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KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY
COLLEGE OF ARCHITECTURE AND PLANNING
DEPARTMENT OF BUILDING TECHNOLOGY
A GENERIC FRAMEWORK FOR CONSULTANCY PRICING: THE CASEOF
QUANTITY SURVEYING PRACTICE
A Master’s Thesis Submitted to the Department of Building Technology of the
Kwame Nkrumah University of Science and Technology in partial fulfillment of
the requirements for the award of a MASTER OF PHILOSOPHY (MPHIL)
degree in BUILDING TECHNOLOGY
Student
ADESI MICHAEL
BSc. (Hons.) Building Technology
SUPERVISOR
Dr. De-Graft Owusu-Manu
SEPTEMBER, 2013
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KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY
COLLEGE OF ARCHITECTURE AND PLANNING
DEPARTMENT OF BUILDING TECHNOLOGY
A GENERIC FRAMEWORK FOR CONSULTANCY PRICING: THE CASEOF
QUANTITY SURVEYING PRACTICE
A Master’s Thesis Submitted to the Department of Building Technology of the
Kwame Nkrumah University of Science and Technology in partial fulfillment of
the requirements for the award of a MASTER OF PHILOSOPHY (MPHIL)
degree in BUILDING TECHNOLOGY
ADESI MICHAEL
BSc. (Hons.) Building Technology
SUPERVISOR
Dr. De-Graft Owusu-Manu
SEPTEMBER, 2013
3
DECLARATION
I declare that I wholly undertook this research under supervision and where other scholarly
works have been used were duly acknowledged as such.
………………………………………. Date……………………………….
ADESI, MICHAEL (STUDENT)
I declare that I have supervised the student in undertaking the research reported herein and I
confirm that the student has effected all corrections suggested.
………………………………………. Date…………………………………
DR. DE-GRAFT OWUSU-MANU (SUPERVISOR)
……………………………………. Date…………………………………
PROF JOSHUA AYARKWA (HOD, Department of Building Technology)
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ABSTRACT
The consultancy industry provides services to clients in diverse sectors of economies globally to
the extent that their roles in the developmental agenda of nations and corporate institutions
cannot be underestimated. One of the key areas of consultancy services provision in the
construction industry is quantity surveying practice. Over the years, quantity surveyors have
provided services to clients in the construction industry at a consideration of a pricing (fees).
However, these prices determined by quantity surveying consultants were not sustainable enough
to ensure continual existence in business. The aim of this research was to explore quantity
surveying practice in Ghana; and to develop a generic framework for gauging quantity surveying
professional services consultancy services. An extensive literature review was conducted on the
consultancy industry; and quantity surveying practice. Similarly, framework on key pricing
concepts was adopted culminating into the postulation of twelve (12) key pricing hypotheses.
Philosophically, the study leaned towards the positivism paradigm culminating into the adoption
of quantitative methods in which survey questionnaires were administered to respondents
yielding a response rate of 72 per cent. The analytical tools utilized in data analysis include chi
square test of independence; factor analysis; and descriptive analysis. Adopting a wide range of
independent variables categorized mainly as risks, taxation and inflation; value, price catalysts,
cost(service cost) management and business management, the study found the dependent
variable (price robustness and level) to be significantly dependent on the independent variables.
The key findings led to the development of a generic framework for pricing quantity surveying
consultancy services.
Keywords: Quantity, surveying, generic, pricing, consultancy, services.
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ACKNOWLEDGEMENTS
I am most indebted to the Almighty God for giving me the clarity and soundness of mind and
good health generally over the period of conducting this research. I highly acknowledge the
protection of the Almighty God on two key separate occasions and would forever remain grateful
to HIM. I am very much thankful to my supervisor without who this research. I am very thankful
to my supervisor, Dr. De-graft Owusu-Manu for supporting me academically, morally and
financially. His mentorship style is enviable and unassailable; he is a father, a friend and a
brother in all respect without which this work would not have existed. I am also grateful to Dr.
Eric Oduro-Ofori of the Department of Planning of KNUST for his support. Professor Edward
Badu, the Provost of the College of Architecture and Planning of KNUST is highly
acknowledged for all his inputs over the period.
I am grateful to Mr Elias Megbetor, Emmanuel Kwami and many others not forgetting my
friends Ernest Kisi, Federick Amoako Sarpong, Meshack Quaye Dadzie and Korley Akutteh
Ebenezer ( my mates) for their support over the course of conducting this research.
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TABLE OF CONTENTS
DECLARATION ...................................................................................................................................... 3
ABSTRACT .............................................................................................................................................. 4
ACKNOWLEDGEMENTS .................................................................................................................... 5
CHAPTER ONE ................................................................................................................................... 13
1.0 INTRODUCTION TO THE RESEARCH ................................................................................... 13
1.1 BACKGROUND OF THE STUDY .............................................................................................. 13
1.2 STATEMENT OF THE PROBLEM ............................................................................................. 15
1.3 AIM AND OBJECTIVES OF THE RESEARCH ....................................................................... 17
1.3.1 AIM ................................................................................................................................................. 17
1.3.2 OBJECTIVES ............................................................................................................................... 18
1.4 JUSTIFICATION/ RELEVANCE OF THE RESEARCH ........................................................ 18
1.5 SCOPE OF THE RESEARCH ....................................................................................................... 20
1.6 RESEARCH METHODOLOGY ................................................................................................... 21
1.7 LIMITATIONS OF THE RESEARCH ........................................................................................ 23
1.8 ORGANIZATION OF THE RESEARCH ................................................................................... 23
CHAPTER TWO .................................................................................................................................. 26
THEORETICAL FRAMEWORK ....................................................................................................... 26
2.0 INTRODUCTION ........................................................................................................................... 26
2.1 Concept of Price and Value ............................................................................................................ 26
2.2 The Just Price .................................................................................................................................... 27
2.3 Importance, Objectives and Goals of Pricing ............................................................................... 28
2.4 Pricing Strategies ............................................................................................................................. 29
2.4 Project Pricing .................................................................................................................................. 30
2.5 Bid Pricing ........................................................................................................................................ 32
2.6 Production and Pricing .................................................................................................................... 33
2.7 The Concept of Risk ........................................................................................................................ 37
2.7.1 Risk and Price ................................................................................................................................ 38
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2.7.2 Types of Risk ................................................................................................................................. 40
2.7.3 Risks at Various Stages of Project Implementation ................................................................. 42
2.8 Concept of Taxation......................................................................................................................... 44
2.8.1 Taxation of consultancy services ................................................................................................ 45
2.8.2 Tax System in Ghana ................................................................................................................... 45
2.8.3 General Provisions under the Tax Law ...................................................................................... 46
2.8.4 Income and Profit Tax Legislation ............................................................................................. 46
2.8.5 The Implementation of VAT ....................................................................................................... 47
2.9. Concept of Inflation ........................................................................................................................ 48
2.9.1 Causes of Inflation ........................................................................................................................ 49
2.9.2 Economic Indicators of Inflation ................................................................................................ 49
2.9.3 Nominal and Real Prices .............................................................................................................. 50
CHAPTER THREE ............................................................................................................................. 52
THE CONSULTANCY INDUSTRY: A GENERAL OVERVIEW ............................................... 52
3.0 INTRODUCTION ........................................................................................................................... 52
3.1 CONCEPTUAL EXPLANATION OF CONSULTANCY ........................................................ 53
3.2 TOWARDS THE SEGMENTATION OF THE CONSULTANCY INDUSTRY ................. 55
3.2.1 THE SCOPE OF CONSULTING SERVICES ......................................................................... 56
3.3 CRITICALLY EXAMINING CONSULTANCY CONTRACTS ............................................ 58
3.4 CRTITICAL REASONS: TOWARDS AN EFFECTIVE CONSULTING ............................. 61
3.5 EXPLORING THE FUNCTIONS OF CONSULTING ............................................................. 64
3.6 EFFECTIVE CONSULTING: THE ROLE OF CONSULTANTS .......................................... 65
3.7 CLIENTS - CONSULTANTS RELATIONSHIP ....................................................................... 66
3.8 THE CONSULTANCY INDUSTRY: ITS CRITICISMS ......................................................... 69
3.8.1 ARGUMENTS SUPPORTING CONSULTANCY PRACTICE .......................................... 71
3.9 THE SELECTION OF AN EFFECTIVE CONSULTANCY FIRM ........................................ 72
3.10 CRITICAL FACTORS FOR SUCCESSFUL CONSULTING ............................................... 73
3.11 FACTORS RESPONSIBLE FOR CONSULTANCY FAILURES ........................................ 76
3.12 TERMS OF REFERENCE: THE BASIS OF AN EFFECTIVE CONSULTANCY ........... 77
3.13 THE ART OF PRICING CONSULTANCY SERVICES ........................................................ 79
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3.14 APPRAISAL AND SYNTHESIS OF THE LITERATURE REVIEW ................................. 82
CHAPTER FOUR ................................................................................................................................ 88
QUANTITY SURVEYING PRACTICE IN CONTEMPORARY GLOBAL............................... 88
4.0 INTRODUCTION ........................................................................................................................... 88
4.1 THE MEANING OF QUANTITY SURVEYING (QS) ............................................................ 89
4.2 THE ROLE OF THE QUANTITY SURVEYOR ....................................................................... 90
4.2.1 The Changing Roles of the Quantity Surveyor ......................................................................... 91
4.3 QUANTITY SURVEYING CONSULTANCY SERVICES..................................................... 92
4.3.1 NON-TRADITIONAL QUANTITY SURVEYING CONSULTANCY SERVICES ........ 96
4.4 QUANTITY SURVEYING CONSULTANCY SERVICES PRICING/FEES ....................... 97
4.4.1 CHALLENGES OF QUANTITY SURVEYING SERVICES PRICING/FEES ................. 99
4.5 CHALLENGES CONFRONTING QUANTITY SURVEYING PRACTICE ...................... 100
4.6 PROFESSIONAL MISCOUNDUCT IN QUANTITY SURVEYING PRACTICE ............ 101
4.7 ADOPTION OF ICT IN QUANTITY SURVEYING OPERATIONS .................................. 102
4.8 EXPLORING THE BILLS OF QUANTITIES (BOQ) IN QS PRACTICE .......................... 103
4.8.1 The Emergence of the BOQ ...................................................................................................... 103
4.8.2 The Definition of Bills of Quantities ........................................................................................ 104
4.8.3 Uses of the Bills of Quantities .................................................................................................. 105
4.8.4 Challenges Confronting BOQ Usage ....................................................................................... 106
4.8.5 The Relevance of BOQ in Modern Construction Industry .................................................... 106
4.9 AN EXPOSITION OF QUANTITY SURVEYING PRACTICE IN GHANA .................... 107
4.10 APPRAISAL AND SYNTHESIS OF THE LITERATURE REVIEW ............................... 109
CHAPTER FIVE ................................................................................................................................ 112
RESEARCH METHODOLOGY ....................................................................................................... 112
5.0 INTRODUCTION ......................................................................................................................... 112
5.1 PHILOSOPHICAL TRADITIONS AND CONSIDERATIONS ............................................ 112
5.1.1 METHOD OF SCIENTIFIC INQUIRY AND REASON ..................................................... 114
5.2 RESEARCH STRATEGY AND DESIGN ................................................................................ 115
5.2.1 Quantitative Research Paradigm ............................................................................................... 115
5.2.1.1 Objectivism and Realism ........................................................................................................ 116
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5.2.1.2 The Survey Process ................................................................................................................. 119
5.2.1.2 .1 Research Scope and Boundaries ....................................................................................... 120
5.2.1.2 .2 Sampling Techniques and Sample Frame ........................................................................ 121
5.2.1.2 .2 .1 Sampling Technique Adopted ....................................................................................... 123
5.2.1.2.3 Data Collection Methods ..................................................................................................... 124
5.3 DATA ANALYSIS METHODS.................................................................................................. 131
5.3.1 Descriptive Analysis ................................................................................................................... 131
5.3.2 Data Presentation Using Tables ................................................................................................ 131
5.3.3. Relative Importance Index (RII) .............................................................................................. 133
5.3.4 Inferential Analysis: Hypothesis Testing .............................................................................. 135
5.3.4.1 Steps for Hypothesis Testing ................................................................................................. 137
5.3.4.2 Approaches/Criteria to Hypothesis Testing ......................................................................... 139
5.3.4.3 Interpretation of Hypothesis Test Result .............................................................................. 140
5.3.4.4 Some Key Statistical Tools for Hypothesis testing ............................................................. 141
5.3.4.4.1 ANOVA ................................................................................................................................. 141
5.3.4.4.2 Correlation ............................................................................................................................. 141
5.3.4.4.3 Regression ............................................................................................................................. 141
5.3.4.5 Adoption of Chi Square Test for Hypotheses Testing ........................................................ 142
5.3.4.6 Framework Development: Utilizing Factor Analysis ......................................................... 145
5.3.4.6.1 Interpretation of Results Produced by Factor Analysis ................................................... 147
5.4 Summary of the Research Process ............................................................................................... 148
CHAPTER SIX....…………………………………………………………………………….153
ANALYSIS OF DATA AND DISCUSSION OF RESULTS ........................................................ 150
6.0 INTRODUCTION ......................................................................................................................... 150
6.1 DESCRIPTIVE ANALYSIS ........................................................................................................ 151
6.1.1 Respondents Profile .................................................................................................................... 151
6.1.2 Legal Status of Respondent’s firms .......................................................................................... 151
6.1.4 Rate of Work Acquisition .......................................................................................................... 153
6.1.5 Sectors of Operation ................................................................................................................... 153
6.2 RANKING OF KEY PRICING VARIABLES .......................................................................... 156
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6.2.1 Concept of Price and Value ....................................................................................................... 157
6.2.2 Project Pricing (Consultancy Pricing) ...................................................................................... 161
6.2.3 Concept of Risk ........................................................................................................................... 162
6.2.4 Concept of Taxation and Inflation ............................................................................................ 164
6.2.5 Quantity Surveying Consultancy Services Pricing Components ......................................... 166
6.2.6 Challenges confronting quantity surveying consultancy practice ........................................ 167
6.2.7 Quantity surveying consultancy services (Seeley, 1997; Olatunde, 2006) ......................... 169
6.3 INFERENTIAL ANALYSIS: HYPOTHESES TESTING ...................................................... 171
6.3.1 Price and Value Hypotheses ...................................................................................................... 172
6.4 FACTOR ANALYSIS................................................................................................................... 186
6.4.1 Concept of Price and Value (Variables) .................................................................................. 186
6.4.1.2 Components Extracted ............................................................................................................ 190
6.4.2 Project Pricing (Consultancy Pricing) ...................................................................................... 191
6.4.2.1 Initial Considerations .............................................................................................................. 191
6.4.2.2 Components Extracted ............................................................................................................ 194
6.4.3 Concept of risk ............................................................................................................................ 195
6.4.3.1 Initial Considerations .............................................................................................................. 195
6.4.3.2 Components Extracted ............................................................................................................ 198
6.4.4 Concept of taxation and inflation.............................................................................................. 199
6.4.4.1 Initial Consideration ................................................................................................................ 199
6.4.4.2 Components Extracted ............................................................................................................ 202
6.4.5 Quantity surveying consultancy services pricing components ............................................. 202
6.4.5.1 Initial Consideration ................................................................................................................ 203
6.4.5.2 Components Extracted ............................................................................................................ 205
6.4.6 Challenges Confronting QS Consultancy Practice ................................................................. 206
6.4.6.1 Initial Consideration ................................................................................................................ 207
6.4.6.2 Components Extracted ............................................................................................................ 209
6.5 DISCUSSION AND INTERPRETATION OF RESULTS...................................................... 210
6.5.1 Concept of price and value ........................................................................................................ 211
6.5.1.1 Component 1: Pricing strategies ............................................................................................ 211
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6.5.1.2 Component 2: Just Pricing ..................................................................................................... 212
6.5.1.3 Component 3: Pricing Roles .................................................................................................. 214
6.5.1.4 Component 4: Social influence .............................................................................................. 216
6.5.1.5 Component 5: Value................................................................................................................ 216
6.5.2 Project Pricing (Consultancy Pricing) ...................................................................................... 217
6.5.2.1 Component 1: Business management ................................................................................... 217
6.5.2.2 Component 2: Service cost management ............................................................................. 218
6.5.2.3 Component 3: Technical and financial capabilities ............................................................ 220
6.5.3 Concept of Risk ........................................................................................................................... 220
6.5.3.1 Component 1: Corporate internal risk................................................................................... 220
6.5.3.2 Component 2: Corporate external risk .................................................................................. 221
6.5.3.3 Component 3: Location Risk ................................................................................................. 222
6.5.4 Concept of Taxation and Inflation ............................................................................................ 223
6.5.4.1 Component 1: Taxes................................................................................................................ 223
6.5.4.2 Components 2 and 3: Price catalysts ..................................................................................... 224
6.5.5 Quantity Surveying Consultancy Services Pricing Components ......................................... 226
6.5.5.1 Component 1: Office Management ....................................................................................... 226
6.5.5.2 Component 2: Overheads ....................................................................................................... 226
6.5.5.3 Component 3: Administration and Training ........................................................................ 227
6.5.5.4 Component 4: Reimbursement and Payments ..................................................................... 228
6.5.6 Challenges confronting Quantity Surveying Consultancy Practice ..................................... 229
6.5.6.1 Component 1: Contractual and technology challenges ...................................................... 229
6.5.6.2 Component 2: Pricing Challenges ......................................................................................... 230
6.5.6.3 Component 3: Market forces .................................................................................................. 230
6.5.6.4 Component 4: Professional fees ............................................................................................ 231
A Generic Framework for Pricing QS Consultancy Services ......................................................... 231
CHAPTER SEVEN ............................................................................................................................ 233
CONCLUSION AND RECOMMENDATIONS ............................................................................. 233
7.1 INTRODUCTION ......................................................................................................................... 233
7.2 REVIEW OF RESEARCH OBJECTIVES ................................................................................ 233
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7.3 FINDINGS ...................................................................................................................................... 238
7.3.1 Special Relationships Identified ............................................................................................... 239
7.4 CONTRIBUTION TO KNOWLEDGE ...................................................................................... 240
7.5 RECOMMENDATIONS FOR PRACTITIONERS .................................................................. 242
7.6 FUTURE RESEARCH AGENDA .............................................................................................. 243
7.7 CONCLUSIONS ............................................................................................................................ 244
REFERENCES.………………………………………………………………………………248
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CHAPTER ONE
1.0 INTRODUCTION TO THE RESEARCH
This chapter presents an overview of the thesis which highlights the research in terms of the
background of the study and the statement of the research problem. The aim and objectives of
the study were also espoused and this is subsequently followed by the justification of the
research, methodology to be adopted, limitations of the research and finally the organization of
the research.
