corfield and Paton (2016) found out that

modeling and leadership support for knowledge management at senior level was

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necessary for culture change. Similar findings were advanced by Lee, Hebaishi, and Hope

(2015) in their study to investigate the role of the senior management in developing and

achieving a successful enterprise. The research highligthed the pivotal role played by

those in leadership positions and the influence such leaders have on their followers (Pihie,

Asimiran, & Bagheri, 2014). It is the role of senior management to identify, manage and

develop the high potential in their employees so that, in time, they replace them in

management (Juhdi, Pa'wan, & Hansaram, 2015).

According to Pozen (2010), members of many boards lack sufficient expertise in the

industries of the firms they govern and devote little to understand the complexities of the

company’s operations (Campbell, Coff, & Kryscynski, 2012). Pozen (2010) cites the

example of Citigroup whose board, in 2008, was ‘filled with many luminaries from many

walks of life’ and yet only one of its independent directors had ever worked in a financial

services firm. General human capital or the directors’ extensive prior experience at top

management levels or boards of other organizations is a source of competitive advantage.

Individuals with more human capital and expertise in given areas relevant to the firm

bring greater intelligence with which they can generate abstract principles from specific

situations (Dalziel et al., 2011).

Board effectiveness can be predicted more accurately if the experience of directors in

other boards and the information processing demands they face are taken into

consideration (Khanna, Jones, & Boivie, 2014). Using data of more than 5,700 directors

from 650 firms randomly selected from the Fortune 1000 using a 2-year lag period,

Khanna et al. (2014) investigated the director human capital, their information processing

demands and the effect on firm performance. The results of the study provided a number

of insights: First, firm performance is likely to benefit from directors’ prior experience

and education because such human capital is likely to make them more effective in their

provision of advice and control. Second, the extent to which the firm is able to benefit

from past experience of the directors can be severely hampered by the demands for

information processing the directors have from other board positions. Consequently, Lee,

Choi, and Kim (2012) in their study suggested that boards relying heavily on highly

renowned outside directors who serve in multiple external positions, as happens for many

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organizations in Korea, are likely to experience a decline in their quality of corporate

governance.

However, not all board members’ and senior management experience results in a superior

organizational performance as has been shown in the study of board interlocks, a

phenomenon in which directors sit on more than one corporate board (Hodgson, 2012;

Tuschke, Sanders, & Hernandez, 2014). According to Stuart and Yim (2010), social ties

between boards and CEOs can enhance a board’s advising ability, but have also the

potential to diminish the board’s monitoring ability due to compromises of director

independence. In their study to investigate the influence of board network on a firm’s

likelihood of being targeted in private equity-backed take-private transactions, Stuart and

Yim (2010) conclude that there is a greater likelihood of receiving private equity offers

for firms with interlocking directorships. Kamardin and Haron (2011) also reach the same

conclusion that multiple directorships are found to have a negative impact on the

management oversight and control roles. A research study by Peng, Mutlu, Sauerwald,

Au, and Wang (2015) focusing on mainland Chinese firms in Hong Kong found a

positive relationship between interlocking directorates and corporate performance. These

positive results are supported by Benton (2016) in a study of publicly held American

corporations in which the researcher concluded that more cohesive subgroups in the board

interlock network have greater managerial control.

2.4.3.3. Board diversity

Diversity refers to the coexistence within a given space of various cultural, economic,

social and political forms brought about by the need to adapt to an increasingly changing

environment (Cabrera-Fernández, Martínez-Jiménez, & Hernández-Ortiz, 2016). Human

diversity means the rich and infinite variety and differences among people and may

include race, gender, ethnicity, age, national origin, religion, values and beliefs (Davis,

Frolova, & Callahan, 2016; Silver, 2017). Diversity has its roots in social agenda

advocating for greater racial and gender rights particularly in North America (Weisinger,

Borges-Mendez, & Milofsky, 2016), but has now been widely used in diversity research

in organizations worldwide (Burns & Ulrich, 2016). The term workplace diversity is

applied to individual differences, work group characteristics and organizational forms

(Guillaume, Dawson, Otaye-Ebede, Woods, & West, 2015; Joshi, Hui, & Hyuntak, 2011).

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Diversity matters to organizations because it brings a wide range of talent, experience and

perspectives into leadership decision-making (Asperion Global, 2015). According to

research by Hunt, Layton, and Prince (2014) based on data drawn from thousands of

executives in the United Kingdom, Canada, Latin America and the United States, there is

a positive correlation between a more diverse leadership and better financial performance.

Companies in the top quartile of racial and ethnic diversity were 30 percent more likely to

have financial returns above their national industry median. Conversely, companies in the

bottom quartile for gender and ethnicity were less likely to achieve an above average

peformance (Hunt et al., 2014). For an organization to benefit from diversity, the

dominant or majority members of groups have to display ‘intercultural competence’ by

consciously include minority members (Bernstein & Bilimoria, 2013; Perry & Southwell,

2011). Increasingly, research on diversity is also exploring the twin notion of inclusion, in

which people are treated the same or where differences are celebrated and leveraged for

the benefit of the organization (Fredette, Bradshaw, & Krause, 2016).

Board diversity refers to composition and the varied combination of attributes,

characteristics, and expertise contributed by individual board members in relation to

board process and decision-making (Muller-Kahle & Lewellyn, 2011). Board diversity

also refers to how a board collects relevant outside information (Marcel, Barr, &

Duhaime, 2010), and this is determined largely by the homogeity or heterogeneity of its

composition (Midavaine, Dolfsma, & Aalbers, 2016). Other researchers see board

diversity as comprising the demographic (gender, age, nationalilty) and the structural

(CEO duality and director ownership) attributes (Hoang, Abeysekera, & Ma, 2016).

The impact of diversity on organizational performance is inconclusive as exisiting

research seems to point to differences in the effects of diversity on various performance

indicators (Klotz, Hmieleski, Bradley, & Busenitz, 2014). For instance, diversity might be

good for organizational growth but not for its survival, and heierarchical assymmetries in

an organization may moderate the effect of diversity of team performance (Coad &

Timmermans, 2014). Board diversity can be a positive attribute for an organization as it

enhances alternatives available to, or considered, by the firm and thereby enhancing

peformance outcomes (Hutzschenreuter & Horstkotte, 2013). However, there can be

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negative effects of diversity due to an affective effect, which refers to people being

attracted to others or forming relationships with those who are similar to them;

consequently those different from the majority are isolated (Byoun, Chang, & Kim,

2016).

Research to establish a business case for diversity continues to elicit debate on the

relationship between diversity variables and financial performance (Guillaume, Dawson,

Woods, Sacramento, & West, 2013). In order to explore the effect of reputational signals

on performance, Cook and Glass (2014) analyzed the impact of diversity recognition

awards for companies with progressive human resource policies, and found that investors

interpreted diversity reputation signals (Connelly, Certo, Ireland, & Reutzel, 2011) as

contributing to financial value of the firm. A board with more divergence is seen to be

more representative of a wide range of interest groups and stakeholders and can more

easily mediate and manage differences in an organization (Liao, Luo, & Tang, 2015).

One of the most important variables of diversity in corporate governance is gender, and

specifically the representation and participation of women in the boardrooms, perhaps due

to the fact that they are under-represented compared to men (Fleck, Hegarty, &

Neergaard, 2011). Despite the significant advances in education and participation in the

economic and political arenas, women remain underrepresented in leadership positions

across the globe and particularly in the boardrooms (Branson, 2012; Pande & Ford,

2011). In the United Kingdom, the FTSE 100 boards had 87.5% men and 12.5% women

(Davies, 2011), while a study in the United States among the 2,000 largest companies

found only 28% women directors who served on one board and 8% who served on more

than one board.

According to Lord Davies of Aberosoch, so skewed is the gender imbalance in the

boardroom that, at the current rate, it would take more than 70 years to achieve parity in

the United Kingdom (Davies, 2011). Consequently, the European Commission in 2011

introduced a directive the “New European Pact for Equality Between Women and Men

for the Period 2011-2020” reaffirming the Commission’s commitment to closing gender

gaps in employment, education and social protection, and in integrating gender

perspective in all its policies (European Union, 2011). However, the growth in the

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number of women in the boardroom has been modest (Grosvold & Brammer, 2011;

Pathak & Purkayastha, 2016) and this has prompted a number of countries to introduce

legislation imposing gender quotas for boards of publicly held companies (Credit Suisse

Research Institute, 2012; ICGN, 2013; Kakabadse, et al., 2015). Despite legislation to

promote equal opportunities for women, there seems to be an invisible glass ceiling

preventing their access to top organizational leadership to equitable compensation

(Kornberger, Carter, & Ross-Smith, 2010).

The observation that participation of women in boardrooms differs from country to

country has been of great interest to researchers (Gallhofer, Paisey, & Roberts, 2011;

Meyer, 2010). According to Verwiebe (2014), there are five basic social institutions that

regulate the behavior of individuals in core areas of society: family and relationship

networks; educational and training; labor market and economy; law, governance and

politics; and cultural, media and religious institutions. In a study that comprised data from

23 countries and framed in neo-institutional theory and the five basic institutions

(Verwiebe, 2014), Grosvold, Rayton, and Brammer (2016) suggested that family,

economy and government had influence on women’s rise to the board, while religion did

not.

The characteristics that determine the appointment of women to a board differ from those

of men. In a study analyzing professional networks of 494 male and female corporate

directors appointed between 2005-2010 in Standard & Poor’s 500 index-listed companies

in the US, Hodigere and Bilimoria (2015) found that certain professions favored women,

relative to men. The results of the study showed that a woman coming from the education

sector is three times more likely to be appointed to a corporate board, and a woman

coming from the public service or government service is almost five times more likely

than a man to be appointed to a US corporate board (Hodigere & Bilimoria, 2015). The

study also found out that being a professional director disadvantages women from being

appointed as corporate board directors, just as women are less likely to be appointed in

multiple directorships (McDonald & Westphal, 2013). Accounting professions, in

particular, seem to attract more women as shown by statitistics from Taiwan showing that

women receiving bachelor degrees in accounting are twice that of men and between 55-

62% of those who qualify for CPA have been women (Hsu, Kuo, & Chang, 2016).

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In the last three decades, the percentage of women in the workforce has steadily increased

especially in the Western world where participation rates are comparable to those of men

(Glass Lewis & Co., 2016; US Bureau of Statistics, 2015). Similarly, in the two-thirds

world, equity, equality and inclusivity have been mainstreamed in public and private

spheres with a lot more purpose (Balasubramanian, 2013). This demographic shift was

initially inspired by the civil rights movement and government legislation (Badal &

Harter, 2014). In recent years, the increase of women in the boardrooms has been inspired

by the recognition that ‘greater gender diversity can lead to more diverse workforce,

better corporate governance practices, and improved stakeholder relations, which, in turn,

will result in better financial performance’(Cabrera-Fernández, et al., 2016; Glass Lewis

& Co., 2016).

Perhaps due to their more recent entry in the boardroom, female directors are often

perceived as a homogenous group in terms of their professional background and their

personality (British Council, 2011). As common perceptions about women become

stereotypes, this results to prejudices that make it difficult for women to assert their own

individual qualities thus imprisoning them to certain specific and closed parameters

(Anca & Gabaldon, 2014). Far from being a homogeneous group, Cha and Abebe (2016)

contend that women belong to diverse social and economic backgrounds such as law,

education, and nonprofit backgrounds and, therefore, more likely than their male

counterparts to bring different perspectives to the board.

Gender diversity provides an organization with a sustained competitive advantage and is a

possible source of intangible resources of market insight, creativity, innovation and

problem solving (Ali, 2016). Gender diversity enhances employee’s overall creativity and

innovation because of a combination of different skills, perspectives and backgrounds as

males and females demonstrate different thinking patterns (Abraham, Thybusch, Pieritz,

& Hermann, 2014; Díaz-García, González-Moreno, & Sáez-Martinez, 2013). Female

directors have been shown to be more sensitive, socially responsible and ethical and so

having a higher percentage of women directors has positive influence on a firm’s

corporate social responsibility (Setó-Pamies, 2015). Women on boards influence firm’s

prosocial actions which results to higher corporate social responsibility, which in turn

improves financial performance (Galbreath, 2016). However, there is evidence that with

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more females sitting on the board, the profitability of male directors decreases and that

female directors are no less inclined to exploit assymetric information advantage (Zhong,

Faff, Hodgson, & Yao, 2014) associated with masculine domination (Malsch & Gendron,

2011; Tremblay, Gendron, & Malsch, 2016).

Abraham et al. (2014) carried out a study that focused on neuroscientific research to

explore the behavioural and brain functioning during creative conceptual expansion as

well as general divergent thinking. The results showed that while men and women were

indistinguishable in terms of behavioural performance across tasks, there were differences

in the brain activity while engaged in strategy tasks. For men, brain areas related to

semantic cognition, rule learning and decision-making were engaged during conceptual

expansion, while for women the areas involved in theory of mind and self-referential

processing were engaged.

An innovation survey by Østergaarda, Timmermans, and Kristinsson (2011) revealed a

positive relation between diversity in education and gender on the likelihood of

introducing innovation as well as a positive relationship between an open culture towards

diversity and innovation. In a longitudinal study using dataset of 562 firm-year

observations in 80 young high-tech ventures in Belgium, Vandenbroucke, Knockaert, and

Ucbasaran (2016) showed that outside board-specific experience, diversity and tenure led

to faster speed to first product and more products on the market.

Gender diversity is also associated with valuable, rare, inimitable and non-substitutable

resources such as creativity, market insight, innovativeness which can provide an

organization with sustained competitive advantage (Ali et al., 2011). Gender diversity has

been positively associated with improved organizational performance as measured by

number of customers, sales revenue, market share, productivity, profits and Tobin’s Q

(Nakagawa & Schreiber, 2014). In a study to explore whether and to what extent women

managers, and not just greater diversity, boosted Japanese economy, Nakagawa and

Schreiber (2014) found a positive relationship between the percentage of women

managers and firm performance. The positive effect due to the women managers

appeared to be independent of the proportion of women among all employees. However,

some of these positive effects are related to the sociodemographic profile of female

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directors, that is, younger and with higher level of education than their male counterparts

on the board, and in the majority of the cases, married (Anca & Gabaldon, 2014).

Armstrong et al. (2010) studied the impact of 17 diversity/equality management practices

on labor productivity, workplace innovation and employee turnover, and concluded that

the practices improved performance. The study based on data from service and

manufacturing firms in Ireland, showed that a diversity and equality management system

contributes in firm performance beyond the effects of a traditional high-performance

work system. In a study of 201 Norwegian firms to investigate the contribution of women

on boards of directors, Nielsen and Huse (2010) found that the ratio of women directors

was positively associated with board strategic control as well decreased level of intra-

group conflict. On the other hand, a study in the US retail industry by Bao, Fainshmidt,

Nair, and Vracheva (2014) showed that the presence of women in the top management

teams and the board of directors was negatively associated with legal risk, a finding

consistent with the findings of Muller-Kahle & Lewellyn, 2011.

A growing body of research shows that the inclusion of women in boards has significant

benefits to organizational performance as measured by shareholder value, increased

customer and employee satisfaction, rising investor confidence and greater market

reputation (Al-Tawi, 2016; Bear, Rahman, & Post, 2010; IFC, 2014). Greater board

diversity is also credited with improving the identifying, evaluating and capturing

entrepreneurial opportunities (Grosvold & Brammer, 2011; Kim & Ozdemir, 2014). In a

research study of 709 micro-finance institutions in 82 countries, Estape-Dubreuil and

Torreguitart-Mirada (2015) included in their variables the percentage of female board

members, as well as proportion of female managers in order to measure performance. The

study also included in its hypothetical model the effect of gender diversity of

management on the MFI performance. The results of the study showed that gender

diversity in the board led to the MFIs serving more clients, reaching poorer clients and

extending their services to more female borrowers.

In another study of 591 microfinance institutions drawn from Sub-Saharan Africa, Middle

East and North Africa, East Asia and Pacific, South Asia, East Europe and Central Asia,

and Latin America and the Caribbean, Estape-Dubreuil and Torreguitart-Mirada (2015)

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showed that corporate governance has more impact on social performance than on

organizational performance. Promotion of gender diversity in the board led to greater

participation of especially poorer and female clients. Similar results were obtained by

Ayadi, Ojo, Ayadi, and Adetula (2015), who explored the relevance of gender diversity in

the management of the Nigerian Stock Exchange. The results of the study indicated that,

at worst, gender diversity does not have an effect on the performance of the Nigerian

Stock Exchange (NSE) but at best, the appointment of women in the management of NSE

was associated with better performance. In a study based on Mauritius Stock Exchange,

Mahadeo, Soobaroyen, and Hanuman (2012) examined data from 42 listed companies

and specifically studied the representation of women and level of heterogeneity in terms

of educational background and age. The study found that women were poorly represented

on boards and yet their involvement had positive impact on performance.

The position that gender diversity leads to higher organizational performance is not

unanimous as other studies show a more neutral or negative effect (Gregory, Jeanes,

Tharyan, & Tonks, 2012). According to Mathisen, Ogaard, and Marnburg (2013), women

are often considered an out-group within the board and more likely to experience a lack

of cohesion, communication and cooperation, which leads to dissatisfaction and conflict.

Analyzing a sample consisting of 2100 banking institutions in the US to study the impact

of racial and gender diversity in management on financial performance, Richard, Kirby,

and Chadwick (2013) concluded that gender diversity in management is negatively

related to performance when participative strategy making is low. Opstrup and Villadsen

(2014) also found out that gender diversity in top management teams was associated with

higher financial performance but only when the management structure supported cross-

functional team work.

A similar result was found by Chapple and Humphrey (2014) studying a sample of 577

firms from S&P and ASX300 Australian firms where the researchers did not find

evidence of association between diversity and performance. In Sri-Lanka, as in India

(Kaur & Singh, 2015) which has little representation of women in corporate boards and

where is there is preference for homogenous boards, increasing the proportion of women

in the boardrooms often lead to increase in conflict (Wellalage & Locke, 2013). Post and

Byron (2015) also found a mixed picture in their study to investigate the relationship

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between women on boards and firm financial performance. In their meta-analysis of 140

studies, the researchers found that women board representation was positively related to

accounting returns and this relationship was more positive in countries with stronger

shareholder protections and with greater gender parity (Post & Byron, 2015). In another

study which aggregated responses from 82 teams in 29 organizations, Post (2015)

suggested that female leadership was more associated with cohesion on teams, more

functionally diverse, dispersed and participative in their communication.

In a study of 5,500 directors of US firms drawn from the S&P 500 Index to examine the

business case for inclusion of women and ethnic minority directors on the board, Carter,

D'Souza, Simkins, and Simpson (2010) did not find any significant relationship with the

organizational performance as measured by return on assets and Tobin’s Q. On the other

hand, Ahern & Dittmar (2012) found that a new law requiring 40% of Norwegian firms

be women (from a baseline of 9% at the time in 2003) led to younger and less

experienced women replacing more experienced men. The introduction of the quota led to

a significant drop in long-term market value of the Norwegian firms as measured by

Tobin’s Q, and also in reduction of public limited firms as some moved to other countries

while others became private limited companies. Enforcing board gender quotas can

undermine the value that women directors create through their own competence as it

diminishes meritocracy in the firm (Kakabadse, et al., 2015).

In a study specifically to examine the effect of women on the board on firm performance

in the construction industry in Europe, Arena, et al. (2015) found out that the presence of

women does not positively affect performance. The authors suggest that the sense of

inferiority and skill underestimation that women face in male-dominated industries

creates relationship conflicts that prevents their value creation. Additionally, the study

found women who had achieved higher academic level compete more ably with men but

that this led to conflicts and negative consequences for firm performance. A similar

conclusion was reached in a meta-analytical study investigating the relationship between

female representation and firm organizational performance (Pletzer, Nikolova, Kedzior,

& Voelpel, 2015). The study analyzed data from 20 studies on 3,097 companies and

found only a small positive, but not significant relationship between the percentage

female representation on corporate boards and firm organizational performance. On the

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other hand, the study found that high female representation on the boards was not

detrimental on the firm performance and so concluded that females should be prioritized

for promotions if suitably qualified for both ethical and performance based reasons.

Across Africa, while many countries have taken initiatives to increase women

representation and participation in governance, there are still far fewer women than men

in decision-making positions at all levels, including at community and household level

(Tandrayen-Ragoobur, 2014). Although the country that leads in the number of women in

parliament is Rwanda (56.25 percent), other African countries have very low levels of

representation and participation at political governance level (UNDP, 2012). According to

Lincoln and Adedoyin (2012), Africa, and Nigeria in particular, is a patriarchal society

where women are considered weak economic agents and are discriminated against in

decision-making. The same situation obtains for Ghana where women have few

ownership rights such as to sell, bequeth or use assets as collateral (Oduro, 2015). Tijani-

Adenle (2016) makes the point about stereotypying and triviliazing women in leadership

and management in the choice of title for their study, namely, “She’s homely, beautiful

and then, hardworking!”

Women in Africa form an underclass and lack equality of opportunity in economic

participation, which condemns them to low paying and insecure jobs and career paths

(Diop, 2015; Lincoln & Adedoyin, 2012). While in 2011 the male employment to

population was 69.2%, the female employment ratio was 39.2% in general in Africa, but

only 20% for North Africa (Anyanwu & Augustine, 2013). Perhaps a positive spin to this

dearth of bad news about gender inequality in Africa is the female proportion of top

executives and directors in MFIs which Strøm, D’Espallier, and Mersland (2014) placed

at 26% compared to a meagre 9% of comparable firms in the United States (Augustine,

Wheat, Jones, Baraldi, & Malgwi, 2016).

In East Africa, females are an important constituency in boards of MFIs and co-operatives

as most customers tend to be women (Mori et al., 2015). In their study of 103 MFIs in

East Africa, Mori et al. (2015) found a positive relationship between gender diversity and

the proportion of female customers, a result similar to another study on MFIs by Strom,

D'Espallier, and Mersland (2014). In Kenya, a study by Madichie and Nyakang'o (2016)

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which aimed at looking at workplace diversity at the Kenya National Bureau of

Statitistics showed that female representation was 24%, on average. However, the middle

age bands had much better representation of females, with 36-40 and 41-45 year bands

being 40% and 42% respectively. In a research of corporate social reporting, Barako and

Brown (2008) studied the annual reports of the entire population of 40 Kenyan banks and

took as independent variables the ratio of non-executive directors on the board and

women representation on the board. Their results of multiple regression indicated that the

ratio of women directors on the board to total number of directors was a significant

determinant of the level of social information disclosed by the banks in their annual

reports. They also found out that the ratio of non–executive directors to the total number

of board members was positively associated with the extent of information disclosed.

2.4.4. Effect of Long-term Orientation on Organizational Performance

Long-term orientation refers to a culture that favors a focus on the future benefit an

organization obtains through patient investment and taking calculated risks (Hwang et al.,

2013; Maleki & de Jong, 2014). It is associated with long-term planning and decision-

making (Hoffman & Wulf, 2016; Lumpkin et al., 2010; Park et al., 2013). Long-term

orientation has to do with incentivizing managers to make decisions that benefit the

organization in the long run, even at the cost of forgoing short-term profits in order to

avoid short-termism and managerial myopia (Abernethy, Bouwens, & Lent, 2013;

Flammer & Bansal, 2017). The choice of performance measures has an incentivizing

effect on whether the managers choose short-term rather than long-term efforts. Short-

term actions include managing current operations, production scheduling and dealing

with personnel issues, all intended to meet quarterly or annual targets, as contrasted with

longer-term actions for multiple year horizons, namely improving customer satisfaction,

training of the work-force, research and development and exploring new products and

markets (Abernethy et al., 2013).

According to Lumpkin and Brigham (2011), long-term orientation has three dimensions:

futurity refers to the utility obtained in focusing on planning for the future; continuity

reflects the view that durability and constancy in time contributes to value creation; while

perseverance refers to the conscientiousness required to reach the future goals. Hoffman

and Wulf (2016) suggest that a long-term orientation fosters pro-organizational,

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stewardship behaviour in top management teams and strengthens their commitment and

mutual trust (Davis, Allen, & Hayes, 2010), thus improving firm performance. A long-

term orientation also balances stakeholder interests, thereby reducing principal-principal

agency problems which often occur in family firms where more influential family

members may take advantage of the less influential ones (Miller, Minichilli, & Corbetta,

2013).

This study reviewed long-term orientation using three constructs: focus on long-term

profitability; management incentivized to take risks; and management held accountable

for performance.

2.4.4.1. Focus on long-term profitability

Long-range orientation has been referred by different names including extended time

horizon, long-term focus, managing for the long run, but all referring to long-term

temporal approach (Brigham et al., 2014; Lumpkin et al., 2010). Researchers have shown

that individuals and organizations make decisions based on sequences incorporating a

holistic view of time, that is, past, present, and the future (Shi & Prescott, 2011; Zahra &

Wright, 2011). Hofstede (2011) distinguished between short-term and long-term

orientations, referring to the choice of focus for peoples’ efforts whether it is in the past,

present or future. For example, Confucianism in East Asia societies is characterized by

harmony, loyalty, cooperation and seniority and that these distinctive ethical norms lead

to long-term orientation and collectivism for Asians.

While it has long been established in research that a long-term orientation contributes

positively to the financial well-being of organizations (Lumpkin & Brigham, 2011),

managing for the long run has other important non-economic goals, which are just as

important for firms (Chrisman, Chua, Pearson, & Barnett, 2012). Cho, Chung, and

Hwang (2015), instead, refer to the non-economic goals as social satisfaction, which

include the psychological aspects of relationships. The non-economic goals may include

succession planning, positive community image and respect due to stewardship

tendencies such as investing in local communities, and making long-term commitments to

customers and employees (Lumpkin & Brigham, 2011). Because of the extent to which

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they prioritize non-economic goals, family firms, mutual and membership societies such

as co-operatives are more likely to have a long-term orientation (Lumpkin et al., 2010)

While an emphasis in long-term performance (LTP) is important for firm performance

and benefit to stakeholders, short-term performance (STP) is just as important because a

long-term strategy that results in a bankruptcy in the short term is not a measure of

success. Both LTP and STP are seen as two facets of the a wider construct of firm

performance (Martynov & Shafti, 2016). Long-term profitability for firms, especially

social enterprises, is important because “if it does not work financially it is not going to

work socially” (Jenner, 2016). Long-term performance, defined as sustainability of

performance over time, is described variously using the notion of a time frame longer

than one observation period and averaging the indicator over the time (Brauer, 2013;

Bauer & Braun, 2010). However, Hamann, Schiemann, Bellora, and Guenther (2013)

measure long-term performance as a construct in its own right by the use of performance

indicators such as whether growth is accelerating or slowing down, or the level of

stability of performance over time.

As long-term orientation increases, customers are prepared to wait to receive their

rewards and the difference in value of immediate and accumulated rewards decreases

(Park et al., 2013). Successful investment is not about making short-term profits but

setting clear-cut and long-term objectives after studying the market and considering the

trade-off between the risk and expected rate of return (Arora & Marwaha, 2014). In order

to obtain long-term profitability, a firm may require access to long-term capital especially

for infrastructural projects (Annamalai & Hari, 2016). Firms also establish long-lasting

and collaborative relationships with their suppliers in order to become more efficient and

achieve competitive advantage (Nyaga, Whipple, & Lynch, 2010). Firms with long-term

orientation are prepared to make short-term sacrifices as they perceive that their business

outcomes depend on partners’ outcomes in the long-run (Hwang et al., 2013). Instead of

focusing on short-term financial indicators such as profit maximization and increased

market share, long-term orientation involves building network relations that contribute

intangible value and impact to the organization (Tretyak & Sloev, 2013).

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Family firms and mutual societies tend to plan with a long time horizon in part because

the family is the oldest running social unit in the world, and their desire is to pass on to

later generations a healthy business (Brigham et al., 2014; Bakoglu & Yildirim, 2016). In

a study comprising a sample of 677 Australian listed companies comparing the long-term

performance of family and non-family firms, Halili, Saleh, and Zeitun (2015) found that

the survival rates of family firms was higher (72.37 percent) than non-family firms (64.81

percent). These results are supported by similar research findings that multi-generational

transition is a powerful motive to set up business (Miller, Breton-Miller, & Lester, 2013).

Firms also need organizational capabilities such as technological, innovation and

financial resources, networks and values developed over time, to obtain the competitive

advantage needed for long-term survival (Löfsten, 2016).

Consequently, family firms create their sustainability by avoiding opportunitistic

treatment of stakeholders that might harm relationships and work to ensure robustness of

their long-term strategy (Berrone, Fosfuri, Gelabert, & Gomez-Mejia, 2013; Cruz,

Larraza-Kintana, Garces-Galdeano, & Berrone, 2014). Research has shown that firms that

incorporate sustainability into their business strategy are able to reap higher financial

rewards than others (Gomez-Bezares, Przychodzen, & Przychodzen, 2016). In managing

for the long run, everyone - including direct stakeholders, later family generations and the

society at large - wins, a notion that Laszlo and Zhexembayera refer to as the “the next

big competitive advantage” in their book entilted “Embedded Sunstainability” (Laszlo &

Zhexembayeva, 2011). Family firms also tend to invest more in R&D, and hence the

latter is often used as an indicator of long-term orientation (Brigham et al., 2014).

Long-term profitability and sustainability are closely linked because a business strategy

that improves long-term social and ecological aims increases the value of the enterprise in

the long run (Jansson, Nilsson, Modig, & Vall, 2017; Maruffi, Petri, & Malindretos,

2013). Meng, (2015) defines sustainability as a human capability for long-term

maintenance of the well-being of all lives including those of future generations.

Sustainability also refers to consumer sustainable benefit (Prothero, et al., 2011), standard

of living (Huang & Rust, 2011), without undermining ecological quality and

underminining ecological awareness (Hunt, 2011). Galpin, Whittington, and Bell (2015),

on the other hand, bundle as sustainability- corporate social responsibility, corporate

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social performance, going green and triple bottom line, and describe it as organizations

enhancing their economic, social and environmental performance. A culture of

sustainability can increase organizations profits by as much as 38 percent (NEEF, 2010)

and corporations adopting environmental and social policies outperform their peers both

in terms of stock market and accounting performance (Eccles, Ionnou, & Serafeim, 2011).

In their study of the Henokiens (2017), the International Association of Bicentary Family

Companies- an association that accepts family firms which are at least 200 years of age-

Bakoglu and Yildirim (2016) analyzed 38 out of the current 46 members of the group.

The analysis explored three dimensions of sustainability, namely: economic, ecological

and social sustainability (Gusc & Veen-Dirks, 2017). The researchers put forward that the

sustainability framework of the triple bottom line goes beyond traditional measures of

profits, ROI, and shareholder value to include environmental and social dimensions, as is

the case for Henokiens group (Bakoglu & Yildirim, 2016; Tapies & Moya, 2012).

Organizations must manage their social, environmental and financial performance in

order to create what Porter and Kramer (2011) call ‘shared value’. Shared value can be

obtained from sustainable development, which Ditlev-Simonsen and Midttun (2011)

equates with corporate social responsibility, whereby a firm can increase its own profit

and improve its long-term competitiveness, as well as make meaningful social impact.

The “triple bottom-line” sustainability of “planet, people and profits” may require

technological innovation in order to create shared value through unique positioning, value

chains and profits for a social purpose (Ahern, 2015).

In order to investigate whether firms that implement corporate social responsibility

strategies achieve higher corporate performance (Chen & Wang, 2011) than those that do

not, Marti, Rovira-Val, and Drescher (2015) utilized data of 153 firms composed of Stoxx

Europe 600 index. From the database, the researchers extracted information on the ROA,

ROE (Inoue & Lee, 2011), total assets, long-term debt, current ration, free cash flow,

R&D expenditure, ratio of market value of equity to book value of equity, the industry to

which they belong, and their country of origin. The results of the study showed that, in

crisis periods, firms that implemented CSR obtained better performance that those who

implemented traditional management strategies, as measured by ROE, ROA and Tobin’s

Q (Marti et al., 2015). Corporate social responsibility, or socially responsible investing

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(SRI) as Revelli and Viviani (2015) refers to it, must be managed for long-term objectives

for it to provide a competitive advantage. Socially responsible behaviour provides a long-

term competitive advantage to firms wanting to build strong customer satifaction (Huang,

Cheng, & Chen, 2017; Junkus & Berry, 2015).

Another concept associated with long-term profitability and sustainability is resilience,

which is defined as the ability of an organization to, in the long-term, anticipate, avoid,

and adjust to environmental shocks (Ortiz-De-Mandojana & Bansal, 2016). On the other

hand Lengnick-Hall, Beck, and Lengnick-Hall (2011) suggest that (strategic) alliance

stems from strategic human resource management and is about continously anticipating

and adjusting to deep secular trends that can permanently impair the earning power of a

core business (Martynov & Shafti, 2016).

Resilient firms must be willing to trade off short-term financial losses for longer-term

benefits in order to ensure that short-term financial pursuits do not compromise the

prosperity of future generations (Bansal & DesJardine, 2014; Slawinski, 2015).

Resilience and sustaibility are connected in that resilience is about quickly processing,

responding to environmenal signals, developing flexible resources and thereby helping

firms adapt to complex dynamic environments (Ortiz-De-Mandojana & Bansal, 2016).

Organizations need to make investments today that will accrue benefits over a longer

term, which is a trade-off between more earnings at the present or greater benefits for the

future (Chen & Miller, 2011).

2.4.4.2. Management incentivized to take risks

Though there is a lack of a universally accepted definition of risk (Andretta, 2014),

scholars acknowledge that it is a measure of the probability and severity of adverse

effects (Tsai & Luan, 2016). Risk taking is the degree to which a person is willing to

undertake actions that involve a significant degree of risk (Majidifard, Shomoossi, &

Ghourchaei, 2014). It refers to bold moves into unknown business areas and/or

commitment to significant business resources under conditions of uncertainty (Amin,

2015). Risk taking is one of the three dimensions of entrepreneurial orientation, namely:

innovation, proactive actions, and risk taking (Franco & Haase, 2013; Oliveira Junior,

Borini, Bernardes, & Oliveira, 2016; Keil, Maula, & Syrigos, 2015). Due to their strategic

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philosophy (Chen, Li, & Evans, 2012), entrepreneurially oriented firms are proactive in

developing breakthrough innovations, products and services and take substantial risk

(Morgan, Anokhin, & Wincent, 2016). Risk is an essential element in the decision-

making process for entrepreneurs starting a new business, finding a new market,

introducing a new product, and transforming uncertainties into opportunities (Alvarez,

Barney, & Anderson, 2013; Khalili, Nejadhussein, & Fazel, 2013).

Managerial risk taking is a crucial and an inevitable component of strategic management

and organizational leadership is confronted with uncertainty in the dynamic business

environment (Hoskisson, Chirico, Zyung, & Gambeta, 2017). According to Marshall and

Ojiako (2015), risk and uncertainty are linked in understanding how an entrepreneur has

to muddle through ‘a wide sphere of uncertainty’ and ‘unanticipated risk’. Further,

uncertainty refers to risk to which probabilities of occurrence ‘have not yet been

assigned’ and which might never be assigned with certainty but, nevertheless, can be

transformed into opportunities (Alvarez et al., 2013; Sarasvathy, Dew, Velamuri, &

Venkataraman, 2010).