1.1 BACKGROUND OF THE STUDY
The contribution of the construction industry to sustainable economic growth and development
of a nation is very significant (Musa et al., 2010, Ogunsemi, 2006, Moavenzadeh and Rossow,
1976). Apart from the fact that the construction industry plays a major contribution to Gross
Domestic Product (GDP) and employment creation (Danso et al., 2011), it also provides the
basic infrastructure needed to accommodate the inputs of all other sectors of the economy
(Danso et al., 2011, Oforeh, 2006, Babalola, 2006). Clearly, the activities of the construction
industry, particularly, the execution of construction projects and the implementation of
infrastructural development projects require the services of built environment professionals
(BEP) as well as engineering professionals mainly; Quantity Surveyors(QS), Architects,
Planners, Valuers, Project Managers, Construction Managers, Engineers, Facility Managers and
Builders (Musa et al., 2010). According to Musa et al., 2010 and Oladapo, 2006, these
professionals are traditionally responsible for pre-contract planning services (i.e. project design,
production of tender and contract documents and selection of suitable contractor etc), contract
planning services (including project supervision and management, claims management, etc) and
14
post-contract planning services (including project closure, commission, maintenance and facility
management).
Within the remits of these professional practices and services, Quantity Surveying Practice
(QSP) plays a critical role in planning, managing and controlling project cost, and the QS is
instrumental in relating and relaying project cost information to the client and other project
parties including contractors and other professionals (Adebola, 2006). Right from conception,
through the design and construction stages and indeed throughout the life of the project, the
consultants and other stakeholders rely strongly on reliable cost information from the QS in order
to discharge their contractual and technical obligations in a professional and objective manner
(Musa et al., 2010).
In spite of the tremendous role that the QS plays on the project team to ensure successful
delivery of projects within budget, the remuneration compensated to the QS stands accused of
not being able to commensurate the efforts and services rendered by the QS compared to the
other project professionals such as the architects and/ engineers (Oladapo, 2006 ). When looking
at other professionals, the architects’ fees increased with 16.9 % ( average over the different
categories) and civil/structural engineers have increased since 1992 by 13.7% ( average over the
different categories) (ASAQS, 2002 and Cruywagen & Snyman, 2005). This deficiency is as a
result of the apparent lack of homogeneity in the pricing of QS services and the lack of
transparency in the traditional process used in gauging consultancy fees of project professionals,
particularly, the QS (Grosskrurth, 2008). In attempt to address such deficiencies, a study
15
designed to develop a generic framework to aid in the pricing of QS services is timely and
necessary (Commonwealth of Australia, 2008 and ESCAP, 2008).
1.2 STATEMENT OF THE PROBLEM
At the turn of the 21st century, globalization has necessitated many construction firms and
practicing consultants (professionals) to position themselves in the wake of competitive business
environment (Anago, 2006 and Meyer, 2009 ). This global-wake of competition has prompted
the quantity surveying professionals (QSP) to offer competitive professional pricing to their
clients without losing sight of market forces (McGaw, 2007 and Cruywagen & Snyman, 2005).
That is, the pricing should be set within the purview of perceived risk factors to avoid the
obvious tendency of overpricing ( which would cause rejection of bids) and under-pricing
syndrome (which would affect profitability and future survival) ( McGaw, 2007, Cruywagen &
Snyman, 2005).
A recent empirical study by Adendorff et al. (2012) strongly highlighted the pricing challenges
confronting built environment consultant for that matter quantity surveyors that consultants in
the built environment are not remunerated for the actual services rendered to clients; there is
inadequate remuneration for consultants in the built environment; developers and employers
using the services of consultants of which the QS is inclusive in the built environment for no
price paid (Chinyiou, 2011); Clark (2012) observed that clients use the services rendered by built
environment consultants to their benefits and do not offer payment for the price of their services.
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Traditionally, Quantity Surveyors and other professionals have depended on the recommended
range of professional fees published by the various professional and regulating bodies such
Ghana Institution of Surveyors (Awal, 2010). Many authors have frequently accused the
published professional fees rates of inability to achieve value (Cruywagen and Snyman, 2005).
Despite the perceived easy way of accessing and utilizing such published professional fees rates
(PPFR), the PPFR stands accused of being outdated, as in many instances those in charge are
unable to update the rates frequently (McGaw, 2007, Cartlidge, 2009 and SACQSP, 2010).
Sadly, professionals who do not depend on the PPFR fix their professional rates arbitrarily
without any basis, and the tendency of over-pricing and under-pricing poses potential threats.
Within the developed world economy, significant researches have been enunciated, and recent
reports have revealed evidences in technology-based advancements and computerized pricing
models(softwares) of gauging consultancy services( Musa et al., 2010 and Oladapo, 2006).
Conversely, in developing countries, a potential lack of apposite and reliable quantity surveying
consultancy pricing frameworks continue to present challenges to practicing consultants. To
remedy this situation, and the need to lessen operational risk, pricing risk and financial risk
associated with professional (consulting) practice has sparked the interest of many academics,
policy-makers as well as practitioners the world over to explore alternative pricing frameworks
to aid consultants in gauging professional fees rate (Nagy et al., 2006 ). There is strong evidence
that suggests there is no scientific process or method for the pricing of consultancy services
(Amstrong & Green, 2011). It is also believed that the current practice of professional bodies
setting the fee (pricing) levels arbitrarily has led to the underpricing or over pricing of
consultancy services (Department of Finance, 2011). Consultancy firms for that matter QS firms
17
have been rendered bankrupt as a result of this practice by the setting of arbitrary fees in which
professional members do not have much input (McGaw, 2007). In a free market economy where
demand and supply determine price levels, it is incumbent that consultancy service providers be
given the needed opportunity to set their own price with their clients (Porter, 2008). This will
reflect the appropriate equilibrium or convergent of demand and supply (Smith, 2000).
Ofori (2012) in a comprehensive study on the development of the construction industry in Ghana
identified multifarious problems confronting consultants which include low level of fees, which
thwarts the development of their technical support system; and insufficient operating cash flow.
It is clear from the work of Ofori (2012) that the price (fees) that consultants for that matter QS
consultants receive in Ghana are not sufficient to keep them in business as indicated clearly by
the study that consultants for that matter quantity surveyors are experiencing problems with
operating cash flow. Unfortunately, the study conducted by Ofori (2012) does not suggest
modalities for improving the pricing of consultancy services provided in the construction
industry. It is important to investigate the dynamics of consultancy services pricing which is a
vehicle for revenue generation for consulting businesses in Ghana. It will therefore be noble and
innovative to develop a generic framework for pricing quantity surveying consultancy services.
1.3 AIM AND OBJECTIVES OF THE RESEARCH
1.3.1 AIM
The main aim of this research is to explore Quantity Surveying (QS) consultancy practice in
Ghana, and to develop a generic framework for gauging QS professional consulting services
pricing in Ghana.
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1.3.2 OBJECTIVES
In an attempt to achieve the above stated aim, the following specific objectives are set:
To conduct a realistic review of quantity surveying and general consultancy practice
including the rudiments of pricing;
To explore the underlying potential challenges confronting Quantity Surveying (QS)
consultancy pricing;
To identify the key determinants (indicators) in pricing QS consultancy service practice;
To establish the relationship between the key indicators of QS consultancy service
pricing; and
To develop a qualitative generic framework (criteria) for pricing QS consultancy service
practice based on identified indicators.
1.4 JUSTIFICATION/ RELEVANCE OF THE RESEARCH
It is of no stretch of imagination that a well-developed and robust generic framework would
inure to the benefit of consultancy practitioners particularly those in the built environment (BE)
(Helmlinger, 2005 and Liang, 2008). This research has the capacity of playing several roles in
the operations of several organizations throughout the world and for that matter Ghana. Hence
there is enough justification for engaging in a research of this nature. This justification can be
viewed in the quantity surveying practice as an opportunity to receive better reward for services
rendered and prices that commensurate the services rendered by quantity surveying (QS)
professionals. On a typical project initiated by a client, the architect renders services such as
preliminary design, detailed design and costing, drawings and specifications; the quantity
surveyor (QS) renders services such as feasibility study, detailed design and costing, tender
19
process and contract award, bills of quantities (BOQ), budget, contracts, planning, personnel
control, materials control and equipment control and the engineer renders services such as
detailed design and costing, tender process and contract award, bills of quantity (BOQ), contracts
and planning (Murray et al., 2001).
From the revelations of Murray et al. (2001), it can be seen that the services rendered by the key
consultants viz: the architect, the quantity surveyor (QS) and the engineer; the quantity surveyor
(QS) provides ten (10) services toward the successful implementation of the project; the architect
provides four (4) services and the engineer provides seven (7) services to the client. In some
instances, quantity surveyors (QS) manage the tender and documentation processes as well as
contract administration of engineered projects which are seen as the preserve of engineers. A
typical example is the road sector project implementation in Ghana where the QS manage all the
contract administration aspect of road projects at the Ghana Highways Authority and the
Department of Feeder roads in Ghana. In the light of the above exposition, it can be realized that
the pricing of services rendered by consultants will put the quantity surveying (QS) practitioners
in a better position and subsequently place the profession high on a pedestal among other
consultants in the built environment.
The development and acceptance of a generic framework for pricing in quantity surveying
practice will ensure the survivability of the quantity surveying consultancy practice in Ghana.
This is because professionals will not underprice to make loses leading to bankruptcy and over
price to lose customers/ clients. Similarly, a generic framework for pricing will inure to the
benefit of the client as they will pay consultants for services rendered towards the successful
20
implementation of the project and subsequently know the actual cost that will be incurred on
consultancy services. Consultancy cost is one of the factors that scare potential clients from
approaching the consultancy desk as a result of their lack of insight into consultancy costs for
that matter price but a well-developed and robust pricing framework for quantity surveying
consultancy pricing will be a panacea to this canker bedeviling the QS profession.
Furthermore, there is enough justification for a research of this nature as the government and
MDAs are concerned, as this framework will aid them in the planning of infrastructural projects,
estimation of the actual contribution of quantity surveying practice as a construction sub-sector
to GDP. A generic framework will aid tax authorities such as the Ghana Revenue Authority in
the determination of the tax obligations of consultants. This is because the framework will help
them to identify the services rendered on a particular project and subsequently, the pricing model
will help them to determine the quantum of income consultants receive for taxation purposes.
Finally, the justification for this research as far as the academia is concerned lies in the fact that
the literature review will serve as a knowledge gathering exercise on consultancy services and
pricing which are scattered in different writings in to one solid body for the development of the
consultancy industry especially quantity surveying practice which will enhance teaching and
learning as far as lecturers and students are concerned in universities and polytechnics.
1.5 SCOPE OF THE RESEARCH
The research study captured majority of services rendered by quantity consultancy practitioners
for the appropriate pricing of services (CIDB, 2005, Economic Commission for Africa, 2001 and
Jaatmaa, 2010). In particular, this research will focus on the pricing of quantity surveying
21
consultancy services (QSCS). The QS practitioners form a very crucial part, and play crucial
roles in the delivery of construction projects hence the focus on the QS practitioners is of much
vitality. Geographically and contextually, this research study would focus on registered quantity
surveying practitioners operating in Accra, the capital city of the Republic of Ghana. The
concentration of the study in Accra emanates from the fact that construction activities are highly
skewed towards Accra (c.f. Ahadzie, 2007). Similarly, there are forty-five (45) QS firms
representing 86.5 per cent of QS firms located in Accra out of a nationwide numerical strength of
52 QS firms (see for instance GhIS, 2012, 43rd Annual General Meeting report).
1.6 RESEARCH METHODOLOGY
In order to conduct a thorough and a robust research, the aim and objectives of the research was
addressed by adopting the appropriate epistemological and positivist philosophies which led to
the adoption of the quantitative approach to aid the collection of appropriate data and
subsequently the analysis and interpretation of the findings. An extensive and elaborate literature
review was conducted to identify the existing body of knowledge within the purview and remit
of the research to expand and reinforce a thorough understanding of the current pricing milieu as
well as the quantity surveying practice environment. The theoretical framework concentrated on
the theory of pricing and the various factors that affect pricing and formulation of hypothesis in
which the dependent variable(DV) was mainly pricing levels and the independent variables(ID)
were the various factors that affect pricing levels consisting of: value of a product or service,
affordability, the government, media action, pressure group, seller’s profit, customer’s intrinsic
value, customer’s affordability, objectivity, failure, success, image, pricing strategies, cost,
profit, demand, competition, time taken to solve the problem, materials used on the project, good
22
financial control system, record of past project costs, accurate forecast of future cost, production
of timely reports, finance, technical, experience, duration, capacity, reputation, business
development, materials, labour/support staff, capital/plant, entrepreneurial and managerial
talent/consultancy, associated business risks, financial risks, market related risks, logistical and
infrastructure risks, managerial and operational risks, technological risks, organizational and
societal risks, legal risks, regulatory risks, political risks, force majeure risks, personal income
tax, VAT/NHIL, corporate tax, profit tax, local rates, property tax, input prices, inflation,
production shortfall, effects of input market, government policies, international trade and trade
barriers.
The quantitative approach was used to collect data from the quantity surveying (QS)
practitioners in Ghana. In this vein, structured survey questionnaire was the main instrument
used. The research philosophies adopted enable statistical tools such as factor analysis, chi-
square test and relative importance index to be used in the analysis, interpretation of data and
discussion of results culminating into the development of an empirical framework for gauging
QS consultancy services pricing. The aim of factor analysis is to reveal any latent variables that
cause manifest variables to covary (Costello and Osborne, 2005), and factor analysis is a
collection of methods used to examine how underlying constructs influence the responses on a
number of measured variables (DeCoster, 1998). The relative importance index (RII) is used to
rank identified factors according to their place value or influences on the delivery of projects.
This is to identify the significance of the identified factors or variables via RII to the
development of a generic framework for QS consultancy services pricing.
23
1.7 LIMITATIONS OF THE RESEARCH
This research has its own limitations just like any other research in its conduct. It is envisaged
that the limitations of this research will be:
The effect of sampling and measurement errors which might affect the collection of data
and the kind of analysis to be carried out and the conclusions drawn;
Only published literature will be used in the analysis and review of literature; and
The analysis and conclusions of this research were based on data collected from
respondents by using questionnaire.
1.8 ORGANIZATION OF THE RESEARCH
This research has been divided into seven (7) independent interrelated chapters. Chapter one
contains the general introduction and background to the research. The problem has been
presented and the research justified. The research aim and its specific objectives, the scope and
limitations were also included. Chapter two dealt with theoretical framework which led to the
construction of cogent hypotheses for the research. The chapter consists of an elaborate review
of various pricing theories spanning over some applicable fields such as economics, marketing
and accounting. The independent variables(ID) used for the development of the theoretical
framework include: value, affordability, pricing strategies, profit, cost, materials, time taken to
solve problem, risk, taxation environment, overheads, inflation and input prices. The literature
review will be covered in chapters three which will consist of general overview of the
consultancy business, models for pricing professional consultancy practice and chapter four will
revolve round general overview of quantity surveying practice including its history and various
stages of development, services rendered, key determinants (indicators) in pricing Quantity
24
Surveying (QS) consultancy practice and the challenges confronting Quantity Surveying (QS)
consultancy in Ghana.
Chapter five consisted of the methodology adopted for the research viz: research philosophy,
sample population, sample size determination, sampling technique questionnaire design and
administration and statistical tools. Philosophically, the position of the research ontologically
will be that of objectivism. It is clear that the core issues that significantly affect the pricing of
consultancy services are real and not the inventions of the researcher. Chapter six consist of
analysis and discussion of results, and chapter seven will be devoted to Generic Framework
which will consist of model (pricing formula) development for gauging QS consultancy service
in Ghana. Chapter seven dwelt on conclusion and recommendations, which will consist of
review of research objectives among others. The simplified version of the conceptual framework
of the research process for the study is demonstrated in figure 1.1 below.
25
Figure 1.1: Conceptual Framework of the ResearchOrganization
Chapter
One
General Introduction
Background, Problem Statement,
Aim, Objectives, Justification,
Scope, Methodology, Limitation.
Chapter
Two
Theoretical Framework Concept of Pricing and Production, Risk,
Taxation, Inflation etc.
Hypothesis Formulation
Chapter
Three
General Overview of Consultancy
Business Types of Consultancy Business,
Consultancy Services, Pricing
Methods
Chapter
Four
General Overview of QS Practice
History and Development of QS
Profession, Professional Bodies,
Services Rendered, Pricing Methods
and key Indicators
Chapter
Five
Research Methodology Research Philosophy, Sampling
Frame, Instrument Design and
Administration, Tools for Statistical
Analysis
Chapter
Six
Analysis and Discussion of Results
Development of generic pricing
framework
Chapter
Seven
Conclusion and Recommendation Review of Objectives, Findings,
Further Research.
26
CHAPTER TWO
THEORETICAL FRAMEWORK
2.0 INTRODUCTION
This chapter delves in to the theoretical framework on pricing leading to the formulation of
hypotheses for the research. It is pertinent to look at some of the existing theories for pricing
goods and services. In this light hypotheses have been formulated as a result of the synthesis of
literature review on these pricing theories for testing to either prove their falsification. The
chapter also looks at the concept of production and subsequently the elements of price
determination.
2.1 Concept of Price and Value
Price is the amount for which product, service or idea is exchanged, or offered for sale regardless
of its worth or value to potential purchasers (Cannon, 1998), price is the value (or its equivalent)
placed on a good or service (Farese et al., 1991) and according to Perreault and McCarthy, 2002,
“price is the amount of money charged for “something” of value.” The key to pricing is
understanding the value buyers place on a product (Pontiskoski, 2009). Value is a matter of
anticipated satisfaction from a product (Zhilin & Robin, 2004, Grahame & Mark, 1997). If
consumers believe they will get a great deal of satisfaction from a product, they will place a high
value on it (Thompson, 2005). They will also be willing to pay a high price for it. A seller must
be able to gauge where a product will rank in the customer’s estimation- valued much, valued
little, or valued somewhere in between (Brand, 1998, Grehalva, 2004, Tommie et al., 2008). This
information can be taken in to decision. The seller’s objective is to set a price high enough for
27
the firm to make a profit and yet not so high that it exceeds the value potential customers place
on the product (Farese et al., 1991).
From the foregoing, therefore, it stands to reason that the ability of price setters to gauge the
value customers place on a good or service is vital in determining a workable price for goods and
services. Thus it is appropriate to hypothesize that:
Hypothesis 1: A significant key to successful pricing is dependent on: (H1a).value of a product
or service and (H1b). affordability
2.2 The Just Price
Underlying the discussion about price is the notion of the ‘fair’ or ‘just’ price, the price that
could be called correct on the basis of social considerations. A great deal of government,
pressure group and media action and discussion is geared towards achieving just prices, but it is
seldom fully appreciated how sensitive this concept is to the point of view of those discussing it
(Allison et al., 2011). To the seller a fair price is probably the amount needed for their offering in
order to make reasonable profit (Canonn, 1998). The notion of a reasonable profit itself has to be
discussed, as there are different approaches to this. To the customer a fair price probably refers to
some general idea of affordability allied to some sense of intrinsic value, with previous
experience a contributory factor. In entering into the exchange both are seeking some degree of
profit from it. Sellers want some excess income over costs, while buyers want an excess of
satisfaction from goods or services over the satisfaction from holding on to their money or
purchasing something else. In determining pricing policies the company needs to understand
both costs involved and alternatives open and the responses of the different groups and the value
they place on the goods or services (Canonn, 1998).
28
From the foregoing, it is therefore clear that both the seller and the buyer want to arrive at a fair
price which they will refer to as correct from the social point of view. At the same time, the
seller wants to make some excess money representing his profit for engaging in a business
venture and buyers would refer to a price as fair if they can afford the goods or services and
derive some satisfaction which is of intrinsic value. Hence it has become necessary to
hypothesize that:
Hypothesis 2: The achievement of just price levels is significantly dependent on: (H2a). the
government. (H2b). media action. (H2c). pressure group (H3d). seller’s profit. (H3e).
customer’s intrinsic value. (H3f). customer’s affordability.
2.3 Importance, Objectives and Goals of Pricing
Price is an important factor in the success or failure of a business because it helps establish and
maintain a firm’s image, competitive edge and profit. Many customers use price to make
judgments about products (Amstrong & Green, 2011, Rajneesh & Kent, 2003). Sometimes price
is the main thrust of a firm’s advertising strategy (Farese et al., 1991). Pricing objectives might
be: to increase profitability, to thwart the efforts of competitors to accept us as a price leader, to
restore order in a chaotic market, to increase market share and to smooth the seasonality of
purchases (Dwyer & Tanner, 2006). According to Farese et al. (1991), pricing objectives
“include share of the market, achieving a return on investment and meeting competition.” Pricing
objectives consist of profit oriented (i.e. target return and maximize profits), sales oriented (i.e.
sales growth and growth in market share) and status quo oriented (i.e. meeting competition and
non-price competition) (Perreault & McCarthy, 2002).
29
From the foregoing, it can be realize that objectivity is one of the critical pillars of price setting
and it plays a key role in the judgement of a firm’s image, success and failure. As a result it can
be hypothesized that:
Hypothesis 3: The role of the firm in setting price levels is significantly dependent on: (H3a).
objectivity. (H3b). failure. (H3c). success. (H3d). image.
2.4 Pricing Strategies
The formulation of a sound pricing strategy requires consideration of demand and cost factors in
a competitive environment (Robert, 2001, Andreea, 2011). A price strategy consists of a specific
approach to achieve the pricing strategies (Ashok et al., 2008, Ioannis, 2002 and Ashok et al.,
2008). Pricing strategies may include: to gain market share by concentrating on small users
served by full-line, to build customer trust by reducing prices on products having highly visible
cost reductions, to win customers from competitors by bundling at a low total price, including
items not carried by rivals (Dwyer & Tanner, 2006). Steps in setting price include: determine
pricing objectives, study costs, estimate demand, study competition, and decide on pricing
strategy and set price (Farese et al., 1991).
Basic pricing strategies include: “cost-oriented pricing: calculate first the costs of acquiring or
making a product and their expenses of doing business. Then they add their projected profit
margin to these figures to arrive at a price (Patsula, 2007, McTaggart & Kontes, 1993, Treacy &
Wiersema, 1993). It include markup pricing that is difference between the price of an item and
its cost; and cost-plus pricing that is all costs and expenses are calculated and then the desired
profit is added to arrive at a price ( Holland, 1998 and Ball, 2011). Demand oriented pricing is
30
used to determine what present consumers are willing to pay for given goods or services
(Patsula, 2007, KIPPRA, 2010, Cicchetti & Haveman, 1972). The key to using this method is the
consumers’ perceived value of the item, and competition pricing is studying competitors to
determine the prices of products (Gale & Swire, 2006; Lewis & Shoemaker, 1997 and Essel,
1996). Sales, costs and expenses determine a firm’s profit (Kaplan, 2006, Roberts et al., 2011).
As a result businesses constantly monitor, analyse and project prices and sales in the light of
costs and expenses (FTC, 2005; CAS, 2003; Burnett, 2008). Businesses improve a product by
adding more features or upgrading the materials used in order to justify a higher price (Farese et
al., 1991).
From the foregoing, therefore it can be seen that there are various strategies of determining price
and fundamental to the success of every pricing strategy is the accurate determination of costs
and expenses and key in every pricing strategy lays demand and competition. Hence it can be
hypothesized that:
Hypothesis 4: The fundamentals of every pricing strategy of a firm depend on:
(H4a). Cost. (H4b). Profit (H4c). Demand (H4d). Competition
2.4 Project Pricing
Another service industry which can be used to illustrate a further problem of setting prices is
pricing projects, which are a form of the special (one-off) product pricing issue (IMP, 1982). In
the consultancy industry, many systems companies have to establish pricing strategies (Brodie,
2009). From the selling company’s perspective the low-risk pricing policy on a ‘time and
materials basis’, whereby the time taken to solve the problem is charged to the client at an agreed
31
daily rate together with any materials used on the project (Jenkins, 2006). However, this low risk
on the part of the selling company means that the customer has the high risk and is potentially
signing a blank cheque to the supplier (OFT, 2008). Therefore as a way of differentiating
themselves from competition some companies started to quote fixed prices for solutions to client
problems (Patsula, 2007). For this pricing strategy to be successful, the company needs to have a
very good financial control system which should be organized to provide accurate information
on a project basis (Rodin-Brown, 2008). The control system should allow managers to learn
about past project costs and hence to be able to forecast more accurately in the future (The World
Bank, 1998). The system should also produce timely reports on current projects compared to
plan so that managers can make decisions and take action on any projects which show signs of
overrunning (IFC, 2007). This means that plans and actual costs have to be capable of being
compared against achievement milestones, not just expenditure levels (Flyvbjerg et al., 2003).
In the construction industry, this problem of pricing and cost control is also a major concern to
customers and it is particularly so when a number of different suppliers ( for example, the actual
building company, architects, quantity surveyors, specialist contractors) are involved in any
major contract (Haider, 2009). Out of this complexity, a new service has been developed,
particularly by quantity surveyors who are expert in construction measurement, which provides
the client with ‘total project management.’ This service should ensure that the client gets what
was wanted for the fixed cost which was agreed at the start of the project, and thus the project
manager resolves any cost overruns and frees the client from any detailed involvement in the
project. Clearly, the client pays a fee for the service provided, but it is a good example of the
complexity of pricing leading to a marketing opportunity for a new product (Ward, 1994).
32
From the foregoing it can be seen that the pricing of projects for that matter construction projects
is beset with some complexities and risks to both the client and the seller of the consultancy
service. In this regard pricing normally takes in to significant consideration the time taken to
solve problems, and materials used on projects. For project pricing to be successful it is pertinent
to take serious note of the financial control system, record of past costs (cost history of projects),
cost forecast and timely delivery of deliverables. As a result, it is therefore of much significant to
hypothesize that:
Hypothesis 5: The successful criteria for consultancy services pricing is dependent on: (H5a).
time taken to solve the problem. (H5b). materials used on the project. (H5c). good financial
control system. (H5b). Record of past project costs. (H5c). accurate forecast of future cost; and
(H5d). production of timely reports.
2.5 Bid Pricing
Bid pricing means offering a specific price for each possible job rather than setting a price that
applies for all customers (Meissner & Strauss, 2010). Bid pricing is more complicated; a big
problem is estimating all the costs that will apply. A complicated bid may involve thousands of
cost components (Reguant, 2011 and Koomey et al., 2009). Further, management must include
an overhead charge and a charge for profit. This system does not allow the seller to set a price
based on the precise situation and what marginal costs and marginal revenue are involved
(McAfee, 2008, Nwokeji, 2007, Anderson & Ross, 2005). Bids are usually based on purchase
specifications provided by the customer. Sometimes, the seller can win the business, even with a
higher bid price, by suggesting changes in the specs that save the customer money (Perreault &
McCarthy, 2002). Competitive bidding is very common in government and quasi- public
33
institution (schools, hospitals, social services agencies) largely to satisfy external constituencies
that otherwise have difficulty auditing performance (Kosar, 2011 & Keidel, 2007). Competitive
bids provide some assurance of input efficiency (Hamilton, 2008 and IFC, 2007). A successful
bid is one that meets the goals of both buyer and seller (Dwyer & Tanner, 2006; Froeb &
McAfee, 1988).
From the foregoing, it has been demonstrated that bidding is just another form of pricing which
considers costs and competition from other bidders. Bidding takes serious and elaborate
cognizance of finance, technical capacity, reputation, experience, and duration and business
development of firms in to consideration. These are therefore fundamental to every bidding
process. Bidding is therefore not a pricing strategy for every product or service; it is mostly
suitable for customized projects for governments and quasi-public institutions. In this light, it is
necessary to hypothesize that:
Hypothesis 6: The success of a bid price is significantly dependent on: (H6a). financial capacity,
(H6b). technical capacity, (H6c). experience, (H6d). duration, (H6e). reputation, (H6f). business
development, and (H6g) Profit and overhead
2.6 Production and Pricing
The basic principles of price determination are not different for factor services than for products
(Porter, 2008 and Leamer, 1995). In the perfectly competitive factor service markets, demand
and supply establish the equilibrium factor price which equates quantity demanded to quantity
supplied (Piermartini & Teh, 2005). Other things equal, the greater the demand for a service or
the less the supply of it, the higher its market price (Lee et al., 1997 and Trostle, 2008). Factor
34
services encompass both material services such as capital equipment or land and personal
services of human beings that is labour and entrepreneurship (Kiriga et al., 2002 and Kapila,
2006). The quantities and prices of the factors involved in the selected technology determine the
cost of the firm, cost stems from the production of a good or service by the business firm
(Swanson & Guttman, 1996 and Cohen & Bailey, 1997). Activities such as property valuation,
land surveying, designing a machine or a building, developing software, editing manuscripts,
teaching, providing consultancy service and selling bananas must all be regarded as production (
Opoku-Afriyie, 2007).
Production activity involves conversion or transformation of certain objects or the services
provided by objects or persons called factor inputs or factors of production into objects or
services called output (Chidambaram et al., 1999). Production is the combination of factors such
as land, because raw materials and auxiliary materials do not transform themselves, some human
intervention is needed to take place, labour, is the factor which provides the human intervention
(c.f. Lynden, 2000; Kefela, 2010 and Opoku-Afriyie, 2007). Other forms of human intervention
required for production are referred to as entrepreneurial talent and managerial skill (Papulova &
Makros, 2007 and Ogechukwu & Latinwo, 2010). These provide mental intervention, notably,
leadership, supervision, planning, coordination and control of production activities. In converting
raw and auxiliary materials into output, various tools, machines, equipment, other physical
implements and often buildings are required; these are collectively referred to as capital.
Firms are interested in output in as much as it contributes to revenue and through profit. The use
of factor inputs, as indicated on the right-hand side of the production function involves cost as
35
the inputs must be paid for. Thus firms are also concerned about the cost of production that is the
value of factor inputs used in as much as it affects profit. The cost of production can be
expressed as the cost function as follows: K= K1V1 + K2V2 + …………. + KnVn, where K is the
total cost of production and K1, …………… Kn, and V1 , ……..Vn, the prices of the inputs
respectively (Opoku- Afriyie, 2007).
In principle, pricing is an important issue among the various activities that the consultancy
industry undertakes, the transfer of knowledge and expertise relating to how to do various tasks,
how to measure and how to communicate the fact and the extent of it to the public. Each of these
is of some potential benefit, achieved only at a cost and pricing in the consultancy industry
mediates between these benefits and costs (Young et al., 2003). The attitude will gradually shift
back to that of one where firms are willing to price higher value services (like consultancy
services) at a higher rate. Business owners are willing to pay more for services that have positive
impact on their businesses even now. Pricing depends on value perceptions of the client, many
firms are being less “fee aggressive” because their clients are being approached by more firms
selling on price (Lewis, 2011).
Firms that have successfully implemented value pricing throughout their practice do so by:
Designing a package deliverable whose value can be understood by the client.
Pricing the deliverable in a manner that considers the market value based on
comparables or by considering the value that is inherent in its utility to the specific client
situation.
Designing the production of the deliverables so that it can be produced profitably (Sinkin
& Putney, 2011).
36
Price trends for different products and services must be measured and indices calculated before
the current prices can be converted in to fixed prices. The services producer price index (SPPI) is
a producer price index for services that aims to measure price trends in industries that produce
business services. The prices may differ from one area to the next especially regarding strategic
issues, where the price can vary as much as 50 percent in comparison with other areas.
Sometimes, a customer may order services within a certain area of activity. There are several
components that affect the price of a service, which can vary considerably depending on the
company. The following components may affect the price of the tender:
How many consultants does the service require?
Which categories of consultants does the service require?
Which areas of activity (also known as “service line”) does the service involve?
How long will it take to perform the service?
How extensive is the service? Geographically? Resource – Demanding?
Who is the customer? (Larsson, 2007).
The variation of price can be arbitrary (we disregard the fact that price changes cannot actually
be smaller than a certain quantity- a ‘tick’). In order to describe the random process X for which
the result is a real number, one uses a probability density P( X ), such that the probability that X
is within a small interval of width dx around X= x is equal to P(x)dx. The mean or the expected
value of X, which we shall note as m in the following, is the average of all possible values of X,
weighted by their corresponding probability: m = ∫ xP(x)dx ( Bouchaud & Potters, 2003).
37
Drawing on from the above, the production of firms involves the combination of factor services
of which the consultancy industry is of no exception. The prices and quantities of these factor
services involved in a selected technology determine the cost incurred by the firm arising out of
production of goods and services. The combination of these factors also known as factor inputs
by firms result into objects or services called output. These factor inputs comprises of: materials,
labour (Support staff), capital (plant) and entrepreneurial and managerial talent (consultants).
The motivation for firms (consultancy firms) for the combination of input factors is to make
profit, and this act of input factor combination gives rise to cost. Finally the use of probability
theorem and indices for services provision can lead to the determination of consultancy pricing
which is the combination of input factor costs and profit.
2.7 The Concept of Risk
Risk is measurable uncertainty (likelihood) for something to occur that lets projects fail,
decreases their utility or increases their costs and duration. Further, to know certain risk alone
does not suffice, risk has to be weighed against the benefits, should the stated goals be achieved
and the activity is successful (European Union, 2010). In the construction industry, risk is often
referred to as the presence of potential or actual threats or opportunities that influence the
objectives of a project during construction, commissioning, or at time of use (RAMP, 1998).
Risk is also defined as the exposure to the chance of occurrences of events adversely or
favourably affecting project objectives as a consequence of uncertainty (Al-Bahar, 1990).
Risky events can be characterized by their magnitude, scope or spread, frequency and duration,
and their history – all of which affect vulnerability (Heitzmann et al., 2002). Risks can be
38
classified as idiosyncratic risks that usually affect individual firms and covariate risks that affect
many firms simultaneously(e.g. major drought or floods, fluctuating market prices) (Skees et al.,
1999). Risk is the possibility that an event will occur that will potentially have a negative impact
on the achievement of a firm’s performance objectives (Boisnier & Chatman, 2002). Expected
losses from risky event include both tangible and intangible losses, and short and long-term
losses (Jaffee et al., 2008). It is critical to consider losses in terms of how they affect short term
outcomes versus livelihoods and outcomes in the longer term (IFC, 2007 and Morduch & Haley,
2002). Thus, in addition to examining whether risks are idiosyncratic or covariate, it is important
to examine if they impact performance flows (e.g. movement of goods and services, incomes)
and/ or also damage assets. The expected losses are a function of probability of a risky event
actually occurring and the exposure to that risky event i.e how performance outcomes might be
influenced if the risk materializes (Jaffee et al., 2008).
From the foregoing contextualization of risk, it can be seen that risk is the occurrence of any
event which can affect almost all the facets of business activities and it is probabilistic in nature
and can cause serious changes to activities such as price setting, performance and maintenance of
quality standard.
2.7.1 Risk and Price
Price uncertainty and price volatility are problems (Dehn, 2000; Dana, 2005 and Fischer & Orr,
1994). In analyzing price risk issues, it is important first to differentiate between direct risk and
indirect risk (Dana, 2005 and Inderst, 2009). Direct risk is the impact of price on specific
commercial transactions: purchase of goods, sales of goods, processing of goods, and lending
39
which supports any of these activities (Andam, 2003; European Union, 2010 and Dana, 2005).
Direct price risk is only experience by market participants who are engaged in these transactions
(Dohring, 2008; Dana, 2005 and Papaioannou, 2006). Direct risk can be classified as financial
and physical (Malkiel, 2003 and Santomero, 1997). Financial risk is the financial impact or
profit/loss position of a producing entity. Financial risk can be quantified by: net risk position, it
can be ‘long’ or ‘short’. A long position describes the commercial position where a fixed priced
inventories or purchase commitment without having equal and offsetting fixed sales contracts
(Dana, 2005 and Jaffee et al., 2008). The risk of long position is that prices will fall below the
level of the purchase price committed (Rappaport, 2005; Elwell, 2011and McCue & Belsky,
2007).
A short position is the opposite scenario. A price level is the price basis at which the inventories
are valued or purchased/sales commitment made (Dana, 2005; Treacy & Wiesema, 1992 and
Beechy & Conrod, 1998). The price level of the risk is expressed in terms of the local price
basis, and if applicable, the corresponding international market or exchange price basis (Kojima,
2009 and Dana, 2005). The difference between the two prices is the cost of getting the product or
service to the market (processing, local transportation, insurance, freight), and a premium or
discount for cash price (Tseng et al., 2005, McAfee, 2008, Micco & Perez, 2002). The terminal
market price is referred to as basis risk (Taylor, 2011 and Huang & Wang, 1997). Volume of
inventories and/or purchase commitments; duration, the time period for which the entity is ‘long’
or ‘short’ and exposed to price movements which may be unfavourable ( Stevenson & Bear,
1970 and Dana, 2005). Physical risk is different from financial risk because it focuses on the
trade of the physical product and issues of volume, quantity, timing and delivery (UNEP, 2004
40
and Morrison et al., 2009). Price risk falls within the category of financial risks. Indirect risks are
the knock-on effects of direct risk felt in the system. Indirect impacts occur when direct price
risk problems experienced at one level create uncertainty or economic and financial instability
(Dana, 2005).