McKelvie, Haynie, and Gustavsson (2011) opine that the ability of entrepreneurs to

interpret and respond to uncertainty is what determines their degree of success of failure,

and perhaps also the allure of entrepreneurship as a vocation. The researchers

differentiate between state, effect and response uncertainty in their research where they

decompose 2800 exploitation decisions policies within a sample of decision makers

working in entrepreneurial software firms. One of the findings of the study is that

entrepreneurs place different weights of importance for decision-making on different

types of uncertainty and that the entrepreneur’s assessment, not prediction, of uncertainty

plays a big part in decision-making (Read, Sarasvathy, Dew, & Wiltbank, 2016; McKevie

et al., 2011). Entrepreneurs perceive risk differently from managers given the novelty,

individualization, and lack of organizational support, which leads entrepreneurs to apply

their discretionar powers as best as they can to improve their circumstances (Marshall &

Ojiako, 2015; Kiss, Danis, & Cavusgil, 2012; Wiklund, Davidsson, Audretsch, &

Karlsson, 2011).

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One of the incentive schemes that may encourage risk taking is the CEO severance pay

through the reduced fear of losing one’s job (Cowen, King, & Marcel, 2016; Rau & Xu,

2013), but the overemphasis on risk-taking may lead to bad risk by managers (Armstrong

& Vashishtha, 2012; Dong, Wang, & Xie, 2010). On the other hand, managers who are

under-diversified and, as a consequence, typically have most of their financial wealth

within the firm, tend to be more risk averse and incentivized to reduce personal exposure

by undertaking investments that reduce firm risk (Belghitar & Clark, 2015). One of the

remedies for this conflict is to improve the compensation (Eling & Marek, 2013) or create

opportunities for the risk-averse managers to diversify outside of the firm (Beladi &

Quijano, 2013; Belghitar & Clark, 2014).

The age and gender of the investor also determines the level of risk tolerance. In a survey

to measure the investment pattern of individuals, Kabra, Mishra, and Dash (2010)

adminstered a questionnaire to measure how the dimensions of investment (security,

opinion, awareness, hedging, benefit and duration) of men and women, as well as various

age groups affected investor perception. The respondents were also asked to indicate their

profession, whether they worked for the government, private sector, or in professional

services, as well as their annual income. The results of the test showed that individuals

prefer to invest according to their risk preference and risk-averse people chose life

insurance, fixed deposits with banks and post office (Kabra et al., 2010). These findings

are supported by a similar study in India by Harikanth and Pragathi (2012) who

concluded that investment decisions depend on individual risk tolerance capacity,

education, occupation, age, sex, income, family background, and whether one has a

financial advisor. A study based in Pakistan by Bashir, et al. (2013) found that females

were more risk averse than males and the young and educated people were attracted more

to new risky investments.

Another concept related to risk-taking is financial risk tolerance which refers to the

investors’ willingness to accept the negative changes in the outcome of an investment

with a goal to generating higher returns (Larkin, Lucey, & Mulholland, 2013). Financial

risk tolerance is dynamic, changes over time, and is affected by past life experiences,

such as financial crises which leave institutions and individuals financially vulnerable

(Yao, Sharpe, & Wang, 2011). Measuring financial risk tolerance has been found

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challenging given its multidimensional nature, and also elusive as it appears to be

influenced by demographic, environmental and psychological factors (Kannadhasan,

Aramvalarthan, Mitra, & Goyal, 2016). People of different ages have been shown to have

dissimilar levels of risk tolerance. Yao et al. (2011) decomposed the age effect into three

independent constructs, namely: aging effect, generation effect, and period effect. The

findings from their study showed that age had a negative effect on the willingness to take

financial risks, and that aging and period effects on financial tolerance were statistically

significant (Yao et al., 2011).

Organizational size has a moderating effect on managerial risk taking, whereby

underperformance relative to aspirations leads to less riks taking for smaller firms but to

more risk for larger firms (Greve, 2011). Similarly, risk taking increases when

organizational performance is above historical aspirations but decreases when

performance is above social aspirations (Kim, Finkelstein, & Haleblian, 2015). Gaba and

Joseph (2013) has also shown a differential response to firm underperformance across the

layers of management with the business unit managers likely to take greater risks

compared to corporate managers. Organizational slack, or resource abundance, has also

been shown to increase managerial risk taking (Arrfelt, Wiseman, & Hult, 2013;

Bhaumik, 2016).

Managerial risk-taking propensities differ in different life cycles in an organization as

firms pass through predictable patterns of development with varying capabilities,

resources and strategies (Dickinson, 2011). In a study to examine the consequences of

different stages of firm lifecycle on corporate risk taking and organizational performance

and using data from Compustat fundamentals annual file, Habib and Hasan (2014)

concluded that risk-taking was higher in the introduction and decline stages of the life

cycle. The likely explanation for this finding is that the firm’s resource base at early and

decline stages are more fluid and thus require more risky investment to expand and return

to profitability, respectively (Faccio, Marchica, & Mura, 2011). Habib and Hasan (2014)

further observed that corporate risk-taking was lower in the growth and mature phases of

firm lifecycle, which stages also have high level of product differentiation and

profitability, respectively (Dickinson, 2011).

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Managerial risk-taking propensity is also influenced by the state of the economy with

expectations of high growth and ease of access to capital correlating with excessive risk-

taking as compared with periods of economic contraction (McLean & Zhao, 2014). As

capital investments often require access to external capital markets, the prevalent state of

the economy as a whole is critical, otherwise risk taking decisions may well depend on

investor sentiment than the share’s underlying risk (Arif & Lee, 2014). Since firms at

different life cycle stages have differing capital requirements with firms at the early stage

requiring more capital to build up capacity, managers of firms in this stage may assume

more risk, if external financing is less costly (Habib & Hasan, 2014). Decline stage firms

also take risks in order to return to profitability and they do so by sourcing cheaper capital

which becomes available during bullish periods of high investor sentiment (McLean &

Zhao, 2014).

An organization’s risk-taking capability and experience is one of its strategic assets in

dealing with different types of risks (Meschi & Métais, 2015; Neves & Eisenberger,

2014). According to Tsai and Luan (2016), risk-taking competence encompasses five

layers: obtaining and framing information; designing a process with a long front end;

building coalitions; allocating risks to parties best able to bear it; and building long-term

coalitions with partner parties. The risk taking capability depends on both internal

resources, what Spithoven and Teirlinck (2015) refer to as absorptive capacity, and

external resources such as social networks. Different kinds of risk require different risk

management strategies (Kaufmann, Weber, & Haisley, 2013). Risk taking capability is

also influenced by country of origin, its economic model (Strobl, 2016) and regulatory

framework (Gatzert & Kosub, 2017), on the one hand, and institutional differences such

as form of ownership, on the other (Geppert, Dorrenbacher, Gammelgaard, & Taplin,

2013).

The study of risk taking in family-owned firms is important as the latter account for a

very significant proportion of all companies in the OECD, S&P 500 and Fortune 500

listings (Craig & Salvato, 2012; Roessl, Fink, & Kraus, 2010). Family firms are typically

considered to be less entrepreneurial in their behaviour and more conservative in their

risk-taking propensity (De Massis et al., 2013; Hiebl, 2014), although this stance is

contradicted by other researchers (Casillas & Moreno, 2010). In their survey using a

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stratified sample of 532 Finnish family firms targeting members of the top management

teams, Craig, Pohjola, Kraus, and Jensen (2014) explored the relationship among

proactiveness, risk-taking and innovativeness in family and non-family firms. Their

results showed that family firms gained from proactivity than non-family firms, while

risk-taking was less influential for family firms than non-family firms, a finding

supported by Pérez-Luño, Wiklund, and Cabrera (2011) whose study revealed that

proactivity and risk taking were positively associated with the number of internally

generated innovations.

For family firms, mutual and membership societies, the non-economic goals and socio-

emotional wealth is a primary driver for their strategic behavior and will embrace risky

decisions even if it lead to a decrease in profitability (Miller, Breton-Miller, Minichilli,

Corbetta, & Pittino, 2014; Munari, Oriani, & Sobrero, 2010). While this finding may

suggest that family firms’ economic and family goals are in conflict, Chrisman and Patel

(2012) suggest that the long-term orientation of family firms mean that strategic time

horizons lengthen and decision makers become less risk averse. Corporate risk-taking is

influenced by national culture both through its effect on manegerial decision-making and

through the effect of its national institutions (Griffin, Guedhami, Kwok, Li, & Shao; Li,

Griffin, Yue, & Zhao, 2013). In countries with strong creditor rights, firms tend to reduce

risk taking by diversifying acquisitions, and undertaking lower cash-flow risk and lower

leverage (Acharya, Amihud, & Litov, 2011). It has also been shown that firms in common

law countries where there is stronger protection of property rights, and those in market

based countries, take less risk (Li et al., 2013).

Analyzing data of industrial firms from 35 countries over the period 1997-2006 and also

using cultural values developed by Hoftede (2011), Li et al. (2013) examined which

cultural values affected corporate risk-taking. The researchers hypothesized that there is a

positive relation between national individualism and corporate risk-taking, a negative

relation between national uncertainty-avoidance and corporate risk-taking, and a negative

relation between national harmony and corporate risk-taking. The results of the study

showed that individualism was positively and significantly associated with corporate risk-

taking, whereas uncertainty-avoidance and harmony were negatively associated with

corporate risk-taking. Further, the results showed that culture influenced risk-taking

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through risky corporate decision-making, and indirectly through formal institutional

development.

The disposition, preferences, behaviour, and the propensity of the CEO to take risks have

been shown to explain new product innovativeness (Kalm & Gomez-Mejia, 2016). Other

scholars have noted that risk-taking decisions are not based entirely on business

calculations, but that it is more predispositional than situational and influenced by

individual proclivity towards risk (Pak & Mahmood, 2015; Zhao, Seibert, & Lumpkin,

2010). In addition, an increase in individual pyschological control can lead people to

increase risk-taking (Chan, Tong, & Tan, 2014). The CEO risk-propensity, defined as the

willingness to commit significant resources to exploit new opportunities and investments

with uncertain income (Felekoglu & Moultrie, 2014) has been shown to be a driver of

innovation (De Massis, Frattini, & Lichtenthaler, 2013; Talke, Salomo, & Kock, 2011).

In a study of 114 German small and medium enterprises in the manufacturing sector,

Kraiczy et al. (2014) provided an empirical test of the effect of an individual behaviour

(Zou & Scholer, 2016), the CEO risk-taking propensity on new product innovativeness as

a measure of the risk taking behaviour. The study results showed CEO risk-taking

propensity had a positive effect on new product innovativeness and that the organizational

context moderated the relationship. The higher the ownership of the firm by the top

management team family members, the weaker the relationship between CEO risk-taking

propensity and innovativeness (Kraiczy et al., 2014).

Research has also shown that there are a number of organizational factors such as family

ownership and control by the top management team, and how they interact with the CEO

risk-taking propensity to affect new product innovativeness (Gomez-Mejia, Cruz,

Berrone, & Castro, 2011). Scholars have also linked the concept of socio-emotional

wealth, the utility that family owners derive from non-economic aspects of the firm, to

explain the CEO risk-taking behaviour (Chrisman & Patel, 2012). When the socio-

emotional wealth (SEW) is at risk in family firms, their R&D increases, but

innovativeness and technological diversification decrease (that is, firms become more

risk-averse) when SEW is not at risk (Gomez-Mejia, et al., 2014; Kotlar, De Massis,

Frattini, Bianchi, & Fang, 2013).

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Information asymmetry and lack of transparency, for example, in Islamic Profit Sharing

Investments Accounts (PSIA) have been shown to give managers incentives to undertake

more risky investments (Hamza & Saadaoui, 2013). Uncertainty and market turbulence

may create new competitive opportunities where rivals are forced to close or retrench,

giving way to increased returns for firms engaging in innovative investment, though

inherently risky (Hang, Chen, & Subramian, 2010). In a exploratory analysis of UK food

companies to study the relationship between uncertainty and firm’s risk-taking behaviour,

Roper and Tapinos (2016) found out that firm’s probability of undertaking green

innovation was positively related to both environmental uncertainty and market-related

risks of innovation. This finding is consistent with the findings of Mzoughi (2011) and

Yu and Hang (2011) who have shown that firms may be willing to embrace innovation

risks both for the environmental benefits and also in the hope of creating disruptive

innovation in order to gain market advantage.

In the banking sector, a number of studies have addressed the influence of ownership on

risk taking and performance of banks (Chen & Chen, 2012; Forssbæck, 2011). Using a

sample of listed commercial banks in East Asia and Western Europe, Haw, Ho, Hu, and

Wu (2010) found that banks with concentrated ownership exhibited lower cost efficiency,

greater return volatility, higher insolvency risk and poorer performance relative to the

widely held peers. A similar finding was reported by Shehzad, Haan, and Scholtens

(2010), who observed that ownership concentration reduces bank riskiness at lower levels

of sharesholder protection rights and supervisory control. Chou and Lin (2011), in a study

comprising 650 observations of Taiwan banks found that banks with higher inside

management and higher government ownership had higher overdue loan and lower

capital adequacy ratios. Conversely, banks with higher foreign ownership and relatively

stronger governance strength had lower overdue loans and higher regulatory capital, a

finding corroborated by Agoraki, Delis, and Pasiouras (2011) and Toboada (2011).

From an emerging economy perspective, Haque and Shahid (2016) analyzed panel data

covering 55 commercial banks and 217 bank-year observations in India in order to

examine the effect of ownership structure risk-taking and performance. To measure risk-

taking behaviour, the study used two measures, namely: default risk – which was

measured using Z-score, and credit risk- which was measured by the ratio of non-

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performing loans to total loans, following after Agoraki et al. (2011). In order to measure

the impact of ownership, the study (Haque & Shahid, 2016) used two ownership

variables, namely: concentration of ownership (for example, the percentage of

shareholding of the largest shareholder) and the types of ownership (for example,

government or foreign ownership) after Shehzad et al. (2010) and Barry, Lepetit, and

Tarazi (2011). The results of this study suggested that government ownership was

positively associated with default risk and negatively related to bank profitability. The

results on foreign ownership were the reverse- positive effect on default risk and negative

effect on profitability (Annamalai & Jain, 2013; Haque & Shahid, 2016).

In Ghana, a survey by Danso, Adomako, Damoah, and Uddin (2016) of 298 SMEs

selected from the Ghana business directory belonging to the Association of Ghana

Industries, showed that high levels of entrepreneurs’ risk-taking propensity enhanced firm

performance. The study’s main argument was that entrepreneurs in emerging economies

who took a higher risk were more likely to succeed in improving the performance of their

firms. The study also found that business networks and political ties moderated the

relationship between the entrepreneurs’ risk-taking and firm performance, a significant

finding given the underdeveloped legal and regulatory institutions in emerging economies

(Julian & Ofori-Dankwa, 2013; Li & Zhou, 2010).

2.4.4.3. Management held accountable for performance

One of the major causes of the financial crisis brought about by the sub-prime mortgages

was lack of accountability and transparency in financial management (Brown, Beekes, &

Verhoeven, 2011). Transparency and accountability are the two basic principles of

corporate governance that were violated by the investment and commercial banks, which

brought about the crisis (Bekiaris, Efthymiou, & Koutoupis, 2013; Dalwai, Basiruddin, &

Rasid, 2015; Kumar & Singh, 2013; Yeoh, 2010). Consequently, shareholders, supported

by legislation, have tightened their vigilance and power over boards by demanding more

accountability (Brown et al., 2016; Goranova & Ryan, 2014). As a result of corporate

scandals in North America, the Sarbanes-Oxley Act of 2002 (SOX) was enacted, which

resulted in increased shareholder power over boards and demand for vigilance and

accountability (Dah, Frye, & Hurst, 2014; Pugliese et al., 2014; Ryan et al., 2010). The

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demand for increased accountability has led to changes in board independence and how

boards hold management accountable (Joseph et al., 2014; Westphal & Zajac, 2013).

The United Kingdom has been at the forefront of leading in the corporate governance

reforms since the Cadbury report (1992). It is this report that gave rise to voluntary

compliance regime of ‘comply or explain’, which has now been adopted by almost every

country in the world. With this backdrop, Elmagrhi, Ntim, and Yan (2016) set out to

investigate voluntary corporate governance compliance and disclosure among firms listed

in the UK, examining in particular the board characteristics of the firms. Using balanced

panel data (Ntim, Opong, Danbolt, & Thomas, 2012) comprising annual reports, financial

and market performance data available over six years that the firms had to be listed, the

study chose board and ownership mechanisms as predictor variables. Regression analysis

showed that there was a high level of disclosure in corporations that had a larger board

size, higher proportion of independent directors, and greater board diversity. The study

also indicated that managerial ownership negatively affected acountability, i.e.

compliance and disclosure practices. This latter finding is consistent with previous studies

that established that managerial ownership had a negative association with accountability

and disclosure (Khan, Muttakin, Badrul, & Siddiqui, 2013).

Firms with high managerial ownership have no incentive to invest in corporate

governance disclosures because the cost of the investment is not consistent with the

expected benefits (Chen & Al-Najjar, 2012; Samaha, Dahawy, Hussainey, & Stapleton,

2012). Similary, firms with a concentrated ownership show less external pressure to

demonstrate dislosure and accountability (Ntim & Soobaroyen, 2013; Samaha & Dahawy,

2011). In a study of 934 Italian small enterprises, using logistic regression, Ciampi (2015)

concluded that CEO duality and owner concentration reduced accountability and

disclosure. Another study examining the relationship between firm and ownership

characteristics on corporate governance of Alternative Investment Market companies

found that disclosure increased with the proportion of the independent non-executive

directors (Mallin & Ow-Yong, 2012). Firms with strong stakeholders will tend to disclose

more information (Melis, Gaia, & Carta, 2015) but, overall, companies will ultimately

pursue a cost-benefit strategy in complying with good corporate governance practices

(Elmagrhi et al., 2016).

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The financial and accounting scandals of the last two decades have put especially the role

of the audit committee at the forefront of the battle against fraudulent financial reporting

and compliance. Ever since the initial recommendations of the Cadbury Committee

(1992), audit committees have been identified as a powerful source of improvement in

governance through improving financial reporting (Ghafran & O'Sullivan, 2013). Audit

committees are now a mandatory feature of corporate governance in most jurisdictions

worldwide and academic interest has moved on from whether an audit committee exists

to issues such as composition, their expertise and independence (Ghafran & O'Sullivan,

2013). Review of literature shows a positive relationship between effectiveness and the

presence of audit committee, the independence of audit committees, and the competencies

of the members (Bedard & Gendron, 2010). A study of 315 public companies traded on

the Sao Paulo Stock Exchange, Brugni, Bortolon, Almeida, and Paris (2013) found out

that half of the sampled population did not have an audit committee.

While it is widely accepted that monitoring and holding managers accountable are good

governance practices, exactly how to do it and what information is useful has been

debatable. Cornelli, Kominek, and Ljungqvist (2013), in their study of how boards

monitor management and under what circumstances they fire their CEOs, make two

conclusions: First, the researchers observe that the boards update their beliefs about their

CEOs ability based on firm performance expectations using hard data, which in itself is

not surprising. What was surprising in their study is that the past performance (hard data)

was much less important than the soft information about the CEO’s competence and

concerns about the company’s future performance. The soft information that Cornelli et

al. (2013) discovered was as important for CEO firing decisions included items such as

‘the top management team is strong’ or the CEO ‘sees the need for a more efficient sales

and marketing strategy’ (Martin & Combs, 2014).

In her research paper ‘Questioning Authority: Why Boards Do Not Control Managers and

How a Better Board Can Help’, Nicola Sharpe (2012) argues that the idea of the board

holding managers accountable is a myth. She noted that 70% of outside directors relied

exclusively on executive management for information on which to control the

organization, and that fewer than half of CEOs believed their board of directors

understood the strategic factors that led to the success of their corporations. Sharpe

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illustrates from the collapse of corporations during the financial crisis that most of the

decisions that led to collapse were made by the CEOs. Sharpe asserts managerialism’s

claims that it is corporate executives who have the de facto authority and that boards have

very little authority in practice.

Othman (2012) investigated the impact of disclosure on the board structure and process

on corporate performance in Anglophone and Francophone emerging markets using a

comprehesive measure of Board Structure and Process Disclosure (BSPD) score

developed by Standard and Poor’s. Data was obtained from 220 annual reports for the

year ended 2006. The BSPD comprised 35 items comprising board structure and

composition, role of the board, director training and compensation, and executive

composition and evaluation. The study used a multiple linear regression model for the

dependent variables which included ROE, Tobin’s Q and MTB (market to book ratio),

which showed significantly higher influence of disclosure on corporate performance for

Anglophone companies than for Francophone ones. The impact of BSPD on corporate

performance was higher for firms operating in the financial sector, which is consistent

with higher requirements for disclosure in the sector.

In a study based in Egypt as an example of a developing country with an emerging capital

market, Desoky and Mousa (2012) focused on measuring transparency and disclosure

(T&D) levels in listed companies. The dependent variable for the study, T&D index

comprised two sets of items, first, general board information and, second, financial and

nonfinancial information, both of which contained a total of 65 items. The board

transparency features in the study included whether the firms had a written corporate

governance code and whether they had a designated officer responsible for ensuring

compliance, as well as a person for stakeholder relations. Proportion of non-executive

directors, number of subcommittees, CEO duality, and the proportion of non-executive

members in the audit committee were also included. The source of information for the

study included the annual reports of the firms as well their websites. The six predictor

variables for the study were: ownership structure, foreign listing, firm size, leverage,

liquidity and audit firm. The study used univariate analysis and multi-variate linear

regression analysis. The findings of the study showed that the majority of the listed

companies in the Egyptian Exchange had weak transparency and disclosure practices.

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Looking at governance of 132 hospitals in Ghana, Abor (2015) analyzed the effects on

performance of presence of a board, board size, board composition, presence of

independent directors, CEO duality, board diversity and frequency of board meetings.

The findings of this study were that the hospitals with a board had a better discharge rate

and those with smaller boards did much better than the larger ones. Those boards that met

more frequently had better results.

Governance’s fiduciary duties are the most basic and mandatory duties that a board must

do on the behalf of the owners and stakeholders of a firm. Accountability is about having

clear expectations within the boundaries set by regulatory bodies and the board, which

must be agreed with, and made clear to the management (Carver & Carver, 2009). A

research study in corporate governance of Dutch agricultural co-operatives revealed that

co-operatives lack external mechanisms for disciplining the management unlike in stock-

listed companies that are often in the financial media. The task of performance evaluation

of the co-operatives lies mainly with the board of directors who must hold the

management accountable (Bijman et al., 2013). Increasingly in the Dutch scene,

agricultural co-operatives are delegating formal and real authority to professional

managers. This has happened as a result of increasing organizational complexity brought

about by their sizes.

A study in Tanzania which surveyed 37 SACCOS revealed that the best rural SACCOs by

performance were audited every year as compared to those audited less frequently. The

study also showed that the best run SACCOs had better Return on Assets (ROA), thus

more profitable and sustainable and outperformed the counterparts by as many as six

times (Magali, 2014). While the audit function, an external mechanism of corporate

governance, is an important element of in enhancing integrity and accountability, the way

this role is played is plagued with inadequacies. The audit function is seen as routine as

opinion of organizations’ financial management rarely gets qualified, and are only

required to ensure books and financial reports are proper and give a ‘true and fair view’ of

the state of affairs of the company (Gakeri, 2013). In a study of transparency and

disclosure of firms in the Egyptian exchange, Desoky and Mousa (2012) found out that

only 29% had audit committees with at least three non-executive members and 41% had

one member of the audit committee as a financial accounting expert.

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While the Co-operative Societies Act of 2005 is quiet on the role of the Audit Committee

(Co-operative Act of Kenya, 2012), it is a common governance practice to ensure that the

committee is in place and should collectively have sufficient qualifications and

experience to fulfill its duties (Institute of Directors in South Africa, 2009; Young, 2010).

In the guidelines on governance of deposit taking Sacco societies in Kenya, the Sacco

Societies Regulatory Authority (SASRA) recommends in its Principle No. 8 that the only

prescribed committee for the SACCOs is the Audit. In the terms of reference for the

Audit and Risk Committee, the guidelines state that the committee shall consist of at least

three members appointed from the board and one of who shall be conversant with

financial and accounting matters. The chairman of the board shall not be a member of the

audit committee (SASRA, 2015).

2.4.5. The Moderating Effect of Market Orientation on the Relationship between

Corporate Governance and Organizational Performance

Market orientation refers to business-oriented organization-wide generation of market

intelligence pertaining to current and future customer needs, dissemination of that

intelligence across departments, and organization-wide responsiveness to market

information (Camarero & Garrido, 2012). As a construct, market orientation is a more

precise and operational view of the first two pillars of the marketing concept- customer

focus and coordination, the third being profitability. Market orientation, according to

Kohli and Jaworski (1990), entails (a) one or more departments engaging in activities

toward developing an understanding of customers’ current and future needs (Mahmoud,

Kastner, & Yeboah, 2010), (b) sharing of this understanding across departments, and (c)

the various departments engaging in activities designed to meet select customer needs.

Narver and Slater (1990), on the other hand, take a broader approach in their definition of

the market orientation concept. They assert that market orientation is the organizational

philosophy by which a firm places the highest priority on the profitable creation and

development of superior customer value. Instead of the three-fold construct comprising

organization-wide generation, dissemination, and responsiveness to market intelligence –

characterized as MARKOR (Jaworski & Kohli, 1993; Kohli & Jaworski, 1990), Narver

and Slater (1990) suggested five dimensions. They posited that market orientation (which

they characterized as MKTOR) comprises five dimensions: three core components

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(customer orientation, competitor orientation, infunctional coordination) and two decision

criteria (long-term focus and profitability). However, Narver and Slater (1990), despite

conceptualizing a five dimensional model for market orientation, operationalized

MKTOR with three dimensions; customer orientation, competitor orientation, and

interfunctional coordination (Zachary et al., 2011). Weng, Chen, Pong, Chen, and Lin

(2016) refer to these three dimensions as organizational climate, and aver that they

generate superior customer value.

As this introduction has shown, the definitions of market orientation that have achieved

the greatest acceptable amongst researchers are those proposed by Narver and Slater

(1990), who stress the cultural perspective of market orientation, and Kohli and Jaworski

(1990) who emphasize the behavioural view of market orientation. While the model by

Narver and Slater has three dimensions (customer orientation, competitor orientation, and

inter-functional coordination, the three constructs of Kohli and Jaworski (1990) are the

generation of market intelligence relevant to current and future customer needs; internal

dissemination of intelligence within the organization; and organization-wide

responsiveness to market intelligence in planning and distributing services and products

(Rodrigues & Pinho, 2012; Tsiotsou, 2010). While the two models overlap each other and

are equally useful and reconcilable (Camarero & Garrido, 2012), this study prefers the

one by Kohli and Jaworski (1990) as the competitor orientation in the model by Narver

and Slater (1990) is not as important in the way co-operatives work. This study reviewed

market orientation under three headings: generating market intelligence; disseminating

market intelligence; and responding to market intelligence.

2.4.5.1. Generating Market Intelligence

Market orientation compels the organization to look beyond itself and towards the

environment in order to gather information that can then be shared within the firm and

later utilized to anticipate the needs of the market (McClure, 2010). Generating market

intelligence refers to the process of continuous gathering, analyzing, and monitoring

information for present and future needs of customers (Pinho, et al., 2014; Zebal &

Goodwin, 2012). The environmental mapping of the exogenous factors, such as

government regulation, competition from other firms, and technology is an important

input in generating the information necessary to build market intelligence (Rodrigues &

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Pinho, 2012). Conceptually, generating market intelligence requires internal marketing in

order to align, motivate, coordinate, and integrate employees towards the implementation

of strategy and improving organization performance (Themba & Marandu, 2013).

The implementation of market orientation, therefore, involves the alignment of people,

processes and policies in a value-adding transformation in order to create superior

organizational performance (Rodrigues & Pinho, 2010). Market orientation has also been

described as a business perspective and an organization culture that makes the customer’s

expressed and latent needs the focal point of an organization’s total strategy and operation

(Jyoti & Sharma, 2012). It is the market-sensing capability and intelligence upon which

organizations develop a combination of marketing resources and capabilities aimed at

outperforming competitors (Jain, et al., 2013). The market-orientation construct is based

on the idea that organizations maximize their profits by focusing on market demands

(Choi, 2014). According to Ngo and O'Cass (2012), market orientation, marketing

resources and marketing capabilities contribute to firm performance and produce even

greater impact as they are complementary to each other.

Market orientation is related to organizational culture, a pattern of shared values and

beliefs, but is also a distinct construct which denotes a ‘pattern of behaviours which are

driven by, or co-exist with, various organization types’ (McClure, 2010). However, some

researchers see a difference between the two. Taking the example of Mahmoud et al.

(2016), the researchers advance that market orientation is market driven while

organization culture, which they equate to innovative culture, is market driving. Further,

they posit that market orientation is an intangible resource reflecting behavioural aspects

of culture, while innovative culture is more internally focused and competive advantage

seeking. Market orientation is a product of market culture, which emphasizes

competitiveness and market superiority, and ultimately corporate performance (Zainul,

Astuti, Arifin, & Utami, 2016). Thus market orientation can be defined as the

implementation of a corporate culture that encourages behaviours which lead to collection

and use of market information, development and execution of market oriented strategy

(Udegbe & Udegbe, 2013). According to Otero-Neira, Arias, and Lindman (2013), the

main task of a market-oriented firm is to create products that are aligned to the customers’

perceptions, needs and wants, but this competence requires the ability to learn from

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customers and competitors. Thus, the essence of a market-orientation philosophy is a

learning orientation (Huang & Wang, 2011; Nasution, et al., 2011).

The introduction of customer orientation and marketing concept from the private sector is

has resulted in a great transformation of the public and non-profit sectors (Rodrigues &

Pinho, 2010). The private sector has also bequethed the market-style concepts of

efficiency, effectiveness, accountability, transparency and value for money, thereby

encouraging the tranformation to market orientation (Rodrigues & Pinho, 2012). A

market orientation raises the morale of employees and pride in the organization, increases

their job satisfaction and commitment, and ultimately improving performance since the

entire organization is aligned towards a common goal of satisfying the customer (Pinho,

Rodrigues, & Dibb, 2014). The key to organizational success is through the anticipation,

response to, and capitalizing on environmental changes in order to satisy the needs, wants

and aspirations of the customers (Mahmoud et al., 2010; Mahmoud & Yasif, 2012).

Research in marketing orientation has shown that the business approach happens both

externally, as the organization interfaces with the external markets, but also internally as

the employees adapt to the new procedures and changes (Themba & Marandu, 2013).

Internal marketing, defined as employee-friendly managerial behaviours, is considered as

a crucial partner to external market orientation as it emphasizes the role of motivated

employees in driving service excellence (Rodrigues & Pinho, 2012). Internal marketing

involves motivating, empowering and training particularly front-line staff to think and

behave in customer orientation (Rodrigues & Pinho, 2010). Since a customer-oriented

posture creates a favourable environment for an organization to meet their needs, many

studies acknowledge that market orientation leads to a superior organizational

performance (Themba & Marandu, 2013).

Some researchers regard market orientation as a marketing as well as management

strategy and that it helps firms develop an external orientation towards its makets,

superior performance, and competitive advantage (Ramayan, Samat, & Lo, 2011).

However, Mokhtar, Yusoff, and Ahmad (2014) aver that market-orientation is different

from marketing as the former is no longer a concern of just the marketing department.

Zachary, McKenny, Short, and Payne (2011) support the notion and aver that coordinated

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marketing, one of the three components of operationlized market-orientation, MKTOR

(Narver & Slater, 1990), requires that a marketing strategy is not just a concern of the

marketing department. Thus the marketing department is not viewed as more important

than other departments (Mokhtar et al., 2014).

In order to examine the relationship between market orientation and export marketing

performance, Julian et al. (2014) analyzed using multiple regression 109 responses from a

survey of export manufacturing firms in Indonesia. The study showed that customer

orientation, competitor orientation and interfunctional coordination had significant

influence on export marketing performance (Gruber-Muecke, Tina, & Hofer, 2015).

Based on the classic work on market orientation by Narver and Slater (1990), Mahmoud

and Yusif (2012) suggest that generating market intelligence is akin to customer

orientation and competitor orientation, that is acquring information from the buyers and

competitors in the target market.

In their study based in Portugal to investigate the impact of internal and external market

orientation on the performance of municipal authorities, Rodrigues and Pinho (2012)

found that information generation had a positive effect on the financial performance. The

study sampled 354 executive board members drawn from 308 Municipalities in the North

Region of Portugal. For information generation, the constructs used included: what

employees wanted; what they felt about their jobs; whether the leaders regularly talked

with employees about their work; internal market research; regular staff appraisals;

regular staff surveys to identify influences on employees’ behavior. The measures of

financial performance were: the degree of budgetary accomplishment; degree of

attainment of financial objectives; growth in income, size of profit/surplus; efficient use

of assets and funds; and degree of activities performed to generate funding/income

(Rodrigues & Pinho, 2012).

Similarly, Polo-Pena, Frias-Jamilena, and Rodriguez-Molina (2012a), in a study of rural

tourism sector aimed at ascertaining the importance of market orientation as a business

strategy, showed that information generation – what they referred to as ‘capturing market

information’, had positive effects on the performance of firms. The constructs used in the

study to measure information generation included: a) obtaining information through

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tourism sector media such as associations, trade fairs, and industry publications b)

obtaining sector information through informal means such as chats with members of other

businesses, friends, and brokers, and c) obtaining information on fundamental changes in

the industry, such as changes in competition, technology, and regulations.

A necessary condition for the ability of the firm to be proactive with respect to customer

needs is an entrepreneurial orientation (Otero-Neira et al., 2013). Entrepreneurial

orientation has three dimensions, namely: innovativeness, proactiveness, and risk taking

(Chad, 2013), and aims at being ahead of the competition. According to Huang and Wang

(2011), innovativeness is a willingness by the firm to pursue new ideas; proactiveness

refers to a forward-looking and responsiveness to the environment; while risk-taking

means pursuit of entrepreneurial opportunities without regard to the resources the firm

may or may not have. Thus entrepreneurial orientation adopted in an organization enables

its members to be more proactive with respect to customer needs and embrace risk in

delivering value to customers (Otero-Neira et al., 2013).

2.4.5.2. Disseminating Market Intelligence

Disseminating of market intelligence involves the vertical and horizontal flow and

sharing of the information that has been generated particularly within the departments and

functions of the organization (Rodrigues & Pinho, 2012). It involves holding discussions

about customer trends across the departments of a firm (Polo-Pena et al., 2012a).

Disseminating market intelligence may also involve cooperation with other similar

organizations with a view to generating a joint competitive response to satisfy

stakeholders, hence also called competitor orientation (Mahmoud & Yusif, 2012). When

adapted to employer and employee exchanges in an organization, the concept of internal

market orientation is used to signify the process of generating and disseminating

intelligence and satisfying those needs (Fang, Chang, Ou, & Chou, 2014).

The essential factors necessary in developing marketing orientation are inter-departmental

coordination and inter- and cross-functional connectedness and integration (Mahmoud,

Kastner, & Akyea, 2011). With a high level of inter-functional coordination, employees

are willing to share and communicate important information with other staff, thus sharing

market intelligence across the organization and improving customer value (Weng et al.,

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2016). Establishing appealing goals, and building a culture in which employees are

encouraged and rewareded for behaviour that promotes market orientation was found to

positively influence relationship quality and patient loyalty in a hospital setting (Huang,

Weng, Lai, & Hu, 2013).

In a similar hospital setting and using a cross-sectional research design, Weng et al.

(2016) analyzed 343 samples from nurses in two Taiwanese hospitals to study the impact

of market orientation on patienty safety and climate. The study found that developing

human resource and training systems improved sensitivity of employees to customer

needs, thus enhancing market orientation (Iliopoulos & Priporas, 2011). The study also

concluded that improving internal marketing can enhance the market orientation of

employees by creating better organizational commitment and service quality (Tsai & Wu,

2011).