From the above exposition, it is crystal clear that business activities encounter situations which
are classified as direct risk and indirect risk. Among these, the direct risk which has a component
financial risk significantly impacts on price levels. In this case it will be appropriate to posit that:
Hypothesis 7: Consultancy services price levels are dependent on financial risks.
2.7.2 Types of Risk
Market related risks exist for inputs and outputs and for the critical services which support
supply chains such as finance and logistics (Jaffee et al., 2008). Generally, market risks are
related to issues which affect price, quality, availability, and access to necessary products and
services, (Stader & Shaw, 1998 and Jaffee et al., 2008), of these market risks are typically the
most volatile (Buehler et al., 2008). Logistical and infrastructural risks are related to logistics
and infrastructure that affect the availability and timing of goods and services, energy and
information (Jaffee et al., 2008; Tseng et al., 2005 and Malhotra, 2005). Thus logistics related
risks are closely related to price and market related risks, including the driving decisions on
product lines and input use which can affect future production, processing, marketing decisions
(Jaffee et al., 2008; Ioannis, 2002 and Wind, 1981). Managerial and operational risks are closely
associated with human judgment and response- i.e. errors and actions and inaction, commission
and omission (Flouris et al., 2010). These risks are mostly associated with productivity
41
reductions, and how quality of products and unreliable delivery of inputs and outputs and support
services (Jaffee et al., 2008).
Demand risk relates to potential or actual disturbances to flow of product, information and cash
emanating from within the network between the focal firm and its market (Braithwaite, 2003;
Wilding, 2007; IMP, 1982). In particular, it relates to the processes, controls, assets and
infrastructure dependencies of the organization downstream and adjacent to the focal firm
(Mungofa, 2009; Belkin, 2008; Braithwaite, 2003 and Teece et al., 1997). Supply risk is the
upstream equivalent of demand risk; it relates to potential or actual disturbances to the flow of
product or information emanating within network upstream of the focal firm. Environmental risk
is associated with external and, from the firm’s perspective, uncontrollable events. The risks can
impact the firm directly or through its suppliers and customers (Braithwaite, 2003).
Technological risks are all those risks that lead to non-completion, underperformance or false
performance of the procured good and service (Edler, 2010 and Pissas, 2007). The risk lies in
technical characteristics of the service or product in its production and thus originates in the
supply side (European Union, 2010 and UNCTAD, 2008). This risk appears in particular
relevance in procurement of products in the fluid phase (European Union, 2010 and Barringer,
2003). Organizational risks are all those risks of procurement failing or under- delivery for
reasons situated within the organization that procures (WTO, 2004). Societal risks are those
related to a lack of acceptance and uptake by the users of the new or changed service delivered
within society (European Union, 2010 and WHO, 2003). Finally, turbulence risks- in fact
turbulence uncertainties as they are hard to predict and measure are associated with large scale
42
projects and emerge from a range of unforeseen events that lead various actors in the whole
process to reassess their priorities or change their expectations (European Union, 2010).
From the above, it is clear that there are myriad of risks facing business entities for that matter
consultancy firms from various sources such as market, demand and supply, financial, physical,
logistics, technological, organizational and societal. It is of no doubt that risks from any of these
sources will affect the price level set by consultancy firms since they operate in environment that
their business activities are related to these sources of risks. Hence it stands to hypothesize that:
Hypothesis 8: The robustness of consultancy pricing is significantly dependent on the existence
of: (H8a). Market related risks (H8b). Logistical and infrastructural risks
(H8c). Managerial and operational risks (H8d). Technological risks (H8e). Organizational and
societal risks.
2.7.3 Risks at Various Stages of Project Implementation
According to UNEP (2006) risks occurring during project implementation are: risks during the
project implementation phase- between the project concept and its implementation stage there
are several steps that require significant time and resource input. There is however, the
possibility that the project concept will never reach implementation stage on account of the
project being considered infeasible or economically unviable. Hence the project does not receive
the necessary regulatory approvals or the project fails to achieve financial closure i.e. raise the
required funds to implement the project (IFC, 2007 and UNEP, 2006). However, the probability
of delays in receiving the regulatory approvals and achieving financial closure is relatively high.
Risks during the construction phase: completion risk- the nature of risk factors associated with
43
completion being time overrun, cost overrun or completed project not being up to the required
technical specifications (Kreydieh, 1996).
The probability of time and cost overruns is pretty high and the extent of impact on account of
these is also relatively high (UNEP, 2006 and Guo, 2004). Counterparty risks- when construction
is undertaken by a construction contractor, there is a risk that the contractor does not perform as
per contract, which results in time and cost overruns (Smith, 2009; UNEP, 2006 & Haider,
2009). Risks during the operation phase include performance risk- the nature of risks associated
with performance is similar to that in the case of infrastructure projects with there being the
possibility of equipment not performing as per required standard (Harris, 2003, UNEP, 2006 and
IFC, 2007). Counterparty risk- when operations are performed and managed by a contractor
there is a risk that the contractor does not perform as per contract which may result in sub-
standard performance. Generic risks for all phases include: financial risk- fluctuations in interest
rate, currency exchange rate and inflation can affect project economics (Kreydieh, 1996; Gray &
Irwin, 2003, Nair & Yescombe, 2008). The probability of fluctuation of these factors is high and
the extent of impact is linked to the extent of fluctuation (Pirog, 2005 and Baker et al., 2008).
Legal risk- there is often problems with respect to contract enforcement as well as contract re-
negotiations in developing countries on account of a poor legal infrastructure (Samuels, 2006 and
Likosky, 2009). The probability of contractual default is high and the extent of impact is also
relatively high (UNEP, 2006). The only way of mitigating this risk is by obtaining some form of
a sovereign guarantee from the host government (Ramamurti & Doh, 2003, Bedoucha, 2010, and
Gupta et al., 2002, UNEP, 2006). Regulatory risk- even where the price is locked in through a
purchase agreement (PA) (Antolin & Stewart, 2009; UNEP, 2006; Finon & Perez, 2008), there is
44
a risk that the regulators may mandate a revised price leading to a renegotiation of the PA
(Grabel, 2002 and UNEP, 2006). Political risk- restriction on currency convertibility may restrict
the repatriation of profits. Political violence may restrict operations and result in damage to
equipment as well. The probability of occurrence of these events is relatively low but the extent
of impact is very high (Hillson & Hulett, 2004). Force majeure risk- natural catastrophes such as
floods, earthquake, etc as well as man-made events such as a war, strike etc, could hamper or
stop activities both during the construction as well as operations phase (UNEP, 2006). The
probability of occurrence of is low but the extent of impact is very high (Chomitz & Gray, 1996).
From the above, it has been clearly demonstrated that the generic risks which run through all the
phases of project implementation affect the provision of consultancy services hence the need for
their pricing. Financial, legal, regulatory, political and force majeure risks have very high extent
of impact on projects as well as consultancy pricing. In the light of this, it is appropriate to
hypothesize that:
Hypothesis 9: The level of consultancy pricing is dependent on: (H9a). Financial risk (H9b).
Legal risk (H9c). Regulatory risks (H9d). Political risk and (H9e). Force majeure risks.
2.8 Concept of Taxation
Economic growth increases the taxable capacity of a country and enables a larger sphere of the
private sector’s resources to be ceded to the government as taxes to provide public goods and
services. Many countries, therefore, depend mainly on taxation as a means of generating the
required resources to meet their expenditure requirements. These countries will likely find
45
themselves in growing fiscal imbalance when their revenue productivity falls below their
expenditure (AERC, 1998).
2.8.1 Taxation of consultancy services
Local tax liabilities originating from consultancy services contracts are often the cause of unclear
proposals and of unsatisfactory contracts. The identification and calculation of local tax amounts
are a difficult and time-consuming task for consultants with little knowledge of the tax system.
Such local taxes generally include the following: indirect taxes, that is ad valorem taxes(VAT)
on contract items for example VAT on consultant remuneration, duties on imported equipment
and supplies later exported by the consultants, for example personal computers, scientific
equipment; duties and levies on equipment imported or locally acquired by the consultants that is
treated as property of client, for example cars, office equipment and local income taxes on the
remuneration of services rendered locally(World Bank, 2002).
2.8.2 Tax System in Ghana
The tax structure in Ghana is generally composed of direct taxes, indirect taxes and international
trade taxes. For the direct taxes, the factors that produce the income are assumed to pay the
associated taxes while for the indirect taxes and international trade taxes, households or firms
that consume or import/export the taxed items are assumed to pay the associated taxes (Owusu-
Afriyie, 2009).
46
2.8.3 General Provisions under the Tax Law
Income tax is levied in each year of assessment on the total income of both resident and non-
resident persons in Ghana. With respect to resident persons, the income must be derived from
accrued in, brought into or received in Ghana. For non-resident persons, the income must be
from or accrued in Ghana. An individual is resident for tax purposes if that individual is a citizen
of Ghana, other than a citizen who has a permanent home outside Ghana for the whole of the
year; present in Ghana for a period or periods equal in total to 183 days or more in any twelve-
month period that commences or ends during the year; an employee or official of the
Government of Ghana posted abroad the year; a Ghanaian who is temporarily absent from Ghana
for a period not exceeding 365 continuous days where that Ghanaian has a permanent home in
Ghana. A company is resident for tax purposes if that company is incorporated under the laws of
Ghana; or has its management and control exercised in Ghana at any time during the year
(Pricewaterhousecopers, 2008).
2.8.4 Income and Profit Tax Legislation
Principle legislation regarding direct taxation is the Income Tax Act 592 (2000) which comprises
both Personal Income Tax (PIT) and corporate Income Tax (CIT). Recently, the Act was
amended by Amendment 622 (2002). The Act sets out tax policy as well as tax procedures. Profit
tax legislation is also part of the Income Tax Act. Profits are calculated on an accrual base.
According to the Act, tax rates on profits are differentiated accordingly into six sectors or
branches, and variate between the region in which the business operates. Companies listed at the
stock exchange are subject to a rate of 30 per cent. The highest rate for ‘other business’ reaches
out to 32.5 per cent (Romer & Romer, 2007; Witt & Lautenbacher, 2003).
47
2.8.5 The Implementation of VAT
VAT was originally established in 1995 to replace the old sales and service tax system. As the
rate was set at 17 per cent, the VAT was fiercely resisted and eventually suspended: the rate was
seen as too high, the threshold (annual turnover of 25 million cedi) was too low; the information,
campaigning and taxpayer education was too poor. After three years of reconsideration, VAT
was successfully introduced in 1998 under VAT Act 546. This time the added value of all goods
(except agriculture and basic goods) and services were taxed with a rate of 10% and a threshold
of 200 million cedi annual turnover (suppliers of goods). In 2000, a major review of the VAT
system was completed, which resulted in a tax rise to 12.5% and a broadening of the tax base by
lowering the threshold for suppliers of goods to an annual turnover 1oo million cedi( Witt &
Lautenbacher, 2003). Other than exempt goods and services, Value Added Tax (VAT) and the
National Health Insurance Levy (‘NHIL’) are charged on the following: every supply of goods
and services made in Ghana, every importation of goods, supply of any imported service. The tax
shall be charged on supply of goods and services where the supply is a taxable supply and made
by a taxable person in the course of his business. The tax shall be paid: in the case of taxable
supply by taxable person making the supply, in the case of the imported service, by the receiver
of the service (Pricewaterhousecopers, 2008).
From the foregoing, it has been realized that by the laws of Ghana, all businesses operating in the
country are obliged by the law to pay taxes. Taxes payable by firms include corporate tax,
income tax of employees, VAT/ ‘NHIL’; profit tax, property tax and local rates. Taxes form the
48
expenditures of firms as the cost of doing business and must be recovered through pricing. In the
light of the above, it is appropriate to hypothesize that:
Hypothesis 10: The level of consultancy prices is significantly dependent on taxes such as:
(H10a). personal income tax (H10b). VAT/ ‘NHIL’ (H10c). Corporate tax (H10d). Profit tax
(H10e). local rates (H10f). Property tax.
2.9. Concept of Inflation
What exactly is inflation? A persistent increase in the level of consumer prices or a persistent
decline in the purchasing power of money, caused by an increase in available currency and credit
beyond the proportion of available goods and services. Inflation occurs when the price level rises
from one period to the next (Robinson, 2007). There is an inverse relationship between the prices
of goods and services and the value of money in an economy. Other things equal, as prices rise
over time, a given amount of money will be able to purchase fewer goods and services. Inflation
has an additional effect on prices when businesses, workers and others experiencing a loss in
purchasing power attempt to adjust upward what they receive for their goods and services in
order to keep pace with their rising costs (FEWS NET, 2009).
From the exposition above we can say that a persistent increase in the price of goods and
services, and for that matter input prices for firms or consultancy service providers will cause
inflation in the economy hence prices set by firms will be affected. Hence it is appropriate to
hypothesize that:
Hypothesis 11: Price level is significantly dependent on: (H11a). input prices (H11b). Inflation
49
2.9.1 Causes of Inflation
The price of any good is influenced by different market forces that can change the balance
between supply and demand (Schnepf, 2006 and FEWS NET, 2009). Many of these forces come
from domestic as well as regional and international markets. This section discusses the causes of
inflation. Production shortfall- for locally produced goods, the differences in product prices
reflect differences in local conditions of supply and demand (FTC, 2005; FEWS NET, 2009,
Ghemawat, 2006; Meijerink & Roza, 2007). In general, prices are lower in regions of surplus
production and higher in densely populated regions of deficit production. Effects of input
markets- if the cost of inputs used in production of a good increases; this can cause a rise in the
cost of production. Government policies can take many forms and could potentially cause
inflationary pressure; and international trade and trade barriers (FEWS NET, 2009).
In summary, it can be seen that price levels for that matter inflation can rise as a result of
production shortfall, effects of input markets, government policies and international trade and
trade barriers. These can cause changes in prices hence it is pertinent to hypothesize that:
Hypothesis12: Significant changes in price levels are dependent on inflationary causes: (H12a).
production shortfall (H12b). Effects of input market (H12c). Government policies; and (H12d).
International trade and trade barriers.
2.9.2 Economic Indicators of Inflation
Leading indicators are those which are believed to change in advance of changes in the economy,
giving a purview of what is going to happen before the change actually. Generally, economic
indicators of inflation are statistical data showing general trends in the economy. Those with
50
predictive value are leading indicators; those occurring at the same time as the related economic
activity are coincident indicators; and those that only become apparent after the activity are
lagging indicators. The most important indicator is the Gross Domestic Product (GDP) report
(Robinson, 2007).
2.9.3 Nominal and Real Prices
The nominal price of anything is simply its stated price; measured in the national currency. The
real price of a commodity, on the other hand is its price adjusted to reflect changes in the overall
price level. A commodity’s real price is therefore its particular price compared to the general
level of all prices. Changes in real prices are a better measure of the real economic burden or
significance of a price, than changes in nominal prices (Robinson, 2007). Nominal prices are
prices that have not been adjusted for inflation (Mills, 1996; FEWS NET, 2009, Ball & Mankiw,
1994). The nominal price is equal to the money that is paid for a unit of a good or service in the
market, at the shop (FEWS NET, 2009). Real prices are prices that have been adjusted for
inflation (Stanford, 2008; FEWS NET, 2009). Real prices hold the value of currency constant,
and allow you to compare the exchange value of a good or service in different time periods. The
most common measure of inflation is the Consumer Price Index (CPI) (Morrison & Labonte,
2008 and FEWS NET, 2009). The CPI is a measure of change in the purchasing power of a
currency. The CPI expresses current prices of a typical consumer basket of goods and services in
terms of the prices during the same period in a previous year( reference to a base year), to show
the effect of inflation on purchasing power. The CPI can be used to calculate inflation using the
following equation:
INFLATION= [(current period CPI)-(Previous period CPI)] / (Previous period CPI.
51
If the information on the CPI is available, we can adjust nominal prices in order to calculate real
prices using the following formula:
REAL PRICE current year = (CPI base year/ CPI current year)* nominal price current year.
If inflation from base year is known we can compute the real prices using the formula:
REAL PRICE = Nominal prices/ (1+ Inflation Rate) (FEWS NET, 2009).
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CHAPTER THREE
THE CONSULTANCY INDUSTRY: A GENERAL OVERVIEW
3.0 INTRODUCTION
There is very little literature on the subject of consultancy in general, and none provides a
comprehensive agenda for describing the consultancy industry (Young et al., 2003 & Hovland,
2003). In the light of the above, Young et al. (2003) advocated that it is imperative to examine
the structure of the consultancy industry; number of firms operating in the consultancy industry
and their definition; and its segmentation. According to Young et al. (2003) and Porter (2008),
the consultancy industry consists of firms that offer similar services to their clients; and
monopolistic firms. Pilsbury and Meaney (2009) perceive the consultancy industry as the
composition of popular firms; few dominant firms in their own sector of operation and large
firms with market power competing with firms of same nature. Fundamental issues in the
consultancy industry clearly borders on conduct, pricing, competition, similarity of firms and
cartel formation; product diversity; and provision of services of right value to clients (Morrill,
2004).
In view of the above exposition, the aim of this chapter is to thoroughly review existing literature
on the consulting industry; and to identify the best practices in the industry and areas that need
urgent improvement. In a bid to achieve the stated aim, this review shall assess critical issues
such as: conceptual explanation of consulting; the segmentation of the consulting industry; the
scope of consulting services; critical reasons for effective consulting assignment; exploration of
the functions of consulting; the role of consultants for the achievement of an effective consulting;
clients-consultants relationship; criticisms against consulting and arguments supporting
53
consulting practice; effective selection of consultants; factors critical for successful consulting;
factors responsible for consulting failures; terms of reference; effectively pricing consulting
services; and finally summarizing and drawing conclusions on some of the pertinent issues
identified.