Internal marketing and internal market orientation, referring to exchanges between

managers and employees, are used synonymously to describe the process of gathering and

disseminating intelligence of employee needs and then responding to those needs (Fang,

Chang, Ou, & Chou, 2014). In a study to examine whether internal market orientation

facilitates the development of external market capabilities, Fang et al. (2014) analyzed

data from 159 service companies in Taiwan. In order to measure the Internal Market

Orientation (IMO), the researchers used three dimensions (generation, dissemination, and

responsiveness of internal market information). Organization performance was measured

using financial, market and innovation performance measures. The results showed that

internal market orientation was positively related to external market capabilities, which in

turn influenced market performance the most, followed by innovation performance and

then innovation performance. The study concluded that an organization may need to build

an information system to collect internal market information and that communication

channels, both formal and informal, should be maintained (Rodrigues & Pinho, 2012).

According to Kazakov (2016), inter-functional coordination is the most vital of the

market orientation dimensions as it delivers a positive impact on the firm’s business

performance. Based on a research of 133 businesses in the Russian service industry, the

items studied included: departments’ interaction with customers; information distribution

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among departments; corporate strategy embracing all departments; inter-departmental

interaction and cooperation; five-year strategic development available; and employees’

work coordination by management. The study showed that inter-functional coordination

increased sales dramatically by building a service organization which was customer-

centric. The coordination benefit was leveraged through distribution of market-specific

information, mutual targets, plans, budgets, shared responsibility and reward systems. In

an analysis of the Nigerian oil market, Onyeniyi (2013) reached the same conclusion and

avered that organizational commitment, built through top management belief and reward

system, affects market orientation positively.

In a study of Indian banks Kaur, Sharma, and Seli (2013) opined that there was signicant

impact of internal market orientation on the overall market orientation compared to

external market orientation. They concluded that, in order to improve market orientation

in the banking sector, the managers should take the following initives: develop a healthy

working environment; ensure parallel inter- and intra-departmental communication;

conduct internal market research regularly to generate information pertaining to job

requirements of internal customers; and retain employees through the successful

implementation of internal marketing strategy.

The marketing orientation and internal marketing orientation are inter-related concepts

and are both shown to influence the customer’s perceived level of service quality and

customer’s subsequent behavior (Gounaris, Vassilikopoulou, & Chatzipanagiotou, 2010).

In a study comprising 127 dyads of companies with their customers, Gounaris et al.

(2010) set out to investigate empirically the relationship between market orientation and

internal market orientation. The researchers measured internal market orientation using

evaluation of three components: collect internal market-related intelligence that helps

specify employees’ needs and expected value; establish internal communication between

supervisors and subordinates; and respond to employees’ needs and expected value.

In order to capitalize on market intelligence, a firm’s internal marketing processes

requires a marketing culture and behavior (Bucic, Ngo, & Sinha, 2016). In a study based

in an emerging market, Vietnam, the authors set out to investigate the roles of product

innovativeness, customer relationship management (CRM) capability, research and

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development integration and brand management capabilities in the institutionalization of

a marketing orientation culture. The results of the study showed that marketing

orientation fully mediated the effects of market-orientation culture on product

innovativeness and CRM capability, which in turn enhanced firm performance.

In a research to examine if a democratic management model can enhance performance

through market orientation, Agirre et al. (2015) analyzed data from 132 business units

from the Mondragon co-operative using the structural equation modelling. The results of

the study indicated that organizational commitment by workers is an antecedent, rather

than a consequence, of market orientation. Further, the results showed the importance of

decentralization and distribution of power and employee participation in decision-making

for strengthening organization commitment. These findings suggest that the adherence to

the co-operative principles lead to organizational commitment, an antecedent of market

orientation, and superior organizational performance.

The study by Agirre et al. (2015) also showed that total quality management (TQM)

enhanced employee commitment and generation of cultural market orientation, which is a

culture that is characterized by appreciating an organization’s internal and exernal

context, functional cooperation and coordination, and adoption of a long-term view of the

market (Owino & Kibera, 2015). Empirical evidence shows that the implementation of

TQM leads to a change from an internal focus to market orientation, in addition to

ensuring that all the firm’s functions are responsible for implementing it (Wang, Chen, &

Chen, 2012). The enhanced inter-departmental dialogue that follows TQM

implementation and the cooperation and communication between the marketing

department and other company functions, all add up to the development of an overall,

organization-wide response to market intelligence (Agirre et al., 2015).

The results obtained by Agirre et al. (2015) are corroborated by similar conclusions by

Arando, Gago, Jones, and Kato (2015) who undertook an econometric study of Eroski,

the largest member of the Mondragon group of worker co-operatives. Of the three types

of stores found within Eroski, co-operatives with significant employee ownership

outperformed co-operatives with only modest employee ownership and conventional

stores without employee ownership. The authors provided evidence that employee

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involvement, stronger economic incentives, and workers training and skill formation led

to higher organizational commitment and adoption of market orientation (Arando et al.,

2015). Companies that make conscious and distinctive choices about what principles to

follow, such as co-operatives, are best placed to generate competitive advantage out of

their management model (Agirre et al., 2015).

The role of intelligence dissemination in relation to innovation speed was noted in the

research by Carbonell and Escudero (2010) of Spanish manufacturing firms where

innovation speed and new product performance were examined. The results of the study

indicated intelligence dissemination influenced innovation speed positively and that

intelligence generation and intelligence dissemination influenced new product

performance indirectly through responsiveness. A similar study on innovation based on

data representing both economic boom and economic crisis showed that the role of

innovation capability as a mediator between market orientation components varied along

the business cycle (Huhtala, Sihvonen, Frosen, Jaakkola, & Tikkanen, 2014).

2.4.5.3. Responding to Market Intelligence

Although market-driven orientation has been shown to be positively related to superior

corporate performance (Narver & Slater, 1990; Jaworski & Kohli, 1993), scholars have

argued successful companies need to adopt a more proactive attitude towards business,

which has been referred to as market-driving orientation (Filieri, 2015). According to

Sajjaviriya and Ussahawanitchakit (2015), market-driving strategy orientation is seeing

opportunities to fill a latent need or offer an unparalled level of customer value. Market

driving is about influencing and redrawing the configuration of the market through

breakthrough innovations (Kwon, 2010) and, thereby, staying ahead of the competition

(Halliru, 2016). In a case analysis of the Benetton Group in Italy to investigate the

relationship between market-driven orientation and business performance using

longitudinal data, Filieri (2015) showed how the firm positioned itself as innovation

leader through creative advertising styles and unique brand image. For Benetton, the

competitive advantage was moving from market driving to market driven orientation in

order to satisfy customers’ changing fashion trends rather than creating new needs (Parry,

Jones, Stern, & Robinson, 2013).

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Market orientation has also been described as an intangible competency that facilitates to

serve targeted customers and more efficiently monitor the organization’s competitors with

a view to improving the performance (Hilman & Kaliappen, 2014). This follows the work

by Narver and Slater (1990) who suggested that market orientation has three other

dimensions, namely: competitor orientation, customer orientation, and inter-functional

orientation. Like Kohli and Jaworski (1990) typology, market orientation is viewed as a

continous variable focusing on, first, gathering information from competitors and

customers all with a view to create value for customers (Julian, et al., 2014).

The difference between the two typologies is that Narver and Slater (1990) see market

orientation as an organizational culture while Kohli and Jaworski (1990) perceive market

orientation as a marketing concept. Consequently, competitor orientation stands for

organizational culture that evaluates abilities and tactics of the main rivals and utilizes

this awareness to get an edge over them and achieve a sustainable competitive advantage

(Kaliappen & Hilman, 2013). Customer orientation, on the other hand, is an

organizational culture that considers customers’ needs and wants for the present and

future in order to provide superior value (Hilman & Kaliappen, 2013). Putting customer

relationships at the forefront is key to a firm’s managing its relationships with external

customers (Fang et al., 2014).

There are other studies that have suggested that entrepreneurial orientation and market

orientation are complementary. A study by Amin, Thurasamy, Aldakhil, and Kaswuri

(2016) set out to examine the effect of market orientation as a mediating variable in the

relationship between entrepreneurial orientation and SMEs performance. Based in

Malaysia and data gathered from the SME Business Directory, 500 firms were targeted

using a judgmental sampling technique. The dimensions of entrepreneurial orientation

(Amin, 2015) measured were innovativenes, proactiveness and risk-taking and analyzed

using a multiple linear regression technique. The results of the study that entrepreneurial

orientation had a significant relationship with market orientation, and that market

orientation had a significant relationship with SME performance. This finding was

consistent with results from other studies that organizations with more more collaboration

and entrepreneurial orientations have greater market information to explore market

opportunities and perform better (Fernandez-Mesa & Alegre, 2015).

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However, there are schools of thought and research evidence pointing to conceptual

shortcomings of market orientation as a management framework. The integration of

sustainability principles to corporate management strategy has been shown to result in a

balanced and sustained economic and social performance (O'Driscoll, Claudy, &

Peterson, 2013; (Wooliscroft, Ganglmair-Wooliscroft, & Noone, 2014). Consequently,

scholars have re-conceptualized market orientation by combining it with sustainable

management in order to achieve organizational efficiency, effectiveness and balance

(Mitchell, Wooliscroft, & Higham, 2013). This is necessitated by deficiencies in

corporate governance, exploitative environmental tendencies and the tendency to

emphasize short-term wealth maximization at the expense of long-term stakeholder

interest (Pantouvakis, 2014). The call is for firms to move beyond MO to sustainable

market orientation (SMO) by adopting more responsible business practices, and to

achieve greater alignment of longer term performance with a wider range of current and

latent stakeholders (Claudy, Peterson, & O'Driscoll, 2013; Mahmoud M. A., 2016).

Mitchell, Wooliscroft, and Higham (2010), using the definition of market orientation

(MO) by Morgan and Strong (1998), argue that MO’s concentration on micro-economic

and functional management is not easily aligned with the roles of a contemporary

marketing organization. Specifically, Mitchell et al. (2010) aver that there is a need of a

much broader view of marketing management necessitated by the ecological, social and

economic impacts arising from market-driven events. Examples of the short-term market-

based strategies, according to the researchers, include exploitation of indigeneous forests,

depletion of fishing resources, socially negligent production management, and marketing

of non-safe products, among many others (Mitchell et al., 2010). To overcome these

challenges, the researchers join those calling for a reconceptualization of market

orientation in order to achieve greater alignment of long-term performance with the

interests of a wide range of stakeholders. Adopting the concept of sustainable market

orientation by synthesizing market orientation with corporate social reponsibility and

sustainable development management will overcome the narrow view of the current

scope of market orientation (Mahmoud, 2016).

Responsiveness to market intelligence includes actions involving the design and selection

of products and services, their production, distribution and promotion (Rodrigues &

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Pinho, 2012). Market orientation shapes the way employees respond to the information

they obtain from the environment and creative new ways of doing things in order to add

new value to customers (Pan & Li-Yun, 2011). The construct ‘organizational

responsiveness’ in Kohli and Jaworski’s (1990) orientation is more or less equivalent to

‘interfunctional coordination’ in Narver and Slater’s (1990) model. Interfunctional

coordination comprises the coordinated efforts of all departments, after acquiring the

information about buyers and the competitions in the target market, and disseminating it

throughout the business, in order to create superior value for the buyers (Mahmoud &

Yusif, 2012).

According to Camarero and Garrido (2012), interfunctional coordination involves sharing

information among all the members of the organization thereby creating synergies

enabling objectives to be accomplished. Interfunctional coordination also enhances

problem solving capabililities, collaboration, communication and relationships between

groups and functions (Camarero & Garrido, 2012). Market orientation is influenced by an

organization’s characteristics, especially in family firms where first-generation and later-

generation can differ a lot in styles of leadership and management (Kohli, Jaworski, &

Kumar, 1993). According to Beck, Janssens, Debruyne, and Lommelen (2011), the

characteristics differentiating first- from later-generation family firms include: centralized

decision making; professional style of management; risk aversion; external orientation,

and growth orientation.

Responsiveness to the market is about learning, in which organizations modify their

actions through tactical adjustments, on the one hand, or question old values, assumptions

and ways of doing things, on the other (Choi, 2014). Responsiveness is also associated

with innovation (product, technological, and organizational) as a key factor to superior

performance and competitive advantage (Garrido & Camarero, 2010). In their study of

386 British, French and Spanish Museums to assess the impact of organizational learning

and innovation on performance, Garrido and Camarero (2010) showed that learning

orientation significantly influenced both innovativeness and performance, with product

innovation having a greater impact. According to Otero-Neira et al. (2013), market

oriented firms generate ‘market-pull’ innovations which are more successful than

innovations developed by firms with an entrepreneurial ‘push’ orientation. The

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explanation for this distinction seems to be that the former allocate resources to respond

to the market response, while the latter do so only as an internal tendency to develop

technology.

According to the research by Agirre, et al. (2015), today’s dynamic and competitive

environment requires purposeful flexibility and agility in order to be succcessful, and

market orientation has been identifed as a key ingredient in successful adaptation to the

environment. An organization can obtain long-term shareholder value as a consequence

of listening to customers (buyers as well as users of products) as the source of inspiration

and development, an approach Lagerstedt (2014) describes as outside-in. The outside-in

perspective is about beginning with the market, not from organization’s own capabilities,

and generating and deploying unique market insights in order to inform the entire

organization to achieve, sustain and profit from customer value (Day & Moorman, 2010).

Polo-Pena et al. (2012a), in their study on market orientation as a business strategy in

Spanish tourist firms, measured organizational responsiveness using a scale developed by

Polo-Pena, Jamilena, and Rodriguez-Molina (2012b) comprising 7-point Likert scale. The

questions asked were: a) ‘we are continously revising the offer (facilities, price levels) to

ensure they are in line with what customers want; b) ‘the services offered are more

responsive to our internal capacity than to the real needs of customers; c) ‘if we find that

customers are not satisfied with the quality of our service, we carry out remedial

measures immediately’. Their study concluded that market orientation undertaken by the

firm had a direct effect on firm outcomes, and that the perceived value had a direct effect

on the customers’ behavioural intentions towards the firm.


This chapter reviewed the theoretical framework of the study on corporate governance

and its effect on organization performance. A conceptual model of the key theory,

stewardship, was developed showing how its dimensions were operationalized. The

chapter also reviewed the relevant literature based on the research questions of the study.

The next chapter deals with the research methodology for the collection and analysis of

data to address the research objectives of the study. The research philosophy, research

design, target population, sampling design and the data analysis methods are presented.

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CHAPTER THREE

3.0. RESEARCH METHODOLOGY

3.1. Introduction


organizational performance of dairy co-operatives in Kenya. This chapter explains the

research philosophy, research design, target population, sampling design, data collection

methods, research procedures and data analysis methods that were used in this study.

Finally, the chapter provides a summary.

3.2. Research Philosophy

A research philosophy as described by Blaxter, Hughes, and Tight (2010) refers to a

principle about how data concerning a study phenomenon should be collected, analyzed

and reported for final use. Saunders, Lewis, and Thornhill (2016) on the other hand, argue

that a research philosophy simply outlines the purpose of conducting the study. They

suggest four philosophical worldviews: positivism, realism; interpretivism and

pragmatism. Positivism, described as the philosophical stance of the scientist (Saunders et

al., 2016), is concerned about collecting data about an observable reality in order to

search for causal relationships and make generalizations (Gill & Johnson, 2010). Realism,

on the other hand, suggests that there is a reality independent of the mind and what we

experience is a sensation and images of the things in the real world, not the things directly

(Saunders et al., 2016). Interpretivism adopts a more personal and empathetic stance and

enters the social world of research subjects to understand their world from their point of

view rather than to generalize like the positivists do (Edirisingha, 2012). Pragmatists are

not attached to either positivism or interpretivism and may use multiple methods in the

search for what works (Creswell, 2014).

Positivism, the philosophy on which this study is based, is based on the belief that reality

is stable and can be observed and described from an objective viewpoint without

interfering with the phenomenon itself (Cooper & Schindler, 2014). Positivist researchers

maintain that occurrences should be isolated and observations should be subject to

repetition (Gicheru, 2013). According to Saunders, et al., (2016), positivism reasons that

an objective reality exists which is independent of human behavior and hence it is not

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created by the human mind. Elements of a positivist research have certain implications on

social research such as (i) all research is assumed to be quantitative, and therefore only

quantitative research can be subject of valid generalizations and laws; (ii) the choice of

the topic of research and the methodology should be determined by objective criteria and

not by human beliefs and interests; (iii) the aim of the study should be to identify causal

explanations and important laws that explain human behavior; (iv) concepts should be

made in a way that enables facts to be measured quantitatively; (v) the researcher’s role is

independent of the subject under examination, and (vi) the issues are better understood if

they are downgraded or summarized to the simplest elements possible (Bryman & Bell,

2011; Saunders, et al., 2016).

Holloway and Wheeler (2010) also share a similar view on the independence of the

researcher’s role and suggest that positivism is the quest for objectivity and distance

between researcher and those subjects under study so that any biases that may arise in the

study are avoided. Creswell (2014) opines that according to positivism, causes determine

outcomes and hence the problems studied by positivists portray the need to identify and

show effects and how they lead to certain outcomes as in the case of experiments.

Mukherji and Albon (2010) contend that by applying highly controlled procedures and

quantifying variables in a research, as positivist philosophy requires, it is possible to

obtain results that help to refine theory. Due to the strict application of scientific method

and the control of variables in positivism, the findings from a positivist study are deemed

as valid and replicable. Further, positivism leads to quantitative methodology and the

application of econometric analysis (Collins, 2010).

Positivism was suitable for this study for several reasons. First, the study adopted a

quantitative research methodology; second, the results were generalized from the

samples. Third, the hypotheses were tested using inferential statistics and decisions made

to either accept or reject the respective hypotheses (Cooper & Schindler, 2014; Saunders

et al., 2016). Fourth, the researcher measured the data and reached conclusions, and

lastly, because the data represented real situations which leads to high reliability and

validity.

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3.3. Research Design

According to Cooper and Schindler (2014), research design is the comprehensive plan,

structure or strategy of collecting data with the aim of obtaining answers to various

research questions. It entails what the study is about, the reasons for carrying out the

study, the location of the study, the type of data required, the possible sources of the data,

the time periods of the study, the sample design, data collection techniques, data analysis

methods and the style of preparing the final report. Saunders et al. (2016) similarly define

research design as the general outline of how the researcher is going to answer the

research questions. The authors explain that the essentials of a research design are such

that it is an activity and time-based plan, which is always centered on the research

question. It is also a guide for selecting sources and types of information, a basis on

which the relationships among the study’s variables are specified and also a practical

outline for every research activity (Bryman & Bell, 2011).

According to Kumar (2011), there are three types of research design: exploratory,

descriptive, and explanatory. A descriptive study attempts to describe systematically a

problem or provides information about a situation with the aim of showing what is

prevalent with respect to the issue. An explanatory study attempts to clarify why and how

there is a relationship between variables. In exploratory research, a study is undertaken to

explore an area about which little is known for feasibility or pilot study in order to assess

if it is worth carrying out a full detailed investigation (Zikmund, 2013).

This study used a descriptive correlation research design to investigate the effect of co-

operative governance on organizational performance of dairy co-operatives in Kenya.

According to Kumar (2011), a descriptive correlation study aims to discover or establish

the existence of relationships or independence between two or more aspects of situations.

A descriptive correlation research design is fitted for this study because an independent

variable causes change in a dependent variable. The design is also concerned with the

descriptions of phenomena or characteristics such as who, what, when, where of a subject

population. In addition, descriptive correlation design is fitted for this study as it

establishes a relationship and association between several variables in the same

population (Leedy & Ormond, 2015) in order to examine the effect of corporate

governance on organizational performance of co-operatives.

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3.4. Target Population

Target population is the full set of cases from which the sample is taken and which the

researcher wants to generalize results from (Saunders et al., 2016). Another definition

regards target population as all elements or people that a researcher would like to study

(Zikmund, Babin, Carr, & Griffin, 2013). In other words, a target population comprises of

all individuals, events or objects that have common characteristics and from which the

researcher wants to generalize results (Cooper & Schindler, 2014).

According to the Kenya National Bureau of Statistics (KNBS, 2016), the total population

of dairy co-operatives in Kenya stood at 427 in 2015. The only database of the dairy co-

operatives was in the Co-operatives department of the Ministry of Industrialization and

Entrepreneurship, which contains a list of 487 registered dairy co-operatives since 1936.

However, the database of these co-operatives was found by the researcher to be

inaccurate and not up to date especially with mergers or closures. Other sources of

information such as the Co-operative Alliance of Kenya (CAC, 2015) stated that there

were 240 registered dairy co-operatives in Kenya as of December 2014 without a name

and location listing. Saunders et al. (2016) recommend that, where no suitable list exists,

the researcher will have to compile their own sampling frame to ensure that it is valid and

reliable.

Due to the lack of an accurate database of active co-operatives, the researcher, with the

help of County Directors of Co-operatives, validated the existing database from the field.

This study selected the Mt Kenya region and chose the eight counties in the area, since it

had a large number and a good mix of sizes of dairy co-operatives as the target

population. The researcher proceeded to the field and visited the eight counties and

contacted all the dairy co-operatives in the region. As a result of this exercise, 198 dairy

co-operatives were found to be actively operating in the eight counties of Mt Kenya

region, as Table 3.1 shows, and as detailed in Appendix C.

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Table 3.1: Dairy Co-operatives in Mt Kenya region of Kenya

County Number of active

Dairy Co-ops

1 Embu 9

2 Kiambu 14

3 Laikipia 16

4 Meru 47

5 Murang'a 42

6 Nyandarua 26

7 Nyeri 24

8 Tharaka-Nithi 20

Total 198

Source: Researcher

The target population for this study was the executive directors (managing directors or

managers) of the 198 dairy co-operatives in the Mount Kenya region. The Co-operative

Act (Co-operative Act of Kenya, 2012) requires co-operatives to have up to nine non-

executive or independent directors and the executive director/manager, and thus each of

the 198 dairy co-operatives has an executive director. According to the Co-operative Act

of Kenya (2012), the main responsibility of the manager is the general management of the

society which includes the maintenance and custody of society books, accounts, assets,

registers, certificates, society seal, checkbooks and other accounting documents. In

addition, it is the duty of the manager to counter-sign societies’ checks, contracts and

other official documents.

3.5. Sampling Design

Sampling design is the method used to find a sample from a specific population and as

such, it is the procedure that a researcher uses while selecting items for the study’s sample

(Cooper & Schindler, 2014). Sampling frame comprises the following: sampling frame,

sampling technique and sample size, which are discussed in turn.

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3.5.1. Sampling Frame

Saunders et al. (2016) define sampling frame as the complete list of individuals or entities

in the population, from which a probability sample is drawn and to which study findings

are to be generalized. This study focused on the executive/managing director drawn from

each of the 198 dairy cooperatives in the Mt Kenya region. This list was obtained from

the County Directors of Co-operatives from eight counties of the Mt Kenya region.

3.5.2. Sampling Technique

Sampling techniques provides a way in which a researcher scientifically selects the

elements to be studied. It is a process of selecting representative elements from the whole

population in order to generalize the results (Saunders et al., 2016). Sampling techniques

can be either probability sampling or non-probability sampling (Creswell, 2014).

Probability sampling is a sampling technique in which every member of the population

has a known, non-zero probability of selection, whereas in non-probability sampling,

units of the sample are selected on the basis of personal judgment or convenience

(Zikmund et al., 2013).

According to Cooper and Schindler (2014), non-probability sampling techniques include

convenience, purposive, quota, and snowball. In convenience sampling, the researcher

has freedom to choose whom to sample and may include pools of friends or neighbors or

persons intercepted on the street. Convenience sampling is useful for gaining or testing

ideas and is often preferred at an early stage of a study as it is the cheapest to conduct

(Zikumnd et al., 2013). Purposive or judgment sampling refers to selection of a sample by

an experienced person based on their judgment, such as the consumer price index (CPI),

which is based on a sample of market-based items (Saunders et al., 2016). In quota

sampling, the various subgroups of a population are represented in the sample, while

snowball sampling refers to participants being volunteered by initial selection of

respondents (Zikmund, et al., 2013).

According to Saunders et al. (2016), probability sampling techniques include simple

random sampling, systematic sampling, stratified sampling, and cluster sampling Simple

random sampling is the most commonly used technique for selecting a random sample

and refers to a method whereby each element in the population is given an equal and

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independent chance of selection (Kumar, 2011). Systematic sampling involves the

selection of elements at regular intervals in the population beginning with a random start

(Cooper & Schindler, 2014). In stratified sampling technique, the population is divided

into heterogeneous sub-groups or strata that are more or less equal and homogenous

within them according to a certain characteristic by using simple random sampling in

order for the sample to reflect the population (Zikmund et al., 2013). In cluster sampling,

the sampling population is divided into many homogeneous subgroups based on visible

characteristics, and the subgroups chosen for study are often heterogeneous within

(Cooper & Schindler, 2014).

This study made use of stratified random sampling technique, which, according to

Saunders et al. (2016), is a probability sampling technique where the population is

divided into two or more relevant strata and a random sample is drawn from each stratum.

The choice of stratified random sampling is based on the fact that the technique enables a

researcher to select a sample which is representative of the entire population (Bryman,

2012). In this study, the sample was stratified according to the county to which the co-

operative belongs. Stratified random sampling was relevant for this study because of the

varied geographical distribution of the sample population and the representativeness of

the sample size (Saunders et al., 2016).

In this study, eight strata were formed as shown in Table 3.1 representing the eight

counties of the Mt Kenya region, namely Embu, Kiambu, Laikipia, Meru, Murang'a,

Nyandarua, Nyeri and Tharaka-Nithi. The first step in stratified random sampling was

dividing the population into heterogenous strata according to the counties. Since each of

the county strata were homogeneous, the simple random sampling was then done to select

the sample using a computer program.

3.5.3. Sample Size

According to Creswell (2014), the sample size is a subset of the population or the number

of items to be selected from the population to constitute a sample. The sample size of a

study is of major concern to the researcher as it aims to remove bias in the selection of the

sample (Kumar, 2011). A small sample size may not serve to achieve the study objectives

and a large one may incur huge cost and waste resources (Zikmund et al., 2013). While

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choosing the sample size, scientific methods need to be used. Saunders et al. (2016) argue

that when the sample size is large, then there is a lower likelihood of error in generalizing

the population.

In this study, Yamane (1974) formula was used because the population is finite and is

known. In addition, the formula is scientific, and can be applied to a large population.

Yamane (1974) formula is specified as equation 3.1 below.

Where:

n denotes the sample size

N is the target population

ε is the precision error. There are three conventional precision errors namely; 0.01, 0.05

and 0.1. The study used a precision error of 0.05 since it is well accepted in social

sciences studies. The precision error, or level of significance of 0.05, is the same as 95%

degree of confidence for statistical tests (Cooper & Schindler, 2014).

Since the sampling frame of this study was not homogenous and the samples were taken

from eight counties or strata, the calculation of the sample size was done for each stratum

(Bryman & Bell, 2011). According to Saunders et al. (2016), dividing the population into

strata means that the sample is more likely to be represented proportionately.

In this study, stratified sampling was used to divide the population into eight

heterogenous groups and Yamane (1974) formula used to determine sample size for each

strata (Yismaw, Mekonen, & Assefa, 2016). Each of the strata is homogenous within

itself and units are then sampled at random for each statum (Singh & Masuku, 2014).

Using the Yamane (1974) formula and given that the target population was 198 executive

directors/managers, the calculation for each stratum is as shown in equation 3.2:

Where [P] is the Population

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Table 3.2 shows how the sample size was calculated using stratified sampling technique.

This implies that a sample size of 184 executive directors/managers of dairy cooperatives

in Mt Kenya was used for this study.

Table 3.2: Distribution of the Sample Size

Stratum P= Population Calculation Sample Size

1 Embu 9 9/{1+[9](.052)} 9

2 Kiambu 14 14/{1+[14](.052)} 14

3 Laikipia 16 16/{1+[16](.052)} 15

4 Meru 47 47/{1+[47](.052)} 42

5 Murang'a 42 42/{1+[42](.052)} 38

6 Nyandarua 26 26/{1+[26](.052)} 24

7 Nyeri 24 24/{1+[24](.052)} 23

8 Tharaka-Nithi 20 20/{1+[20](.052)} 19

Total 198 184

Source: Researcher

3.6. Data Collection Methods

The study used a questionnaire to collect data from the executive directors from the 184

dairy co-operatives in Mt Kenya region. Christensen, Johnson, and Turner (2014) argue

that questionnaires are the most commonly used method of data collection because they

enable a researcher to save time, since it is possible to collect a large amount of

information in case of a large population. However, the authors caution that

questionnaires must be kept short and that they are subject to non-response to selective

items as well as reactive effects.

The questionnaire was divided into various sections and aimed to first capture general

information about the respondents, and then to solicit specific information arising from

the research questions. Each section was divided into further sub-sections, the first to

assess the existence of the components of each independent variable, while the others

assessed the perceived effect each component had on the organizational performance. The

questionnaires were self-administered to the respective respondents who were asked to

indicate their response on a five-level Likert scale ranging from 1 to 5 where 1 reflected

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Strongly Disagree, 2 reflected Disagree, 3 reflected Neutral, 4 reflected Agree, and 5

reflected Strongly Agree.

3.7. Research Procedure

Research procedure is a step in the scientific method where the research process is

described in sufficient detail to permit another researcher to repeat the research (Cooper

& Schindler, 2014). In this study, the research procedure included the permission sought

for the research, how the pilot study was conducted, the reliability and the validity of the

instruments used, how the instruments were administered, and ethical considerations

made in the study.

3.7.1. Permission

Permission to conduct this research was granted in stages: initially by the research

supervisors and then the Dean, Chandaria School of Business (Appendix D). A research

permit was obtained from the National Commission for Science, Technology and

Innovation (NACOSTI) in order to comply with the Science and Technology Act, Cap

250 of the Laws of Kenya (Appendix E and F). Permission was also sought from all the

co-operatives included in the study.

3.7.2. Pilot Study

Zikmund et al. (2013) define a pilot study as a small-scale research project that collects

data from respondents similar to those that will be used in the full study. The purpose of

piloting is especially to test the questionnaire and any weaknesses that may exist in it.

Bryman (2012) posits that pilot studies are particularly crucial in self-completion

questionnaires since the interviewer will not be present to clear up any confusion. Further,

inappropriate questions and instructions can be identified and corrected. Bryman and Bell

(2011) recommend that the pilot should be not be carried out on people who might be

members of the sample employed in the full study as that may affect representatitiveness

of any subsequent sample. Instead, it is best to find a small set of respondents who are

comparable to members of the population from which the samples are taken.

According to Saunders et al. (2016), the pilot sample size should be sufficient to include

any major variations in the population that are likely to affect responses, and recommend

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a minimum number of 10 respondents. For this study, 11 executive directors from 11 co-

operatives participated in pilot testing. In each co-operative, the executive

director/manager was chosen from co-operatives that were not among those selected for

the main study. Once data for pilot testing was collected, it was coded and entered in

SPSS to test for reliability and validity of the research instrument. After the pilot study,

the questionnaire was refined and amended before distribution for the main study.

3.7.3. Reliability of the Instruments

Reliability refers to the accuracy and precision of a measurement procedure (Cooper &

Schindler, 2014), and seeks to determine if scores to items on a research instrument are

internally consistent, stable, and whether the test administration and scoring was

consistent (Creswell, 2014). Zikmund et al. (2013) argue that pre-testing the research

instruments reduces biases that may be caused by measurement errors. Zohrabi (2013)

extensively categorizes reliability into two forms, that is, external and internal reliability.

External reliability focuses on the replication of the study and how it can be increased if

the researcher gives attention to the important aspects of the inquiry. On the other hand,

the internal reliability constitutes the consistency in collection, analysis and interpretation

of the data. Internal reliability can be found when an independent researcher comes to

similar findings as the original researcher after re-analyzing the information.

According to Creswell (2013) external reliability deals with the interaction of the

experimental treatment with other factors and the impact those results have on the ability

to generalize to times, settings, or persons. Internal validity seeks to determine whether

the conclusions drawn about a demonstrated experimental relationship accurately indicate

cause (Creswell, 2014). According to Cooper and Schinder (2014), threats to internal

reliability are experimental procedures, treatments, or research participants’ experiences

that may jeopardize the researcher’s ability to draw correct inferences from the data about

the population in an experiment.

Warrens (2014) posits that Cronbach’s alpha is the most commonly used coefficient for

approximation of reliability of test scores for structured questionnaires and for calculating

internal consistency. According to Saunders et al. (2016), internal consistency involves

correlating the responses to each question to other questions in the questionnaire and

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measuring the consistency of responses. Cronbach’s alpha values range between 0 and 1

where a value of 0 indicates no reliability, while 1 indicates high reliability (Warrens,

2014). However, the threshold for interpretation of reliability of the research instrument is

Cronbach’s alpha value of 0.7. According Tavakol and Dennick (2011), Cronbach’s alpha

values of less than 0.7 indicate that the research instrument is unreliable while Cronbach’s

alpha values equal to or greater than 0.7 indicate that the research instrument is reliable.

For this study, the research instrument was tested for reliability using Cronbach’s

Coefficient Alpha estimate. The results indicated that all variable constructs had

Cronbach’s alpha values greater than 0.7 and thus the instrument was found reliable. The

measurements for Cronbach’s alpha for the respective constructs are as shown in Table

3.3.

Table 3.3: Results of Cronbach’s Alpha Measurements for the Pilot Study

Construct Cronbach’s Alpha Number of

Items

Assessment of Strategic Decision-making 0.701 3 Effect of Strategic Decision-making on Revenue per

Customer 0.788 3

Effect of Strategic Decision-making on ROA 0.931 3 Effect of Strategic Decision-making on Product

Innovation 0.798 3

Assessment of Participative Governance 0.838 3 Effect of Participative Governance on Revenue per

Customer 0.955 3

Effect of Participative Governance on ROA 0.950 3 Effect of Participative Governance on Product

Innovation 0.972 3

Assessment of Human Capital 0.933 3 Effect of Human Capital on Revenue per Customer 0.886 3 Effect of Human Capital on ROA 0.934 3 Effect of Human Capital on Product Innovation 0.948 3 Assessment of Long-term Orientation 0.726 3 Effect of Long-term Orientation on Revenue per

Customer 0.919 3

Effect of Long-term Orientation on ROA 0.934 3 Effect of Long-term Orientation on Product Innovation 0.986 3 Assessment of Market Orientation 0.974 3 Effect of Market Orientation on Revenue per Customer 0.980 3 Effect of Market Orientation on ROA 0.982 3 Effect of Market Orientation on Product Innovation 0.970 3 Overall (Whole Questionnaire) 0.976 60

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3.7.4. Validity of the Instruments

Research validity refers to the correctness or truthfulness of an inference that is made

from a research study so that the results reflect the differences among the participants

drawn from the population (Cooper & Schindler, 2014). According to Christensen et al.

(2014), there are four major types of validity: Statistical conclusion validity is the

inference made about whether an independent and dependent variable covary; Construct

validity is the extent to which a construct is adequately represented by the measures used;

Internal validity is the correctness of inferences made about cause and effect in

connection with independent and dependent variables; and external validity, which is the

degree to which results can be generalized to other people, settings, and time.

According to Creswell (2013), the validity of a research instrument is improved by use of

a pilot study. For this study, the questionnaire was subjected to supervisors and key

informants from co-operatives, as a result of which the instrument was improved before

embarking on the main data collection.

3.7.5. Administration of the Questionnaire

This study utilized self-administered questionnaires. According to Bryman and Bell

(2011), with a self-administered questionnaire (SAQ), respondents answer questions by

completing the questionnaire themselves. As there is no interviewer in the administration

of the self-completion questionnaire, the research instrument has to be especially easy to

follow and its questions have to be particularly easy to answer (Saunders et al., 2016).

Bryman and Bell (2011) describe several advantages to using self-administered

questionnaires over structured interviews: They are quicker to administer; there is

absence of interviewer effects; no interviewer variability; and convenience for

respondents. However, self-administered questionnaires have some shortcomings as well

and these include: no one present to prompt if needed; cannot probe; have to ensure

questions are salient to respondents; difficulties of asking questions in a different way;

respondents can read all the questions before they start answering and this means they are

not independent of each other; cannot ask a lot of questions; there is a risk of missing data

and also poor response rates (Bryman & Bell, 2011; Cooper & Schindler, 2014).

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After the research instrument was pilot tested and approved for main survey data

collection, the researcher recruited qualified research assistants to help in data collection.

The researcher ensured that the research assistants were well facilitated in terms of paying

for their transport costs and allowances. To ensure authenticity that the respondents

completed the questionnaires, the respective co-operative stamped on the filled

questionnaires. The method for administering the questionnaire was dropping the

questionnaire to the directors of the selected co-operative and picking them up either

immediately or at an agreed date. Reminders and follow up calls were done at regular

intervals in order to elicit a higher response rate.

3.7.6. Ethical Considerations

Ethics in research is about the appropriateness of the researcher’s behavior in relation to

the rights of those who become the subject of a research project, or who are affected by it

and protecting them from harm (Saunders et al., 2016). In order to advance knowledge

and find solutions to problems, it is often necessary to impinge on the rights of

individuals and it is necessary for the researcher to give consideration to such ethical

issues (Saunders et al., 2016; Zikmund et al., 2013). Research ethics are a set of

guidelines to assist the researcher in conducting ethical research and comprise three areas:

relationship between society and science; professional issues; and treatment of research

participants (Christensen et al., 2014). Of particular concern in business research are

professional ethics and misconduct.

Research misconduct includes ‘fabrication, falsification or plagiarism in proposing,

performing or reviewing research (Christensen et al., 2014; OSTP, 2016). The study

observed both the beneficence and nonmaleficence principles, which stand for ‘doing

good’ and ‘doing no harm’, respectively (Christensen et al., 2014). Research ethics in

this study were guided by standards of ethical behavior widely accepted in the research

community, namely voluntary participation, informed consent, and confidentiality.

Specifically, due care and attention was paid in order to protect the identity of everyone

giving information. The objective of the study was made clear to all respondents and

confidentiality assured in their responses. The questionnaire did not require personal

details of the respondents but only the information about the specific co-operative.

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3.8. Data Analysis Methods

Data analysis methods comprised first, the preparation of the data, after which descriptive

and inferential statistics were conducted.

3.8.1. Data Preparation

The data collected was cleaned up of errors and to remove inconsistencies,

incompleteness, misclassification and gaps in the information obtained from the

respondents (Kumar, 2011). Missing data is a common problem with questionnaires and

can come in several forms: invalid data is data with entry errors; incomplete data is

missing data needed to make a decision; inconsistent data could result from mistakes of

aligning databases; while incorrect data occurs when data is falsified (Cooper &

Schindler, 2014). Having edited the data, the next step was coding it according to the

study variables using numerical values, as far as possible (Creswell, 2014). Each

questionnaire was given a unique number for ease of processing the information.

3.8.2. Descriptive Statistics

Descriptive statistics are measurements that depict the center, spread, and shape of

distributions and are helpful as preliminary tools for data description. They help to

describe the basic features of the data, to organize and summarize it in a simple way

(Cooper & Schindler, 2014; Peck & Devore, 2012). Descriptive statistics make it possible

to discern patterns that are not clearly apparent in the raw data through use of graphs, pie

charts, and tables for ease of visual explanation. Descriptive statistics include

measurement of central tendency and dispersion (Saunders et al., 2016). For this study,

the descriptive statistics used were the mean, standard deviation, coefficient of variation

and frequency distribution.

3.8.3. Inferential Statistics

Inferential statistics refer to statistical methods used to make inferences or to project from

a sample to an entire population. Statistical analysis can be univariate when testing

hypotheses involving only one variable, bivariate when involving two variables, or

multivariate when testing hypotheses and models involving three or more variables

(Zikmund et al., 2013). This study employed several inferential tests including analysis of

variance (ANOVA), factor analysis, correlation, and regression.

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3.8.3.1. Factor Analysis

Factor analysis is a data reduction program and a technique for discovering patterns

among the variables to determine if an underlying combination of the original variables (a

factor) can summarize the original set (Cooper & Schindler, 2014). On collection of data,

the factor analysis test is run to indicate whether all the items are interrelated or whether

there are some subsets of items (called dimensions or factors) that are more closely

related to one another. The analysis helps determine whether the test is uni-dimensional

or multidimensional (Christensen et al., 2014). The aim of factor analysis is to determine

the interdependence of the independent and dependent variables, as no one variable or

variable subset should be predicted from or explained by the other. The Principal

Components Analysis is one method of factor analysis that transforms a set of variables

into a new set of composite variables, which are linear and not correlated with each other

(Zikmund et al., 2013).

This study used factor analysis to reduce data (the many items) and come up with items

that are strongly related with the construct. Kaiser-Meyer-Olkin (KMO), a measure of

sampling adequacy, was used to test whether data can be factor analyzed. KMO was

complemented by Bartlett's test of sphericity, which also qualifies use of factor analysis.

For factor analysis to be appropriate, KMO value should be equal to or greater than 0.5

while Bartlett's test of sphericity should be significant (Williams, Brown, & Onsman,

2012). Principal Component Analysis (PCA) was used as a method of factor analysis

while varimax was used as a factor rotation method (IBM, 2012). This procedure enabled

the researcher to identify factors that were heavily loaded to the construct. For each of

the four independent variables, KMO and Bartlett’s test was run and results noted. The

total variance explained was then noted for each of the constructs in order to show the

variability explained by each item, after which a scree plot for each variable was shown.

The study used summated scores to create an index for each of the variables to show how

the factors were loaded.

3.8.3.2. Correlation Analysis

Correlation coefficient is an index indicating the strength and direction of relationship

when there is a quantitative dependent variable and a quantitative independent variable.

The strength of the relationship is denoted by the absolute size of correlation coefficient,

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r, which ranges from -1.00 and +1.00, while the direction of the relationship is either

negative or positive (Christensen et al., 2014). If the value of r is +1.0, a perfect positive

relationship exists, while the r value of -1.0 is a perfect negative correlation (Zikmund et

al., 2013). Correlation is a measure of association and can be for linearly related variables

(such as Pearson’s product-moment), partial (where three variables relate) or multiple

where one variable relates with the other two (Cooper & Schindler, 2014).

Two commonly used measures of correlation are, first, the Pearson’s correlation

coefficient, which is a standardized measure of covariance and can compare two

correlations without regard to the amount of variance exhibited by each variable

separately. The second is the Coefficient of Determination, R2, which is the proportion of

the total variance of a variable accounted for by another value of another variable

(Zikmund et al., 2013). In this study, Pearson’s Product Moment was used to measure the

strength and direction of the relationship between each of four dimensions of corporate

governance and organizational performance of dairy co-operatives in Kenya. In addition,

correlation was also measured for each dimension of corporate governance against each

measure of organizational performance (revenue per customer, ROA, and product

innovation).

3.8.3.3. Analysis of Variance

The analysis of variance (ANOVA) is an inferential statistic to determine whether

statistically significant differences in means occur between two or more groups. The

objective of ANOVA is to analyze differences between group means and not the

variances although the analysis of the variation among and within groups can lead to

conclusions about their means (Levine et al., 2011). The key statistical test for the

ANOVA model is the F-test, which determines whether there is more variability in the

scores of one sample than in the scores of another sample. ANOVA uses squared

deviations of the variance so that computation of distances of the individual data points

from their own mean or from the grand mean can be summed (Cooper & Schindler, 2014;

Zikmund et al., 2013). In this study, the F-Test was used for all research questions.

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3.8.3.4. Regression Analysis and Hypothesis Testing

Regression analysis is a statistical technique used when all the variables are quantitative

and is used to predict or explain the values of a dependent variable based on the values of

one or more independent (predictor) variables. Regression analysis can be simple, when

there is a single independent variable, or multiple for two or more independent variables

(Christensen et al., 2014). In multiple linear regression, R2 represents the coefficient of

multiple determination, which is the proportion of the variation in the dependent variable,

Y, that is explained by the set of independent variables. Adjusted R2 is preferred when

comparing multiple regression models that predict the same dependent variable but have

different number of independent variables (Levine et al., 2011).

3.8.3.4.1. Regression Analysis Assumption Tests

Regression analysis tests make some assumptions about data and violation of these alters

the conclusion of the study and interpretation of the findings. Each data point is assumed

to have the same amount of information, thus if some had less than others, then a study’s

regression slope would be only attracted towards the data-rich information (Casson &

Farmer, 2014). All research using the various tests must therefore follow these

assumptions for correct interpretation (Garson, 2012). The assumptions for the linear

regression model were tested in three ways: linearity, multicollinearity, and normality.

3.8.3.4.1.a Testing for Linearity

Linearity can be tested by through residual plots which are usually drawn by the statistical

analysis software. Linearity may be violated by either the outliers or the values for one or

more variables. A curve indicates that a linear model may not be the best fit and thus a

complex model may be necessary (Casson & Farmer, 2014; Saunders et al., 2016). There

is significant nonlinearity if the F statistic value for the nonlinear component is below the

critical value (Garson, 2012).

3.8.3.4.1.b Testing for Multicollinearity

The most straightforward way to test for multicollinearity is through the correlation

coefficients whereby extreme multicollinearity is represented by a correlation coefficient

of 1 (Saunders et al., 2016). Multicollinearity can also be tested by examining the

correlation matrix whereby large correlation coefficients, that is, values greater or equal

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to 0.8, in the correlation matrix of predictor variables indicate severe multicollinearity

(Joshi, Kulkarni, & Deshpande, 2012).

3.8.3.4.1.c Testing for Normality

Normal distribution is shaped like a symmetric bell-shaped curve with a standard normal

distribution of 1 with a mean of 0 and a standard deviation of 1. Normality can be tested

using Shapiro-Wilk's W test which is recommended for smaller samples of up to 2000.

The Kolmogorov-Smirnov test is recommended for larger samples and it can examine

goodness-of-fit against any theoretical distribution and not only the normal distribution.

There are also graphical methods of assessing normality such as a histogram, a P-P plot, a

Q-Q plot and a graph of empirical by theoretical cumulative distribution functions

(Garson, 2012).

3.8.3.4.2. Multiple Linear Regression Analysis

In order to take into account the effect of each dimension of corporate governance on

organizational performance taking into account other dimensions of corporate

governance, multiple linear regression was used in this study. The study conducted

diagnostic tests to choose between multiple linear regression and multivariate regression.

The diagnostic tests showed that the error terms were not multivariate normal hence

necessitating the use of multiple linear regression model. The use of multiple linear

regression enabled the researcher estimate the effect of each dimension of corporate

governance on organizational performance. Thus the magnitude of the effect was given

by the β while the sign of the coefficients gave the direction of the effect (Greene, 2011).

The results from the multiple linear regression model were presented in tables and the

interpretation evaluated at 0.05 significance level.

The study estimated the following four models based on Ordinary Least Squares (OLS)

technique. These models are un-moderated.

The model where Revenue per Customer is a measure of organizational performance:

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The model where Return on Asset (ROA) is a measure of organizational performance:

𝐴𝑖 = 0 + 1 𝑖 + 2 𝑖+ 3 𝑖 + 4 𝑖 + 𝑖 . . . 3.4

The model where Innovation is a measure of organizational performance:

𝐼 𝑖 = 0 + 1 𝑖 + 2 𝑖+ 3 𝑖 + 4 𝑖 + 𝑖 . . . 3.5

Where REV denoted revenue per customer; ROA denoted return on asset; INV denoted

Innovation of new products and services; SDM denoted comprehensive strategic

decision-making; PG denoted participative governance; HC denoted human capital; and

LTO denoted long-term orientation. are the parameters to be estimated and are the

error terms that are regarded as white noise.

To test the moderating effect of market orientation, the study introduced the interaction

terms between corporate governance variables and market orientation as shown:

The moderated model of SDM was specified as follows:

𝑖 = 0 + 1

+ 2 𝑖+ 3 𝑖 + 4 𝑖 + 5 𝑖 + 6( ∗ )𝑖 + 7( ∗ )𝑖

+ 8( ∗ )𝑖 + 9( ∗ )𝑖 + 𝑖 . . . . . 3.6

The moderated model of ROA was specified as follows:

𝐴𝑖 = 0 + 1

+ 2 𝑖+ 3 𝑖 + 4 𝑖 + 5 𝑖 + 6( ∗ )𝑖 + 7( ∗ )𝑖

+ 8( ∗ )𝑖 + 9( ∗ )𝑖 + 𝑖 . (3.7)

The moderated model of INV was specified as follows:

𝐼 𝑖 = 0 + 1

+ 2 𝑖+ 3 𝑖 + 4 𝑖 + 5 𝑖 + 6 ∗ 𝑖 + 7 ∗ 𝑖

+ 8 ∗ 𝑖 + 9 ∗ 𝑖 + 𝑖 3.8

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Where: MO denoted market orientation, ∗ denoted interactions between

comprehensive strategic decision-making and market orientation, ∗ denoted

interactions between participative governance and market orientation, ∗

denoted interactions between human capital and market orientation and ∗

denoted interactions between long-term orientation and market orientation. The other

variables were defined as before. These models were estimated separately using the

SPSS.


The chapter anchored the study on the positivism research philosophy and used a

descriptive correlational research design. The chapter presented the study target

population of 198 executive directors/managers from 198 dairy cooperatives in the Mt

Kenya region and the sample size was estimated based on Yamane (1974) formula. The

chapter used stratified random sampling technique to select 184 directors from a total

population of 198 directors. A structured questionnaire was used to collect data. Finally,

the chapter outlined four methods of data analysis that were used: factor analysis, analysis

of variance, correlation analysis, and multiple linear regression.

The next chapter, chapter four, presents the results and findings of the study.

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CHAPTER FOUR

4.0 RESULTS AND FINDINGS

4.1 Introduction

This chapter presents the analysis and results in regard to the research questions of the

study. The chapter is divided into 7 sections with section 4.1 being the introduction,

section 4.2 presenting demographic information, section 4.3 presenting results on the

influence of comprehensive strategic decision-making on organizational performance of

dairy co-operatives in Kenya, section 4.4 presents findings on the effects of participative

governance on organizational performance of dairy co-operatives in Kenya, while section

4.5 presents results on the influence of human capital on organizational performance of

dairy co-operatives in Kenya, section 4.6 presents effects of long-term orientation on

organizational performance of dairy co-operatives in Kenya. Finally, section 4.7 presents

the results of moderating effect of market orientation on the relationship between

corporate governance and organizational performance of dairy co-operatives in Kenya.

From the 184 questionnaires that were administered, 141 were returned, thus giving a

response rate of about seventy seven percent.

4.2. Demographic Information

This section presents the descriptive statistics and information regarding the demographic

and general data derived from the questionnaires. The information sought included: the

year of registration; position held; gender of respondents; age of the respondents, highest

level of education; professional qualifications; work experience; and the daily milk

production.

4.2.1 Year of Registration

The analysis showed that about forty-three percent (43.3%) of the cooperatives were

registered between 2012-2015, approximately twenty five percent (24.8%) were

registered between 2001-2011, about eleven percent (11.3%) registered between 1983-

2000, and about eighteen percent (17.7%) of them were registered between 1949-1973.

The results are shown in Table 4.1.

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Table 4.1: Year of Registration

Year Distribution

Frequency Percent

2012-2017 61 43.3

2001-2011 35 24.8

1983-2000 16 11.3

1949-1973 25 17.7

Missing 4 2.8

Total 141 100.0

4.2.2 Position Held

The study results indicated that approximately sixty four percent (63.7%) of the

respondents were managers, followed by chairpersons at twenty two percent, accountants

at five percent, and treasurers were about two percent (2.1%). These results are shown in

Table 4.2.

Table 4.2: Position Held

Position Distribution

Frequency Percent

Accountant 7 5.0

Chairperson 31 22.0

Clerk 8 5.7

Extension officer 1 0.7

Manager 90 63.7

Treasurer 3 2.1

Missing 1 0.7

Total 141 100.0

4.2.3 Gender of the Respondent

The analysis of gender showed that about sixty-eight percent (67.9%) of the respondents

were male while about thirty-two percent (32.1%) were female. The results are shown in

Figure 4.1

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Figure 4.1: Gender of the Respondents

4.2.4 Age of the Respondents

Regarding the age of the respondents, as Figure 4.2 shows, the study found that about

twenty-seven percent (27.3%) of the respondents were aged between 40 and 49 years

followed by respondents within the age group of 30 to 39 years at about twenty percent

(20.1%). About nineteen percent (18.7%) of the respondents were aged between 21 to 29

years, eighteen percent between 50 to 59 years, and nearly sixteen percent (15.8%) were

above the age of 60 years.

Male

67.9

Female

32.1

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Figure 4.2: Age of the Respondents

4.2.5 Highest Level of Education

The study sought to establish the highest level of education of the respondents. Figure 4.3

shows that more than half (52%) of the respondents had studied up to certificate level,

followed by diploma at thirty four percent, bachelor’s degree at twelve percent and only

two percent at the master’s level.

Figure 4.3: Highest Level of Education

0

5

10

15

20

25

30

21-29 years 30-39 years

40-49 years 50-59 years

60+ years

18.7 20.1

27.3

18

15.8

Per

cen

tage

Age

Age of Respondents

Certificate

52%

Diploma

34%

Bachelors

12%

Masters

2%

Highest Level of Education

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4.2.6 Professional Qualification

The study sought to establish the professional qualifications of the respondents. The

results are shown in Table 4.3 and indicate that about twenty percent (21.3%) of the

respondents had qualifications in finance and accounting followed by about twelve

percent (12.1%) who were teachers. The study further found that about nine percent

(8.5%) of the respondents were qualified in cooperative management, as were technicians

(8.5%), while about eight percent (7.8%) had qualifications in agribusiness management

and about seven percent (7.1%) in dairy technology.

Table 4.3: Professional Qualification

Qualification Distribution

Frequency Percent

Finance and Accounting 30 21.3

Agribusiness Management 11 7.8

Agricultural Engineering 2 1.4

Animal Health 5 3.5

Business Management 8 5.7

Police training 2 1.4

Community development social work 1 0.7

Cooperative Management 12 8.5

Dairy Technology 10 7.1

Human Resource Management 1 0.7

ICT 6 4.3

Mason 1 0.7

Quality Control 1 0.7

Secretarial Studies 5 3.5

Teaching 17 12.1

Technician 12 8.5

Tourism 2 1.4

Missing 15 10.6

Total 141 100.0

140

4.2.7 Work Experience

The study sought to establish the number of years worked in the co-operative by the

respondents. Figure 4.4 shows that more than forty-two percent (42.4%) of the

respondents had worked for 2 to 5 years, while less than a quarter (24.5%) had worked for

6 to 10 years. The results further showed that about twelve percent (12.2%) of the

respondents had worked for 11 to 15 years and lastly, nearly nine percent (8.6%) had

worked for 15 years and above.

Figure 4.4: Work Experience

4.2.7 Daily Milk Production

Table 4.4 shows that the majority (53%) of the cooperatives collected between 1,000 to

5,000 liters of milk daily, twenty eight percent collected below 1,000 litres of milk daily

and ten percent collected between 5,001 to 10,000 liters of milk daily.

12.2

42.4

24.5

12.2

8.6

0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0

Below 1 year

2-5 years

6-10 years

11-15 years

15 years and above

Percentage

Yea

rs

141

Table 4.4: Distribution of Daily Milk Production

Milk Production Distribution

Frequency Percentage

Below 1,000 Liters 40 28%

1,000-5,000 Liters 75 53%

5,001-10,000 Liters 14 10%

10,001-15,000 Liters 5 4%

15,001-20,000 Liters 2 1%

Above 20,000 Liters 5 4%

Total 141 100

4.3 Comprehensive Strategic Decision-Making and Organizational Performance

This section presents results for the assessment of comprehensive decision-making on the

organizational performance of dairy co-operatives in Kenya and also the effect of

comprehensive decision-making on organizational performance as measured by revenue

per customer, ROA, and product innovation.

4.3.1 Frequency and Percentage Distribution for Comprehensive Strategic Decision-

Making

4.3.1.1 Strategic Decision-Making

As Table 4.5 shows, nearly sixty percent (58.3%) of the respondents strongly agreed that

the board of their co-operative was involved in making strategic decisions, while about

sixty percent (60.4%) strongly agreed that the board worked as a team. About forty-four

percent (43.9%) of the respondents agreed that their board empowered the management.

142

Table 4.5: Frequency and Percentage Distribution for Strategic Decision-Making

Constructs

Strongly

Disagree

1

Disagree

2

Neutral

3

Agree

4

Strongly

Agree

5

Total

The board of our co-

operative is involved in

making strategic decisions

f 2 2 4 50 81 139

% 1.4 1.4 2.9 36.0 58.3 100


operative empowers the

management

f 4 5 9 60 61 139

% 2.9 3.6 6.5 43.2 43.9 100


operative works as a team

f 6 6 43 84 139

% 4.3 4.3 30.9 60.4 100

4.3.1.2 Effect of Strategic Decision-making on Revenue per Customer

About fifty one percent (51.4%) of the respondents indicated that the board’s role in

making strategic decisions affected the revenue per customer, while nearly seventy-five

percent (74.5%) said that empowering of the management by the board affected the

revenue per customer. In addition, eighty percent (79.1%) of the respondents indicated

that working as a team by the board affected the revenue per customer in their co-

operatives from moderate to very large extent. These findings are shown in Table 4.6.

Table 4.6: Frequency and Percentage Distribution of the Effect of Strategic

Decision-Making on Revenue per customer

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

To what extent does the

board’s role in making

strategic decisions affect the

revenue per customer in your

co-operative?

f 16 15 72 20 17 140

% 11.4 10.7 51.4 14.3 12.1 100


empowering of the

management by the board

affect the revenue per

customer in your co-

operative?

f 19 16 68 23 13 139

% 13.7 11.5 48.9 16.5 9.4 100

To what extent does working

as a team by the board affect

the revenue per customer in

your co-operative?

f 18 11 58 30 22 139

% 12.9 7.9 41.7 21.6 15.8 100

143

4.3.1.3 Effect of Comprehensive Strategic Decision-Making on ROA

As Table 4.7 shows, about forty percent (39%) of the respondents indicated that, to a

small extent, the board’s role in making strategic decisions affected the ROA, while about

thirty percent (29.5%) said that empowering of the management by the board affected the

ROA. In addition, about thirty percent (28.8%) of the respondents indicated that working

as a team by the board affected the ROA in their co-operatives.

Table 4.7: Frequency and Percentage Distribution of the Effect of Comprehensive

Strategic Decision-Making on ROA

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderat

e Extent

3

Large

Exten

t

4

Very

Large

Extent

5

Tota

l



strategic decisions affect

ROA in your co-operative?

f 39 15 38 24 23 139

% 28.1 10.8 27.3 17.3 16.5 100


empowering of the


affect ROA in your co-

operative?

f 41 13 31 35 19 139

% 29.5 9.4 22.3 25.2 13.7 100




f 40 10 30 34 25 139

% 28.8 7.2 21.6 24.5 18.0 100

4.3.1.4 Effect of Strategic Decision-Making on Product Innovation

Twenty seven percent of the respondents indicated, to a large extent, that the board’s role

in making strategic decisions affected product innovation, while about twenty-five

percent (25.5%) said, to a large extent, that empowering of the management by the board

affected product innovation. In addition, about twenty-five percent (25.5%) of the

respondents said, to a large extent, that working as a team by the board affected the

product innovation in their co-operatives. Table 4.8 shows these results.

144

Table 4.8: Frequency and Percentage Distribution of the Effect of Strategic

Decision-Making on Product Innovation

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total



strategic decisions affect

product innovation in your co-

operative?

f 34 26 28 38 15 141

% 24.1 18.4 19.9 27.0 10.6 100


empowering of the


affect product innovation in

your co-operative?

f 36 22 31 36 16 141

% 25.5 15.6 22.0 25.5 11.3 100




operative?

f 35 15 29 36 26 141

% 24.8 10.6 20.6 25.5 18.4 100

4.3.2 Descriptive Statistics for Comprehensive Strategic Decision-Making

The study analyzed the mean and standard deviation of the components of comprehensive

strategic decision-making. Table 4.9 shows the mean for “The board of our co-operative

is involved in making strategic decisions”, (M = 4.48, SD = 0.76), and the mean for “The

board of our co-operative empowers the management”, (M = 4.22, SD = 0.93).

145

Table 4.9: Descriptive Statistics for Comprehensive Strategic Decision-Making

Constructs

N

Mean

(M)

Standard

Deviation

(SD)

The board of our co-operative is involved in making strategic

decisions

139 4.48 .755

The board of our co-operative empowers the management 139 4.22 .931

The board of our co-operative works as a team 139 4.47 .774

To what extent does the board’s role in making strategic

decisions affect the revenue per customer in your co-operative?

140 3.05 1.095

To what extent does the empowering of the management by

the board affect the revenue per customer in your co-operative?

139 2.96 1.099

To what extent does working as a team by the board affect the

revenue per customer in your co-operative?

139 3.19 1.191


decisions affect ROA in your co-operative?

139 2.83 1.433


the board affect ROA in your co-operative?

139 2.84 1.436

To what extent does working as a team by the board affect


139 2.96 1.484


decisions affect product innovation in your co-operative?

141 2.82 1.350


the board affect product innovation in your co-operative?

141 2.82 1.366

To what extent does working as a team by the board affect

product innovation in your co-operative?

141 3.02 1.451

4.3.3 Factor Analysis Results on Comprehensive Strategic Decision-Making

In order to reduce the items of comprehensive strategic decision-making and develop an

appropriate measure, the study carried out factor analysis to obtain the values for KMO

and Bartlett’s test of sphericity and determine the total variance explained by the

components.

4.3.3.1 KMO and Bartlett's Test for Comprehensive Strategic Decision-Making

In order to reduce the items of comprehensive strategic decision-making and develop an

appropriate measure, the study carried out factor analysis and found out that KMO had a

value of 0.628, while Bartlett's test of sphericity was 2 (3, N=141) = 63.08, p = <0.000.

This finding is shown in Table 4.10.

146

Table 4.10: KMO and Bartlett's Test for Comprehensive Strategic Decision-Making

Kaiser-Meyer-Olkin Measure of Sampling Adequacy .628

Bartlett's Test of Sphericity

Approx. Chi-Square 63.076

Df 3

Sig. .000

4.3.3.2 Total Variance Explained for Comprehensive Strategic Decision-Making

Results for total variance explained showed that one component of comprehensive

strategic decision-making explained 59.9% of the total variability in the three items.

Table 4.11 depicts this finding.

Table 4.11: Total Variance Explained for Comprehensive Strategic Decision-Making

Component Initial Eigenvalues Extraction Sums of Squared

Loadings

Total % of

Variance

Cumulativ

e %

Total % of

Variance

Cumulative

%

1 1.797 59.884 59.884 1.797 59.884 59.884

2 .716 23.862 83.747

3 .488 16.253 100.000

4.3.3.3 Scree Plot for Comprehensive Strategic Decision-Making

The results on the scree plot for comprehensive strategic decision-making indicate that

only one component had eigenvalues greater than 1 hence confirming the findings of the

total variance explained for comprehensive strategic decision-making. The results are

shown in Figure 4.5.

147

Figure 4.5: Scree Plot for Comprehensive Strategic Decision-Making

4.3.3.4 Component Matrix for Comprehensive Strategic Decision-Making

The study used summated scores based on the three components to create an index of

comprehensive strategic decision-making. All the three components had factor loadings

greater than 0.5 and thus they are strongly loaded to component one. This finding is

indicated in Table 4.12.

Table 4.12: Component Matrix for Comprehensive Strategic Decision-Making

Constructs

Component

1

The board of our co-operative is involved in making strategic decisions .699

The board of our co-operative empowers the management .831

The board of our co-operative works as a team .786

148

4.3.4 Correlation between Comprehensive Strategic Decision-Making and

Organizational Performance

The study tested for the correlation between comprehensive strategic decision-making

and organizational performance using three variable constructs. The Pearson correlation

results showed that “the board of our co-operative is involved in making strategic

decision” was not significantly correlated with either revenue per customer, ROA or

product innovation, r(135) = -0.142, p>0.05, r(134) = -0.106, p>0.05 and r(135) = -0.145,

p>0.05 respectively. These findings are summarized in Table 4.13.

Table 4.13: Correlation between Comprehensive Strategic Decision-Making and


Constructs Organizational Performance

Revenue Per

Customer ROA

Product

Innovation


operative is involved in

making strategic decisions

Pearson Correlation -.142 -.106 -.145

Sig. (2-tailed) .100 .225 .093

N 135 134 135


operative empowers the

management

Pearson Correlation .058 .016 .054

Sig. (2-tailed) .507 .850 .536

N 135 134 135


operative works as a team

Pearson Correlation -.048 -.102 -.007

Sig. (2-tailed) .583 .241 .936

N 134 133 135

p ≤ 0.05

Additionally, the study found that strategic decision-making was not significantly

correlated with organizational performance, r(130) = -0.069, p>0.05. This finding is

shown in Table 4.14.

149

Table 4.14: Correlation between Strategic Decision-Making and Organizational

Performance


Strategic Decision-Making

Pearson Correlation -.069

Sig. (2-tailed) .433

N 130

p ≤ 0.05

4.3.5 One-way ANOVA on Comprehensive Strategic Decision-Making

A one-way analysis of variation test was carried out to establish if there was significant

difference between the mean of comprehensive strategic decision-making and gender and

between the mean of comprehensive strategic decision-making and education. As Tables

4.15 and 4.16 show, the tests established no significant differences between the mean

scores for comprehensive strategic decision-making and both male and female

respondents F(1, 132) = 3.8, p = .053. There was also no significant differences between

the mean scores for comprehensive strategic decision-making and different levels of

education F(3, 131) = 1.32, p =.272. Bonferroni test confirms this result as shown in

Table 4.17.

Table 4.15: One-way ANOVA for Strategic Decision-Making and Gender

Sum of Squares df Mean Square F Sig.

Between Groups 13.657 1 13.657 3.804 .053

Within Groups 473.925 132 3.590

Total 487.582 133

p ≤ 0.05

Table 4.16: One-way ANOVA for Strategic Decision-Making and Level of Education

Sum of

Squares

df Mean Square F Sig.

Between Groups 14.336 3 4.779 1.315 .272

Within Groups 475.990 131 3.634

Total 490.326 134

p ≤ 0.05

150

Table 4.17: Bonferroni Test for Strategic Decision-Making and Level of Education

(I) Highest

Education

Level

(J) Highest

Education Level

Mean

Difference

(I-J)

Std.

Error

Sig. 95% Confidence

Interval

Lower

Bound

Upper

Bound

Certificate

Diploma .56645 .36051 .711 -.3993 1.5322

Bachelors -.35720 .51613 1.000 -1.7399 1.0255

Masters -.21014 1.36726 1.000 -3.8729 3.4526

Diploma

Certificate -.56645 .36051 .711 -1.5322 .3993

Bachelors -.92365 .53949 .535 -2.3689 .5216

Masters -.77660 1.37625 1.000 -4.4634 2.9103

Bachelors

Certificate .35720 .51613 1.000 -1.0255 1.7399

Diploma .92365 .53949 .535 -.5216 2.3689

Masters .14706 1.42495 1.000 -3.6703 3.9644

Masters

Certificate .21014 1.36726 1.000 -3.4526 3.8729

Diploma .77660 1.37625 1.000 -2.9103 4.4634

Bachelors -.14706 1.42495 1.000 -3.9644 3.6703

p ≤ 0.05

4.3.6 Regression Analysis and Hypothesis Testing for Comprehensive Strategic

Decision-Making

The section first shows the results of assumption tests for regression analysis. Data was

tested for the critical linear regression model assumptions. The tests chosen for this study

were linearity, multicollinearity, and normality. The section also presents multiple linear

regression results for the effect of comprehensive strategic decision-making on revenue

per customer, ROA and product innovation. The study conducted a diagnostic test to

choose between multiple linear regression and multivariate regression. The diagnostic

tests showed that the error terms were not multivariate normal and so multiple linear

regression was used.

4.3.6.1 Assumptions for Regression Analysis

The assumptions for the linear regression model were tested in three ways: linearity,

multicollinearity, and normality.

151

4.3.6.1.1 Testing for Linearity

As Table 4.18 shows, the study found a linear relationship between revenue per customer

and comprehensive strategic decision-making, F(1, 8) = 1.52, p = .16. ROA had a

nonlinear relationship with comprehensive strategic decision-making, F(1, 8) = 2.15, p =

.036 and product innovation had a linear relationship with comprehensive strategic

decision-making, F(1, 8) = .37, p = .93.

Table 4.18: Test of Linearity for Comprehensive Strategic Decision-Making and


Sum of Squares

df Mean Square

F Sig.

Revenue Per Customer Strategic Decision-Making

Between Groups

(Combined) 1828.315 9 203.146 1.389 .200 Linearity 56.767 1 56.767 .388 .534 Deviation from Linearity

1771.548 8 221.444 1.515 .159

Within Groups 18130.081 124 146.210 Total 19958.396 133

ROA Strategic Decision-Making

Between Groups

(Combined) 4822.769 9 535.863 2.013 .043 Linearity 252.463 1 252.463 .948 .332 Deviation from Linearity

4570.305 8 571.288 2.146 .036


Product Innovation Strategic Decision-Making

Between Groups

(Combined) 948.456 9 105.384 .366 .949 Linearity 88.753 1 88.753 .309 .580 Deviation from Linearity

859.704 8 107.463 .374 .933


p ≤ 0.05

4.3.6.1.2 Testing for Multicollinearity

The results for multicollinearity indicate that revenue per customer and comprehensive

strategic decision-making had no severe multicollinearity, r(134) = -.05, p > .05. ROA

and comprehensive strategic decision-making had no severe multicollinearity, r(133) = -

.08, p > .05 and product innovation and comprehensive strategic decision-making had no

severe multicollinearity, r(134) = -.05, p > .05. Table 4.19 shows these findings.

152

Table 4.19: Multicollinearity test for Comprehensive Strategic Decision-Making


Revenue Per Customer



N 134

ROA



N 133

Product Innovation



N 134

p ≤ 0.05

4.3.6.1.3 Testing for Normality

This study used Shapiro-Wilk normality test since the sample was less than 2000. The

Shapiro-Wilk test showed that comprehensive strategic decision-making was not

normally distributed, t(132) = .85, p < .01. Table 4.20 depicts this finding.

Table 4.20: Normality test for Comprehensive Strategic Decision-Making

Kolmogorov-Smirnov Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Comprehensive Strategic

Decision-making .182 132 .000 .845 132

.00

0

p ≤ 0.05

4.3.6.2 Regression Analysis and Hypothesis Testing

The study sought to establish the effect of comprehensive strategic decision-making on

the dependent variable constructs, namely revenue per customer, return on assets, and

product innovation.

4.3.6.2.1 The effect of comprehensive strategic decision-making on revenue per

customer

Multiple regression was used to test if comprehensive strategic decision-making

significantly predicted revenue per customer. The results are shown in three tables, the

Model Summary (Table 4.21a), ANOVA (Table 4.21b), and Coefficients (Table 4.21c).

153

4.3.6.2.1a Model Summary

The multiple regression results in Table 4.21a indicate that comprehensive strategic

decision-making predicted 49.7 percent of the variance in revenue per customer

(R2=.497).