3.1 CONCEPTUAL EXPLANATION OF CONSULTANCY
Consulting involves the cross-fertilization of best practices, analytical techniques, change
management and coaching skills, technology implementations, strategy development or even the
simple advantage of an outsider’s perspective (INSEAD, 2011). Greiner and Metzger (1983)
opined that consulting is an advice-giving service contracted for and provided to organizations
by expressly trained and qualified persons who assist, in an objective and independent manner,
the client organization to identify management problems, analyze such problems, and help, when
requested, in the implementation of solutions. Adding on, Pittinsky and Poon (2005) clearly
asserted that consulting is a phenomenon in which one person has a difficulty and seeks
assistance from a professional with a special skill. Consultancy can also be defined as activity,
recommending appropriate action and helping to implement those recommendations (Naarmala
& Tuomi, 2006).
Consultancy has been categorized into two main aspects comprising management consultancy
which includes services contracted for and provided to organizations by specially trained and
qualified persons, who assist in an objective and independent manner, the client organization to
identify management problems, analyze such problems, recommend solutions to these problems,
and help, when requested, in the implementation of solutions; and engineering consultancy
54
which is the application of physical laws and philosophies of engineering consisting of the
application of scientific principles to practical ends as the design, construction, and operation of
efficient and economical structures, equipment and systems to a broad range of activities in the
areas of construction, manufacturing, mining, transportation and environment (Consultancy
Development Centre, 2006).
According to Nees and Greiner (1985) consultants are categorized into five groups in accordance
with their approach to deliver the services enshrined in their terms of contract comprising of the
mental adventurer who analyses unyielding problems such as development problems by
application economic methods; the strategic navigator bases service delivery on the contribution
of rich quantitative understanding of the market and competitive dynamics to the development of
the client and recommends the courses of action without too much regard of the client’s own
perspective; the management physician provides recommendations from a profound
understanding of the internal dynamics of the client organization, often willingly sacrificing
some objectivity to gain a realistic viewpoint on what is practicable; the system architect is much
concerned about helping the client in the redesigning of methods, customs, and systems- always
in tandem with the client; the friendly co-pilot provides guidance to senior managers as a catalyst
rather than as an specialist, and has no aspiration to provide new information to the client.
The demand for consulting services tends to increase with the economic development of a
particular country (Weller, 2001); the requirement for consultancy services stems from a diverse
range of clients, largely governed by the large corporate sector and the Government in various
forms, viz: country, institutions, and bilateral/multilateral agencies; and the development of
55
consultancy capabilities and business is directly proportional to growth in economic and
industrial development (Consultancy Development Centre, 2006). In view of the above,
especially the views of Weller (2001) a further empirical study on the relationship between
economic development and demand for consultancy services would be a novelty to undertake at
a higher level of research.
3.2 TOWARDS THE SEGMENTATION OF THE CONSULTANCY INDUSTRY
In exploring the consultancy industry, the Islamic Development Bank (2005) and The World
Bank (2002) noted that the industry operatives or firms can be segmented as independent
consulting firms which is made up of private companies, partnerships, corporations(globally and
nationally), financial institutions and procurement agencies; autonomous/semi-autonomous
government organizations; UN-agencies; or non-governmental organizations (NGOs);
universities/research institutes; consulting firms formed by trade associations like contractors or
manufacturers; and individual consultants. Since the origin of the consultancy industry;
consulting firms have been characterized by diverse functional areas such as engineering,
accounting, law, or banking; consulting organizations are generally classified as management
consultancy organizations, engineering consultancy organizations and others which include legal
consultancy organizations, socio economic consultancy organizations and financial consultancy
organizations (Consultancy Development Centre, 2006).
Consultancy firms operate along some detailed philosophies in their attempt to render services
to their clients and this in turn establish the nature of services they render as professional service
firms (among which they include Arthur D. Little and the big accountancy firms; specialist
56
consultants; non-governmental organizations and public interest groups; membership
organizations; business schools (in which include their own organization); independent
consultants set up by practitioners recently moved from the corporate sector (Young et al.,
2003). Consulting assignments are in all sectors, from socio economic and environmental
projects to reforms of state and financial sectors, privatization, information technology, and
infrastructure (The World Bank, 2002).
3.2.1 THE SCOPE OF CONSULTING SERVICES
The expression “consulting services” is defined as services of an intellectual and advisory nature
provided by consultants using their professional skills to study, design, and organize specific
projects, advice clients, conduct training, and transfer knowledge; also consulting services
consist of preparation services(master plans, feasibility studies, design studies); implementation
services(tender documents, procurement assistance, construction supervision, project
management, quality management and commissioning); and advisory services (policy and
strategy, reorganization/privatization, institution building, training/knowledge transfer,
management advice and technical/operating advice) (ACENZ, 2004 and The World Bank, 2002).
Other forms of consulting services include advisory or counseling services comprising staffing,
training and institution building and specific advice on issues and projects; pre-investment
studies consisting of identification, pre-feasibility and feasibility studies include regional or
sectoral planning, policy and investment priorities (Jobeus & Sikorski, 2000).
57
In addition to the identified services above, consulting services nomenclature include
engineering and design studies having detailed services to encompass preparation of drawings,
specifications, cost estimates, tender documentation and evaluation, contract administration and
procurement; implementation or supervision services expenditure management (Construction
Industry Development Board (CIDB, 2005); and certification of materials submitted by
contractors and suppliers(IFAD, 2010); introducing modification in design as demanded by the
client; project management ( Islamic Development Bank, 2005 and McDowell, 2011). Similarly
other consulting services typology comprise project planning and feasibility studies; quality
management; project assessment studies; construction management; financial analysis; cost
management; environmental studies and impact; contract management; assessments; consultancy
for commissioning and sustainability studies; decommissioning; geological and soils
investigations, maps; valuation services; architectural/engineering design; failure investigation;
preparation of tender documents; forensic services; evaluation of bids; technical training;
construction supervision; risk analysis and management; project management; operation and
maintenance; research and development (ACENZ, 2004).
Consulting services can also be purely management bias Public Relation and Communication
oriented in nature namely supply chain; business strategy issues; finance strategy issues;
functional areas; HR issues; IT consultancy; customer relationship management(CRM); investor
relations; marketing PR; business communication; crisis communication; internal
communication; public affairs (lobbying); global analysis/surveys ( Larsson, 2007). The project
management consultant acts as the beneficiary’s executing arm in all matters connected with the
execution of a project; and in this particular case, there is no standardized model according to
58
which services under this category are rendered; sometimes a consultant may be engaged to act
as the sole project consultant often with enormous powers; or an independent consultant may be
appointed under a project manager and be entrusted with the delivery of comprehensive tasks
(Islamic Development Bank, 2005).
3.3 CRITICALLY EXAMINING CONSULTANCY CONTRACTS
Two main considerations determine what type of contract to adopt in consultancy assignments:
the nature and degree of definition of the assignment; and the distribution of risks between the
client and the consultants (Appelbaum & Steed, 2004); and the level of contract supervision
(Islamic Development Bank, 2005). The types of contracts prevailing in the consultancy industry
comprise of lump sum; time-based; retainer and/or success fee; percentage; and indefinite
delivery (The World Bank, 2002 and Islamic Development Bank, 2005).
Similarly, the Islamic Development Bank (2005) identified consultancy contracts to encompass
lump sum contracts for complex assignments; lump sum contracts for simple assignments; time-
based contracts for complex assignments; time-based contracts for simple assignments; and lump
sum and time-based contracts for individual consultants. Lump-sum contracts are used for
assignments which involve wide ranging services and demands delivery of services in a precise
manner (Ministry of Finance, 2010). The lump sum contracts require that the client pays a fixed
sum of money for particular services provided by the consultant according to certain critical
requirements notably study reports; project design; tender document; timely delivery; and quality
(van Rijn, 2005).
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According to ADB (2010) lump-sum contracts are uncomplicated, well defined and appropriate
for assignments such as planning and feasibility studies, environmental studies, detailed design
of infrastructures, preparation of databases, and surveys. Lump-sum contracts are also adopted in
multifaceted situations and clear-cut assignments in which external factors delay and substantial
changes do not influence the outcome of the advice or study being provided (Palmer, 2000 and
The World Bank, 2002). Recompense is fixed for the duration of the contract; and contingencies
are not provided largely (The World Bank, 2002 and ADB, 2010). Payments are made in
harmonization with a contractually agreed upon timetable at the delivery of an agreed upon
service (ADB, 2010). The next type of contract in consulting practice is the time-based contracts
borders on the provision of services on timely basis; the services provided must be in consonance
with quality specification for which the consultant is paid based upon an agreed unit rates
multiplied by the time utilized by the consultant’s staff in delivering the assignment plus
reimbursable expenses at agreed units (The World Bank, 2002; ACENZ, 2004 and CEBC, 2011).
Time-based contracts require the transfer of cost to clients; monitoring and control systems for
progress of service delivery in order to prevent the incentivization of consulting firms from
putting too much resources and personnel in to the assignment delivery to inflate cost to better
their payment (Wideman, 1987 and ACENZ, 2004). Time-based contracts are appropriate for
consulting assignments whose nature and scope of the services are such that the terms of
reference (TOR) cannot establish them with sufficient precision (The World Bank, 2002;
ACENZ, 2004; ADB, 2010 and Touwen, 2001). For instance in the case of complex or unusual
assignments that are hard to define notably management of complex institutions or studies of
new approaches; the duration and quantity of services depends on variables that are beyond the
control of the consultants, or the services are related to activities by third parties-for instance,
60
supervision of implementation assignments; then in this situations the output required of
consultants is difficult to assess, such as for technical assistance, institutional development, or
emergency situations, in which the client’s needs for assistance may evolve during execution of
the assignment (Panayotou et al., 2000; ACENZ, 2004; ADB, 2010 and The World Bank, 2002);
and transfer of knowledge and training between the consultant and client’s trainees is required
(ADB, 2010).
Another type of consulting contract to be considered is the retainer and/or success fee which are
adopted with the intention of remunerating financial and management advisers who deliver
services to clients in the sale of assets, such as privatization operations (ACENZ, 2004).
Retainer/success fees are suitable when success is related to the efforts of the firms involved and
is relatively easy to quantify (The World Bank, 2002). The retainer/success fee is generally
structured by taking two factors into account namely the value of the asset against which
advisers will be rewarded; and the structure of the incentive itself. The widely used form of
contract in consulting is the percentage contracts; in this type of consultancy contracting,
consultants receive an agreed upon percentage of the actual project cost or of the transaction sale
price (ACENZ, 2004). The percentage form of contract is widely used currently by consultants
operating architecture and construction but there are attempts in some jurisdiction to discourage
its utilization in pricing consultancy services because it offers no incentive to lower the cost of
the services; similarly it has the tendency to induce consultants to adopt more expensive design
solutions in order to increase the absolute value of their remuneration (The World Bank, 2002).
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3.4 CRTITICAL REASONS: TOWARDS AN EFFECTIVE CONSULTING
It is important at this juncture of this review to critically examine and demonstrate the rationale
for the existence of the consultancy industry. This is to identify copiously the factors that compel
clients to seek consulting services. Indeed, empirical research confirms that clients turn to
outside consultants primarily for new ideas, proficiency, and impartiality/objectivity (Gattiker &
Larwood, 1985). Consultants will be hired to provide services as they provide competence not
available elsewhere; they have varied experience outside the client; they have time to study the
problem; they are professionals; they are independent; and they have the ability to create action
based on their recommendations (Bower, 1982).
Consultants offer clients a more efficient allocation of resources by providing specialized
services for limited amounts of time without any obligation of permanent employment on the
part of the client. Consultants, engaged for their superior knowledge, transfer skills and upgrade
the knowledge base of their client while executing the assignment. Knowledge transfer from
consultants to the client often forms an important part of the assignment. Consultants can offer
independent advice to their client on the most suitable approaches, methodologies, and solutions
for their projects (The World Bank, 2002). It is equally important for management to resort to
consulting in circumstances when “management believes that performance could be better but is
not sure what to do to gain improvements; management does not have the specific knowledge
and skills necessary to solve the problems it has identified; management has the necessary
knowledge and skills but not the time or personnel to solve problems; management’s efforts have
not produced the desired long-term improvements; and management requires an independent,
62
third party opinion, either to confirm a decision or to provide alternatives” ( Washburn et al.,
2002).
Uncertainty is one of the major reasons upon which most clients sought to employ consultants to
solve organizational problems; this is clearly demonstrated in Wittreich (1966) that frequently a
client who wishes to acquire a specialized service senses that he has a problem, but is uncertain
as to what the specific character of his problem really is. As long as organizational problems
exist in industries, states, economies; and every organization managed by humans, managers
will always consult to find solution to the daily problems that confront the organization, this
assertion is very significant as ‘the consultancy industry exists because of the existence of
persistent organizational and management problems which creates an ambiance of uncertainty
and exerts difficulty on managers to be seen to be acting both rationally and innovatively
(Blunsdon, 2002). Consultants play variety of roles that will be to the advantage and
improvement of their clients. These multi-faceted roles that consultancy engagements play is
very much demonstrable and copious as consultants fulfill a number of roles that they judge to be
appropriate for the client; the state of affairs; and their own approach (Lippitt & Lippitt, 1986).
Consultants can play array of roles depending on the demands of the condition (Chapman, 1998).
It is very crucial that the consultant in a bid to play its role selects the appropriate roles that will
commensurate with the expectation of the client for the realization of a successful assignment
(Massey & Walker, 1999).
The rationale for consultancy is not only the ability of consultants to identify and analyze
problems thus ‘the importance of consulting has changed from solving problems to building
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clients competence for diagnosing situations on their own and thus managing more effectively;
consultants are worth their fees not only because of their ability to analyze client problems and
provide sound recommendations, but also because of their skills in conducting a human process
that facilitates needed learning and change (Turner, 1988). Lindon (1995) claims that
consultancy is to aid clients to resolve their problems whilst not being eventually answerable for
solving them. Consulting provides a scholarship situation for clients to identify what they need to
know for enhancement and competence of organizations; thus Steele (1975) observed that
learning is the spirit of the consulting process. For instance, in problematic situations; individuals
within an organization experience a problematic situation and enquire into it on the
organization’s behalf that lead them to modify their images of organizational phenomena and to
restructure their activities so as to bring outcomes and expectations (Argyris & Schön, 1978).
Today’s complex business environment requires high transaction costs to function. This in turn
increases demand for symbolic analysts, the kinds of professionals found in modern consulting
firms (Marra & Carlei, 2011 and Canback, 1998). In transaction-cost terms, the external
consultant is more likely than an internal counterpart to lessen the bureaucratic narrow-
mindedness of top management and to reduce internal transaction costs due to misallocation of
resources within and between functions (Canback, 1999, 1998). External consultants can build
experience more effectively than inside consultants; and having seen similar problems before,
the cost to external consultants for leveraging this knowledge base will be low; in contrast,
internal consultants are experts in how their own company works, but seldom are they in a
position to create an experience base by problem type (Papulova & Mokros, 2007). Further ,
specialization in identifying management problems and in developing methodical solutions
(economies of scope) associated with scale advantages due to repeated use of standardized
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methods (economies of scale) allow consultancies to achieve a greater degree of efficiency than
any single firm would be able to acquire (Canback, 1998). The consultant often has the
opportunity to engage in joint problem solving with colleagues (Paroush, 1985).
Reasons for contracting an external consultant can be related to three decisive issues in
management decision making. The first issue is the management capability for information
gathering and analysis that may be extended as consultants for instance consultants having time
to study the problems and have additional proficiency. Consultants’ experience and specific
knowledge can be considered to be another issue, e.g. allowing to perceive where your position”,
to convey knowledge from other industries, to shun reinventing the wheel and “focusing
attention”. As a third issue it is necessary to recognize that consultants may enforce decisions,
“facilitating highly politicized decision-making” when no agreement can be found without
external intervention (Nippa & Petzold, 2002). Permanent exposure to many different problems
and situations in a number of different industries can be considered the main characteristic and at
the same time the unique advantage of consultants (Drucker, 1979).
3.5 EXPLORING THE FUNCTIONS OF CONSULTING
The decision to hire an external consultant may signal concern about employees and about
survival of the organization. Engaging consultants may also serve to mollify dissatisfied groups
and thus prevents de-motivation and low performance or helps to reduce conflicts (Nippa &
Petzold, 2002). Consultancy becomes means to enforce the favored alternative by providing an
accepted, sometimes unquestionable reference; and as consultants do not belong to the client
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company; responsibility for certain decisions and their consequences can be attributed to them
(GIZ, 2010 and Nippa & Petzold, 2002).
Clients are willing to pay more for a higher price signaling quality, when facilitating the
enforcement of their interests (Nippa & Petzold, 2002 and Janes, 2011). In order to prevent a loss
of personal reputation within the social community of the company, as well as a loss of personal
market value, managers may hire consultants especially for risky, difficult or unpopular tasks
and decisions such as lay-offs; if consultants fail or third parties complain about unfair treatment,
insufficient consideration of their goals, or wrong decisions, managers may blame it on the
consultants making them scapegoats. However, if consultants are successful, managers can at
least claim to have hired the right consultants or they can even claim the success their own
achievement (Nippa & Petzold, 2002). Consulting companies fulfill the important function of
transferring and spreading knowledge between organizations and industries. General information
on other industries, competitors, market structures, technological advancements etc. are at first
non-specific and can be used repeatedly. Only through filtering, adapting, and interpreting
provided information the general information becomes firm specific and perceiving consulting
companies as institutions that span boundaries between companies (Scott, 1998). Consulting
firms also act as intermediaries between business research, and university education and the
practical application.
3.6 EFFECTIVE CONSULTING: THE ROLE OF CONSULTANTS
Schein (1990) has significantly demonstrated the critical roles of consultants by the use of three
main categories of models as purchase of expertise, doctor-patient, and process consultation.
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Schein (1990) asserted that the purchase-of-expertise requires clients to hire consultants to render
independent services that address the challenges of the client in a detached manner; the doctor-
patient model has the consultant focusing on using a diagnostic approach to scrutinize the client
organization’s problems. The experience, knowledge and diagnostic ability of consultants aid
them to identify strategic and organizational problems. According to Schein (1990), the process
consultation model considers the consultant as a facilitator with the client actually providing
much of the relevant expertise. Turner (1982) developed the eight task categories to demonstrate
the roles of consultants as: providing information to a client; solving a client’s problem; making
a diagnosis, which may necessitate redefinition of the problem; making recommendations based
on the diagnosis; assisting with implementation of recommended actions; building a consensus
and commitment around a corrective action; facilitating client learning; and permanently
improving organizational effectiveness.
3.7 CLIENTS - CONSULTANTS RELATIONSHIP
Most consultancy assignments originate with the request from the client. A useful technique for
identifying the real decision-maker early in the project is to propose several reasonable outcomes
for the client's problem (IFC, 2007). The reaction to these reasonable ideas indicates whether or
not the consultant is dealing with the real client or the decision-maker. In consulting sector, the
clients are broadly classified into different categories i.e. Government institutions, funding
agencies (Bilateral Agencies and Multilateral Agencies), corporate clients and others like Non-
Government Organizations (Consultancy Development Centre, 2006). It is generally accepted
that how the consultant puts together the consulting process will affect the relationship with the
client and consequently the success of the project (Appelbaum & Steed, 2004 and Curtain,
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2000). In consultancy engagements clients have expectations for the assignment and it is
necessary to examine such expectations of clients for successful consulting thus ‘clients look for
new ideas and an objective perspective. Interviews with 250 executives confirmed that clients are
looking for expert advice. There is also an expectation that consultants will convey their
competencies to company personnel’ (Vogl, 1999). Consulting projects must take time to
importune inputs for execution planning; stakeholder information is also a critical input; proper
project management process must be followed; and the impacts on employees must be
considered and solutions provided to help employees deal with change. There must also be
effective guidance of senior management (Smith, 2002).
Clients require consultants to appreciate their situation; and that they put into consideration not
being overly theoretical; and clients crave tailor made solutions which mirror the challenges they
face, not formulas applied as general panaceas (Appelbaum & Steed, 2004). Consultancy
provides emotional support to both parties, Lundberg and Young (2001) claim that flourishing
consultants need to be in touch with and have ways of dealings with their own concern, their own
moods and sentimental reasons, so as to feel reasonably alert, secure, comfortable and centered
to interact with their clients. Chapman (1998) demonstrates that consultants are engaged in
helping the relationship with the client, rather than simply being a provider of expertise and little
more. Lundberg and Young (2001) affirmed the earlier assertion by Chapman (1998) that
turning emotional anguish into constructive organizational action, even excitement, after all is
what all consultants are really about.
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The most important thing in the work of a consultant is building and maintaining a relation with
client (De Jong & Van Eekelen, 1999). Since emotions are involved in every phase of the
consultancy process, consultants must learn to work smoothly; consultants must be able to create
a climate where clients feel that they can trust the consultant, however (Appelbaum & Steed,
2004), the consultant is to provide exclusive and sole attention to the client and his objectives.
Consultants should never serve more than one master; and consultants should place the client’s
interest ahead of theirs’ (Shenson, 1990). The lack of team and institutional relationship success
is directly related to the failure of the consultants to develop their personal approach to create or
connect with team and institutional marketing efforts (Stumpf & Longman, 2000). Stumpf and
Longman (2000) further opine that a long term relationship must produce a mutually beneficial
result.
McLachlin (1999) significantly demonstrated that climate is critically important, if you find that
your thinking and the clients are not on the same wavelength, do not hang around. Werr et al.
(1997) claim that the consultant and client must be expected to have quite different schemas of
the change process at the beginning of the project. The divergence of opinions forces consultants
to cram to deal smoothly with frail situations (Kakabadse et al., 2006); and one has to develop
the skill of telling clients they are wrong in such a way that they thank you for giving helpful
advice; and one has to learn how to disagree without being disagreeable (Stumpf & Tymon Jr,
2001). It is of immerse importance that the consultant display an enormous proactive behavior
which is necessary for an effective consultant-client relationship thus being upbeat in consulting
implies that the consultant thinks even of those needs and necessities of which a client has not
been aware, and helps the clients to realize all his or her possibilities, and needs (Kubr, 1996).
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The management of the consultant-client relationship cannot be underestimated thus care must
be taken not to scare clients with an uninterrupted flow of words and ideas but rather you have to
listen and try to understand what is their main concern before offering anything, and when you
do that, always use the simplest way’ (Crucini & Kipping, 2001).
3.8 THE CONSULTANCY INDUSTRY: ITS CRITICISMS
The role and efficiency of consultants is subject to numerous criticisms and one cannot write on
consultancy without mentioning the main criticisms overwhelming the role of business
consultants (Kakabadse et al., 2006). Thus Williams (2001) affirms that, external consulting is
never far from criticism; Ormerod (1997) claims that consultants are “opportunistic”; and further
opined that as consultants secure one contract, they are thinking about the next one. Consultants
are perceived to be hypocritical in their pursuit to secure contract from clients (Bloch, 1999). De
Burgundy (1995) also noted that consultants do not render any spectacular services and that their
agenda is to continually keep a particular group of people in employment which of course does
not inure to the relieve of client organizations from their problems.
Consultants are aware of the turbulent environment of managers and that instead of relieving
them from that feeling of uncertainty, managers are kept in that state of mind in order to sell
even more consulting services (Kakabadse, et al., 2006). Massey (2003) argues that consultants
are not at all times conscious of the major theoretical frameworks for organizational consulting.
Even the pervasive nature of consultants has drawn sharp criticisms from both observers and
participants of the industry to the extent that unfavourable jokes about consulting bordering on
unethical behaviours have found their way into critical literature (O’Shea & Madigan, 1997;
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Wooldridge, 1997; Ashford, 1998 and Pinault, 2000). Numerous phrases have been used in
literature to critique the consultancy industry comprising the potential harm that flows from
unworkable or faulty consulting advice (O’Shea & Madigan, 1997); the large sums of money
spent on consultants; the tendency of consultants to sell standardized solutions (Pringle, 1998);
the role of consultants as peddlers of management whims (Gill & Whittle, 1993; Huczynski,
1993; Abrahamson, 1996 and Kieser, 1997); by portraying consultants as folk-devils (Cohen,
1972); and the increasing reliance of managers on consulting advice (Micklethwait &
Wooldridge, 1996 and Shapiro, 1996).
Other criticisms of the expert model of consultancy included the failure of consultants to take
responsibility for their advice, their failure to stay and assist in the implementation of their
recommendations, and that consultants fake standard methodologies or patterns of advice from
client to client irrespective of the specific industry or context (Curtain, 2000 and Appelbaum &
Steed, 2004). Fundamental to these criticisms was a belief that meaningful organizational change
could only result from a consultant who had a detailed understanding of the oddity of the client’s
organization, and that this required long-term and cherished involvement in the client
organization (Kitay & Wright, 2004). Clients complain that consultants’ competencies are rarely
as high as promised, social and emotional skills are scarcely recognizable, advice given, and
results accomplished do not correspond with raised expectations and charged fees, as well as that
consultants would spend most of the time on identifying new problems than on those they have
been contracted for ( Pinault, 2000).
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3.8.1 ARGUMENTS SUPPORTING CONSULTANCY PRACTICE
As a result of the declining philosophy of do-it-yourself over the decades and the inability of
senior executives to utilize problem solving techniques couple with the increasing complexities
in organizational management, it is imperative to seek external support in the very nature of
consulting (Simon, 1976). Arnaud (1998), made a startling revelation that considerable fees
charged demonstrate that the consultant is only interested in money, but if the fee is low, or if the
consultant offers the service free of charge commonly referred to as pro bono, the only possible
interpretation is that the consultant is using the client as a guinea-pig. Williams (2004) contends
some criticisms against the consulting industry are simplistic and just popular views held by
many people which have not been thoroughly investigated.
It has been clearly refuted in Crucini and Kipping (2001) that the perception of consultants as
using vocabulary and words that clients do not understand by making a case that the very nature
of some projects such as process engineering, JIT demands the usage of such terms. There are
unquestionably grounds for criticizing particular consultants in specific instances; however;
broad-brush negative portrayals of the industry appear to contain as much exaggeration and hype
as the purported excesses of their targets (Cohen, 1972); and Kitay and Wright, (2004) also
supported the earlier assertion of Cohen (1972) by claiming that criticisms against consultancy
practice are oversimplification of existing complex issues. In response to the business limitations
of the external role and the critique of expert consultancy, a growing trend within the consulting
industry has been the concept of relationship consulting, whereby a consultancy seeks to develop
long-standing and close relationships with core clients (Perry, 1987 and Brizz, 1998). The
development of closer relations with clients also seeks to deflect criticisms of the expert model
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of consultancy, by emphasizing the consultant’s ability to assist in the implementation of
strategic recommendations (Morris, 2000).
3.9 THE SELECTION OF AN EFFECTIVE CONSULTANCY FIRM
In every assignment engagement, consultants are chosen from diverse background based solely
on technical qualifications since expertise is crucial to the success of the assignment (APEGGA,
2006). The Islamic Development Bank (2005) identified price consideration and cost as selection
criteria for potential consultants to execute projects but concluded that cost is given a higher
weight than price during selection of consultants. The main activities involved in the selection of
consultants comprise of short listing of qualified consultants; determination of selection method
and criteria; issuance of Request for Proposal to short listed consultants; technical and financial
evaluation; and negotiation, award and signing of contract; preparation of the Terms of
Reference (TOR); preparation of the cost estimate (budget); notification and advertising of the
envisaged consulting assignment; drawing up a short-list of qualified consultants; agreement on a
selection method and criteria between the beneficiary; preparing and issuing a Request for
Proposals (RfP) (Islamic Development Bank, 2005). In a bid to ensure the sanctity of selection of
consultants, selection methods have been devised to ensure fairness, clarity, transparency and
confidentiality (JICA, 2009; ADB, 2010; Islamic Development Bank, 2005 and The World
Bank, 2002). In promoting the virtues espoused above, the integrity of the selection process
ought to be maintained by treating critical information confidentially and notifying the winning
consultancy firm for the award of contract and it should be strictly adhered to once a winner has
been notified of an award (Ministry of Finance, 2009 and The World Bank, 2002).
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Depending on the selection method adopted, the selection process carried out by the client
includes the following steps: preparation of the TOR of the assignment; preparation of the cost
estimate to determine the budget of the assignment; advertising to invite expressions of interest
from consultants; short listing to identify consultants qualified for the assignment; preparation
and issuance of the RFP; preparation and submission of proposals by the consultants; evaluation
of technical proposals- quality evaluation; evaluation of financial proposals- cost evaluation;
final combined quality and cost evaluation to select the winning proposal (QCBS); and
negotiations and signing of the contract between the borrower and the consultants (The World
Bank, 2002).
Seven methods for the selection of consultants are provided under the Consultant guidelines; and
these include the following: Quality and Cost Based Selection (QCBS); Quality Based Selection
(QBS); Selection under a Fixed Budget (SFB); Least Cost Selection (LCS); Selection Based on
Consultant’s Qualifications (SBCQ); Single Source Selection (SSS); and Commercial Practices
(CP). The choice of the appropriate method of selection is related to the nature, size, and
complexity, likely impact of the assignment, technical and financial considerations, and the
particular circumstances of the borrower. It is therefore necessary to carefully define the
assignment, particularly the objective and the scope of the services, before deciding on the
selection method (Ministry of Finance, 2009; DevComm, 2005 and The World Bank, 2002).
3.10 CRITICAL FACTORS FOR SUCCESSFUL CONSULTING
The factors that will influence the selection of a consultant are very critical to the consulting
process; and these are crucial for a thorough consultation exercise to occur; thus the key factors
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include breadth of experience that encompasses and goes beyond the situation as defined;
demonstrated ability to complete assignments within budget and on schedule; demonstrated
ability to develop practical recommendations and to have them implemented successfully;
demonstrated ability to work with people diplomatically and effectively and to minimize
disruption of ongoing operations; and degree of trust and rapport established with management
during initial contacts ( Washburn et al., 2002). Schaffer (2002) developed a model of three
specific results necessary for a consulting project to be regarded as a success: firstly, the
consultant must provide a solution or a method new to the client; secondly, the client must
accomplish measurable improvement in its results by adopting the client’s solution; and thirdly,
the client must be able to maintain the improvement over time.
Based on anecdotes; conceptual frameworks; and empirical studies, consulting engagements are
deemed to be successful when they are hinged upon the factors comprising the recruitment of
competent consultants; an emphasis on client results versus consultant deliverables; clear and
well communicated expectations and outcomes; visible executive support and adaptation to
client readiness; an investment up front in learning the clients environment; defined in terms of
incremental successes; real partnership with consultants; and inclusion of the consultants through
the implementation phase (Appelbaum & Steed, 2004).
Adding on to the critical factors necessary for successful consulting, Rynning (1992) advanced
clarity in need/problem formulation; number/quality of new ideas; new knowledge; special
planning; new ways of thinking; level of planning; level of co-operational abilities;
management of time; planning capabilities; efficiency of execution; strategy formulation;
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problem solving; implementation; follow-up; and economy. Consultants gather information
about their client to increase their understanding of the group they were working with and to
develop their intervention, and interpret data for the client, and who provided feedback to the
organization to enhance successful consulting assignment (IFC, 2007). Consultants must exhibit
integrity, in particular by always putting the client’s best interest first; clients must be involved in
the project, and ready to change (Stumpf & Longman, 2000 and IMCA, 2010). It is pertinent
that there is a clear agreement, which may or may not be a formal contract, concerning project
requirements and expectations; the client must ultimately control the engagement, partly by
using clear and limited assignments; the consultants must be competent. Finally, there must be a
good fit between clients and consultants along a number of dimensions, including models of
consultancy, client expectations, consultant capabilities, and consultant type (McLachlin, 1999).
Drawing on from the above, it has been copiously demonstrated by the literature review that
consulting success factors purely borders on both the efforts of consultant, the client and in some
cases both the client and the consultant. Table 3.1 below summarizes the key factors responsible
for successful consulting engagements.
Table 3.1: Summary of consulting success factors
CONSULTING SUCCESS FACTORS LITERATURE SOURCE
A. Consultant
1. Emphasis on client result Appelbaum and Steed(2004)
2. Clear and well communicated outcomes Appelbaum and Steed(2004)
3. Efficiency of execution Rynning (1992)
4. Gathering information about the assignment and interpret it
to the clients
IFC (2007)
5. Exhibiting integrity Stumpf and Longman (2000)
and IMCA (2010)
6. Provide solution to the client Schaffer (2002)
B. Client
1. Effectively control the engagement McLachlin (1999)
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2. Active involvement in the project and accepting change Stumpf and Longman (2000 )
and IMCA (2010)
3. Clarity in problem formulation Rynning (1992)
4. Ability to sustain improvement Schaffer (2002)
5. Adopting the client’s solution for considerable improvement Schaffer (2002)
Source: Author’s Construct (2013)
3.11 FACTORS RESPONSIBLE FOR CONSULTANCY FAILURES
Comparatively only a small number of consulting projects seem to be successful as majority of
projects achieve their goals only partly and with considerable delays (Klenter & Möllgard,
2006); Brunesson (2000) also admitted that consulting projects are sometimes abandon in the
implementation phase while Obolensky (2001) confirmed that numerous implementation plans
do not survive contact with reality. Some consultants acknowledge in general that regardless of
all our efforts and good intentions, many of their methods and interventions do not meet the
desired goals of their engagement in totality (Warren, 2004). Others suggest a failure rate
between 25 and 50 percent (Czander, 2001), or estimate that even 80 percent of all consulting
interventions fail (Zackrison & Freedman, 2003). In other cases, the consultants’
recommendations have disastrous consequences for the organization (O’Shea & Madigan, 1997;
Byrne, 2002; Sorge & van Witteloostuijn, 2004). At other times, failure is attributable to
personal characteristics of the consultant and client (lack of skills), technical shortcomings
(ineffective project management), unstable or bad consultant -client relationships (lack of
communication), and/or socio-political aspects of the client organization (e.g. hidden agendas;
unreadiness for/resistance to change) ( Seidl &Mohe, 2007). The two issues responsible for most
failed consultations are notably the intrusion of internal politics into the consultation process and
the failure to clearly establish and maintain consensual goals (Lister & Pirrotta, 1996). The most
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critical reasons for failed consulting projects are the absence of tight project controlling and an
bloating of projects cost (Klenter & Mollgard, 2006).
Drawing on from the above, it has been realized that consulting failures emanates from diverse
sources hinged on the opinions of several authors in consulting research. It is important to
summarise the key factors responsible for consultancy failures in Table 3.2 below.
Table 3.2: Summary of consulting failure factors
CONSULTING FAILURES LITERATURE SOURCE
1. Considerable delays (Klenter and Möllgard ( 2006)
2. Project abandonment at implementation phase Brunesson (2000)
3. Executing unpractical implementation plans Obolensky (2001)
4. Methods adopted not meeting the desired goals of
engagement
Warren (2004)
5. Implementing disastrous consulting recommendations O’Shea & Madigan (1997); Byrne(
2002); Sorge & van Witteloostuijn(
2004
6. Lack of desirable personal characteristics for
Consulting.
Seidl & Mohe (2007)
7. Internal politics in organizations creeping into the
consultancy process
Lister & Pirrotta (1996)
8. Lack of consensual goals Lister & Pirrotta (1996)
9. Absence of project control and inflating project cost Klenter & Mollgard (2006)
10. Bloating of project cost Klenter & Mollgard (2006)
Source: Author’s Construct
3.12 TERMS OF REFERENCE: THE BASIS OF AN EFFECTIVE CONSULTANCY
The Terms of Reference (TOR) is the key document in the Request for Proposal (RFP). It
explains the objectives, scope of work, activities, tasks to be performed, respective
responsibilities of the client and the consultant, and expected results and deliverables of the
assignment (Westland, 2007). The TOR constitute the basic document defining the work that the
consultant is required to perform and, together with any modifications thereof at the negotiation
stage, becomes part of the contract that is eventually entered into between the consultant and the
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client. The Islamic Development Bank (2005) and The World Bank (2002) detailed the
composition of the TOR to include the scope and objective of the project (GNPC, 2009 and
ADB, 2010); relevant background; types of services required; implementation schedules and
outcomes; transfer of technology and training; method of remuneration; responsibility of clients
and consultants; main terms of conditions of appointment; and duration for execution of
assignment. Transfer of knowledge have also been identified recently to be critical part of TOR
formulation for projects; in this instance, the TOR provides for specific inputs of consultants
regarding the training approaches and methods the consultants intend to propose to the client for
consideration ( NPA, 2007; Ministry of Finance, 2009 and The World Bank, 2002 ). A key
requirement contained in the Terms of Reference that cannot be swept under the carpet in any
consulting engagement is reports and their schedules of delivery. It is in this direction that
several forms of report have been identified to include inception report (NEPA, 2009; The World
Bank, 2002; SADC and ZRA, 2006); progress reports(The World Bank, 2002 and Ministry of
Finance, 2009); and interim reports(The World Bank, 2002).