Table 4.21a: Model Summary*

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

Durbin-

Watson

1 .668 .446 .423 8.87899

2 .705 .497 .459 8.59874 2.039

Model 1 has no moderator, Model 2 has moderator

*Dependent variable: Revenue per Customer

*Predictor variable: Comprehensive Strategic Decision-Making

4.3.6.2.1b ANOVA

Table 4.21b shows that comprehensive strategic decision-making statistically

significantly predicted revenue per customer, F(9,121)= 73.938, p <.05.

Table 4.21b: ANOVA*

Model Sum of Squares df Mean Square F Sig.

1

Regression 7922.669 5 1584.534 20.099 .000

Residual 9854.552 125 78.836

Total 17777.221 130

2

Regression 8830.690 9 981.188 13.270 .000

Residual 8946.532 121 73.938

Total 17777.221 130




4.3.6.2.1c Coefficients

The multiple linear regression results of the study showed that, for the model without the

moderator, comprehensive strategic decision-making was not significant in predicting

revenue per customer, = -.42, t(141) = -.93, p > .05. For the model with the moderator,

comprehensive strategic decision-making significantly predicted revenue per customer,

= -2.85, t(141) = -2.24, p < .05. This means that a unit increase in comprehensive

154

strategic decision-making would reduce revenue per customer by 2.85 units. This result is

shown in Table 4.21c.

Table 4.21c: Coefficients*

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1

Constant 21.653 6.432 3.367 .001

Strategic Decision-

Making -.419 .453 -.069 -.925 .357

2

Constant 71.869 17.003 4.227 .000

Strategic Decision-

Making -2.854 1.272 -.470 -2.243 .027




4.3.6.2.2 The effect of comprehensive strategic decision-making on return on assets


significantly predicted return on assets. The results are shown in three tables, the Model

Summary (Table 4.22a), ANOVA (Table 4.22b), and Coefficients (Table 4.22c).


The multiple regression results in Table 4.22a indicate that comprehensive strategic

decision-making predicted 29.4 percent of the variance (R2=.294).


Model R R Square Adjusted R Square Std. Error of

the Estimate

Durbin-

Watson

1 .519 .269 .239 14.61926

2 .543 .294 .241 14.60498 1.214


*Dependent variable: ROA


4.3.6.2.2b ANOVA


significantly predicted ROA, F(5, 123) = 9.06, p < .05).

155

Table 4.22b: ANOVA*


1

Regression 9681.507 5 1936.301 9.060 .000

Residual 26287.888 123 213.723

Total 35969.395 128

2

Regression 10586.056 9 1176.228 5.514 .000

Residual 25383.339 119 213.305

Total 35969.395 128





The multiple linear regression results showed that, for the model without the moderator,

comprehensive strategic decision-making was not significant in predicting ROA, = -.41,

t(141) = -.54, p > .05. For the model with the moderator, comprehensive strategic

decision-making was not significant in predicting ROA, = -2.66, t(141) = -1.23, p >.05.

This result is shown in Table 4.22c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1

Constant 30.464 10.650 2.860 .005

Strategic Decision-

Making -.406 .752 -.047 -.540 .590

2

Constant 64.619 29.104 2.220 .028

Strategic Decision-

Making -2.661 2.168 -.307 -1.227 .222




4.3.6.2.3 The effect of comprehensive strategic decision-making on product

innovation


significantly predicted product innovation. The results are shown in three tables, the

Model Summary (Table 4.23a), ANOVA (Table 4.23b), and Coefficients (Table 4.23c).

156


The multiple regression results in Table 4.23a indicate comprehensive strategic decision-

making predicted 41.2 percent of variations in product innovation (R2 = 0.412).



Square

Std. Error of

the Estimate

Durbin-Watson

1 .616 .380 .355 13.19379

2 .642 .412 .368 13.05597 1.825


*Dependent variable: Product Innovation


4.3.6.2.3b ANOVA


significantly predicted product innovation, F(5, 124) = 15.18, p < .05.

Table 4.23b: ANOVA*

Model Sum of Squares df Mean

Square

F Sig.

1

Regression 13213.045 5 2642.609 15.181 .000

Residual 21585.448 124 174.076

Total 34798.492 129

2

Regression 14343.475 9 1593.719 9.350 .000

Residual 20455.017 120 170.458

Total 34798.492 129





The multiple linear regression results showed that, for model without the moderator,

comprehensive strategic decision-making was not significant in predicting product

innovation, = -.94, t(141) = -1.39, p > .05. For the model with the moderator,

comprehensive strategic decision-making was not significant in predicting product

innovation, = -3.37, t(141) = -1.74, p > .05. This result is shown in Table 4.23c.

157



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1

Constant 13.640 9.561 1.427 .156

Strategic Decision-

Making -.939 .674 -.110 -1.393 .166

2

Constant 54.880 25.720 2.134 .035

Strategic Decision-

Making -3.374 1.934 -.396 -1.744 .084




4.4 Participative Governance and Organizational Performance

This section presents results for the assessment of participative governance on the

organizational performance of dairy co-operatives in Kenya and also the effect of

participative governance on organizational performance as measured by revenue per

customer, ROA and product innovation.

4.4.1 Frequency and Percentage Distribution for Participative Governance

4.4.1.1 Participative Governance

As Table 4.24 shows, nearly seventy percent (68.1%) of the respondents indicated that:

all members in the co-operative had equal voting rights while nearly half (47.5%) of the

respondents indicated members participated actively in the AGMs. Just more than half

(51.1%) of the respondents indicated that members received timely information from the

board and management.

Table 4.24: Frequency and Percentage Distribution for Participative Governance

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

All members in the co-

operative have equal voting

rights

f 4 3 11 27 96 141

% 2.8 2.1 7.8 19.1 68.1 100

Members participate actively

in the AGMs

f 4 5 26 39 67 141

% 2.8 3.5 18.4 27.7 47.5 100

Members receive timely

information from the board

and management

f 3 6 13 47 72 141

% 2.1 4.3 9.2 33.3 51.1 100

158

4.4.1.2 Effect of Participative Governance on Revenue per Customer

About forty-three percent (42.6%) of respondents indicated that, to a moderate extent,

having equal voting rights for members affected revenue per customer, while about forty

one percent (41.1%) said, to a moderate extent, that participation in the AGM by

members affected revenue per customer. In addition, nearly forty percent (39.7%) said, to

a moderate extent, that receiving of timely information by members from the board and

management affected revenue per customer in their co-operatives. These findings are

summarized in Table 4.25.


Governance on Revenue per Customer

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

To what extent does having equal

voting rights for members affect

revenue per customer in your co-

operative?

f 25 10 60 29 17 141

% 17.7 7.1 42.6 20.6 12.1 100

To what extent does active

participation in the AGM by

members affect revenue per

customer in your co-operative?

f 29 10 58 29 15 141

% 20.6 7.1 41.1 20.6 10.6 100

To what extent does the receiving

of timely information by members

from the board and management

affect revenue per customer in your

co-operative?

f 29 12 56 28 16 141

% 20.6 8.5 39.7 19.9 11.3 100

4.4.1.3 Effect of Participative Governance on ROA

As Table 4.26 shows, about thirty nine percent (38.6%) of the respondents indicated that,

only to a small extent, having equal voting rights for members affected ROA, while

nearly thirty-six percent (35.7%) of the respondents indicated that participation in the

AGM by members affected ROA. In addition, about thirty-seven percent (37.1%) of the

respondents said that receiving of timely information by members from the board and

management affected ROA in their co-operatives.

159

Table 4.26: Frequency and Percentage Distribution of Effect of Participative

Governance on ROA

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

To what extent does having

equal voting rights for members

affect ROA in your co-

operative?

f 54 15 32 24 15 140

% 38.6 10.7 22.9 17.1 10.7 100



members affect ROA in your

co-operative?

f 50 14 36 24 16 140

% 35.7 10.0 25.7 17.1 11.4 100


receiving of timely information

by members from the board and

management affect ROA in

your co-operative?

f 52 15 34 28 11 140

% 37.1 10.7 24.3 20.0 7.9 100

4.4.1.4 Effect of Participative Governance on Product Innovation

About thirty-two percent (31.9%) of the respondents indicated that, to a small extent,

having equal voting rights for members affected product innovation, while about thirty-

one percent (31.2%) said, to a small extent, that participation in the AGM by members

affected product innovation. In addition, nearly thirty percent (28.4%) indicated that, to a

small extent, receiving of timely information by members from the board and

management affected product innovation in their co-operatives. These findings are


160


Governance on Product Innovation

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total


equal voting rights for members

affect product innovation in

your co-operative?

f 45 16 30 30 20 141

% 31.9 11.3 21.3 21.3 14.2 100



members affect product

innovation in your co-

operative?

f 44 16 32 31 18 141

% 31.2 11.3 22.7 22.0 12.8 100


receiving of timely information

by members from the board and

management affect product

innovation in your co-

operative?

f 40 18 28 36 19 141

% 28.4 12.8 19.9 25.5 13.5 100

4.4.2 Descriptive Statistics for Participative Governance

The study analyzed the mean and standard deviation of the components of participative

governance. Table 4.28 shows the mean for “all members in the co-operative equal voting

rights”, (M = 4.48, SD = 0.93), and the mean for “members participate actively in the

AGMs”, (M = 4.13, SD = 1.02).

161

Table 4.28: Descriptive Statistics for Participative Governance

Constructs N Mean

(M)

Standard

Deviation

(SD)

All members in the co-operative equal voting rights 141 4.48 .938

Members participate actively in the AGMs 141 4.13 1.023

Members receive timely information from the board and

management

141 4.27 .948

To what extent does having equal voting rights for members

affect revenue per customer in your co-operative?

141 3.02 1.216

To what extent does active participation in the AGM by

members affect revenue per customer in your co-operative?

141 2.94 1.238

To what extent does the receiving of timely information by

members from the board and management affect revenue per


141 2.93 1.252


affect ROA in your co-operative?

140 2.51 1.422


members affect ROA in your co-operative?

140 2.59 1.414


members from the board and management affect ROA in your

co-operative?

140 2.51 1.370


affect product innovation in your co-operative?

141 2.74 1.456


members affect product innovation in your co-operative?

141 2.74 1.428


members from the board and management affect product

innovation in your co-operative?

141 2.83 1.429

4.4.3 Factor Analysis Results on Participative Governance

In order to reduce the items for participative governance and develop an appropriate

measure, the study carried out factor analysis and found that the KMO and Bartlett’s test

of sphericity and determined the total variance explained by the components.

4.4.3.1 KMO and Bartlett's Test for Participative Governance

In order to reduce the items for participative governance and develop an appropriate

measure, the study carried out factor analysis and found out that KMO had a value of

0.674 and Bartlett's test of sphericity, 2 (3, N=141) = 122.23, p = .000. The KMO value

was greater than 0.5 while the p-value for Bartlett's test was lower than 0.05. This finding

is shown in Table 4.29.

162

Table 4.29: KMO and Bartlett's Test for Participative Governance




df 3

Sig. .000

p ≤ 0.05

4.4.3.2 Total Variance Explained for Participative Governance

Results for total variance explained indicated that one component of participative

governance explained 69.647% of the total variability in the three items. Table 4.30

shows this finding.

Table 4.30: Total Variance Explained for Participative Governance

Component Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of

Variance

Cumulative

%

Total % of

Variance

Cumulative %

1 2.089 69.647 69.647 2.089 69.647 69.647

2 .554 18.470 88.117

3 .356 11.883 100.000

4.4.3.3 Scree Plot for Participative Governance

The results on the scree plot for participative governance indicate that only one

component had eigenvalues greater than one confirm the findings of the total variance

explained for participative governance. The results are shown in Figure 4.6.

163

Figure 4.6: Scree Plot for Participative Governance

4.4.3.4 Component Matrix for Participative Governance


participative governance. All the three components had factor loadings greater than 0.5

and thus they are strongly loaded to component one. These findings are indicated in Table

4.31.

Table 4.31: Component Matrix for Participative Governance

Constructs

Component

1

All members in the co-operative equal voting rights .817

Members participate actively in the AGMs .805

Members receive timely information from the board and

management .881

164

4.4.4 Correlation between Participative Governance and Organizational

Performance

The study tested for correlation between items of participative governance with revenue

per customer, ROA and product innovation and found that only item “All members in the

co-operative equal voting rights” was significantly correlated with revenue per customer

r(135) = 0.18, p<0.05, but was not significantly correlated with both ROA or product

innovation, r(135) = .005, p>0.05 and r(137) = .130, p>0.05 respectively. The results are



Performance

Constructs


Revenue per

Customer ROA

Product

Innovation

All members in the co-

operative equal voting rights

Pearson Correlation .180* .005 .130

Sig. (2-tailed) .037 .955 .130

N 135 135 137

Members participate actively

in the AGMs

Pearson Correlation -.023 -.163 .090

Sig. (2-tailed) .787 .060 .298

N 135 135 137

Members receive timely

information from the board

and management

Pearson Correlation .122 -.053 .131

Sig. (2-tailed) .159 .545 .127

N 135 135 137

p<0.5

Using the summated scores based on the three components, the study created an index of

participative governance, which was then correlated with organizational performance.

The results showed that participative governance was not significantly correlated with

organizational performance r(130) = 0.038, p>0.05. This finding is shown in Table 4.33.

165


Performance



Pearson Correlation .038


N 131

p ≤ 0.05

4.4.5 One-way ANOVA on Participative Governance

A one-way analysis of variation was carried out to establish if there was significant

difference between the mean of participative governance and gender and between the

mean of participative governance and education. As Tables 4.34 and 4.35 show, the tests

established that the mean for participative governance was the same for both male and

female respondents F(1, 135) = 2.46, p = .12. There was also no significant differences

between the mean scores for participative governance and different levels of education

F(3, 134) = 0.61, p = .61. Bonferroni test confirms this result as shown in Table 4.36.

Table 4.34: One-way ANOVA for Participative Governance and Gender


Between Groups 14.408 1 14.408 2.458 .119

Within Groups 791.373 135 5.862

Total 805.781 136

Table 4.35: One-way ANOVA for Participative Governance and Education


Between Groups 10.905 3 3.635 .613 .608

Within Groups 794.747 134 5.931

Total 805.652 137

166

Table 4.36: Bonferroni Test for Participative Governance and Education

(I) Highest

Education

Level

(J) Highest

Education Level

Mean

Difference

(I-J)

Std.

Error

Sig. 95% Confidence Interval

Lower

Bound

Upper Bound

Certificate

Diploma -.17790 .45669 1.000 -1.4009 1.0451

Bachelors -.77614 .65670 1.000 -2.5348 .9825

Masters -1.30556 1.74581 1.000 -5.9808 3.3697

Diploma

Certificate .17790 .45669 1.000 -1.0451 1.4009

Bachelors -.59825 .68925 1.000 -2.4441 1.2476

Masters -1.12766 1.75831 1.000 -5.8364 3.5811

Bachelors

Certificate .77614 .65670 1.000 -.9825 2.5348

Diploma .59825 .68925 1.000 -1.2476 2.4441

Masters -.52941 1.82054 1.000 -5.4048 4.3460

Masters

Certificate 1.30556 1.74581 1.000 -3.3697 5.9808

Diploma 1.12766 1.75831 1.000 -3.5811 5.8364

Bachelors .52941 1.82054 1.000 -4.3460 5.4048

4.4.6 Hypothesis Testing and Hypothesis Testing for Participative Governance

The section first shows the results of assumption tests for regression analysis. The

assumptions for the linear regression model were tested in three ways, namely: linearity,

multicollinearity, and normality. The section also presents multiple linear regression

results for the effect of comprehensive strategic decision-making on revenue per

customer, ROA and product innovation. The study conducted a diagnostic test to choose

between multiple linear regression and multivariate regression. The diagnostic tests

showed that the error terms were not multivariate normal and so multiple linear



The assumptions for the linear regression model were tested in three ways, namely:

linearity, multicollinearity, and normality.

4.4.6.1.1 Test for Linearity


and participative governance, F(1, 9) = 1.61, p = .12. ROA had a nonlinear relationship

with participative governance, F(1, 9) = 3.37, p = .001 and product innovation had a

linear relationship with participative governance, F(1, 8) = .37, p = .10.

167

Table 4.37: Test of Linearity for Participative Governance and Organizational

Performance

Sum of Squares df Mean

Square

F Sig.

Revenue per Customer

Participative

Governance

Between

Groups

(Combined) 2320.900 10 232.090 1.614 .110

Linearity 241.601 1 241.601 1.680 .197

Deviation from

Linearity 2079.299 9 231.033 1.607 .120

Within Groups 17830.181 124 143.792

Total 20151.081 134

ROA

Participative

Governance

Between

Groups

(Combined) 7728.865 10 772.886 3.156 .001

Linearity 307.310 1 307.310 1.255 .265

Deviation from

Linearity 7421.554 9 824.617 3.367 .001

Within Groups 30369.239 124 244.913

Total 38098.104 134

Product Innovation

Participative

Governance

Between

Groups

(Combined) 4095.448 10 409.545 1.537 .134

Linearity 734.796 1 734.796 2.758 .099

Deviation from

Linearity 3360.652 9 373.406 1.401 .194

Within Groups 33575.121 126 266.469

Total 37670.569 136

p ≤ 0.05

4.4.6.1.2 Test for Multicollinearity

The results for multicollinearity indicate that revenue per customer and participative

governance had no severe multicollinearity, r(135) = .12, p > .05. ROA and participative

governance had no severe multicollinearity, r(135) = -.09, p > .05 and product innovation

and participative governance had no severe multicollinearity, r(137) = .14, p > .05. Table

4.38 shows these findings.

Table 4.38: Multicollinearity test for Participative Governance





N 135

ROA



N 135

Product Innovation



N 137

168


The Shapiro-Wilk test showed that participative governance was not normally distributed,

t(132) = .83, p < .01. Table 4.39 shows this finding.

Table 4.39: Normality test for Participative Governance



Participative Governance .181 132 .000 .828 132 .000


The study sought to establish the effect of participative governance on the dependent

variable constructs, namely revenue per customer, return on assets, and product

innovation.

4.4.6.2.1 Revenue per Customer

Multiple regression was used to test if participative governance significantly predicted

revenue per customer. The results are shown in three tables, the Model Summary (Table

4.40a), ANOVA (Table 4.40b), and Coefficients (Table 4.40c).


The multiple regression results in Table 4.40a indicate that participative governance

predicted 49.7 percent of variations in revenue per customer (R2 = .50). These results are

shown in the Model Summary, Table 4.40a.



Square

Std. Error of the

Estimate

Durbin-Watson

1 .668 .446 .423 8.87899

2 .705 .497 .459 8.59874 2.039



*Predictor variable: Participative Governance

169

4.4.6.2.1b ANOVA

Table 4.40b shows that participative governance statistically significantly predicted

revenue per customer, F(5, 125) = 20.10, p < .05).

Table 4.40b: ANOVA*

Model Sum of

Squares


1

Regression 7922.669 5 1584.534 20.099 .000

Residual 9854.552 125 78.836

Total 17777.221 130

2

Regression 8830.690 9 981.188 13.270 .000

Residual 8946.532 121 73.938

Total 17777.221 130





The multiple linear regression results revealed that, for the model without the moderator,

participative governance was not significant in predicting revenue per customer, = -.27,

t(141) = -.63, p > .05. For the model with the moderator, participative governance was not

significant in predicting revenue per customer, = -.94, t(141) = -1.13, p > .05. This

result is shown in Table 4.40c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1

Constant 21.653 6.432 3.367 .001

Participative

Governance .236 .378 .046 .625 .533

2

Constant 71.869 17.003 4.227 .000

Participative

Governance -.943 .832 -.186 -1.133 .259




170

4.4.6.2.2 Return on Assets


return on assets. The results are shown in three tables, the Model Summary (Table 4.41a),

ANOVA (Table 4.41b), and Coefficients (Table 4.41c).


The multiple regression results in Table 4.41a indicate that participative governance

predicted 29.4 percent of variations in ROA (R2 = 0.269).



Square

Std. Error of the

Estimate

Durbin-Watson

1 .519 .269 .239 14.61926

2 .543 .294 .241 14.60498 1.214


*Dependent variable: Return on Assets


4.4.6.2.2b ANOVA

Table 4.41b shows that participative governance statistically significantly predicted return

on assets, F(5, 123) = 9.06, p < .05).

Table 4.41 b: ANOVA*

Model Sum of Squares df Mean

Square

F Sig.

1

Regression 9681.507 5 1936.301 9.060 .000

Residual 26287.888 123 213.723

Total 35969.395 128

2

Regression 10586.056 9 1176.228 5.514 .000

Residual 25383.339 119 213.305

Total 35969.395 128




171



participative governance was not significant in predicting ROA, = -1.10, t(141) = -1.75,

p > .05. For the model with the moderator, participative governance was not significant in

predicting revenue per customer, = -.78, t(141) = -.54, p > .05. This result is shown in

Table 4.41c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1

Constant 30.464 10.650 2.860 .005

Participative

Governance -1.104 .631 -.150 -1.749 .083

2

Constant 64.619 29.104 2.220 .028

Participative

Governance -.778 1.431 -.105 -.544 .588




4.4.6.2.3 Product Innovation


product innovation. The results are shown in three tables, the Model Summary (Table



As Table 4.42a indicates, the multiple regression results showed that participative

governance explained 41.2 percent of variations in product innovation (R2 = 0.412).



Square

Std. Error of the

Estimate

Durbin-Watson

1 .616 .380 .355 13.19379

2 .642 .412 .368 13.05597 1.825




172

4.4.6.2.3b ANOVA

Table 4.42b shows that participative governance statistically significantly predicted

product innovation, F(5, 124) = 15.18, p = <.05.

Table 4.42b: ANOVA*

Model Sum of

Squares


1

Regression 13213.045 5 2642.609 15.181 .000

Residual 21585.448 124 174.076

Total 34798.492 129

2

Regression 14343.475 9 1593.719 9.350 .000

Residual 20455.017 120 170.458

Total 34798.492 129





The multiple linear regression results for the model without the moderator, participative

governance was not significant in predicting product innovation, = -.20, t(141) = .36, p

> .05. For the model with the moderator, participative governance was not significant in

predicting product innovation, = .93, t(141) = -.73, p > .05. This result is shown in

Table 4.42c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 Constant 13.640 9.561 1.427 .156

Participative Governance -.204 .561 -.029 -.364 .717

2 Constant 54.880 25.720 2.134 .035

Participative Governance .929 1.265 .131 .734 .464




173

4.5 Human Capital and Organizational Performance

This section presents results for the assessment of human capital on the organizational

performance of dairy co-operatives in Kenya and also the effect of human capital on

organizational performance as measured by revenue per customer, ROA and product

innovation.

4.5.1 Frequency and Percentage Distribution for Human Capital

4.5.1.1 Human Capital

As Table 4.43 shows, more than thirty-three percent (33.3%) of the respondents agreed,

to a very large extent, that board members and senior management staff had knowledge

and skills for their roles, while thirty-five percent agreed, to a very large extent, that board

members and senior management staff had the experience for their roles. In addition,

nearly thirty-two percent (31.6%) agreed, to a very large extent, that both male and

female were well represented in the board.

Table 4.43: Frequency and Percentage Distribution for Human Capital

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

Board members and senior

management staff have knowledge

and skills for their roles

f 6 6 42 40 47 141

% 4.3 4.3 29.8 28.4 33.3 100

Board members and senior

management staff have the

experience for their roles

f 4 7 34 46 49 140

% 2.9 5.0 24.3 32.9 35.0 100

Both male and female are well

represented in the board

f 18 12 33 30 43 136

% 13.2 8.8 24.3 22.1 31.6 100

4.5.1.2 Effect of Human Capital on Revenue per Customer

Forty percent of the respondents indicated that, to a moderate extent, having knowledge

and skills for their roles by the board and senior management affected revenue per

customer, while about forty-one percent (40.7%) said that having experience for their

roles by board and senior management affected revenue by customer. In addition, about

thirty-six percent (36.2%) of the respondents indicated that having both males and

174

females represented in the board affected revenue per customer. These results are

presented in Table 4.44.

Table 4.44: Frequency and Percentage Distribution of the Effect of Human Capital

on Revenue per Customer

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total


knowledge and skills for their roles

by board members and senior

management staff affect revenue per


f 24 12 56 27 21 140

% 17.1 8.6 40.0 19.3 15.0 100


experience for their roles by board

members and senior management

staff affect revenue per customer in

your co-operative?

f 21 11 57 32 19 140

% 15.0 7.9 40.7 22.9 13.6 100

To what extent does having both

male and female represented in the

board affect revenue per customer in

your co-operative?

f 31 18 50 24 15 138

22.5 13.0 36.2 17.4 10.9 100

4.5.1.3 Effect of Human Capital on ROA

About thirty percent (30.2%) of the respondents indicated that, to a small extent, having

knowledge and skills for their roles by board members and senior management staff

affected the ROA in their co-operative, while more than thirty percent (30.4%) said that,

to a small extent, having experience for their roles by board members and senior

management staff affected the ROA in their co-operative. In addition, nearly thirty-three

percent (32.8%) of the respondents said that, to a small extent, having both male and

female represented in the board affected the ROA in their co-operative. These results are

presented in Table 4.45.

175

Table 4.45: Effect of Human Capital on ROA

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total


knowledge and skills for their

roles by board members and

senior management staff affect


f 42 16 36 26 19 139

% 30.2 11.5 25.9 18.7 13.7 100




staff affect ROA in your co-

operative?

f 42 18 38 24 16 138

% 30.4 13.0 27.5 17.4 11.6 100


male and female represented in

the board affect ROA in your co-

operative?

f 45 20 34 23 15 137

% 32.8 14.6 24.8 16.8 10.9 100

4.5.1.3 Effect of Human Capital on Product Innovation

About forty-five percent (45.4%) of the respondents indicated that, to a very small extent,

having knowledge and skills for their roles by board members and senior management

staff affected product innovation in their co-operative, while more than a quarter (25.7%)

indicated, to a moderate extent, that having experience for their roles by board members

and senior management staff affected product innovation in their co-operative. In

addition, more than thirty percent (30.2%) of the respondents agreed, to a very small

extent, that having both male and female represented in the board affected product

innovation in their co-operative. These results are shown in Table 4.46.

176

Table 4.46: Effect of Human Capital on Product Innovation

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total


knowledge and skills for their

roles by board members and

senior management staff affect


operative?

f 35 20 33 31 22 141

% 24.8 14.2 23.4 22.0 15.6 100




staff affect product innovation in

your co-operative?

f 35 17 36 29 23 140

% 25.0 12.1 25.7 20.7 16.4 100


male and female represented in

the board affect product


f 42 24 30 24 19 139

% 30.2 17.3 21.6 17.3 13.7 100

4.5.2 Descriptive Statistics for Human Capital

The study analyzed the mean and standard deviation of the components of human capital.

Table 4.47 shows the mean for “board members and senior management staff have the

experience for their roles”, (M = 3.92, SD = 1.03), and the mean for “to what extent does

having both male and female represented in the board affect ROA in your co-operative”,

(M = 2.58, SD = 1.38).

177

Table 4.47: Descriptive Statistics for Human Capital

Constructs

N

Mean

(M)

Standard

Deviation

(SD)

Board members and senior management staff have

knowledge and skills for their roles

141 3.82 1.078

Board members and senior management staff have the

experience for their roles

140 3.92 1.025

Both male and female are well represented in the board 136 3.50 1.366

To what extent does having knowledge and skills for their

roles by board members and senior management staff affect


140 3.06 1.254

To what extent does having experience for their roles by

board members and senior management staff affect revenue

per customer in your co-operative?

140 3.12 1.202

To what extent does having both male and female represented

in the board affect revenue per customer in your co-

operative?

138 2.81 1.270




139 2.74 1.416


board members and senior management staff affect ROA in

your co-operative?

138 2.67 1.374


in the board affect ROA in your co-operative?

137 2.58 1.381




141 2.89 1.408


board members and senior management staff affect product


140 2.91 1.412


in the board affect product innovation in your co-operative?

139 2.67 1.416

4.5.3 Factor Analysis Results on Human Capital

In order to reduce the items of human capital and develop an appropriate measure, the

study carried out factor analysis to obtain the values for KMO and Bartlett’s test of

sphericity and determine the total variance explained by the components.

178

4.5.3.1 KMO and Bartlett's Test for Human Capital

In order to reduce the items of human capital and develop an appropriate measure, the

study carried out factor analysis and found out that KMO had a value of 0.607 and

Bartlett's test of sphericity, 2 (3, N=141) = 186.32, p = <0.000. This finding is shown in

Table 4.48.

Table 4.48: KMO and Bartlett's Test for Human Capital




df 3

Sig. .000

4.4.3.2 Total Variance Explained for Human Capital

The study showed that one component of human capital construct explained 71.31% of

the total variability in the items since it has eigenvalues greater than 1. Table 4.49 shows

this finding.

Table 4.49: Total Variance Explained for Human Capital


Total % of

Variance

Cumulative

%

Total % of

Variance

Cumulative %

1 2.139 71.314 71.314 2.139 71.314 71.314

2 .694 23.149 94.463

3 .166 5.537 100.000

4.4.3.3 Scree Plot for Human Capital

The results on the scree plot for human capital indicate that only one component had

eigenvalues greater than one hence confirming the findings of the total variance explained

for human capital. The results are shown in Figure 4.7.

179

Figure 4.7: Scree Plot for Human Capital

4.5.3.4 Component Matrix for Human Capital


human capital. All the three components have factor loadings greater than 0.5 and thus

they are strongly loaded to component one. This finding is indicated in Table 4.50.

180

Table 4.50: Component Matrix for Human Capital

Constructs

Component

1

Board members and senior management staff have knowledge and skills for their roles .917

Board members and senior management staff have the experience for their roles .920

Both male and female are well represented in the board .673

4.5.4 Correlation between Human Capital and Organizational Performance

The study tested for correlation between human capital and organizational performance

using three variables. The Pearson Correlation results showed that “Board members and

senior management staff have knowledge and skills for their roles” was correlated with

product innovation r(137) = 0.197, p<0.05. The study also found that the item “Board

members and senior management staff have the experience for their roles” and product

innovation were correlated r(137) = 0.214, p<0.05. These findings are summarized in

Table 4.51.

Table 4.51: Correlation between Human Capital and Organizational Performance

Constructs


Revenue Per

Customer ROA

Product

Innovation

Board members and

senior management staff

have knowledge and skills

for their roles

Pearson

Correlation

.069 .041 .197*

Sig. (2-tailed) .430 .636 .021

N 135 135 137

Board members and

senior management staff

have the experience for

their roles

Pearson

Correlation

.097 .080 .214*

Sig. (2-tailed) .262 .356 .012

N 135 134 136

Both male and female are

well represented in the

board

Pearson

Correlation

-.048 .007 .100

Sig. (2-tailed) .584 .937 .248

N 133 132 134

The correlation between human capital and organizational performance was insignificant

r(129) = -0.136, p>0.05. This finding is summarized in Table 4.52.

181

Table 4.52: Correlation between Human Capital and Organizational Performance


Human Capital Pearson Correlation .136


N 129

p ≤ 0.05

4.5.5 One-way ANOVA on Human Capital


difference between the mean of human capital and gender and between the mean of

human capital and education. As Tables 4.53 and 4.54 show, the tests established

significant differences between the mean scores for human capital and both male and

female respondents F(1, 130) = 10.79, p = .001. There was no significant differences

between the mean scores for human capital and different levels of education F(3, 129) =

0.52, p = .67. Bonferroni test confirms this result as shown in Table 4.55.

Table 4.53: One-way ANOVA for Human Capital and Gender


Between Groups 81.527 1 81.527 10.791 .001

Within Groups 982.132 130 7.555

Total 1063.659 131

Table 4.54: One-way ANOVA for Human Capital and Education


Between Groups 13.025 3 4.342 .522 .668

Within Groups 1073.260 129 8.320

Total 1086.286 132

182

Table 4.55: Bonferroni Test for Human Capital and Education

(I) Highest

Education Level

(J) Highest

Education Level

Mean

Difference

(I-J)

Std.

Error

Sig. 95% Confidence

Interval

Lower

Bound

Upper

Bound

Certificate

Diploma -.59655 .55065 1.000 -2.0720 .8790

Bachelors -.69118 .78215 1.000 -2.7870 1.4046

Masters -.66176 2.06937 1.000 -6.2067 4.8832

Diploma

Certificate .59655 .55065 1.000 -.8790 2.0720

Bachelors -.09463 .81870 1.000 -2.2884 2.0991

Masters -.06522 2.08346 1.000 -5.6479 5.5175

Bachelors

Certificate .69118 .78215 1.000 -1.4046 2.7870

Diploma .09463 .81870 1.000 -2.0991 2.2884

Masters .02941 2.15623 1.000 -5.7483 5.8071

Masters

Certificate .66176 2.06937 1.000 -4.8832 6.2067

Diploma .06522 2.08346 1.000 -5.5175 5.6479

Bachelors -.02941 2.15623 1.000 -5.8071 5.7483

p ≤ 0.05

4.5.6 Regression Analysis and Hypothesis Testing for Human Capital



were linearity, multicollinearity, and normality. The section also presents regression

results for the effect of human capital on organizational performance (revenue per

customer, ROA and product innovation). The study conducted a diagnostic test to choose





The assumptions for the linear regression model were tested in three ways, namely




and human capital, F(1, 10) = 1.49, p = .15. ROA had a linear relationship with human

183

capital, F(1, 10) = 1.16, p = .32 and product innovation had a linear relationship with

human capital, F(1, 10) = .51, p = .88.

Table 4.56: Test of Linearity for Human Capital and Organizational Performance

Sum of

Squares


Revenue per

Customer

Human

Capital

Between

Groups

(Combined) 2141.221 11 194.656 1.406 .179

Linearity 77.290 1 77.290 .558 .456

Deviation

from Linearity 2063.931 10 206.393 1.491 .151

Within Groups 16751.877 121 138.445

Total 18893.098 132

ROA Human

Capital

Between

Groups

(Combined) 3420.560 11 310.960 1.107 .362

Linearity 151.766 1 151.766 .540 .464

Deviation

from Linearity 3268.794 10 326.879 1.164 .322

Within Groups 33703.955 120 280.866

Total 37124.515 131

Product

Innovation

Human

Capital

Between

Groups

(Combined) 2933.450 11 266.677 .978 .470

Linearity 1545.707 1 1545.707 5.669 .019

Deviation

from Linearity 1387.744 10 138.774 .509 .881

Within Groups 33267.005 122 272.680

Total 36200.455 133


The results for multicollinearity indicate that revenue per customer and human capital had

no severe multicollinearity, r(133) = .06, p > .05. ROA and human capital had no severe

multicollinearity, r(132) = .06, p > .05 and product innovation and human capital had no

severe multicollinearity, r(137) = .14, p > .05. Table 4.57 shows this finding.

Table 4.57: Multicollinearity Test for Human Capital

Human Capital




N 133

ROA



N 132

Product Innovation

Pearson Correlation .207*


N 134

184


The Shapiro-Wilk test showed that human capital was not normally distributed, t(132) =

.94, p < .01. Table 4.58 shows this finding.

Table 4.58: Normality test for Human Capital


Statistic df Sig. Statisti

c

df Sig.

Human Capital .123 13

2 .000 .940 132 .000


The study sought to establish the effect of human capital on the dependent variable

constructs, namely revenue per customer, return on assets, and product innovation.

4.5.6.2.1 The effect of human capital on revenue per customer

Multiple regression was used to test if human capital significantly predicted revenue per

customer. The results are shown in three tables, the Model Summary (Table 4.59a),



The multiple regression results in Table 4.59a indicate that human capital predicted 49.7

percent of the variance in revenue per customer (R2=.497).