In particular, TOR should include name of the client; project location; rationale of the project;
project history (what has been done so far and by whom); list of relevant studies and basic data;
need for consultants in the project and issues to be resolved; activities to be carried out by the
consultants; source of financing for the assignment; and supervision arrangements (ACENZ,
2004). Adequate and clear TOR is important for the understanding of the assignment and its
correct execution; and reduces bottlenecks in the nature of extra works and expenses; delays;
ambiguities in proposal preparation, contract negotiation and execution (Ministry of Finance,
2009).
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3.13 THE ART OF PRICING CONSULTANCY SERVICES
In principle, pricing is an important issue; among the numerous activities that the consultancy
industry undertakes notably the transfer of knowledge and expertise relating to how to do various
tasks, how to measure and how to communicate the fact and extent of it to the public (ACENZ,
2004 and ADB, 2010). The potential benefit of each of these activities can be achieved only at a
cost; and pricing is the medium through which these benefits can be realized by mediating
between benefits and costs. At a social best, costs and benefits would be equated at the margin
and this would require the prices of consultancy industry products and services to be neither too
high nor too low (Young et al., 2003 and Jacquemin, 1990). In an oligopolistic market, there is
no achievement of optimum pricing as identified above rather the market is witnessed by price
wars; collusive pricing agreements; and implicit collusion (Young et al., 2003).
Consultancy pricing is affected by a number of factors including the client’s need for special
knowledge and experience; how much competition for clients there is; the consultant’s
reputation; and, if known, the benefit to the client of a successful outcome (ACENZ, 2004).
Consultancy pricing manifest in diverse shades by stage pricing till the final submission of
reports; flat fee pricing; and payment in advance (ACENZ, 2004). Serving in advisory position
on consulting assignments gives the opportunity to consultants to price their services by flat fee
nomenclature for each advisory session that services are provided (ADB, 2010). Variations to
pricing consultancy services occurs when consultants encounter clients preferring contingency
pricing; this form of pricing consultancy services may work depending on the cardinal principles
of integrity from both client and consultant (ACENZ, 2004 and ADB, 2010).
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Consultancy services cost include expenses for travel, entertainment, communications, and
special services on monthly intervals (Washburn et al., 2002); consultant staff remuneration;
travel and transport; mobilization and demobilization; staff allowances; communications; office
rent, supplies, equipment, shipping, and insurance; surveys and training programs; report
translation and printing; taxes and duties; and contingencies (JICA, 2006 and The World Bank,
2002); salary and wages; net profit; staff benefits; and overheads (CEBC, 2011). In terms of
travels and transport remuneration structure comprises local travel and transport costs based on
local tariffs; number and type of vehicles including operation and maintenance costs while
mobilization and demobilization may include reasonable travel time, a medical checkup, hotel
costs, local transportation, and miscellaneous items and costs for shipping personal effects
should also be estimated (TRF, 2011 ).
Cost estimates in consultancy pricing take cognizance of number of experts required for
assignment (Elliott, 2009 and ADB, 2010). It is important to define these inputs as accurately as
possible when preparing cost estimates, it is useful to draft bar charts indicating the time needed
to carry out each main activity (activity schedule) and the time to be spent by the consultant staff
(staffing schedule) (Department of Energy, 2011).
Cost estimates include a breakdown of the total costs of the assignment; hence consultant staff
remuneration may be subdivided into professional or high-level specialists and support staff
(Butcher & Demmers, 2003). Remuneration rates for staff vary according to sector and depend
on the experience, and qualifications of the consultants (ADB, 2010 and The World Bank, 2002).
In general, staff remuneration rates include different proportions of the following components,
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depending on company and industry specific factors and country laws namely basic salary;
social charges; overhead; fees or profit; and allowances (Ministry of Finance, 2009).
As far as communication cost is concerned, reasonable monthly allocation for international and
local telecommunications; and teleconferencing and the Internet are tolerable (PPB, 2003). In the
case of cost build up for office utilization to deliver consulting services to clients, consideration
is given to office rent; supplies, office equipment and insurance (c.f. The World Bank, 2002).
Taxes and duties also form part of the costing of consultancy services for pricing agenda, taxes
and duties that normally form part of consultancy services cost include value added tax(VAT)
and levies (ACENZ, 2004 and The World Bank, 2002). Contingencies in pricing of consultancy
services are twofold in the nature of physical contingency ranging from 10 to 15 percent
encompassing issues notably price items; providing for unforeseen work; monetary inflation
(Washburn et al., 2002 and The World Bank, 2002); and price contingencies which are
considered to cushion inflationary impacts (The World Bank, 2002).
It is essential that the cost estimate fully cover the requirements of the TOR to ensure that the
financial commitments of the consultants fully reflect their technical proposals, which if
inaccurate could result in deficient proposal evaluation and contract award, and unsatisfactory
contract implementation (Washburn et al., 2002 and Islamic Development Bank, 2005). Finally,
consultancy costs are categorized as remuneration (fees) and reimbursable cost items (travel and
transport, communications, office rent, local staff salaries, local taxes, etc.). Local taxes (indirect
and direct) and customs duties on imported equipment and supplies shall be identified separately
(Islamic Development Bank, 2005).
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3.14 APPRAISAL AND SYNTHESIS OF THE LITERATURE REVIEW
In view of the elaborate review of the above literature on various aspects of the consulting
industry, it is imperative to draw some conclusion on the subject matter. It can be concluded that
consultancy is a process of finding solution to perceived genuine problems existing in
organizations by soliciting the expertise of individuals or organizations that are not part of the
customer organization to study, analyze and suggest solutions to the existing problem for
implementation. Consultancy can be classified into management consultancy and engineering
consultancy. Engineering consultancy involves the use of physical laws and engineering
principles to solve problems in the fields of design, construction, and operation of structures,
mining, manufacturing, transportation, structures and environment. Management consultancy
deals with the analysis of management problems in organizations and recommending solutions
for these problems for implementation. This type of consultancy is suitable for areas such as
accountancy, auditing, management public relations and communication, customer care
management, lobbying, global analysis and others like the legal consultancy. Consultants can be
classified according to the manner in which they approach their consulting assignment; hence
consultants can be seen approaching their duties as mental adventurers, strategic/navigator,
management physician, system architect and friendly co-pilot. The structure of the firms
operating in the consultancy industry is demonstrated as partnerships, private companies,
corporations, financial institutions, procurement agencies, government organizations, NGOs,
universities and research institutes.
It has also been identified that the consultancy industry is segmented along the specialization of
industry practitioners, this thus make the industry to be purely a knowledge base industry. The
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works of Consultancy Development Centre (2006); Young et al. (2006); The World Bank (2002)
and Islamic Development Bank (2005), copiously demonstrated that the consultancy industry can
be in functional areas such as banking, accounting, management, law and all aspects of
technology and engineering. Consultancy services are the ‘goods’/ ‘products’ manufactured by
the consulting industry. In this light, any services rendered intellectually and advisory in nature
to clients by the use of skills/expertise of consultants can be regarded as consulting services. The
literature review revealed consulting services as master plans, feasibility studies, design studies,
tender documentation, procurement assistance, construction supervision, project management,
policy and strategy, knowledge transfer, commissioning, management, institution building,
identification and investment priorities, planning, valuation, cost estimates, preparation of
drawings, specifications, project management, implementation, environmental studies and
impact, financial analysis, forensic, research and development and IT. It is important to note that
as long as knowledge continues to evolve and problems keep on emanating in areas that are new
to humans, consultancy services will emerge from these areas. This assertion is strongly
reinforced by the evidential evolution of the computer age leading to rise in Information
Technology (IT) consulting services which were not part of the traditional consulting services.
Contracts serve as the basis for the definition of roles and responsibility of the parties to a
consulting assignment. Contracts also serve as the conduit or modalities for the payment of
consultancy fees by clients to consultants. The literature review led to the identification of
consulting contracts consisting of lump-sum, time-based, retainer and/or success fees and
percentage contracts. The type of contract arrangement chosen is determined by the nature of the
consultancy assignment. It is also imperative to identify the rationale as well as the situations that
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necessitate the procurement of consultancy services. In this vein, the services of consultants are
engaged by clients to provide: new ideas, proficiency; where impartiality is needed; to inject
competency not existing into the system; provide and infuse experience gathered into the client’s
organization and in addition; consultants have time not available to the client to study problems;
consultants are professionals and have wealth of expertise; and upgrading client’s knowledge by
transferring skills. Situations which necessitate consulting manifest in organizations as a result of
management’s quest to realize an improved performance but do not know the process of
achieving such a goal; when it is obvious that the client does not have the requisite skills and
knowledge to solve problem; in situations where the efforts of the client does not produce the
desired result; when the client has the knowledge and skills but not the time or personnel to solve
the problem.
Consultancy functions in diverse ways by making clients as well as customers robust and
efficient. The review of literature on the consultancy industry revealed vital functions of
consultancy such as conflict reduction; helping to enforce favoured alternative; preventing the
loss of personal reputation and market value; serving as intermediary between research and
business. In order to facilitate these functions of consultancy enumerated above, consultants
ought to play crucial roles such as provision of independent perspective to bear on the challenges
facing clients; diagnostic approach in the examination of the client’s problems; and the serving
as a facilitator in all respect as far as the consulting assignment is concerned.
The client-consultant relationship is very vital to the realization of both the functions of
consultancy and the role of consultants. The manner in which the consultant institutes the
consulting process will affect the relationship with the client and consequently the success of the
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consulting assignment. It is demonstrated in the works of Appelbaum and Steed (2004) that the
client-consultant relationship is fundamentally linked to the success of the consultancy
assignment. Consultants provide emotional support to their clients and customers by making
them alert, secure, comfortable and interactive. The consultant ought to be proactive in behavior,
and must ensure that his words and ideas do not scare clients and customers. The types of clients
also determine the nature of the relationship that exists between client and consultant. Clients in
the consultancy industry include: contact clients, intermediate clients, unwitting clients, indirect
clients and ultimate clients.
Enormous literature have revealed that consultants are criticized as being opportunistic; not
performing any real practical role; consultancy has done little to revive management; consultants
keep managers in the state of uncertainty to sell their consultancy services; having pervasive
influence; the harm that flows from consultancy advice; huge sums of money spent on
consultancy; consultants do not take responsibility for their advice; and their inability to stay and
assist in implementation. In spite of these criticisms, other works demonstrated their support for
consultancy; and these supports in favour of the industry that; the decline in the ‘do it yourself’
philosophy as a result of inefficiency has brought the consultancy industry in to the fore. The
accusation that the consultancy industry charges high fees is untenable since price is
axiomatically the measure of value and quality which goes to support the fact that consultancy
services are of high standards. Again, all the criticisms against the consulting industry have not
been empirically verified, they are just the thought or the imaginations being expressed and
oversimplification of issues.
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The selection of consultants or consultancy firms is also an important area in the industry.
Technical qualification and price consideration are very pertinent in the selection process. The
selection process is to ensure fairness, clarity, transparency and confidentiality. The selection of
consultants consists of short listing qualified candidates, determination of selection methods and
criteria. The seven methods of selecting consultants consist of Quality and Cost based Selection
(QCBS); Quality based Selection (QBS); Selection under a Fixed Budget (SFB); Least cost
Selection (LCS); Selection Based on Consultant’s Qualifications (SBCQ); Single Source
Selection (SSS) and Commercial Practices (CP). The appropriateness of each method is based on
the nature, size, and impact, technical and financial considerations.
The factors responsible for successful consultancy assignment cannot be underestimated in any
attempt to have a critical overview of the industry. These factors are crucial for a vibrant and
thriving industry. Works such as Washburn et al.(2002); Appelbaum and Steed (2004); Rynning
(1992); Stumpf and Longman (2000) have copiously demonstrated the successful factors for
consultancy as: experience beyond the situation defined; ability to complete the assignment
within the stipulated budget and time; diplomacy; trust and rapport; ability to develop practical
recommendations; competence; excellent communication; executive support; partnership; clarity
in problem formulation; quality of ideas and follow-ups. In so far there are factors that propel the
consulting industry; there exist factors that contribute to its failure. Czander (2001) contends that
the failure rate of successfully executing a consulting assignment is between twenty-five (25)
and fifty (50) percent; this is further supported strongly by Zackrison and Freedman (2003) that
eighty (80) percent of all consulting interventions fail. Consulting failures manifest as a result of:
technical inadequacy; poor personal characteristics of both client and consultant; unstable client-
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consultant relationship; poor social and political environment of the client’s organization and
unwillingness to change on the part of the client.
The Terms of Reference (TOR) is a vital document in the request for proposal (RFP); it serves as
the basis for effective consulting and defines the objective, scope, activities, tasks,
responsibilities, expected results and deliverables of the consulting assignment. The TOR helps
in the effective pricing of consulting services rendered to the client. Pricing is the medium
through which the consultant receives remuneration and it is a vital process in the consulting
industry. The consultant’s remuneration for that matter price (fees) is significantly affected by:
competition; consultant’s reputation; the need for special knowledge; and experience.
Consultants’ remuneration as fees come in the form of flat fees; contingency basis; billing
separately for expenses. The most reliable way of arriving at these fees is by cost estimating. The
cost estimate for consultancy assignment encompasses consultant’s staff remuneration; travel
and transport; mobilization and demobilization; communication; staff allowances; rent;
equipment and supplies; taxation; shipping; surveys; training programs; legal; and accounting
services. These components of the cost estimate for consulting can be classified as direct cost
and overhead/indirect cost.
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CHAPTER FOUR
QUANTITY SURVEYING PRACTICE IN CONTEMPORARY GLOBAL
ENVIRONMENT: A GENERAL OVERVIEW
4.0 INTRODUCTION
This chapter is very pertinent to this research, in view of the fact that it comprehensively
reviewed quantity surveying practice in order to position well in the globalize complex
construction industry. The review consist of the meaning of quantity surveying; the role of the
quantity surveyor; the changing roles of the quantity surveyor; quantity surveying consultancy
services; non-traditional quantity surveying consultancy services; quantity surveying consultancy
services pricing(fees); challenges confronting quantity surveying services pricing; challenges
confronting quantity surveying practice; professional misconducts in quantity surveying practice;
the adoption of ICT in quantity surveying operations; and bills of quantities (BOQ), the most
valuable working document of the quantity surveyor.
According to Olatunde (2006); the Quantity Surveying Profession has developed a long way
spanning over two centuries ago when it was only a measurement and accounting profession.
Over the years the role of the Quantity Surveyor (QS) increased, partly to the rapid development
and urbanisation of cities and town and with increased emphasis placed upon costs of building
(Olatunde, 2006). In order to accurately forecast and control costs the profession began to
develop various methods. Only initial costs in use were taking into account. The importance and
work of the Quantity Surveyor expanded during the 1980s due to the interest in whole life cycle
costing.
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Various challenges faced the profession by the end of the twentieth century. The Profession has
been able to develop and utilize skills more usefully due to the increased activities associated
with information technology which removed some of the repetitive tasks associated with their
work. In addition to solely considering initial costs of construction emphasis has shifted to
identifying and adding value to the development process. All over the world Quantity Surveyors
are now involved in a variety of projects ranging from homes, airports, power stations, highways,
sports stadium to offshore oil rigs. They are involved at all levels of the process, starting with
advising on the initial proposal for a project to meeting the client’s needs, right through its
working life and even how to recycle the building. They provide complex solution based services
on a scale that few have imagined. Although Quantity Surveyors (QSs) do still provide
traditional services, they now service new industries and offer a wider spread of services to a
wider spread of clients. This is opening new commercial possibilities for QSs whether working
for companies, client groups, contractors or other advisory and consulting firms.
4.1 THE MEANING OF QUANTITY SURVEYING (QS)
Anago (2006) observed that quantity surveying, as a basically cost-literate profession, should
play a key role in developmental resource allocation, the core- efficiency driver in economic
development. Quantity surveying as a numeric discipline has a peculiar dynamism that should
enable it drive competition in the market place (Anago, 2006). According to Olawale (2006), a
quantity surveyor is the financial professional of the construction industry whose training and
experience qualify him to advise on cost and arrangement of projects and to prepare contract
documents in respect of such project. As opined by Westcott and Burnside (2003); quantity
surveying is the central importance of measurement or quantification is clearly confirmed, as it
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distinguishes us (the QS) from the architect as designer and the engineer who delivers function.
According to RICS (1991) a quantity surveyor is a professional who ensures that the resources of
a construction industry are used to the best advantage by providing sound financial management
and consultancy service to the client during the construction process. The quantity surveyor is
appointed to provide advice to the client; offer alternative design solutions; and be responsible
for specific aspects of the project where integration of knowledge from various subject areas is
concerned (Bonnar, 2007).
4.2 THE ROLE OF THE QUANTITY SURVEYOR
As a professional of the construction industry, the quantity surveyor acts in liaison with other
professionals particularly the architects, the builders, the engineers, the estate surveyors and
valuers, the constructors/contractors and the suppliers to safeguard the client’s interest. A large
part of the quantity surveyor’s work is directly or indirectly related to aim of achieving a
reasonable contract price (Olawale, 2006). According to Eke (2006), quantity surveyors take a
methodical and balanced approach to all tasks, an approach which is often lacking in other
professionals allied to the building industry. Again Eke (2006) asserted that it is in the area of
cost control that the QS play the dominant role. As the financial expert it is incumbent on the QS
to establish maintain and update realistic cost reporting and monitoring and financial
management procedures, which take full account of the client’s requirements and cater for all
aspects of the particular infrastructure (Eke, 2006).
McGaw (2007) opined that clients employ quantity surveyors to maintain budget surplus thus
controlling the finance of the project; providing realistic price for development as shown on the
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drawing supplied by the architect; provide adequate feedback on documentation provided for
tender purposes, thus reducing the uncertainty placed on the developer who must carry the
burden of construction contingency. In similar manner, McGaw (2007) further asserted that the
quantity surveyor provides budgetary options in the post contract when design deficiencies need
to be resolved; the position of McGaw (2007) is further confirmed by Burnside and Westcott
(1999) that the traditional role of the quantity surveyor is to provide advice about cost and
financial management of construction process. Also, Bonnar (2007) adds that the quantity
surveyor is a professional with myriad of expertise in technical ( understanding of the methods
of construction, materials used, and the principles of building design); professional (quantifying
drawn information to provide bills of quantities or other documentation for pricing); managerial
(understanding the principles and processes of management construction, project and resource);
financial undertaking the responsibility for cost control( setting budget limits at inception,
financial control during construction, settlement of the final account on completion); and
provision of legal (advice on appropriate procurement routes (forms of contract) including the
rights, obligations and remedies of each party to the contract).