Square

Std. Error of the

Estimate

Durbin-Watson

1 .668 .446 .423 8.87899

2 .705 .497 .459 8.59874 2.039



*Predictor variable: Human Capital

185

4.5.6.2.1b ANOVA

Table 4.5b shows that human capital statistically significantly predicted revenue per

customer, F(5, 125) = 20.10, p < .05.

Table 4.59b: ANOVA*

Model Sum of

Squares


1

Regression 7922.669 5 1584.534 20.099 .000

Residual 9854.552 125 78.836

Total 17777.221 130

2

Regression 8830.690 9 981.188 13.270 .000

Residual 8946.532 121 73.938

Total 17777.221 130






human capital was not significant in predicting revenue per customer, = -.04, t(141) =

.15, p > .05. For the model with the moderator, human capital was not significant in

predicting revenue per customer, = .01, t(141) = .01, p > .05. This result is shown in

Table 4.59c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 Constant 21.653 6.432 3.367 .001

Human Capital .048 .316 .012 .153 .879

2 Constant 71.869 17.003 4.227 .000

Human Capital .010 .797 .003 .013 .990




186

4.5.6.2.2 The effect of human capital on return on assets

Multiple regression was used to test if human capital significantly predicted return on

assets. The results are shown in three tables, the Model Summary (Table 4.60a), ANOVA

(Table 4.60b), and Coefficients (Table 4.60c).



percent of variations, (R2 = .29).


Model R R

Square

Adjusted R

Square

Std. Error of the

Estimate

Durbin-Watson

1 .519 .269 .239 14.61926

2 .543 .294 .241 14.60498 1.214




4.5.6.2.2b ANOVA

Table 4.60b shows that human capital statistically significantly predicted ROA, F(5, 123)

= 9.06, p < .05.

Table 4.60b: ANOVA*

Model Sum of

Squares


1

Regression 9681.507 5 1936.301 9.060 .000

Residual 26287.888 123 213.723

Total 35969.395 128

2

Regression 10586.056 9 1176.228 5.514 .000

Residual 25383.339 119 213.305

Total 35969.395 128




187

4.5.6.2.2b Coefficients


human capital was not significant in predicting ROA, = .69, t(141) = 1.33, p > .05. For

the model with the moderator, human capital was not significant in predicting ROA, = -

.42, t(141) = -.32, p > .05. This result is shown in Table 4.60c.


Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 Constant 30.464 10.650 2.860 .005

Human Capital .693 .522 .115 1.328 .187

2 Constant 64.619 29.104 2.220 .028

Human Capital -.422 1.334 -.070 -.316 .752 Model 1 has no moderator, Model 2 has moderator



4.5.6.2.3 The effect of human capital on product innovation

Multiple regression was used to test if human capital predicted product innovation. The

results are shown in three tables, the Model Summary (Table 4.61a), ANOVA (Table

4.61b), and Coefficients (Table 4.61c).



percent of variations in product innovation (R2 = .412).



Square

Std. Error of

the Estimate

Durbin-Watson

1 .616 .380 .355 13.19379

2 .642 .412 .368 13.05597 1.825




188

4.5.6.2.3b ANOVA

Table 4.61b shows that human capital statistically significantly predicted product

innovation, F(9, 120) = 9.35, p < .05.

Table 4.61b: ANOVA*

Model Sum of

Squares

Df Mean

Square

F Sig.

1

Regression 13213.045 5 2642.609 15.181 .000

Residual 21585.448 124 174.076

Total 34798.492 129

2

Regression 14343.475 9 1593.719 9.350 .000

Residual 20455.017 120 170.458

Total 34798.492 129






human capital significantly predicted product innovation, = .94, t(141) = 2.01, p <.05.

This means that a unit increase in human capital would increase product innovation by

0.94 points. For the model with the moderator, human capital was not significant in

predicting product innovation, = -.16, t(141) = -.13, p > .05. This result is presented in

Table 4.61c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 Constant 13.640 9.561 1.427 .156

Human Capital .940 .468 .161 2.008 .047

2 Constant 54.880 25.720 2.134 .035

Human Capital -.155 1.185 -.027 -.131 .896




189

4.6 Long-Term Orientation on Organizational Performance

This section presents results for the assessment of long-term orientation on the

organizational performance of dairy co-operatives in Kenya and also the effect of long-

term orientation on organizational performance as measured by revenue per customer,

ROA, and product innovation.

4.6.1 Frequency and Percentage Distribution for Long-Term Orientation

4.6.1.1 Long-term Orientation

As Table 4.62 shows, a quarter (25%) of all respondents agreed that, to a moderate extent,

their co-operative invests for long-term profits, while about thirty percent (30.5%)

indicated that, to a moderate extent, in their co-operative the management is encouraged

to take risks by the board. About forty-three percent (42.6%) of the respondents said that,

to a large extent, the board holds the management accountable for performance.

Table 4.62: Frequency and Percentage Distribution for Long-term Orientation

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

Our co-operative invests for

long-term profits

f 21 22 35 32 30 140

% 15.0 15.7 25.0 22.9 21.4 100

In our co-operative the

management is encouraged to

take risks by the board

f 28 22 43 30 18 141

% 19.9 15.6 30.5 21.3 12.8 100

In our co-operative the board

holds the management

accountable for performance

f 9 7 21 44 60 141

% 6.4 5.0 14.9 31.2 42.6 100

4.6.1.2 Effect of Long-Term Orientation on Revenue per Customer

About forty percent (40.4%) of respondents agreed, to a moderate extent, that their

investing for long-term profits affected revenue per customer in their co-operative, while

nearly thirty-seven percent (36.9%) indicated that, to a moderate extent, the board

encouraging the management to take risks affected revenue per customer in their co-

operative. In addition about thirty-one percent (30.5%) of the respondents agreed, to a

moderate extent, that the board holding the management accountable for performance

affected revenue per customer in their co-operative. This information is shown in Table

4.63.

190


Orientation on Revenue per Customer

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

To what extent does investing

for long-term profits affect

revenue per customer in your

co-operative?

f 25 18 57 27 14 141

% 17.7 12.8 40.4 19.1 9.9 100

To what extent does the board

encouraging the management to

take risks affect revenue per


f 27 21 52 27 14 141

% 19.1 14.9 36.9 19.1 9.9 100


holding the management


affect revenue per customer in

your co-operative?

f 27 15 43 35 21 141

% 19.1 10.6 30.5 24.8 14.9 100

4.6.1.3 Effect of Long-Term Orientation on ROA

Nearly forty percent (38.1%) of the respondents agreed, to a small extent, that their board

encouraging the management to take risks affected ROA in their co-operative, while

about thirty-five percent (35.3%), said that, to a small extent, the board holding the

management accountable for performance affected ROA in their co-operative. In

addition, about thirty-seven percent (37.4%) of the respondents indicated that, to a small

extent, investing for long-term profits affected ROA in their co-operative. This

information is shown in Table 4.64.

191


Orientation on ROA

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

To what extent does investing for

long-term profits affect ROA in

your co-operative?

f 53 21 28 26 11 139

% 38.1 15.1 20.1 18.7 7.9 100



take risks affect ROA in your co-

operative?

f 49 20 29 31 10 139

% 35.3 14.4 20.9 22.3 7.2 100




affect ROA in your

co-operative?

f 52 12 28 33 14 139

% 37.4 8.6 20.1 23.7 10.1 100

4.6.1.4 Effect of Long-Term Orientation on Product Innovation

As Table 4.65 shows, thirty percent of the respondents agreed, to a moderate extent, that

investing for long-term profits affected product innovation in their co-operative, while

more than thirty percent (31.7%) agreed, to a small extent, that their board encouraging

the management to take risks affected product innovation in their co-operative. In

addition, about a third (30%) of the respondents agreed, to a small extent, that their board

holding the management accountable for performance affected product innovation in their

co-operative.

192


Orientation on Product Innovation

Constructs

Very

Small

Extent

1

Small

Extent

2

Moder

ate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

To what extent does investing for

long-term profits affect product

innovation in your co-operative? f

41 17 42 30 10 140

% 29.3 12.1 30.0 21.4 7.1 100



take risks affect product


f 44 20 38 29 8 139

% 31.7 14.4 27.3 20.9 5.8 100




affect product innovation in your

co-operative?

f 42 17 30 35 16 140

% 30.0 12.1 21.4 25.0 11.4 100

4.6.2 Descriptive Statistics for Long-Term Orientation

The study analyzed the mean and standard deviation of the components of long-term

orientation. Table 4.66 shows the mean for “In our co-operative the board holds the

management accountable for performance”, (M = 3.99, SD = 1.17), and the mean for “To

what extent does investing for long-term profits affect ROA in your co-operative” (M =

2.43, SD = 1.37).

193

Table 4.66: Descriptive Statistics for Long-Term Orientation

Constructs

N

Mean

(M)

Standard

Deviation

(SD)

Our co-operative invests for long-term profits 140 3.20 1.348

In our co-operative the management is encouraged to take

risks by the board 141 2.91 1.296

In our co-operative the board holds the management

accountable for performance 141 3.99 1.165

To what extent does investing for long-term profits affect

revenue per customer in your co-operative? 141 2.91 1.195

To what extent does the board encouraging the

management to take risks affect revenue per customer in

your co-operative? 141 2.86 1.222

To what extent does the board holding the management

accountable for performance affect revenue per customer in

your co-operative? 141 3.06 1.314



139 2.43 1.368


management to take risks affect ROA in your co-operative?

139 2.52 1.359


accountable for performance affect ROA in your co-

operative?

139 2.60 1.443



140 2.65 1.297


management to take risks affect product innovation in your

co-operative?

139 2.55 1.287


accountable for performance affect product innovation in

your co-operative?

140 2.76 1.408

4.6.3 Factor Analysis Results on Long-Term Orientation

In order to reduce the items of long-term orientation and develop an appropriate measure,

the study carried out factor analysis to obtain the values for KMO and Bartlett’s test of


4.6.3.1 KMO and Bartlett's Test for Long-Term Orientation

In order to reduce the items long-term orientation and develop an appropriate measure,

the study carried out factor analysis and found out that KMO had a value of 0.576 and

Bartlett's test of sphericity, 2 (3, N=141) = 44.89, p = .000, which was significant. This

finding is shown in Table 4.67.

194

Table 4.67: KMO and Bartlett's Test for Long-Term Orientation




df 3

Sig. .000

4.6.3.2 Total Variance Explained for Long-Term Orientation

Results for the total variance explained showed that one component of long-term

orientation construct explained 54.61% of the total variability in the three items. This

finding is presented in Table 4.68.

Table 4.68: Total Variance Explained for Long-Term Orientation


Total % of

Variance

Cumulative

%

Total % of

Variance

Cumulative %

1 1.638 54.613 54.613 1.638 54.613 54.613

2 .834 27.801 82.414

3 .528 17.586 100.000

4.6.3.3 Scree Plot for Long-Term Orientation

Scree plot for long-term orientation indicates that only one component had eigenvalues

greater than one hence confirming the findings of the total variance explained for long-

term orientation. The results are shown in Figure 4.8.

195

Figure 4.8: Scree Plot for Long-Term Orientation

4.6.3.4 Component Matrix for Long-Term Orientation

The study showed that all the three components had factor loadings greater than 0.5 and

were strongly loaded to component one. The summated scores of the three items were

used to create an index of long-term orientation. These findings are presented in Table

4.69.

Table 4.69: Component Matrix for Long-Term Orientation

Constructs

Component

1

Our co-operative invests for long-term profits .773

In our co-operative the management is encouraged to take

risks by the board .825

In our co-operative the board holds the management

accountable for performance .600

196

4.6.4 Correlation between Long-Term Orientation and Organizational

Performance

The study tested for the correlation between long-term orientation and organizational

performance using three variable constructs. The Pearson Correlation results showed that

“Our co-operative invests for long-term profits” and both revenue per customer and

product innovation were significantly correlated r(134) = 0. 263, p<0.05, r(134) = 0. 450,

p<0.05. The item “In our co-operative the management is encouraged to take risks by the

board” was significantly correlated with revenue per customer, ROA and product

innovation r(135) = 0.439, p<0.05, r(135) = 0.243, p<0.05, r(137) = 0.458, p<0.05

respectively. The study also found that the item “In our co-operative the board holds the

management accountable for performance” was significantly correlated with revenue per

customer r(135) = 0.215, p<0.05. This is summarized in Table 4.70.

Table 4.70: Correlation between Long-Term Orientation and Organizational

Performance

Constructs


Revenue

Per

Customer ROA

Product

Innovation

Our co-operative invests for

long-term profits

Pearson

Correlation

.263**

.137 .450**

Sig. (2-tailed) .002 .113 .000

N 134 134 136

In our co-operative the

management is encouraged to

take risks by the board

Pearson

Correlation

.439**

.243**

.458**

Sig. (2-tailed) .000 .005 .000

N 135 135 137

In our co-operative the board

holds the management


Pearson

Correlation

.215* .008 .052

Sig. (2-tailed) .012 .928 .545

N 135 135 137

p<0.05

Additionally, the study found that long-term orientation was positively and significantly

correlated with organizational performance r(130) = -0.366, p<0.05. This result is


197

Table 4.71: Correlation between Long-Term Orientation and Organizational

Performance


Long-Term Orientation Pearson Correlation .366**


N 130

p ≤ 0.05

4.6.5 One-way ANOVA on Long-Term Orientation


difference between the mean of long-term orientation and gender and between the mean

of long-term orientation and education. As Tables 4.72 and 4.73 show, the tests

established no significant differences between the mean scores for long-term orientation

and both male and female respondents F(1, 134) = .05, p = .82. There was also no

significant differences between the mean scores for comprehensive strategic decision-

making and different levels of education F(3, 133) = 0.71, p = .55. Bonferroni test

confirms this result as shown in Table 4.74.

Table 4.72: One-way ANOVA for Long-Term Orientation and Gender


Between Groups .405 1 .405 .052 .820

Within Groups 1046.654 134 7.811

Total 1047.059 135

p ≤ 0.05

Table 4.73: One-way ANOVA for Long-Term Orientation and Education


Between Groups 16.509 3 5.503 .707 .549

Within Groups 1035.126 133 7.783

Total 1051.635 136

p ≤ 0.05

198

Table 4.74: Bonferroni Test for Long-Term Orientation and Education

(I) Highest

Education Level

(J) Highest

Education Level

Mean

Difference

(I-J)

Std.

Error

Sig. 95% Confidence

Interval

Lower

Bound

Upper

Bound

Certificate

Diploma -.41804 .52461 1.000 -1.8231 .9870

Bachelors -.05634 .75328 1.000 -2.0739 1.9612

Masters -2.55634 2.00027 1.000 -7.9136 2.8010

Diploma

Certificate .41804 .52461 1.000 -.9870 1.8231

Bachelors .36170 .78956 1.000 -1.7530 2.4764

Masters -2.13830 2.01421 1.000 -7.5329 3.2563

Bachelors

Certificate .05634 .75328 1.000 -1.9612 2.0739

Diploma -.36170 .78956 1.000 -2.4764 1.7530

Masters -2.50000 2.08549 1.000 -8.0856 3.0856

Masters

Certificate 2.55634 2.00027 1.000 -2.8010 7.9136

Diploma 2.13830 2.01421 1.000 -3.2563 7.5329

Bachelors 2.50000 2.08549 1.000 -3.0856 8.0856

p ≤ 0.05

4.6.6 Regression Analysis and Hypothesis Testing for Long-Term Orientation



were linearity, multicollinearity, and normality. This section presents regression results

for the effect of long-term orientation on organizational performance (revenue per









The study found a linear relationship between revenue per customer and long-term

orientation, F(1, 11) = 1.48, p = .15. ROA had a nonlinear relationship with long-term

199

orientation, F(1, 11) = 2.02, p = .032 and product innovation had a linear relationship

with long-term orientation, F(1, 11) = 1.28, p = .25. Table 4.75 presents these results.

Table 4.75: Long-Term Orientation and Organizational Performance

Sum of

Squares

df Mean

Square

F Sig.

Revenue per

Customer

Long-Term

Orientation

Between

Groups

(Combined) 5138.873 12 428.239 3.676 .000

Linearity 3247.006 1 3247.006 27.874 .000

Deviation

from Linearity 1891.866 11 171.988 1.476 .149

Within Groups 14095.165 121 116.489

Total 19234.037 133

ROA

Long-Term

Orientation

Between

Groups

(Combined) 6827.349 12 568.946 2.247 .013

Linearity 1205.917 1 1205.917 4.763 .031

Deviation

from Linearity 5621.432 11 511.039 2.018 .032

Within Groups 30635.106 121 253.183

Total 37462.455 133

Product

Innovation

Long -Term

Orientation

Between

Groups

(Combined) 10401.051 12 866.754 3.956 .000

Linearity 7323.367 1 7323.367 33.428 .000

Deviation

from Linearity 3077.684 11 279.789 1.277 .245

Within Groups 26946.831 123 219.080

Total 37347.882 135

p ≤ 0.05


The results for multicollinearity, as depicted in Table 4.76, indicate that revenue per

customer and long-term orientation had no severe multicollinearity, r(134) = .41, p < .01.

ROA and long-term orientation had no severe multicollinearity, r(134) = .18, p < .05 and

product innovation and long-term orientation had no severe multicollinearity, r(136) =

.44, p < .001.

Table 4.76: Multicollinearity test for Long-Term Orientation

Long-Term Orientation


Pearson Correlation .411**


N 134

ROA

Pearson Correlation .179*


N 134

Product Innovation



N 136

200


The study used Shapiro-Wilk normality test which showed that long-term orientation was

not normally distributed, t(132) = .97, p < .05. Table 4.77 shows this finding.

Table 4.77: Normality test for Long-Term Orientation



Long-Term Orientation .097 132 .004 .971 132 .006


The study sought to establish the effect of long-term orientation on the dependent variable


4.6.6.2.1 The effect of long-term orientation on revenue per customer

Multiple regression was used to test if long-term orientation significantly predicted

revenue per customer. The results are shown in three tables, the Model Summary (Table



The multiple regression results in Table 4.78a indicate that long-term orientation

predicted 49.7 percent of variations in revenue per customer (R2=.497).



Square

Std. Error of the

Estimate

Durbin-Watson

1 .668 .446 .423 8.87899

2 .705 .497 .459 8.59874 2.039



*Predictor variable: Long-term orientation

201

4.6.6.2.1b ANOVA

Table 4.78b shows that long-term orientation statistically significantly predicted revenue

per customer, F(5, 125) = 20.10, p < .05.

Table 4.78b: ANOVA*


1

Regression 7922.669 5 1584.534 20.099 .000

Residual 9854.552 125 78.836

Total 17777.221 130

2

Regression 8830.690 9 981.188 13.270 .000

Residual 8946.532 121 73.938

Total 17777.221 130






long-term orientation significantly affected revenue per customer, = 1.04, t(141) = 3.35,

p <.05. This means that a unit increase in long-term orientation would increase revenue

per customer by 1.04 units. For the model with the moderator, long-term orientation was

not significant in predicting revenue per customer, = .99, t(141) = 1.49, p >.05. This

result is shown in Table 4.78c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 Constant 21.653 6.432 3.367 .001

Long-Term Orientation 1.035 .309 .250 3.347 .001

2 Constant 71.869 17.003 4.227 .000

Long-Term Orientation .985 .660 .238 1.493 .138




202

4.6.6.2.2 The effect of long-term orientation on return on Assets

Multiple regression was used to test if long-term orientation predicted return on assets.

The results are shown in three tables, the Model Summary (Table 4.79a), ANOVA (Table




predicted 29.4 percent of variations in ROA (R2 = .269).



Square

Std. Error of the

Estimate

Durbin-Watson

1 .519 .269 .239 14.61926

2 .543 .294 .241 14.60498 1.214




4.6.6.2.2b ANOVA

Table 4.79b shows that long-term orientation statistically significantly predicted return on

assets, F(5, 123) = 9.06, p < .05.

Table 4.79b: ANOVA*

Model Sum of

Squares

df Mean

Square

F Sig.

1

Regression 9681.507 5 1936.301 9.060 .000

Residual 26287.888 123 213.723

Total 35969.395 128

2

Regression 10586.056 9 1176.228 5.514 .000

Residual 25383.339 119 213.305

Total 35969.395 128




203



long-term orientation was not significant in predicting ROA, = .18, t(141) = .29, p >.05.

For the model with the moderator, long-term orientation was not significant in predicting

ROA, = .79, t(141) = .13, p >.05. This result is shown in Table 4.79c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 Constant 30.464 10.650 2.860 .005

Long-Term Orientation .177 .528 .029 .336 .738

2 Constant 64.619 29.104 2.220 .028

Long-Term Orientation .788 1.170 .130 .673 .502




4.6.6.2.3 The effect of long-term orientation on product innovation

Multiple regression was used to test if long-term orientation predicted product innovation.





predicted 41.2 percent of variations in product innovation (R2 = 0.412).



Square

Std. Error of the

Estimate

Durbin-Watson

1 .616 .380 .355 13.19379

2 .642 .412 .368 13.05597 1.825




204

4.6.6.2.3b ANOVA

Table 4.80b shows that long-term orientation statistically significantly predicted product

innovation, R2 = .38, F(5, 124) = 15.18, p < .05.

Table 4.80b: ANOVA*

Model Sum of

Squares


1

Regression 13213.045 5 2642.609 15.181 .000

Residual 21585.448 124 174.076

Total 34798.492 129

2

Regression 14343.475 9 1593.719 9.350 .000

Residual 20455.017 120 170.458

Total 34798.492 129






long-term orientation significantly predicted product innovation = 1.56, t(141) = 1.43, p

< .05. This means that a unit increase in the long-term orientation would increase product

innovation by 1.56 units. For the model with the moderator, long-term orientation was not

significant in predicting product innovation, = .55, t(141) = .51, p > .05. This result is

presented in Table 4.80c.



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 Constant 13.640 9.561 1.427 .156

Long-Term Orientation 1.558 .470 .266 3.316 .001

2 Constant 54.880 25.720 2.134 .035

Long-Term Orientation .552 1.040 .094 .531 .597




205

4.7 Market Orientation and Organizational Performance

The section presents results for the assessment of market orientation and its moderating

effect on the relationship between corporate governance and organizational performance

of dairy co-operatives in Kenya and also the effect of market orientation on

organizational performance as measured by revenue per customer, ROA, and product

innovation.

4.7.1 Frequency and Percentage Distribution for Market Orientation

4.7.1.1 Market Orientation

As Table 4.81 shows, a third of the respondents agreed, to a very large extent, that their

co-operative generated market intelligence needed for present and future needs, while

more than a third (34%) agreed, to a very large extent, that their co-operative

disseminated market intelligence. In addition, about thirty-eight percent (37.6%) agreed,

to a very large extent, that their co-operative responded to the market intelligence in

planning and distributing services and products.

Table 4.81: Frequency and Percentage Distribution for Assessment of Market

Orientation

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

Generates market

intelligence needed for

present and future needs

Frequency 32 9 32 47 21 141

% 22.7 6.4 22.7 33.3 14.9 100

Disseminates market

intelligence within the

co-operative

Frequency 36 16 26 48 15 141

% 25.5 11.3 18.4 34.0 10.6 100

Responds to the market

intelligence in planning

and distributing

services and products

Frequency 34 11 26 53 17 141

% 24.1 7.8 18.4 37.6 12.1 100

4.7.1.2 Effect of Market Orientation on Revenue per Customer

As Table 4.82 shows, about forty percent (39.7%) of the respondents agreed, to a

moderate extent, that their co-operative generating market intelligence needed for present

and future needs affected revenue per customer, that disseminating market intelligence

206

within the co-operative affected revenue per customer, and that responding to market

intelligence affected revenue per customer.

Table 4.82: Frequency and Percentage Distribution for the Effect of Market

Orientation on Revenue per Customer

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total

To what extent does generating

market intelligence needed for

present and future needs affect


operative?

f 27 12 56 32 14 141

% 19.1 8.5 39.7 22.7 9.9 100

To what extent does

disseminating market

intelligence within the co-

operative affect revenue per


f 28 13 56 32 12

141

% 19.9 9.2 39.7 22.7 8.5 100

To what extent does responding

to market intelligence affect


operative?

f 29 14 56 26 16 141

% 20.6 9.9 39.7 18.4 11.3 100

4.7.1.3 Effect of Market Orientation on ROA

Thirty percent of the respondents agreed, to a small extent, that their cooperative

generating market intelligence needed for present and future needs affected ROA, while

about twenty-nine percent (29.3%) of the respondents agreed, to a small extent, that their

co-operative disseminating market intelligence within the co-operative affected ROA. In

addition, about thirty-two percent (32.1%) of the respondents indicated that their co-

operative responding to market intelligence affected ROA. This result is presented in

Table 4.83.

207


Orientation on ROA

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total



present and future needs affect ROA

in your co-operative?

f 42 18 33 34 13 140

% 30.0 12.9 23.6 24.3 9.3 100

To what extent does disseminating

market intelligence within the co-

operative affect ROA in your co-

operative?

f 41 20 34 32 13 140

% 29.3 14.3 24.3 22.9 9.3 100

To what extent does responding to

market intelligence affect ROA in

your co-operative?

f 45 18 30 31 16 140

% 32.1 12.9 21.4 22.1 11.4 100

4.7.1.4 Effect of Market Orientation on Product Innovation

About thirty percent (30.5%) of the respondents agreed, to a small extent, that their

cooperative generating market intelligence needed for present and future needs affected

product innovation, while nearly thirty percent (29.8%) of the respondents agreed, to a

small extent, that disseminating market intelligence within the co-operative affected

product innovation. In addition, about thirty percent (30.5%) of the respondents indicated

that responding to market intelligence affected product innovation. These results are


208


Orientation on Product Innovation

Constructs

Very

Small

Extent

1

Small

Extent

2

Moderate

Extent

3

Large

Extent

4

Very

Large

Extent

5

Total



present and future needs affect


operative?

f 43 14 31 33 20 141

% 30.5 9.9 22.0 23.4 14.2 100

To what extent does

disseminating market intelligence

within the co-operative affect


operative?

f 42 17 34 30 18 141

% 29.8 12.1 24.1 21.3 12.8 100

To what extent does responding

to market intelligence affect


operative?

f 43 13 39 26 20 141

% 30.5 9.2 27.7 18.4 14.2 100

4.7.2 Descriptive Statistics for Market Orientation

The study analyzed the mean and standard deviation of the components of comprehensive

strategic decision-making. Table 4.85 indicates the mean for “generates market

intelligence needed for present and future needs”, (M = 3.11, SD = 1.38), and the mean

for “to what extent does responding to market intelligence affect ROA in your co-

operative?”, (M = 2.68, SD = 1.42).

209

Table 4.85: Descriptive Statistics for Market Orientation

Constructs

N

Mean

(M)

Standard

Deviation

(SD)

Generates market intelligence needed for present and future

needs

141 3.11 1.379

Disseminates market intelligence within the co-operative 141 2.93 1.382

Responds to the market intelligence in planning and distributing

services and products

141 3.06 1.382

To what extent does generating market intelligence needed for

present and future needs affect revenue per customer in your co-

operative?

141 2.96 1.218

To what extent does disseminating market intelligence within

the co-operative affect revenue per customer in your co-

operative?

141 2.91 1.207

To what extent does responding to market intelligence affect


141 2.90 1.250


present and future needs affect ROA in your co-operative?

140 2.70 1.366


the co-operative affect ROA in your co-operative?

140 2.69 1.352



140 2.68 1.416


present and future needs affect product innovation in your co-

operative?

141 2.81 1.449


the co-operative affect product innovation in your co-operative?

141 2.75 1.410



141 2.77 1.422

4.7.3 Factor Analysis Results on Market Orientation

In order to reduce the items of market orientation and develop an appropriate measure,

the study carried out factor analysis to obtain the values for KMO and Bartlett’s test of


4.7.3.1 KMO and Bartlett's Test for Market Orientation

In order to reduce the items of market orientation and develop an appropriate measure,

the study carried out factor analysis and found out that KMO had a value of 0.774 and

Bartlett's test of sphericity, x2

(3, N=141) = 435.38, p = <0.000. This finding is shown in

Table 4.86.

210

Table 4.86: KMO and Bartlett's Test for Market Orientation




df 3

Sig. .000

4.7.3.2 Total Variance Explained for Market Orientation

Total variance explained showed that one component of human capital construct

explained 91.577% of the total variability in the three items. This finding is presented in

Table 4.87.

Table 4.87: Total Variance Explained for Market Orientation


Total % of

Variance

Cumulative

%

Total % of

Variance

Cumulative %

1 2.747 91.577 91.577 2.747 91.577 91.577

2 .146 4.860 96.437

3 .107 3.563 100.000

4.7.3.3 Scree Plot for Market Orientation

The results of the scree plot for market orientation indicate that only one component had

eigenvalues greater than one hence confirming the findings of the total variance explained

for market orientation. The results are shown in Figure 4.9.

211

Figure 4.9: Scree Plot for Market Orientation

4.7.3.4 Component Matrix for Market Orientation

The study used summated scores on the three components to create an index of market

orientation. All three components had factor loadings greater than 0.5 hence were

strongly loaded to component one. These three items were summed to create an index of

market orientation. This finding is indicated in Table 4.88.

Table 4.88: Component Matrix for Market Orientation

Constructs

Component

1

Generates market intelligence needed for present and future needs .952

Disseminates market intelligence within the co-operative .956

Responds to the market intelligence in planning and distributing services

and products .964

212

4.7.4 Correlation between Market Orientation and Organizational Performance

The study tested for the correlation between market orientation and organizational

performance using three items. The Pearson correlation showed that the items “generates

market intelligence needed for present and future needs”, “disseminates market

intelligence within the co-operative” and “responds to the market intelligence in planning

and distributing services and products” were all significantly correlated with revenue per

customer, ROA and product innovation respectively, r(135) = .575, p<0.05, r(135) =.655,

p<0.05 and r(135) = .625, p<0.05 respectively. This finding is summarized in Table 4.89.

Table 4.89: Correlation between Market Orientation and Organizational

Performance

Constructs

Organization Performance

Revenue Per

Customer ROA

Product

Innovation

Generates market intelligence

needed for present and future

needs

Pearson

Correlation

.575**

.464**

.504**

Sig. (2-tailed) .000 .000 .000

N 135 135 137

Disseminates market intelligence

within the co-operative

Pearson

Correlation

.655**

.518**

.556**

Sig. (2-tailed) .000 .000 .000

N 135 135 137

Responds to the market

intelligence in planning and

distributing services and products

Pearson

Correlation

.625**

.512**

.537**

Sig. (2-tailed) .000 .000 .000

N 135 135 137

p<0.05

Additionally, the study found that market orientation was significantly correlated with

organizational performance r(131) = 0.644, p<0.05. This finding is summarized in Table

4.90.

213

Table 4.90: Correlation between Market Orientation and Organizational

Performance


Market Orientation Pearson Correlation .644**


N 131

4.7.5 One-way ANOVA on Market Orientation

A one-way analysis of variance was carried out to establish if there was significant

difference between the mean of market orientation and gender and between the mean of

market orientation and education. As Tables 4.91 and 4.92 show, the tests established no

significant differences between the mean scores for market orientation and both male and

female respondents, F(1, 135) = 5.04, p = .03. There was also no significant differences

between the mean scores for comprehensive strategic decision-making and different

levels of education, F(3, 134) = 2.16, p = .096. Bonferroni test confirms this result as


Table 4.91: One-way ANOVA for Market Orientation and Gender


Between Groups 76.202 1 76.202 5.044 .026

Within Groups 2039.593 135 15.108

Total 2115.796 136

Table 4.92: One-way ANOVA for Market Orientation and Education


Between Groups 97.963 3 32.654 2.159 .096

Within Groups 2027.139 134 15.128

Total 2125.101 137

214

Table 4.93: Bonferroni Test for Market Orientation and Education

(I) Highest

Education Level

(J) Highest

Education Level

Mean

Difference

(I-J)

Std.

Error

Sig. 95% Confidence

Interval

Lower

Bound

Upper

Bound

Certificate

Diploma -1.57683 .72937 .194 -3.5301 .3764

Bachelors -1.20261 1.04880 1.000 -4.0113 1.6061

Masters -4.05556 2.78820 .889 -11.5223 3.4112

Diploma

Certificate 1.57683 .72937 .194 -.3764 3.5301

Bachelors .37422 1.10079 1.000 -2.5737 3.3221

Masters -2.47872 2.80817 1.000 -9.9990 5.0415

Bachelors

Certificate 1.20261 1.04880 1.000 -1.6061 4.0113

Diploma -.37422 1.10079 1.000 -3.3221 2.5737

Masters -2.85294 2.90755 1.000 -10.6393 4.9334

Masters

Certificate 4.05556 2.78820 .889 -3.4112 11.5223

Diploma 2.47872 2.80817 1.000 -5.0415 9.9990

Bachelors 2.85294 2.90755 1.000 -4.9334 10.6393

4.7.6 Regression Analysis and Hypothesis Testing for Market Orientation



were linearity, multicollinearity, and normality. This section also presents regression

results for the effect of market orientation on organizational performance (revenue per


between multiple linear regression and multivariate regression. The study conducted a

diagnostic test to choose between multiple linear regression and multivariate regression.

The diagnostic tests showed that the error terms were not multivariate normal and so

multiple linear regression was used.




215



and market orientation, F(1, 11) = 1.14, p = .33. ROA had a linear relationship with

market orientation, F(1, 11) =1.02, p = .43 and product innovation had a linear

relationship with market orientation, F(1, 11) = 1.73, p = .07.

Table 4.94: Test of Linearity for Market Orientation and Organizational

Performance

Sum of

Squares

df Mean

Square

F Sig.

Revenue per

Customer

Market

Orientation

Between

Groups

(Combined) 9540.685 12 795.057 9.142 .000

Linearity 8446.185 1 8446.185 97.116 .000

Deviation

from

Linearity

1094.500 11 99.500 1.144 .334

Within Groups 10610.397 122 86.970

Total 20151.081 134

ROA

Market

Orientation

Between

Groups

(Combined) 12719.895 12 1059.991 5.096 .000

Linearity 10377.744 1 10377.744 49.889 .000

Deviation

from

Linearity

2342.151 11 212.923 1.024 .430

Within Groups 25378.209 122 208.018

Total 38098.104 134

Product

Innovation

Market

Orientation

Between

Groups

(Combined) 15162.640 12 1263.553 6.961 .000

Linearity 11704.368 1 11704.368 64.481 .000

Deviation

from

Linearity

3458.272 11 314.388 1.732 .074

Within Groups 22507.929 124 181.516

Total 37670.569 136

4.7.6.1.2 Testing for multicollinearity

The results for multicollinearity indicate that revenue per customer and market orientation

had no severe multicollinearity, r(135) = .65, p < .01. ROA and market orientation had no

severe multicollinearity, r(135) = .52, p < .01 and product innovation and market

orientation had no severe multicollinearity, r(137) = .56, p < .001. Table 4.95 shows this

finding.

216

Table 4.95: Multicollinearity test for Market Orientation

Market Orientation




N 135

ROA



N 135

Product Innovation



N 137


The study used Shapiro-Wilk normality test and showed that market orientation was not

normally distributed, t(132) = .88, p < .01. Table 4.96 shows this finding.

Table 4.96: Normality test for Market Orientation



Market Orientation .180 132 .000 .876 13

2 .000


The study sought to establish the effect of market orientation on the dependent variable


4.7.6.2.1 The effect of long-term orientation on revenue per customer

Multiple regression was used to test if market orientation significantly predicted revenue

per customer. The results are shown in three tables, the Model Summary (Table 4.97a),


217


The multiple regression results in Table 4.97a indicate that 49.7 percent of variations in

revenue per customer are predicted by market orientation (R2=.497).


Model R R

Square

Adjusted R

Square

Std. Error of the

Estimate

Durbin-Watson

1 .668 .446 .423 8.87899

2 .705 .497 .459 8.59874 2.039



*Predictor variable: Market Orientation

4.7.6.2.1b ANOVA

Table 4.97b shows that market orientation statistically significantly predicted revenue per

customer, F(5, 125) = 20.10, p < .05.

Table 4.97b: ANOVA*


1

Regression 7922.669 5 1584.534 20.099 .000

Residual 9854.552 125 78.836

Total 17777.221 130

2

Regression 8830.690 9 981.188 13.270 .000

Residual 8946.532 121 73.938

Total 17777.221 130





The multiple linear regression results showed that, for the model without interactions,

market orientation was not significant in predicting revenue per customer, = -.42, t(141)

= -.93, p > .05. For the model with interactions, market orientation was not significant in

predicting revenue per customer, = -2.85, t(141) = -2.24, p < .05. This result is shown in

Table 4.97c.

218



Coefficients

Standardized

Coefficients

t Sig.

B Std.

Error

Beta

1 Constant 21.653 6.432 3.367 .001

Market Orientation 1.644 .215 .537 7.660 .000

2

Constant 71.869 17.003 4.227 .000

Market Orientation -4.200 1.799 -1.371 -2.335 .021

Interaction between Strategic

Decision-Making and Market

Orientation

.238 .124 1.106 1.916 .058

Interaction between

Participative Governance and

Market Orientation

.158 .094 .750 1.670 .098

Interaction between Human

Capital and Market

Orientation

.031 .081 .138 .379 .706

Interaction between Long-

Term Orientation and Market

Orientation

.011 .067 .051 .166 .868




4.7.6.2.2 The effect of long-term orientation on return on assets

Multiple regression was used to test if market orientation significantly predicted return on

assets. The results are shown in three tables, the Model Summary (Table 4.99a), ANOVA

(Table 4.99b), and Coefficients (Table 4.99c).



ROA are predicted by market orientation (R2=.294).



Square

Std. Error of the

Estimate

Durbin-Watson

1 .519 .269 .239 14.61926

2 .543 .294 .241 14.60498 1.214




219

4.7.6.2.2b ANOVA

Table 4.98b shows that market orientation statistically significantly predicted ROA, F(5,

123) = 9.06, p < .05.

Table 4.98b: ANOVA*

Model Sum of

Squares


1

Regression 9681.507 5 1936.301 9.060 .000

Residual 26287.888 123 213.723

Total 35969.395 128

2

Regression 10586.056 9 1176.228 5.514 .000

Residual 25383.339 119 213.305

Total 35969.395 128





The multiple linear regression results showed that, for model without interactions, market

orientation significantly predicted ROA, = 2.14, t(141) = 5.9, p < .05. This means that a

unit increase in market orientation would increase ROA by 2.14 units. For the model with

interactions, market orientation, market orientation did not moderate the relationship

between corporate governance and organizational performance, = -1.93, t(141) = -.62, p

> .05, = -.02, t(141) = -.12, p > .05, = .15, t(141) = 1.09, p > .05, =-.07, t(141) = -

.56, p > .05. These results are shown in Table 4.98c.

220


Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std.

Error

Beta

1 Constant 30.464 10.650 2.860 .005


2

Constant 64.619 29.104 2.220 .028

Market Orientation -1.930 3.140 -.439 -.615 .540

Interaction between


and Market Orientation .233 .211 .755 1.100 .274

Interaction between


and Market Orientation -.020 .167 -.067 -.120 .905


Capital and Market

Orientation .152 .140 .477 1.091 .277

Interaction between Long-

Term Orientation and

Market Orientation -.066 .118 -.211 -.560 .577




4.7.6.2.3 The effect of long-term orientation on product innovation

Multiple regression was used to test if market orientation predicted product innovation.





product innovations are predicted by market orientation (R2 = 0.412).



Square

Std. Error of the

Estimate

Durbin-Watson

1 .616 .380 .355 13.19379

2 .642 .412 .368 13.05597 1.825




221

4.7.6.2.3b ANOVA

Table 4.99b shows that market orientation statistically significantly predicted product

innovation, F(5, 124) = 15.18, p < .05.

Table 4.99b: ANOVA*

Model Sum of

Squares

df Mean

Square

F Sig.

1

Regression 13213.045 5 2642.609 15.181 .000

Residual 21585.448 124 174.076

Total 34798.492 129

2

Regression 14343.475 9 1593.719 9.350 .000

Residual 20455.017 120 170.458

Total 34798.492 129





The multiple linear regression results showed that, for the model without interactions,

market orientation significantly predicted product innovation, =1.89, t(141) = 5.77, p <

.05. This means that a unit increase in market orientation would increase product

innovation by 1.89 units. For the model with interactions, market orientation does not

moderate the relationship between corporate governance and organizational performance,

= -2.87, t(141) = -1.05, p > .05. This result is shown in Table 4.99c.

222



Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 Constant 13.640 9.561 1.427 .156


2

Constant 54.880 25.720 2.134 .035

Market Orientation -2.868 2.723 -.669 -1.053 .294

Interaction between Strategic

Decision-Making and Market

Orientation

.269 .189 .893 1.425 .157

Interaction between

Participative Governance and

Market Orientation

-.131 .143 -.446 -.914 .363


Capital and Market Orientation .134 .122 .428 1.105 .271

Interaction between Long-Term

Orientation and Market

Orientation

.120 .104 .392 1.144 .255




4.8 Chapter Summary

The chapter presented the results and findings of the study. The study used several

analytical techniques namely, correlation analysis, ANOVA and multiple linear

regression to test the hypotheses.

Findings for the first research question on the effect of comprehensive strategic decision-

making on the organizational performance revealed that the strategic decision-making

was not significantly correlated with organizational performance, r(130)= -0.069, p>0.05.

The results of the One-way ANOVA showed that there was no significant difference

between the means of comprehensive strategic decision-making and gender, F(1, 132) =

3.8, p = .053, and different levels of education, F(3, 131) = 1.32, p = .272. The ANOVA

results showed that comprehensive strategic decision-making statistically significantly

predicted revenue per customer revenue per customer, F(9,121)= 73.938, p <.05, return

on assets, F(5, 123) = 9.06, p < .05), and product innovation, F(5, 124) = 15.18, p < .05.

The results of the multiple regression analysis showed that comprehensive strategic

decision-making was not significant in predicting revenue per customer, = -.42, t(141) =

-.93, p > .05 in the unmoderated model, but significantly and negatively affected revenue

per customer in the moderated model, = -2.85, t(141) = -2.24, p < .05. In addition, the

223

results indicated that comprehensive decision-making was not significant in predicting

ROA, = -.41, t(141) = -.54, p > .05, and product innovation, = -.94, t(141) = -1.39, p >

.05. Thus, the null hypothesis was accepted that comprehensive strategic decision-making

does not significantly affect organizational performance of dairy co-operatives in Kenya.

In respect to the second research question, the results of the study indicated that

participative governance was not significantly correlated with organizational

performance, r(130) = 0.038, p>0.05. The results of the One-way ANOVA showed that

there was no significant differences between the mean scores for participative governance

and gender, F(1, 135) = 2.46, p = .12, and different levels of education, F(3, 134) = 0.61,

p = .61. The ANOVA results showed that participative governance statistically

significantly predicted revenue per customer, F(5, 125) = 20.10, p < .05), return on assets,

F(5, 123) = 9.06, p < .05), and product innovation, F(5, 123) = 9.06, p < .05). The results

of multiple regression showed that, for both the model without and with the moderator,

participative governance was not significant in predicting revenue per customer, = -.27,

t(141) = -.63, p > .05, = -.94, t(141) = -1.13, p > .05. Similarly, the regression results for

both unmoderated and moderated models showed that participative governance was not

significant in predicting ROA, = -1.10, t(141) = -1.75, p > .05, = -.78, t(141) = -.54, p

> .05. The study further found that in both unmoderated and moderated models,

participative governance was not significant in predicting product innovation, = -.20,

t(141) = .36, p > .05, = .93, t(141) = -.73, p > .05. Consequently, the null hypothesis

was accepted that participative governance does not significantly affect organizational


In relation to human capital, the results of the study showed that human capital and

organizational performance were not significantly correlated, r(129) = -0.136, p>0.05.

The results of the One-way ANOVA showed that the means for human capital were

statistically different for male and female respondents F(1, 130) = 10.79, p = .001. The

mean for human capital was the same for different levels of education, F(3, 129) = 0.52, p

= .67. The ANOVA results showed that human capital statistically significantly predicted

revenue per customer, F(5, 123) = 20.10, p < .05), ROA, F(5, 123) = 9.06, p < .05), and

product innovation, F(5, 124) = 15.18, p < .05). The results of multiple regression test

showed that human capital was not significant in predicting revenue per customer, = -

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.04, t(141) = .15, p > .05, and ROA, = .69, t(141) = 1.33, p > .05. For the model without

the moderator, human capital significantly affected product innovation, = .94, t(141) =

2.01, p <.05 thus rejecting the null hypothesis and accepting the alternate hypothesis that

human capital significantly affects organizational performance of dairy co-operatives in

Kenya.

Long-term orientation was positively and significantly correlated with organizational

performance r(130) = -0.366, p<0.05. Pearson’s correlation results also showed that the

item “our co-operative invests for the long-term profits” was significantly correlated with

revenue per customer, r(134) = 0. 263, p<0.05, and product innovation, r(134) = 0. 450,

p<0.05. The item “in our co-operative the management is encouraged to take risks by the

board” was significantly correlated with revenue per customer, ROA and product

innovation r(135) = 0.439, p<0.05, r(135) = 0.243, p<0.05, r(137) = 0.458, p<0.05

respectively. In addition, the item “in our co-operative the board holds the management

accountable for performance” was significantly correlated with revenue per customer

r(135) = 0.215, p<0.05. The results of the One-way ANOVA showed that there was no

significant difference between the mean of long-term orientation and gender, F(1, 134) =

.05, p = .82, and different levels of education, F(3, 133) = 0.71, p = .55. The ANOVA

results showed that long-term orientation statistically significantly predicted revenue per

customer, F(5, 125) = 20.10, p < .05, ROA, F(5, 123) = 9.06, p < .05, and product

innovation, F(5, 124) = 15.18, p < .05. Results of the multiple regression showed that

long-term orientation significantly predicted revenue per customer, = 1.04, t(141) =

3.35, p <.05 and product innovation = 1.56, t(141) = 1.43, p < .05. These results led to

the rejection of the null hypothesis and accepting the alternate hypothesis that long-term

orientation significantly affects organizational performance of dairy co-operatives in

Kenya.

In respect to the fifth research question related to the moderator variable, market

orientation items comprising generating market intelligence; disseminating market

intelligence; and responding to market intelligence, were all significantly correlated with

revenue per customer, ROA and product innovation respectively, r(135) = .575, p<0.05,

r(135) =.655, p<0.05 and r(135) = .625, p<0.05 respectively. Market orientation was

significantly correlated with organizational performance r(131) = 0.644, p<0.05. The

225

results of the one-way ANOVA established that the means for market orientation were

significantly different for both male and female respondents F(1, 135) = 5.04, p = .03.

The mean for market orientation was also the same for different levels of education, F(3,

134) = 2.16, p = .096. The ANOVA results showed that market orientation statistically

significantly predicted revenue per customer, F(5, 125) = 20.10, p < .05, ROA, F(5, 123)

= 9.06, p < .05, and product innovation, F(5, 124) = 15.18, p < .05.

The multiple regression results indicated that market orientation significantly predicted

revenue per customer, = -2.85, t(141) = -2.24, p < .05; ROA, = 2.14, t(141) = 5.9, p <

.05; and product innovation, =1.89, t(141) = 5.77, p < .05. However, results showed that

market orientation does not moderate the relationship between corporate governance and

organizational performance, = -2.87, t(141) = -1.05, p > .05. This result led to accepting

the null hypothesis that market orientation has no significant moderating effect on the



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CHAPTER FIVE

5.0 SUMMARY, DISCUSSION, CONCLUSION AND RECOMMENDATIONS

5.1 Introduction

This chapter begins by presenting a summary of the study and the research findings on

the effect of corporate governance on the organizational performance of dairy co-

operatives in Kenya. The chapter then proceeds to give a detailed discussion and

conclusion of the findings and comparing the results with a critical review of the

literature. Lastly, the chapter makes recommendations for improvements and provides

suggestions for further research.

5.2 Summary


organizational performance of dairy co-operatives in Kenya. The study was guided by

five research questions: How does comprehensive strategic decision-making affect the

organizational performance of dairy co-operatives in Kenya? How does participative

governance affect the organizational performance of dairy co-operatives in Kenya? How

does human capital affect the organizational performance of dairy co-operatives in

Kenya? How does long-term orientation affect the organizational performance of dairy

co-operatives in Kenya? The study also examined to what extent market orientation

moderates the relationship between corporate governance and organizational performance

of dairy co-operatives in Kenya.

The study was guided by a positivist research philosophy and descriptive correlational

research design. The population of the study consisted of 198 executive

directors/managers of active dairy co-operatives in eight counties in the Mt Kenya region.

A sample size of 184 was drawn using stratified random sampling, and data was collected

using self-administered questionnaires. The data was analyzed, first using descriptive

statistics in terms of frequencies, means and standard deviation. Inferential statistics,

namely, Pearson’s correlational analysis and ANOVA were then used to measure the

relationship between independent and dependent variables, while multiple linear

regression analysis was used to test the hypotheses.

227

In respect to the first research question on the effect of comprehensive strategic decision-

making on the organizational performance, the study found that strategic decision-making

was not significantly correlated with organizational performance, r(130) = -0.069,

p>0.05). The results of the One-way ANOVA showed that there was no significant

difference between the means of comprehensive strategic decision-making and gender

and different levels of education. Multiple regression analysis was used to test if

comprehensive strategic decision-making significantly predicted revenue per customer,

ROA and product innovation. The results of the regression indicated that revenue per

customer explained 49.7% of the variance, (R2=.497, F(9,121) = 73.938, p <.05, while

ROA explained 29.4%, (R2=.294, F(5, 123) = 9.06, p < .05). Product innovation

explained 41.2% of the variance, (R2 = 0.412, F(5, 124) = 15.18, p < .05. It was found

that comprehensive strategic decision-making was not significant in predicting revenue

per customer in the unmoderated model, but significantly and negatively affected revenue

per customer in the moderated model, = -2.85, t(141) = -2.24, p < .05. In addition, the

results revealed that comprehensive decision-making was not significant in predicting

ROA and product innovation. The null hypothesis was accepted that comprehensive

strategic decision-making did not significantly affect organizational performance of dairy

co-operatives in Kenya.

Regarding the second research question, participative governance was not significantly

correlated with organizational performance. The results of the One-way ANOVA showed

that there was no significant difference between the mean of participative governance and

gender and different levels of education. The results of the regression indicated that

revenue per customer explained 50% of the variance, (R2 = .50, F(5, 125) = 20.10, p <

.05), while ROA explained 26.9%, (R2 = 0.269, F(5, 123) = 9.06, p < .05). Product

innovation explained 41.2% of the variance, (R2 = 0.412, F(5, 124) = 15.18, p < .05. It

was found that participative governance was not significant in predicting revenue per

customer, ROA and product innovation. The null hypothesis was accepted that

participative governance did not significantly affect organizational performance of dairy

co-operatives in Kenya.

In respect to the third research question, the results of the study showed insignificant

correlation between human capital and organizational performance. The results of the

228

regression indicated that revenue per customer explained 49.7% of the variance, (R2 =

.497, F(5, 125) = 20.10, p < .05, while ROA explained 29.4 %, (R2 = .29, F(5, 123) =

9.06, p < .05. Product innovation explained 41.2% of the variance, (R2 = 0.412, F(9, 120)

= 9.35, p < .05. It was found that human capital was not significant in predicting revenue

per customer and ROA but significantly predicted product innovation, = .94, t(141) =

2.01, p <.05 thus rejecting the null hypothesis and accepting the alternate hypothesis that

human capital significantly affected organizational performance of dairy co-operatives in

Kenya.

In relation to the fourth research question, long-term orientation was positively and

significantly correlated with organizational performance, r(130) = -0.366, p<0.05. The

results of the regression indicated that revenue per customer explained 49.7% of the


2 =


0.412, F(9, 120) = 9.35, p < .05. It was found that long-term orientation significantly

predicted revenue per customer, = 1.04, t(141) = 3.35, p <.05 and product innovation,

= 1.56, t(141) = 1.43, p < .05. These results led to the rejection of the null hypothesis

and accepting the alternate hypothesis that long-term orientation significantly affected


Regarding the fifth research question related to the moderator variable, market orientation

items comprising generating market intelligence; disseminating market intelligence; and

responding to market intelligence, were all significantly correlated with revenue per


p<0.05 and r(135) = .625, p<0.05 respectively. Market orientation was significantly

correlated with organizational performance r(131) = 0.644, p<0.05. The results of the

regression indicated that revenue per customer explained 49.7% of the variance, (R2 =

.497, F(5, 125) = 20.10, p < .05, while ROA explained 29.4 %, (R2 = .294, F(5, 123) =

9.06, p < .05. Product innovation explained 41.2% of the variance, (R2 = 0.412, F(5, 124)

= 15.18, p < .05. It was found that market orientation significantly predicted revenue per

customer, = -2.85, t(141) = -2.24, p < .05; ROA, = 2.14, t(141) = 5.9, p < .05; and

product innovation, =1.89, t(141) = 5.77, p < .05. However, results showed that market

orientation did not significantly moderate the relationship between corporate governance

229

and organizational performance. This result led to accepting the null hypothesis that

market orientation had no significant moderating effect on the relationship between

corporate governance and organizational performance of dairy co-operatives in Kenya.

5.3 Discussion

In this section, the results of the study are discussed for each of the research questions and

in relation to the literature reviewed.

5.3.1 Effect of Comprehensive Strategic Decision-making on Organizational

Performance

The study results indicated that comprehensive strategic decision-making was not

significantly correlated with organizational performance, r(130) = -0.069, p>0.05). This

result is mirrored by a number of researchers from two schools of thought. First, there are

researchers who have noted that the difficulty of accessing data about boards. For

instance Machold and Farquhar (2013) observed that what happens in the boardroom is

beset by access and methodological issues. In order to overcome the issues around single

incursions into board rooms to study their board tasks, these researchers undertook a

longitudinal study of six UK boards where they observed and noted the items for

discussion in the agenda, and also studied minutes of the previous meetings. The study,

whose objective was to show the range of tasks boards engaged with, categorized the

board tasks according to four categories: monitoring, control, strategy, and service. They

concluded that boards should curtail spending a lot of time on mere dissemination of

information so that they have room for debate on strategic issues.


between the mean of comprehensive strategic decision-making and gender, F(1, 132) =

3.8, p = .053, and different levels of education, F(3, 131) = 1.32, p = .272. From these

findings, gender diversity and different levels of education did not show any relationship.

This result may be related to the correlation results in the study which showed that

comprehensive strategic decision-making was not significantly related with

organizational performance. In their research based on 197 family firms and using key

informant approach, Eddleston et al. (2010) reported moderate levels of correlations in

their variables. Comprehensive strategic decision-making, = .243, p <.01, was found to

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significantly impact corporate entrepreneurship, the dependent variable of the study. In

their study, the researchers surmised that comprehensive decision-making was

characterized by diligent and in-depth analysis of strategic options available to stewards

in order to maximize organizational performance.

There are many studies that link board decision-making leads to better organizational

outcomes (L'Huillier, 2014; Li, Wei, & Liu, 2010; Saj, 2013; Zhou & Li, 2010). In

Germany, a study by Buchner et al. (2013) found that strategy setting of the board led to

positive hospital performance as measured by market-related, employment, social, and

innovation-related objectives. In a study based in the United States of the same sector,

Ford-Eickoff et al. (2011) reached the conclusion that boards that participate in decision-

making have a greater impact on their organization’s strategic focus and performance.

Multiple regression results in this study showed that comprehensive strategic decision-

making was not significant in predicting revenue per customer, = -.42, t(141) = -.93, p >

.05 in the unmoderated model, but significantly and negatively affected revenue per

customer in the moderated model, = -2.85, t(141) = -2.24, p < .05. This result means

that a unit increase in comprehensive strategic decision-making reduced revenue per

customer by 2.85 units. This result is supported by researchers who posit that there is a

fine line between the active engagement of the board, on the one hand, and being seen to

impinge on management’s delegated responsibility (Crow & Lockhart, 2016).

Researchers of that school of thought suggest that the role of the board in strategic

decision-making should only be at high level in order not to micro-manage the executive

management in the implementation of the strategy (Bordean et al., 2011). Instead, the

board should empower, delegate and allocate more responsibility and autonomy to the

management in order to enable executives to more actively participate in decision-making

(Zhang & Bartol, 2010). Empowering the management involves equalization of power

and communication of trust and confidence (Lorinkova & Perry, 2014), which in turn

translates to greater initiative-taking, improvization and ultimately to greater performance

(Magni & Maruping, 2013).

The regression results further showed that comprehensive strategic decision-making was

not significant in predicting ROA, = -.41, t(141) = -.54, p > .05, or product innovation,

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= -.94, t(141) = -1.39, p > .05. This result may confirm findings by other researchers

that posit that boards should be more strategic with their use of time and opportunity and

not get bogged down by operational and routine matters in order to make strategic choices

(Chait, Ryan & Taylor, 2013; Friis et al., 2016). Such strategic boards spend relatively

less time on compliance so that they can concentrate on strategic and sense-making roles

(Bordean et al., 2011; Caesar & Page, 2013; Combe & Carrington, 2015). The role of the

board in strategy development includes the review, development and monitoring of

strategy (Kim & Ozdemir, 2014) on the one hand, and strategy implementation on the

other (Tarus & Aime, 2014). In a study to investigate the role of leadership in strategy

development and implementation in Kenya, Tuwey and Tarus (2016) studied 1200 private

firms. The study found that board members’ knowledge, board chairman’s leadership

efficacy, board members’ personal motivation and board members’ background all had

positive and significant effect on their involvment in the organizational strategy.

In addition, the regression results of this study showed that comprehensive decision-

making was not significant in predicting ROA, = -.41, t(141) = -.54, p > .05, and

product innovation, = -.94, t(141) = -1.39, p > .05. Some researchers opine that one of

the difficulties in researching effects of corporate governance on organizational

performance is basically methodological. Crow and Lockhart (2016), noted the

methodological challenges of observing a board in action and the need to move

governance research beyond correlations. In particular, the researchers challenge the

positivist and interpretivist assumptions that governance is comprised of separate

attributes that be isolated and studied discretely (Crow & Lockhart, 2014). According to

Tricker (2012b), the board is a complex, socially dynamic construction that cannot be

studied in isolation from the structure in which it exists and the constituency it serves.

Consequently, causality in socially dynamic phenomena is dependent on certain

contingent conditions and, therefore, board activity is unlikely to be explained through

reduction of roles of individual directors (Crow & Lockhart, 2016) or over-reliance on

secondary data (Minichilli, Zattoni, Nielsen, & Huse, 2012). The need to collect reliable

data on how boards operate speaks to the issue of access and which, in turn, requires

narrowing the gap between research and practice as witnessed in the “great academic-

practitioner divide” (McNatt, Glassman, & Glassman, 2013).

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In this study, the null hypothesis was accepted that comprehensive strategic decision-

making did not significantly affect organizational performance of dairy co-operatives in

Kenya; These results echo other findings that concluded that the active engagement of the

board in strategic decision-making a myth given that most independent directors rely

exclusively on executive management for information on which to control the

organization (Sharpe, 2012). However, there are other studies that have advanced the

view that it is strategy that comes before leadership in driving the success of a firm and

that it is the former that drives the latter (Almatrooshi et al., 2016; Allio, 2015; Freedman,

2013). Harvard professor David Yoffie and MIT professor Michael Cusumuno, in their

study of Apple, Microsoft, and Intel concluded that the success of Jobs, Gates and Grove,

respectively, was more aligned to their strategies than their leadership styles (Yoffie &

Cusumuno, 2015). The proactive role of the board is also critical if it is going to exert

influence beyond the boardroom (Huse et al., 2011). Without involvement in strategic

decision-making, a board is not equipped to perform its fiduciary monitoring role, leave

alone contributing its vast expertise which is best made available while developing

strategy (Bordean et al., 2011).

The rejection of the alternate hypothesis that comprehensive strategic decision-making

significantly affect organizational performance of dairy co-operatives in Kenya may be

supported by researchers who see the role strategy development as that of management.

Those researchers posit that the role of corporate governance is the formulation and

visioning of the organizational ends (Nickols, 2016), or the reason for the existence or

results expected of the firm (Montgomery, 2012). Thus the board should be preoccupied

with the ends while the management is responsible for the means (Fryday-Field, 2013) or

the implementation of the strategy. Instead of getting too involved in strategic decision-

making, the board should empower management (Cui, 2016) to make the necessary

operational decisions aligned to the strategic outcomes spelt out in the organizational

ends. The board brings most value to an organization by offering a wide spectrum of

perspectives and strategic considerations of possible alternatives (Tuwey & Tarus, 2016)

and when offering advice on strategic choices (Nas & Kalaycioglu, 2016).

5.3.2 Effect of Participative Governance on Organizational Performance

The study found that participative governance was not significantly correlated with

organizational performance, r(130) = 0.038, p>0.05). These results are corroborated by

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studies of participatory governance in co-operatives in China which showed that in

reality, participation in decision-making is only nominal as most decisions are made by

board members and management (Liang et al., 2015). The study found that the

distribution of ownership rights and profits were skewed towards a small portion of core

members to the exclusion of the majority. Power imbalance, lack of accountability, and

resource differentials between various partners may undermine participation its

legitimancy (Bell & Stockdale, 2016). Mere presence does not engender participation and

neither does representation (Belle, 2015). Meaningful engagement and participation are

what characterize learning organizations as they engage in critical reflection (Matsuo,

2015; Newig et al., 2016).


between the mean of participative governance and gender, F(1, 135) = 2.46, p = .12, and

different levels of education, F(3, 134) = 0.61, p = .61. This result may relate to the lack

of correlation between participative governance and organizational performance. Some

researchers have shown that the benefits of participation in decision-making (Liang et al.,

2015), regardless of gender and educational level, are largely psychological (Chaundhuri,

2016). Some studies suggest that the sense of psychological ownership and belongingness

can result in higher productivity and performance (Cheyney et al., 2014). In co-

operatives, participative governance is associated with the principle of one member one

vote, which balances managerial direction with members’ concerns (Liang et al., 2015).

Some studies suggest that the participation of members in a co-operative gives them voice

and authority to monitor management (Dayanandan, 2013; Francesconi & Ruben, 2012).

Other researchers have shown that participation is about power and how an empowered

membership can demand their space (Chaundhuri, 2016) and requires ‘emancipation’ or

‘fostering of critical consciousness’ as a precondition (Aasgaard et al., 2012).

Participation is about collaboration, deliberation, involvement, engagement and co-

management (Carr, 2015). It is a shift in power, much needed especially in emerging

economies where minority shareholders do not get sufficient protection; participation

renders managers and directors more accountable thus giving shareholders more attention

than in purely board-centric models of governance (Goranova & Ryan, 2015). Other

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researchers posit that participation engenders democracy, transparency and accountability

and leads to higher performance outcomes (Scholl & Sherwood, 2014).

The regression results in this study showed that participative governance was not

significant in predicting revenue per customer, = -.27, t(141) = -.63, ROA, = -1.10,

t(141) = -1.75, p > .05, or product innovation, = -.20, t(141) = .36, p > .05. The null

hypothesis was accepted that participative governance does not significantly affect

organizational performance of dairy co-operatives in Kenya. This result is in agreement

with studies that opine that participation has many outcomes and benefits for

organizations, but improved performance may not necessarily be one of them. According

to Pozzobon and Zylbersztajn (2013), participative governance comes with “democratic

costs”, which are the decision-making costs incurred in managing conflicts of interest and

providing incentives for member participation.

Brazil, Pozzobon and Zylbersztajn (2013) reached similar findings in their study of 12 co-

operatives in Rio Grande do Sul. The researchers observed that member participation can

be problematic especially in large co-operatives with heterogeneous membership. They

noted that conflicts of interest could arise at two levels: horizontal conflicts of interests

are when members attempt to collectively make decisions about the distribution of

benefits and costs; diagonal conflicts of interest occur among the members and board of

directors when they are either under- or over-represented. The researchers concluded that

the higher the level of member participation at the general assembly, the higher the

democractic costs as the co-operatives spent more resources on the collective decision-

making process.

5.3.3 Effect of Human Capital on Organizational Performance

In this study, the correlation between human capital and organizational performance was

insignificant, r(129) = -0.136, p>0.05. However, ANOVA results indicated that revenue

per customer predicted 49.7% of the variance, (R2 = .497, F(5, 125) = 20.10, p < .05,

while ROA explained 29.4 %, (R2 = .29, F(5, 123) = 9.06, p < .05. Product innovation

explained 41.2% of the variance, (R2 = 0.412, F(9, 120) = 9.35, p < .05. Other studies

have shown that human capital, comprising an organization’s intangible assets such as

employee skills and capabilities (Al-Musali & Ismail, 2015), are needed to facilitate

235

growth and development (Lin, 2015). Human capital is the resource an organization has

in the workforce and refers to education, skills, and experience of the staff and board of

directors (Gottesman & Morey, 2010; N. Kim & Kim, 2015).

Human capital can also be conceptualized as comprising knowledge, abilities and skills

(Neeliah & Seetanah, 2016); education, experience and knowledge (Felicio et al., 2014);

problem solving ability, work environment interaction (Nkundabanyanga et al., 2014); or

knowledge of industry, skills and knowledge board members bring to the decision-

making processes (Johnson et al., 2013). From the results of this study, it shows that the

dairy co-operatives may be constrained by inadequate human capital to facilitate their

growth and development.

The regression results showed that human capital was not significant in predicting

revenue per customer, = -.04, t(141) = .15, p > .05, and was also not significant in

predicting ROA, = .69, t(141) = 1.33, p > .05. However, for product innovation, the

ANOVA results for unmoderated and moderated models showed that jointly the

independent variables had significant effect on the dependent variable, F(5, 124) = 15.18,

p = .00 and F(9, 120) = 9.35, p = .00. In addition, the descriptive statistics on the level of

education showed that more than half of the respondents had studied up to the certificate

level, followed by diploma at thirty four percent, bachelor’s degree at twelve percent and

only two percent at the master’s level. There are numerous studies that can corroborate

the findings of this study that human capital significantly and positively affects product

innovation and higher levels of education leads to better outcomes and higher

organizational performance (Appuhami & Bhunyan, 2015; Bertoni et al., 2014; Fidanoski

et al., 2014). Barroso et al. (2011) posits that the higher the educational level, the better

the ability to process information, absorb new ideas, and find creative solutions. Board

directors use their knowledge, experience and networking opportunities to build

intellectual capital (Claver-Cortes et al., 2015) and thus creative value for the firm

(Berezzinets et al., 2016).

In addition, a study of electronic firms in Taiwan found that directors’ educational level,

CEO experience and international experience had a positive effect on firms’ decisions

towards internationalization. On the other hand, Perez-Calero et al. (2016) showed that

236

both human and external social capital provided the board with knowledge and

information about the environment of the firm, while internal social capital brought

bonding, cohesiveness and facilitated pursuit of collective goals (Arnegger et al., 2014).

In this study, only about a third of the respondents were female, and this proportion was

assumed to represent the leadership of dairy co-operatives in the target population. Board

diversity in relation to gender has also been noted as an important aspect of human capital

and with positive effect on performance (Hillman, 2014; Kumar & Zattoni, 2016; Ntim,

2015). Female members of the board have been shown to have a positive impact on

organizational performance (Fidanoski et al., 2014; Gotsis & Grimani, 2016; Velte,

2016). Gender diversity contributes to creativity and improves the quality of decision-

making as a result of increasing alternatives considered by members (Kumar & Zattoni,

2016).

However, there are studies that show different results of the contribution of gender

diversity depending on performance measures chosen, such as the research by Willows

and van der Linde (2016), which showed positive impact when using accounting based

measures and negative impact when using market-based measures. Similar mixed results

were obtained by Post and Byron (2015) who found positive results using accounting

measures and in countries with stronger shareholder protections. There are also studies

that show no effect or negative relationship between gender and organizational

performance (Manini & Abdillahi, 2015; Wessels, Wansbeek, & Dam, 2015).

5.3.4 Effect of Long-term Orientation on Organizational Performance

In this study, long-term orientation was positively and significantly correlated with

organizational performance, r(130) = -0.366, p<0.05. Some researchers have posited that

long-term orientation is a culture that favors patient investment and a tendency to

prioritize long-range implications and impact of decisions and actions that bear fruit after

an extended time period (Hoffman & Wulf, 2016; Lumpkin et al., 2010; Park et al.,

2013). Other scholars suggest that long-term orientation has to do with incentivizing

managers to make decisions that benefit the organization in the long run, even at the cost

of forgoing short-term profits in order to avoid short-termism and managerial myopia

(Abernethy, Bouwens, & Lent, 2013; Flammer & Bansal, 2017). It is a focus on future

237

benefits and reflects a desire to build and maintain long-term relationships (Hwang,

Chung, & Jin, 2013; Maleki & de Jong, 2014).

Similar to the results of this study, long-term orientation has been shown to contribute

positively to financial performance (Lumpkin & Brigham, 2011) as well as other

important non-economic goals such as social satisfaction, positive community image and

making long-term commitments to the community (Charisman et al., 2012; Cho et al.,

2015). This study used three dimensions of long-term orientation: First, a focus on long-

term profitability referred to an extended time horizon in making decisions, (Annamalai

& Hari, 2016), prepared to make short-term sacrifices (Hwang et al., 2013) while not

sacrificing the need for short-term performance (Brigham et al., 2014; Martynov &

Shafti, 2016). In this study, most respondents agreed that investing for long-term profits

affected organizational performance, F(1, 141) = 2.02, p = .007. Long-term profitability

and sustainability are closely linked because firms that improve social and ecological

aims have been shown to increase the value of their enterprises in the long run (Jansson et

al., 2017). Firms that invest for the long-term are also resilient to and adjust to

environmental shocks (Ortiz-De-Mandojana & Bansal, 2016).

Second dimension used for long-term orientation in this study was their propensity for

risk and the majority of the respondents agreed that their board encouraging the

management to take risks significantly affected the revenue per customer, F(1, 141) =

2.02, p = .007, but not the ROA, F(1, 141) = 1.71, p = .029. Other studies corroborate this

finding that managerial risk-taking is an inevitable component of strategic management in

a dynamic and uncertain business environment (Hoskinsson et al., 2017; Mckelvie et al.,

2011). In order to encourage responsible risk-taking (Armstrong & Vashishtha, 2012),

organizations use different incentives, including CEO severance pay that reduced fear of

losing one’s job (Cowen et al., 2016), improving compensation (Eling & Marek, 2013), or

encouraging risk-averse managers to diversify outside the firm (Belghitar & Clark, 2014).

The third dimension of long-term orientation used in this study was holding management

accountable for performance. Most respondents in the study agreed that the board holding

management accountable for performance affects revenue per customer in their co-

operative. ANOVA results showed that there was significant difference between holding

238

management accountable and effect on ROA in the dairy co-operatives, F(1, 141) = 2.92,

p = .000. Many studies have shown that it was failure to hold management accountable

that led to the financial crises brought by sub-prime mortgages in the US (Bekiaris et al.,

2013; Brown et al., 2011; Dalwai et al., 2015; Kumar & Singh, 2013; Yeoh, 2010).

Consquently, supported by legislation corporate boards have tightened their vigilance and

accountability (Dah et al., 2014; Goranova & Ryan, 2014; Pugliese et al., 2014; Ryan et

al., 2010). Other studies recommended board independence by inclusion of non-executive

directors as a good corporate governance practice (Elmarghi et al., 2016; Mallin & Ow-

Yong, 2012; Melis et al., 2015; Ntim & Soobaroyen, 2013).

The results of regression analysis in this study indicated that long-term orientation

significantly affected revenue per customer, = 1.04, t(141) = 3.35, p <.05 and product

innovation = 1.56, t(141) = 1.43, p < .05. These results led to the rejection of the null

hypothesis and accepting the alternate hypothesis that long-term orientation significantly

affects organizational performance of dairy co-operatives in Kenya. The link between

long-term orientation and innovation has been noted by researchers such as Lofsten

(2016) who opined that firms need technological capabilities and resources developed

over time in order to obtain competitive advantage and survival (Ahern G. M., 2015).

Entrepreneurial orientation, associated with CEO risk-propensity to exploit new

opportunities is also a driver of innovation (De Massis et al., 2013; Felekoglu & Moultrie,

2014).

5.3.5 The Moderating Effect of Market Orientation on the Relationship between


The results of this study showed that the three items of the moderating variable - market

orientation, generating market intelligence, disseminating market intelligence, and

responding to market intelligence, were all significantly correlated with revenue per


p<0.05 and r(135) = .625, p<0.05 respectively. In addition, the market orientation was

significantly correlated with organizational performance, r(131) = 0.644, p<0.05.These

results are corroborated by Camarero and Garrido (2012) who showed that market

orientation is the organization-wide responsiveness to market information. Amin et al.

(2016), who equated market orientation with entrepreneurial orientation, analyzed three

239

dimensions, namely: innovativeness, pro-activeness and risk-taking, and showed a

significant relationship with SME performance. A similar study by Fernandez-Mesa and

Alegre (2015) showed that firms with more collaboration and entrepreneurial orientation

have greater market information to explore market opportunities and thus perform better.

The regression results for this study indicated that market orientation significantly

affected revenue per customer, = -2.85, t(141) = -2.24, p < .05; ROA, = 2.14, t(141) =

5.9, p < .05; and product innovation, =1.89, t(141) = 5.77, p < .05. The link between

market orientation and product innovation has been demonstrated by the research of

Vega-Vazquez, Cossıo-Silva, and Martın-Ruız (2012). In their study comprising 294

Spanish firms, the researchers concluded that market orientation emphasizes a firm’s

ability to connect with its customers and desires and, as a result, reorganize its functions

in order to build a greater value for the new product. Similar results were obtained from

the study by Boso, Cadogan, and Story (2012) of 164 Ghanian exporters who showed that

both export entrepreneurial-oriented behaviour and export-market oriented behaviour

drive export product innovation success.

Research by Rodrigues and Pinho (2012), based in the North Region of Portugal and by

Polo-Pena et al. (2012a) corroborates the findings of this study by showing that

information generation, one of the three dimensions of market orientation used in this

study, had a positive effect on performance. In support of the findings of the second

dimension of this study, intelligence dissemination, Wang et al. (2016) found that

developing human resource and training systems improved sensitivity of employees to

customer needs, thus improving organizational commitment and service quality

(Iliopoulos & Priporas, 2011; Tsai & Wu, 2011). Polo-Pena et al. (2012a) in their study of

organizational responsiveness, the third dimension of market orientation in this study,

showed that continuously revising facilities and services to align them to customer wants

had a positive effect on firm outcomes.

Although the individual items of market orientation were all shown to be correlated and

significantly affected organizational performance, the regression results showed that

market orientation did not moderate the relationship between corporate governance and

organizational performance, = -2.87, t(141) = -1.05, p > .05. This result led to accepting

240

the null hypothesis that market orientation had no significant moderating effect on the



5.4 Conclusion

This section presents the conclusion of the study based on the research questions.

5.4.1 Effect of Comprehensive Strategic Decision-making on Organizational

Performance

Multiple regression analysis was used to test if comprehensive strategic decision-making

significantly predicted organizational performance. The results of the regression indicated

that comprehensive strategic decision-making did not significantly predict revenue per

customer, ROA and product innovation. The null hypothesis was accepted that

comprehensive strategic decision-making did not significantly affect organizational

performance of dairy co-operatives in Kenya. Therefore, the null hypothesis was accepted

and the alternate hypothesis rejected. Based on this result, the study concluded that

keeping the respective roles of governance and management distinct allowed the board to

prioritize organizational ends while empowering the management to be responsible for

the operational means.

5.4.2 Effect of Participative Governance on Organizational Performance

The results of the regression indicated that participative governance was not significant in

predicting revenue per customer, ROA and product innovation. The null hypothesis was

accepted that participative governance did not significantly affect organizational

performance of dairy co-operatives in Kenya. This result suggests that participation of

members and shareholders in organizations may have other benefits, including non-

economic ones, but enhancing organizational performance may not be one of them.

Further, participative governance comes with democratic costs, decision-making costs

incurred in managing the dynamics of member participation.

5.4.3 Effect of Human Capital on Organizational Performance

Multiple regression analysis was used to test if human capital significantly predicted

organizational performance. The results of the regression indicated that human capital

241

was not significant in predicting revenue per customer and ROA but significantly

predicted product innovation, = .94, t(141) = 2.01, p <.05. Product innovation also

explained 41.2% of the variance, (R2 = 0.412, F(9, 120) = 9.35, p < .05. These results led

to rejecting the null hypothesis and accepting the alternate hypothesis that human capital

significantly affected organizational performance of dairy co-operatives in Kenya.

5.4.4 Effect of Long-Term Orientation on Organizational Performance

The results of the regression indicated that long-term orientation significantly predicted

revenue per customer, = 1.04, t(141) = 3.35, p <.05 and product innovation, = 1.56,

t(141) = 1.43, p < .05. It was also found that revenue per customer explained 49.7% of the


2 =


0.412, F(9, 120) = 9.35, p < .05. These results led to the rejection of the null hypothesis

and accepting the alternate hypothesis that long-term orientation significantly affected

organizational performance of dairy co-operatives in Kenya. This study concludes that

firms need technological capabilities and resources developed over time in order to obtain

competitive advantage and survival.

5.4.5 The Moderating Effect of Market Orientation on the Relationship between


The results of the regression revealed that market orientation significantly predicted

revenue per customer, = -2.85, t(141) = -2.24, p < .05; ROA, = 2.14, t(141) = 5.9, p <

.05; and product innovation, =1.89, t(141) = 5.77, p < .05. It was also found that

revenue per customer explained 49.7% of the variance, (R2 = .497, F(5, 125) = 20.10, p <

.05, while ROA explained 29.4 %, (R2 = .294, F(5, 123) = 9.06, p < .05. Product

innovation explained 41.2% of the variance, (R2 = 0.412, F(5, 124) = 15.18, p < .05.

These findings led to the conclusion that developing human resource and training systems

improved sensitivity of employees to customer needs, thus improving organizational

commitment, service quality and, as a result, a positive effect on firm outcomes. Although

the individual items of market orientation were shown to be significantly affect

organizational performance, the regression results showed that market orientation does

not moderate the relationship between corporate governance and organizational

performance. This result led to accepting the null hypothesis that market orientation had

242

no significant moderating effect on the relationship between corporate governance and


5.5 Recommendations

From the findings of this study, the following recommendations are made.

5.5.1 Recommendations for Improvements

5.5.1.1 Effect of Comprehensive Strategic Decision-making on Organizational

Performance

The study found that comprehensive strategic decision-making was not significant in

predicting organizational performance. Several suggestions were proposed for this result

including the methodological challenge of studying board tasks outside of board

meetings. Another suggestion given for this result is that strategic decision-making by the

board may conflict with the management role of strategy implementation. This study

recommends that the role of boards in strategic decision-making should only be at policy

level in order to keep away from micro-managing the management. The respective roles

of governance and management in the co-operatives should be kept distinct in order to

allow the board to prioritize organizational ends while empowering the management to be

responsible for the operational means.

5.5.1.2 Effect of Participative Governance on Organizational Performance

The regression results in this study showed that participative governance was not

significant in predicting revenue per customer, ROA, or product innovation. The study

concluded that participation of members and shareholders in organizations may have

other benefits, including non-economic ones, but enhancing organizational performance

may not be one of them. Further, the study noted that participative governance comes

with democratic costs, decision-making costs incurred in managing the dynamics of

member participation. The study recommends that participation in governance, an

important co-operative principle, be balanced with directive leadership, especially during

difficult times, so that it does not compromise their growth and development.

243

5.5.1.3 Effect of Human Capital on Organizational Performance

The results of the multiple linear regression analysis showed that human capital

significantly predicted product innovation. In order not to be constrained by inadequate

human capital, and to innovate for their growth and performance, this study recommends

that dairy co-operatives should invest in skilled leadership with higher academic

qualifications.

5.5.1.4 Effect of Long-Term Orientation on Organizational Performance

The study found that long-term orientation significantly predicted revenue per customer,

ROA, and product innovation. This study recommends that co-operatives should put into

place strategies and processes that incentivize managers to invest for the long-term

sustainability and profitability. The study further recommends that co-operatives should

develop technological capabilities and resources over time in order to obtain competitive

advantage and survival.

5.5.1.5 The Moderating Effect of Market Orientation on the Relationship between


The study found that market orientation statistically and significantly predicted revenue

per customer, ROA, and product innovation. These findings led to the conclusion that

developing human resource and training systems improved sensitivity of employees to

customer needs. This study recommends that co-operatives invest in strategies and

systems that will foster information generation, dissemination and responsiveness in order

to serve and produce for the market. Specifically, the study recommends that co-

operatives invest in human resource and training systems that lead to improved sensitivity

of employees to customer needs, thus improving organizational commitment, service

quality and, as a result, a positive effect on firm outcomes.

5.5.2 Recommendations for Further Research

This study adopted a positivist research philosophy and a descriptive correlational design

using a self-administered questionnaire for data collection. The design of the study was

cross-sectional in nature, which may lead to common method bias, on the one hand, or,

on the other, reliability issues associated with use of proxies of governance instead of

direct observation of the boardroom. This study was potentially subject to the latter

244

challenge since stewardship-related variables, the underpinning theory, normally take

time to generate positive outcomes. Consequently, this study recommends a longitudinal

design that would allow for closer access to the board functions as well study over a

period of time.

Secondly, the CEOs (executive director/manager) were the targeted population for this

study on corporate governance. While the choice of the CEO provided the information

required from both governance and management perspectives, multiple respondents from

boards and top management would have strengthened the study design. Accordingly, this

study recommends inclusion of board members, other than the CEO, as respondents for

future research into the corporate governance of dairy co-operatives.

Thirdly, although the individual items of market orientation, the moderating variable

chosen for this study, were all shown to be correlated and to significantly affect

organizational performance, the regression results showed that market orientation did not

moderate the relationship between corporate governance and organizational performance.

This study recommends research of other moderators of corporate governance, such as

educational level of the CEO, in the study of dairy co-operatives in Kenya.

Fourthly, this study recommends that a governance code be developed for co-operatives

based on stewardship theory as it is better aligned to co-operative principles which are

predicated on democracy, inclusive economic participation, and concern for the

community.

245

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APPENDIX A: LETTER OF INTRODUCTION TO THE RESPONDENTS

Joshua Wathanga

PO Box 24446-00502

Karen

Dear Dairy Co-operative Manager/Executive Director

I am a research student at the United States International University pursuing a Doctorate

in Business Administration (DBA) in Leadership and Change Management. I am doing a

research to investigate the effect of corporate governance on the organizational

performance of dairy co-operatives in Kenya. I have been authorized to conduct research

by the National Commission for Science, Research and Innovation (NACOSTI) and their

approval letter is attached to this questionnaire.

I would be most grateful if you could kindly complete this questionnaire in full so that I

can get enough data for this study which, I believe, will make a contribution to the

improvement in the way co-operatives are governed and by so doing improving their

performance.

Any information provided will be treated with utmost confidentiality and at no instance

will it be used for any other purpose other than this research study.

Thank you for your cooperation and I look forward to your prompt response.

Yours sincerely

Joshua Wathanga

Mobile: 0710121054

Email: [email protected]

mailto:[email protected]

321

APPENDIX B: THE SURVEY QUESTIONNAIRE

PLEASE COMPLETE ALL QUESTIONS: DO NOT LEAVE ANY BLANKS

1. SECTION ONE: GENERAL QUESTIONS

1.1. What year was your Co-operative registered?…………………….

1.2. What is your position/title?………………………………………………………

1.3. What is your gender? Please tick (√) one Male Female

1.4. What is your age? Please tick (√) one

21-29 years 30-39 years 40-49 years 50-59 years

60 and above

1.5. What is the highest level of education you attained? Please tick (√) one

Certificate Diploma Bachelors degree Masters Doctorate

1.6. What are your professional qualifications?…………………………………………

……………………………………………………………………………………………

1.7. For how long have you worked or served in the co-operative? Please tick (√) one

Below 1 year 2-5 years 6-10 years 11-15 years

15 years and above

1.8. How much milk did you collect per day on average in 2016? ………………litres.

322

2. SECTION TWO: STRATEGIC DECISION-MAKING

This section assesses the strategic decision-making of the board and also examines the

perceived effect of strategic decision-making on organizational performance

2.1. Assessment of Strategic Decision-making

Please indicate by ticking (√) the extent to which you agree or disagree with the

statements below, using a scale of 1 to 5 where:

1 = Strongly disagree (SD); 2 = Disagree (D); 3 = Neutral (N); 4 = Agree (A); 5 =

Strongly Agree (SA).

2.1.

Assessment of Strategic Decision-making

SD D N A SA

1 2 3 4 5

1. The board of our co-operative is involved in making

strategic decisions

2. The board of our co-operative empowers the

management

3. The board of our co-operative works as a team

2.2. Effect of Strategic Decision-making on Revenue per Customer

Please indicate by ticking (√) the extent to which the perceived strategic decision-making

of the board has an effect on the Revenue per Customer (milk prices in the last financial

year) by using a scale of 1 to 5 in where:

1 = Very Small Extent (VS) - Up to Ksh 25 per liter

2 = Small Extent (S) - Ksh 26-30 per liter

3 = Moderate Extent (M) - Ksh 31-35 per liter

4 = Large Extent (L) - Ksh 36-40 per liter

5 = Very Large Extent (VL) - Over Ksh 41 per liter

2.2. Effect of Strategic Decision-making on Revenue

per Customer

VS S M L VL

1 2 3 4 5

1. To what extent does the board’s role in making

strategic decisions affect the revenue per customer


2. To what extent does the empowering of the

management by the board affect the revenue per


3. To what extent does working as a team by the board

affect the revenue per customer in your co-

operative?

323

2.3. Effect of Strategic Decision-making on Return on Assets (ROA)

First, complete table below from the financial statements of the past year indicating

the ROA of your dairy co-operative measured by the Net Profit divided by Total

Assets.

Year Net Profit Total Assets ROA = Net Profit x 100%

Total Assets

2015/2016

Please indicate by ticking (√) the extent to which the perceived strategic decision-

making of the board has an effect on the ROA of your dairy co-operative measured

over the last financial year, using a scale of 1-5:

1 = Very Small Extent (VS) - Up to 1%

2 = Small Extent (S) - Up to 2%

3 = Moderate (M) - Up to 3%

4 = Large Extent (L) - Up to 4%

5 = Very Large Extent (VL) - 5% and higher

2.3.

Effect of Strategic Decision-making on ROA

VS S M L VL

1 2 3 4 5

1. To what extent does the board’s role in making strategic

decisions affect ROA in your co-operative?

2. To what extent does the empowering of the management

by the board affect ROA in your co-operative?



2.4. Effect of Strategic Decision-making on Product Innovation

Please indicate by ticking (√) the extent to which the board’s strategic decision-making,

affects innovation of new products such as: milk processing; provision of Artificial

Insemination (AI) services, loaning of cattle dip chemicals, provision of cattle loans,

provision of cattle and other insurances, provision of veterinary services, etc.

1 = Very Small Extent (VS) - One new product

2 = Small Extent (S) - Two new products

3 = Moderate (M) - Three new products

4 = Large Extent (L) - Four new products

5 = Very Large Extent (VL) - More than 5 new products

324

2.4. Effect of Strategic Decision-making on Product

Innovation

VS S M L VL

1 2 3 4 5

1. To what extent does the board’s role in making

strategic decisions affect product innovation in your

co-operative?

2. To what extent does the empowering of the

management by the board affect product innovation




3.0. SECTION THREE: PARTICIPATIVE GOVERNANCE

This section assesses participative governance and also examines its perceived effect on


3.1. Assessment of Participative Governance

Please indicate by ticking (√) the extent to which these characteristics describe your co-

operative.

Tick your response in the appropriate answer box.

1 = Very Small Extent (VS)

2 = Small Extent (S)

3 = Moderate Extent

4 = Large Extent (L)

5 = Very Large Extent (VL)

3.1.

Assessment of Participative Governance

VS S M L VL

1 2 3 4 5

1. All members in the co-operative equal

voting rights

2. Members participate actively in the AGMs

3. Members receive timely information from

the board and management

325

3.2. Effect of Participative Governance on Revenue per Customer

Please indicate by ticking (√) the extent to which the perceived participative governance

in your co-operative has an effect on the revenue per customer (milk prices in the last

financial year) by using a scale of 1 to 5 in where:






3.2. Effect of Participative Governance on Revenue

per Customer

VS S M L VL

1 2 3 4 5

1. To what extent does having equal voting rights for

members affect revenue per customer in your co-

operative?

2. To what extent does active participation in the AGM

by members affect revenue per customer in your co-

operative?

3. To what extent does the receiving of timely

information by members from the board and

management affect revenue per customer in your co-

operative?

3.3. Effect of Participative Governance on Return on Assets (ROA)

First, complete the table below from the financial statements of the past year indicating

the ROA of your dairy co-operative measured by the Net Profit divided by Total Assets.


Total Assets

2015/2016

Please indicate by ticking (√) the extent to which the perceived participative governance

has an effect on the ROA of your dairy co-operative measured over the last financial year,

using a scale of 1-5:






326

3.3.

Effect of Participative Governance on ROA

VS S M L VL

1 2 3 4 5



2. To what extent does active participation in the AGM by


3. To what extent does the receiving of timely information

by members from the board and management affect ROA


3.4. Effect of Participative Governance on Product Innovation

Please indicate by ticking (√) the extent to which participative governance affects

innovation of new products such as: milk processing; provision of AI services, loaning of

cattle dip chemicals, provision of cattle loans, provision of cattle and other insurances,

provision of veterinary services, etc.






3.4. Effect of Participative Governance on Product

Innovation

VS S M L VL

1 2 3 4 5


members affect product innovation in your co-

operative?

2. To what extent does active participation in the AGM

by members affect product innovation in your co-

operative?

3. To what extent does the receiving of timely

information by members from the board and

management affect product innovation in your co-

operative?

327

4. SECTION FOUR: HUMAN CAPITAL

This section will assess the human capital and also examine its perceived effect on


4.1. Assessment of Human Capital

Please indicate the extent to which these characteristics describe your co-operative.

Tick your response in the appropriate answer box.



3 = Moderate Extent



4.1.

Assessment of Human Capital

VS S M L VL

1 2 3 4 5

1. Board members and senior management

staff have knowledge and skills for their

roles

2. Board members and senior management

staff have the experience for their roles

3. Both male and female are well represented

in the board

4.2. Effect of Human Capital on Revenue per Customer

Please indicate by ticking (√) the extent to which the perceived human capital in your co-

operative has an effect on the revenue per customer (milk prices in the last financial year)

by using a scale of 1 to 5 in where:






328

4.2 Effect of Human Capital on Revenue per Customer VS S M L VL

1 2 3 4 5

1 To what extent does having knowledge and skills for

their roles by board members and senior management

staff affect revenue per customer in your co-operative?

2 To what extent does having experience for their roles by

board members and senior management staff affect


3 To what extent does having both male and female

represented in the board affect revenue per customer in

your co-operative?

4.3. Effect of Human Capital on Return on Assets (ROA)

First, complete table below from the financial statements of the past year indicating the

ROA of your dairy co-operative measured by the Net Profit divided by Total Assets.


Total Assets

2015/2016

Please indicate by ticking (√) the extent to which the perceived human capital has an

effect on the ROA of your dairy co-operative measured over the last financial year, using

a scale of 1-5:






4.3.

Effect of Human Capital on ROA

VS S M L VL

1 2 3 4 5

1. To what extent does having knowledge and skills for

their roles by board members and senior management

staff affect ROA in your co-operative?

2. To what extent does having experience for their roles by

board members and senior management staff affect ROA


3. To what extent does having both male and female

represented in the board affect ROA in your co-

operative?

329

4.4. Effect of Human Capital on Product Innovation

Please indicate by ticking (√) the extent to which Human Capital affects innovation of

new products such as: milk processing; provision of AI services, loaning of cattle dip

chemicals, provision of cattle loans, provision of cattle and other insurances, provision of

veterinary services, etc.






4.4.

Effect of Human Capital on Product Innovation

VS S M L VL

1 2 3 4 5

1. To what extent does having knowledge and skills for

their roles by board members and senior

management staff affect product innovation in your

co-operative?

2. To what extent does having experience their roles by

board members and senior management staff affect


3. To what extent does having both male and female

represented in the board affect product innovation in

your co-operative?

5. SECTION FIVE: LONG-TERM ORIENTATION

This section will assess long-term orientation and also examine its perceived effect on


5.1. Assessment of Long-term Orientation

Please indicate the extent to which these characteristics describe your board. Tick your

response in the appropriate answer box.



3 = Moderate Extent



330

5.1.

Assessment of Long-term Orientation

VS S M L VL

1 2 3 4 5

1. Our co-operative invests for long-term profits

2. In our co-operative the management is encouraged

to take risks by the board

3. In our co-operative the board holds the

management accountable for performance

5.2. Effect of Long-term orientation on Revenue per Customer

Please indicate by ticking (√) the extent to which the perceived long-term orientation in

your co-operative has an effect on the Revenue per Customer (average milk price in the

last 5 years) by using a scale of 1 to 5 in where:






5.2. Effect of Long-term Orientation on Revenue per

Customer

VS S M L VL

1 2 3 4 5

1. To what extent does investing for long-term profits

affect revenue per customer in your co-operative?

2. To what extent does the board encouraging the

management to take risks affect revenue per


3. To what extent does the board holding the

management accountable for performance affect


331

5.3. Effect of Long-term Orientation on Return on Assets (ROA)

First, complete this table from the financial statements of the last five years indicating the

ROA of your dairy co-operative measured by the Net Profit divided by Total Assets for

five years from 2011-2015.


Total Assets

2011

2012

2013

2014

2015

Please indicate by ticking (√) the extent to which the perceived long-term orientation

affects the ROA of your dairy co-operative measured over the last five years from

2011-2015, using a scale of 1-5:






5.3.

Effect of Long-term Orientation on ROA

VS S M L VL

1 2 3 4 5

1. To what extent does investing for long-term profits affect



management to take risks affect ROA in your co-

operative?

3. To what extent does the board holding the management

accountable for performance affect ROA in your co-

operative?

332

5.4. Effect of Long-term Orientation on Product Innovation

Please indicate by ticking (√) the extent to which long-term orientation affects innovation

of new products such as: milk processing; provision of AI services, loaning of cattle dip








5.4. Effect of Long-term Orientation on Product

Innovation

VS S M L VL

1 2 3 4 5

1. To what extent does investing for long-term profits



management to take risks affect product innovation


3. To what extent does the board holding the

management accountable for performance affect


6. SECTION SIX: MARKET-ORIENTATION

6.1. Assessment of Market Orientation

Please indicate the extent to which these characteristics describe your board. Tick your

response in the appropriate answer box.

1 = Very Small Extent (VS); 2 = Small Extent (S); 3 = Moderate Extent; 4 = Large

Extent (L); 5 = Very Large Extent (VL).

6.1.

Assessment of Market Orientation

VS S M L VL

1 2 3 4 5

1. Generates market intelligence needed for

present and future needs

2. Disseminates market intelligence within

the co-operative

3. Responds to the market intelligence in

planning and distributing services and

products

333

6.2. Effect of Market Orientation on Revenue per Customer

Please indicate by ticking (√) the extent to which the perceived long-term orientation in

your co-operative has an effect on the revenue per customer (average milk price in the

last 5 years) by using a scale of 1 to 5 in where:






6.2. Effect of Market Orientation on Revenue per

Customer

VS S M L VL

1 2 3 4 5

1. To what extent does generating market intelligence

needed for present and future needs affect revenue


2. To what extent does disseminating market

intelligence within the co-operative affect revenue


3. To what extent does responding to market

intelligence affect revenue per customer in your co-

operative?

6.3. Effect of Market Orientation on Return on Assets (ROA)

First, complete table below from the financial statements of the past year indicating the

ROA of your dairy co-operative measured by the Net Profit divided by Total Assets.


Total Assets

2015/2016

Please indicate by ticking (√) the extent to which the market orientation has an effect on

the ROA of your dairy co-operative measured over the last financial year, using a scale of

1-5:






334

6.3.

Effect of Market Orientation on ROA

VS S M L VL

1 2 3 4 5


needed for present and future needs affect ROA in your

co-operative?

2. To what extent does disseminating market intelligence

within the co-operative affect ROA in your co-operative?

3. To what extent does responding to market intelligence


6.4. Effect of Market Orientation on Product Innovation

Please indicate by ticking (√) the extent to which Market Orientation affects innovation of

new products such as: milk processing; provision of AI services, loaning of cattle dip








6.4. Effect of Market Orientation on Product

Innovation

VS S M L VL

1 2 3 4 5


needed for present and future needs affect product


2. To what extent does disseminating market

intelligence within the co-operative affect product


3. To what extent does responding to market

intelligence affect product innovation in your co-

operative?

Thank you for taking the time to complete this questionnaire.

STAMP OF THE CO-OPERATIVE AND DATE OF COMPLETION

335

APPENDIX C: TARGET POPULATION – DAIRY CO-OPERATIVES IN MT.

KENYA REGION

Total

Number County

County

Number Name of Coop

1 Nyandarua 1 Churiri DFCS

2 Nyandarua 2 Bamboo Forest FCS

3 Nyandarua 3 Dairymen Sacco

4 Nyandarua 4 Gathanga DFCs

5 Nyandarua 5 GETA dairy Farmers Ltd

6 Nyandarua 6 Gikara dfc ltd

7 Nyandarua 7 Kahuho DFCS

8 Nyandarua 8 Karaba DFCS

9 Nyandarua 9 Karati DFC

10 Nyandarua 10 Kitiri Dairy & Investment

11 Nyandarua 11 Kwarahuka DFC

12 Nyandarua 12 Maina UMOJA FCS -processing

13 Nyandarua 13 Miharati DFCS

14 Nyandarua 14 Muki Dairies (KDL)-processing

15 Nyandarua 15 New Murungaru DFC

16 Nyandarua 16 Nandarasi FCS

17 Nyandarua 17 New Ngorika Milk Producers

18 Nyandarua 18 Ngarua DFCS

19 Nyandarua 19 Nineva Muti-ini

20 Nyandarua 20 Nyala Dairy Ltd-processing

21 Nyandarua 21 Njabini DFCS

22 Nyandarua 22 Olkalou Dairy Ltd

23 Nyandarua 23 Pesi DFCS

24 Nyandarua 24 South Kinangop (in Karangatha)

25 Nyandarua 25 Tulaga Dairy Farmers Cooperative

26 Nyandarua 26 Wanjohi DFCS

27 Nyeri 1 Bikira Dairy

28 Nyeri 2 Endarasha Farmers Cooperative Society

29 Nyeri 3 Gakindu Dairy Cooperative

30 Nyeri 4 Guthi Kieni

31 Nyeri 5 Gaturiri Dairy Fcs

32 Nyeri 6 Gichira Dairy cow

33 Nyeri 7 Ihururu DFCS

34 Nyeri 8 Island

35 Nyeri 9 Kiandu milk

36 Nyeri 10 Kieni Dairies

37 Nyeri 11 Lusoi

38 Nyeri 12 Maziwa bora- Karatina

39 Nyeri 13 Muiga Farmers Cooperative Society

40 Nyeri 14 Narumoro DFCS-Mungetho cooler

336

41 Nyeri 15 Ndama Njeru

42 Nyeri 16 New United Tetu

43 Nyeri 17 Ngukurani-(Naromoro) Mt Kenya

44 Nyeri 18 Othaya DFCS

45 Nyeri 19 Samaki Dairy Farmers

46 Nyeri 20 Shama Milk ltd

47 Nyeri 21 Slopes DFC-Karatina (MIK)

48 Nyeri 22 Wahora Dairy farmers

49 Nyeri 23 Wakulima DFCS -Mukurweini

50 Nyeri 24 Watuka Farmers Cooperative Society

51 Kiambu 1 Kiambaa

52 Kiambu 2 Ndumberi

53 Kiambu 3 Githunguri

54 Kiambu 4 Gatamaiyu

55 Kiambu 5 Gatundu

56 Kiambu 6 Limuru

57 Kiambu 7 Kabete

58 Kiambu 8 Bibirioni

59 Kiambu 9 Kikuyu

60 Kiambu 10 Kiriita

61 Kiambu 11 Kinare

62 Kiambu 12 Kamahia

63 Kiambu 13 Lari Dairies

64 Kiambu 14 Gikambura

65 Laikipia 1 Gatero Dairy Farmers

66 Laikipia 2 Gakwa

67 Laikipia 3 Irura FCS

68 Laikipia 4 Marmanet DFCS

69 Laikipia 5 Melwa DFCS-Gatundia

70 Laikipia 6 Muhotetu DFCS (Laikipia)

71 Laikipia 7 Ngarua FCS

72 Laikipia 8 Nturukima DFCS

73 Laikipia 9 Nyambugich DFCS

74 Laikipia 10 Oljabet DFCS

75 Laikipia 11 Pondo Park DFCS

76 Laikipia 12 Solio Umoja Coop Ltd

77 Laikipia 13 Suguroi DFCS

78 Laikipia 14 Sweet Waters

79 Laikipia 15 Tigithi Umoja DFCS

80 Laikipia 16 Winyitie DFCS

81 Embu 1 Gakundu Coop DFCS

82 Embu 2 Mukulima Bora DFCS

83 Embu 3 Mukulima Tujinjenge DFCS

84 Embu 4 Mutugi Commercial DFCS

337

85 Embu 5 Mburugu DFCS

86 Embu 6 Kirimiri DFCS

87 Embu 7 Tumaini DFCS

88 Embu 8 Ina Multi-Purpose DFCS

89 Embu 9 Rugendo DFCS

90 Tharaka Nithi 1 Chuka Ithamba Ng’ombe DFCS

91 Tharaka Nithi 2 CI Dairy

92 Tharaka Nithi 3 Cia Mbugi cia Ngoi FCS

93 Tharaka Nithi 4 Ethai DFCS

94 Tharaka Nithi 5 Hekima DFCS

95 Tharaka Nithi 6 Ithai

96 Tharaka Nithi 7 Kabuboni DFCS

97 Tharaka Nithi 8 Kamukondi DFCS

98 Tharaka Nithi 9 Maara DFCS

99 Tharaka Nithi 10 Mbunga Multi-Purpose DFCS

100 Tharaka Nithi 11 Mission DFCS-(Maara DFCS)

101 Tharaka Nithi 12 Muthiru dairy FCS

102 Tharaka Nithi 13 Mugumango DFCS

103 Tharaka Nithi 14 Munga Kiriani DFCS

104 Tharaka Nithi 15 Mwimbi-Chogoria DFCS

105 Tharaka Nithi 16 Mwiria DFCS

106 Tharaka Nithi 17 Ndunguri DFCS

107 Tharaka Nithi 18 Tharaka DFCS

108 Tharaka Nithi 19 Thunguri DFCS

109 Tharaka Nithi 20 Timac DFCS

110 Meru 1 Abogeta DFCS

111 Meru 2 Arithi

112 Meru 3 Buuri

113 Meru 4 Ciombiri

114 Meru 5 chiune DFCS

115 Meru 6 Chuuri DFCS

116 Meru 7 Ex-Lewa DFCS

117 Meru 8 Githongo DFCS

118 Meru 9 Igoki DFCS

119 Meru 10 Katheri DFCS

120 Meru 11 Kamakai

121 Meru 12 Kanyakine

122 Meru 13 Kiamitumi

123 Meru 14 Kibirichia DFCS

124 Meru 15 Kiburine

125 Meru 16 Kichoka DFCS

126 Meru 17 Kigaane DFCS

127 Meru 18 Kigane DFCS

128 Meru 19 Kigakia

338

129 Meru 20 Kiirua DFCS

130 Meru 21 Kithino DFCS

131 Meru 22 Kithithina

132 Meru 23 Kithirune DFCS

133 Meru 24 Kithoka

134 Meru 25 Kithunguri DFCS

135 Meru 26 KKK

136 Meru 27 Kuene DFCS

137 Meru 28 Machungulu

138 Meru 29 Magati

139 Meru 30 Mbaranga DFCS

140 Meru 31 Mboori DFCS

141 Meru 32 Mbwinjeru Arithi

142 Meru 33 Meru North

143 Meru 34 Mitune

144 Meru 35 Muiwa

145 Meru 36 Mt Kenya

146 Meru 37 Naari DFCS

147 Meru 38 Ngwataniro

148 Meru 39 Ng'onyi

149 Meru 40 Nkandone

150 Meru 41 Nkuene DFCS

151 Meru 42 Nyambene Arimi DFCS

152 Meru 43 Sirmon

153 Meru 44 South Imenti DFCS

154 Meru 45 Ukuu DFCS

155 Meru 46 Umoja

156 Meru 47 Uruku DFCS

157 Murang’a 1 Buguti

158 Murang’a 2 Central Aberdares

159 Murang’a 3 Highland

160 Murang’a 4 Gaichanjiru

161 Murang’a 5 Gakungu

162 Murang’a 6 Gatanga mwangaza

163 Murang’a 7 Gathaithi

164 Murang’a 8 Gathariki

165 Murang’a 9 Ichichi

166 Murang’a 10 Ithiru

167 Murang’a 11 Iyego

168 Murang’a 12 Kagaki

169 Murang’a 13 Kagata

170 Murang’a 14 Kagunduini Umoja

171 Murang’a 15 Kahumbu

172 Murang’a 16 Kahuro Livestock Breeders

339

173 Murang’a 17 Kamahuha

174 Murang’a 18 Kandara

175 Murang’a 19 Kiarutara

176 Murang’a 20 Kiarwaki

177 Murang’a 21 Kigika

178 Murang’a 22 Kigoro Dairy

179 Murang’a 23 Kigumo18

180 Murang’a 24 Kikama

181 Murang’a 25 Kikama

182 Murang’a 26 Kimorori Wempa

183 Murang’a 27 Makoboki

184 Murang’a 28 Mbiri Unity Investment

185 Murang’a 29 Muranga County Creameries Union

186 Murang’a 30 Muruka jubilee

187 Murang’a 31 Muthithi Dairy

188 Murang’a 32 New Murarandia

189 Murang’a 33 New Nginda

190 Murang’a 34 Ng'araria

191 Murang’a 35 Ruchu

192 Murang’a 36 Rugiki

193 Murang’a 37 Saba Saba Agribusiness

194 Murang’a 38 Uiguano wa muthithi

195 Murang’a 39 Umoja

196 Murang’a 40 Upper Kigumo

197 Murang’a 41 Wangu

198 Murang’a 42 Wanjengi Dairy value chain