4.2.1 The Changing Roles of the Quantity Surveyor
As globalization is increasing, the role of all professions over the world is changing and the
quantity surveyor is of no exception; Ashworth (1981) pointed out that the role of the quantity
surveyor has changed significantly over the decades. Ashworth (1981) further buttressed this
point by asserting that thirty years ago, the of the quantity surveyor was the preparation of bills
of quantities and the final account only but in recent years the role of the quantity surveyor has
changed from cost to value with emphasis on procurement and management skills (Ashworth,
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1994; RICS, 1991). This claims were further confirmed by the empirical study of Keel et al.
(1994) in which they found that 80% of clients see the role of the quantity surveyor as changing;
and 67% of respondents in the study see the role of the quantity surveyor to be increasing in
areas of project management, lead consultancy, cost and value management, mechanical and
electrical services and advising on overseas methods and costs.
4.3 QUANTITY SURVEYING CONSULTANCY SERVICES
In terms of contract phases; Olatunde (2006) variedly classify consultancy services provided by
quantity surveying professionals in contract phases or stages as pre contract work (sector-
specific design advice; early stage comparative cost planning; advising on cost of design
options; analysis and scheduling of work; measuring work to define rules; preparing cost
estimates; preparing tender documents; drafting contracts; assembling frameworks;
benchmarking and value management; funders/mergers and acquisitions due diligence); post-
contract work (acting as contracts administrator; valuation of variations; valuation of work in
progress; valuation of variations; settling final accounts contractual advice; evaluation of
claims for additional cost; settling final accounts; setting capital allowances calculations; acting
as adjudicator or mediator; acting as expert witness or arbitrator; risk management). In
management of contracts the consultancy services provided by quantity surveyors; Olatunde
(2006) further identify services rendered by quantity surveyors in terms of management by
clearly demonstrating project management services as (the management of the overall planning,
control and co-ordination of a project, or portfolio of projects, from inception to completion to
deliver the clients' objective); facilities management (this encompasses capital expenditure,
facilities management and lifecycle costing, preparing frameworks through procuring service
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and implementing performance driven solutions; building engineering and ground maintenance
and health and safety issues); program management ( this consist of all facets of major
programme such as project controls, communication platforms, design standards and
management, policies and procedures, resourcing and procurement).
Olatunde (2006) observed that critical future program management roles are likely to include
provision of services in the energy sector in the building of power stations and distribution of
energy to consumers); development management (this involves the management and co-
ordination of all key areas of the development process, from site location searches and studies,
preparing feasibility studies, managing the design and procurement process, construction process
and design team to facilities management of completed building); supply chain management
(supply-chain management is a radical approach to procurement. It aims to set up long-term
relationships with suppliers in order to develop leaner, value-adding and more efficient ways of
working. It offers simplification and risk reduction and significant cost savings); construction
management (it entails construction advice, design management, logistics, programming,
procurement of trade packages, direction and control of the construction site, commercial
management and payments, safety management and quality management); and project
monitoring (quantity Surveyors providing this service ensure that planning conditions are
cleared, surveys have been undertaken, insurance levels are correct for the type of project and
chosen procurement route and building contract is correct for the project) (Olatunde, 2006).
Olawale (2006) also demonstrated clearly the services that quantity surveyors render to their
clients as estimating and cost advice often referred to as preliminary cost advice; advising on
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contractual methods; advising on contractor selection; preparing tender documents; obtaining or
negotiating tenders; cost planning; valuing construction work; preparing and agreeing accounts
with contractors; preparing expenditure statements for tax and accounting; technical auditing;
and assessing replacement values for insurance; project control; giving expert evidence in
arbitration and disputes; feasibility studies; investment appraisals; cost control and post contract
management; project management and co-ordination; value management; risk management;
security management; financial analysis; condition surveys; expert witness advice; property
management; asset management; property condition appraisals; and facilities management.
Anago (2006) asserted that quantity surveying is an aggregation of various skills and disciplines
which come under the umbrella of procurement management (consisting of preliminary cost
advice; estimating; measurement and quantification; advising on contractual methods; advising
on contractor’s selection; preparing tender documents; obtaining or negotiating tenders/bids;
valuing construction work; preparing and agreeing accounts with contractors; project control;
cost control and post contract management; project management and co-ordination; scheduling
and planning; technical auditing); management advisory services(consisting of feasibility and
viability studies; cost planning/management; property management; facility management; asset
management; property conditions appraisals; risk management; conditions survey; value
management, analysis and engineering; and replacement cost for insurance purposes); financial
advisory services( consisting of investment appraisals; financial analysis; life cycle costing;
expenditure statements for taxation and account purposes; capital allowance management; and
due diligence studies); and legal advisory services( includes expert testimony/litigation support;
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arbitration; dispute and conflict management (ADR); advice on claims preparation and claims
defense; contract auditing).
Burnside and Westcott (1999) identified the traditional services rendered on technical basis by
the quantity surveyor as preparing the cost plan and the bills of quantities, tender documentation
and tender appraisal, interim payments, measuring and valuing variations, advising on
anticipated final costs and preparing the final account. Seeley (1997) clearly pointed out the
services provided by quantity surveyors as preliminary cost advice; cost planning and cost
checking; advice on contracting methods; construction procurement systems; valuation of
construction work; preparing tender documents and negotiating contract prices; preparing
contract documents and participating in contract administration; preparing cash flow forecasts
and exercising cost control over the project; value management; interim valuations and
payments; financial statements; variations, final account preparation and agreement; project
management; settlement of contractual claims; and giving expert evidence in arbitrations and
disputes. The services identified by Seeley (1997) are provided in wide range of projects as
identified by Davis et al. (2007) to include building construction, civil and structural
engineering, mechanical building and engineering services, petro-chemical, mineral extraction,
planning and urban.
The Canadian Institute of Quantity Surveyors, CIQS (2002) adds cost consulting (consisting:
feasibility studies and conceptual estimating; project budgeting; cost planning / cost control
estimates (in either elemental or trade format); assembly of tender packages; tender review and
contractor selection; functional cost analysis; review and recommendation of project progress
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payments; review and negotiation of change orders and contractual claims) ; mortgage
monitoring (consisting: review and verification that project budget is adequate to complete
project; progress draw review and monitoring of costs incurred; and verification of borrower
payments; value management( incorporating: review of project program, design and cost studies;
service provider for value management workshops; evaluating processes and components;
preparation of recommendations); life cycle costing( including: life cycle cost plans; discounted
cash flows; sensitivity analysis); and Other Services( consisting: reserve fund studies and cost to
complete reports; property condition reports; risk analysis; insurance replacement cost
assessment; project management; project scheduling; construction management; construction and
project cash flows; mediation and arbitration; expert witness; bills of quantities and/or materials;
material take-offs).
4.3.1 NON-TRADITIONAL QUANTITY SURVEYING CONSULTANCY SERVICES
Olatunde (2006) again identify services that quantity surveyors can provide in seemingly non-
traditional sectors as in oil and gas (quantity surveyors provide services such as management of
capital expenditure, procurement management and construction management); in rail network,
quantity surveying (QS) services include cost and business planning, procurement and supply
chain management, commercial management, facilities management of stations, risk and value
management and whole life cycle cost management; in the power sector, Olatunde (2006)
observed cost planning and budgeting, program management and construction management,
expertise in maintenance programme, providing advice on procurement strategy, contract
administration, project management, development and facilities management.
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According to Olatunde (2006) the expertise of the QS in the telecommunication sector
encompasses cost planning, cost management and reporting; and in airports and air
transportation, Olatunde (2006) opined that quantity surveyors are needed for preparing
development appraisals, advising client on project brief, preferred procurement route and cash-
flow, advising whole life costs, planning the construction process, controlling the project on
behalf of the employer, to risk and value management.
4.4 QUANTITY SURVEYING CONSULTANCY SERVICES PRICING/FEES
According to Fee Bureau (2011) quantity surveying fees relate to the full service provided by
quantity surveyors at the pre-contract and post-contract stages of a project; and fees are
expressed as a per cent of total building construction cost. The Fees Bureau(2011) further
asserted that the services rendered for fees consist of preparing full bills of quantities; tender
documents; tender reports and contracts; valuation of works in progress; preparing final
accounts. The Fee Bureau (2011) opined that fees exclude expenses and VAT.
The Alberta Infrastructure and Transportation (2005) clearly pointed out that fee calculation
should be based on the anticipated construction cost, the schedule and the scope and nature of
work contained within the approved budget for the project. The Alberta Infrastructure and
Transportation (2005) uses the project phase, report provided by cost consultant (quantity
surveyor) and the amount in percentage as key guidelines in the calculation of fees. For instance
the Alberta Infrastructure and Transportation (2005) adopted the following criteria for its fee
calculation as a feasibility report at the functional phase of a project attracts five percent(5%) of
the amount of project cost; design selection studies in the block schematics phase attracts seven
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and half percent (7.5%) of project amount; schematic design cost plan at the selected sketch
design phase of a project attracts twelve and half percent (12.5%); design development cost
check at the design development phase attracts twenty percent(20%) of the project amount; cost
checks, pre-tender estimate reports at the construction documents preparation phase attracts fifty-
five percent(55%) of the project cost; and tender analysis report during the bidding phase attracts
fifty-five percent (55%) of the project amount.
These guidelines of Alberta Infrastructure and Transportation (2005) are in consonance with the
practice of The South African Council for the Quantity Surveying Profession (2010) which
opined that appropriate percentage the basic fee shall be apportioned to each category before
multiplying each apportionment by the applicable appropriate percentage. In contrast The South
African Council for the Quantity Surveying Profession (2010) apply the appropriate percentage
for fess in categories such as alteration works, building works, redecoration works, replication,
multiple procurement contracts, civil engineering works, electrical engineering works,
mechanical engineering works and process engineering works. The Alberta Infrastructure and
Transportation (2005) opined that the agreed fee may be varied for any of the following reasons:
a significant approved variation in scope or nature of the project; a significant approved variation
in schedule of the project; project suspension or abandonment; and termination or suspension of
cost consultant services. Any variation in fee amount shall take into account the cost of the
services completed. Snyman (2004) in a survey identified factors influencing fee proposals as
prospects of follow-up work 44% ; credibility of client 31%; affordability of the fee 20%; type of
contract 20%; and competitiveness of the market 7%. Other fee influencing factors identified in
Snyman (2004) consist of availability of suitable personnel; location of the project; programme
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of the project; current workload; level of service required; complexity of the work; and client
involvement. According to Cruywagen and Snyman (2005) the services rendered by quantity
surveyors can be priced in stages namely estimating and cost advice attracting ten percent (10%)
fee; tender documentation which attract twenty percent (20%) fees; contract administration stage
with forty seven and half percent (47.5%); and final account stage which attracts twenty-two and
half percent (22.5%).
4.4.1 CHALLENGES OF QUANTITY SURVEYING SERVICES PRICING/FEES
Just like any other profession which is bedeviled with challenges, the quantity surveying
profession is not an exception; thus Cruywagen and Snyman (2005) observed that it has become
a norm for professional quantity surveyors to offer reduced professional fees on construction
projects as a result of the competitive nature of the market. Cruywagen & Snyman (2005) further
opined that these reduced professional fees offered by quantity surveying practitioners usually
fall far below what is considered a fair remuneration for services rendered. In their empirical
studies, Cruywagen and Snyman (2005) asserted that quantity surveying fees can be rendered
affordable on a particular project types but the quantity surveyor will be more exposed to risk;
and that the risk further increases with a decrease in project value. In tandem with the findings of
Cruywagen and Snyman (2005) on fee reduction; Smith (2004) in a survey on trends in the
Australian quantity surveying profession identified fee cutting as a threat to the quantity
surveying profession. In a descriptive survey conducted, Snyman (2004) found out that eighty-
six percent (86%) of quantity firms offer discount in the between sixteen percent(16%) and
twenty(20%) on the recommended fees of Association of South African Quantity Surveyors
(ASAQS) to their clients in the Gauteng province of South Africa. Hoxley (1998) observed that
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the fee cutting syndrome is prevalent among quantity surveying practitioners even to the point of
venturing in to loss-making territory. Also Cruywagen and Snyman (2005) opined that it is
universally accepted that the fee reduction syndrome invariably compromises quality; this
position is supported by Hoxley (1998), that most players in the market acknowledge that the
quality of work suffers when fees get below certain point.
In the light of the above shortcomings of the professional fees, Cruywagen and Snyman (2005)
in their empirical research posed some pertinent questions which are worthy of critical
consideration, namely on what basis is the tariff of professional fees calculated? Are there
differences between various types of construction projects? How do quantity surveyors
determine their proposed fees on construction projects? and how can an affordable fee be
calculated on construction projects? Also Cruywagen and Snyman (2005) observed a fluctuation
in the tariff of fees charged by quantity surveyors and concluded that poses a risk allocation to
the quantity surveyor.
4.5 CHALLENGES CONFRONTING QUANTITY SURVEYING PRACTICE
There are numerous challenges confronting the QS profession especially in contract
arrangements for execution of projects. Thus according to Odeyinka (2006), the QS faces
response challenges in contractual arrangements such as Private Finance Initiative (PFI) and
Public Private Partnership (PPP); supply chain management; partnering and alliancing; prime
contracting; and performance based contracting. Again Odeyinka (2006) identify other
challenges facing the QS profession as the challenge of appropriate response to shift from
traditional technical competence to business and management competence to be able to function
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in new areas such as: facilities management, project management, value management,
commercial management and risk management; the challenge of appropriate response to
information technology and communication revolution; and the challenge of integrating the
outputs of applied research into the practice of Quantity Surveying.
Cartlidge (2002) summed up the challenge for the profession with the observation “quantity
surveyors must get inside the head of their clients, fully appreciate their business objectives, and
find new ways in which to deliver value and conversely remove waste from the procurement and
construction process.” Ashworth and Hogg (2000) reviewed the development of quantity
surveying and identified a shift in emphasis from cost to value with many QS firms extending the
range of services that they offer clients. Eke (2006) observed some of the challenges confronting
the QS profession as the impact of competition, the changing natures of client demand and the
advances in information technology. Cartlidge (2000) identified the challenges confronting the
QS as higher clients' requirements through the increasing complexity of modern construction
projects; impact of computerization; and competition from other professionals.
4.6 PROFESSIONAL MISCOUNDUCT IN QUANTITY SURVEYING PRACTICE
The quantity surveying profession is not an exception when it comes to ethical misconducts that
plague other professional bodies. Thus Ferrell and Weaver (1978) identify practices that could be
considered as negative to include the attempt to provide trade secret for inducements;
compromise to discharge professional service with very low level of honesty; and negligence and
denial of fault. McDonald and Zepp (1988) added the tendency to exaggerate services to deceive
clients; Olatunji (2007) reports that there are cases where quantity surveyors connive with greedy
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contractors to defraud unsuspecting clients; falsification of reports to favour selfish interests;
concealment of errors to justify negligence.
Quantity surveyors also misconduct themselves professional by helping to save other
consultants whose roles cause project failure (Newstom and Ruch, 1975; Albratt et al., 1992;
Olatunji et al., 2006). Receiving bribes, gifts and inducements during site visitation and
valuation at the inception stage to compromise professional responsibility constitute professional
misconduct (Olatunji, 2007). Dubinsky et al.(1980) also add abuse of office, misappropriation of
organization, official time and resources for personal use to include some of the notable
professional misconducts in the quantity surveying profession. Other misconducts include
wasting longer time on a job than envisaged (Ferrell & Weaver, 1978); indolence at work
(Albratt et al., 1992); compromising personal standards or professional principles to fulfill
employer’s demand at the expense of the client or the public at large (Dolecheck and Dolecheck,
1984); and forming cartel to prevent free flow of competition (Dubinsky at al., 1980).
4.7 ADOPTION OF ICT IN QUANTITY SURVEYING OPERATIONS
Globalization has influenced the operations of quantity surveying profession especially in the
way services are rendered to clients (Smith, 2004 and Peansupap, 2004); as a result quantity
surveying firms since the late 1980s have been adopting the Information and Communication
Technology (ICT) in the delivery of quality services (Akintoye, 2001; Peansupap, 2004; and
Ayeni, 1989). According to Musa et al. (2010), it is pertinent to adopt technology in improving
the quality of services delivered to clients. Thus Page et al. (2004) opined that the critical roles
of the quantity surveyors have placed them potentially at the centre of ICT that will integrate the
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contributions of all the participants of the design team. This ICT integration in quantity
surveying practice will ensure that resources are used to the best advantage of project partners by
providing financial management and cost consultancy services during the construction process
(Musa et al., 2010). The shift paradigm shift from paper-based operations to computer based
(digital) cost information production and exchange has necessitated the adoption of ICT in
quantity surveying practice (Oladepo, 2006 and Musa et al., 2010). According to Musa et al.
(2010), a new work order has evolved through the advent of technological innovations with the
main aim of optimizing resources; thus Goyal (1991) opined that this new work order for
quantity surveyors involves collection, storage, processing and transmission of cost information,
electronically, using computer and modern telecommunication networks.
Hinged on the above, Adeoye (1996) pointed out that the adoption of new technologies for new
order of work will involve the development of specialist software packages for performing the
array of tasks involved in work practices of quantity surveyors. In this vein, Musa et al. (2010)
identified software packages for quantity surveying in a globalize competitive environment to
include Digitizers, Autocard, Autosketch, Super Project, Master Bill, WinQs, QSlotus, Computer
Aided Taking Off (CATO), Estimator Pro.MB 3, QS Cad, RIPAC, EVEREST, Kwikest inter
alia for processing of operations.
4.8 EXPLORING THE BILLS OF QUANTITIES (BOQ) IN QS PRACTICE
4.8.1 The Emergence of the BOQ
The Bills of Quantities (BOQ) was introduced in to the United Kingdom’s construction industry
after the industrial revolution in the 19th century. They were used by master tradesmen for paying
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their workmen and claiming payments from building owners (Rashid et al., 2006). In its early
stage, the BOQs were prepared by “measurers” who were also known as “custom surveyors” or
“surveyors” who acted for master tradesmen (contractors for today). The “measurers” quantify
the work after completion and submit partisan final account to the building owner for payment
(ASAQS, 2006). The BOQ since then has become a tool for project costing and obtaining
tenders from contractors (Rashid et al., 2006). In addition, architects and other consultants use it
to have a bird’s eye view in terms of controlling project cost and finance (Rashid et al., 2006).
Kodikara et al. (1993) pointed out that the purpose of the BOQ is to give equal opportunity to all
contractors a level playing field to price the same characteristics of work items during bidding.
4.8.2 The Definition of Bills of Quantities
According to Hackett and Robinson (2003); and Chan (2002), the BOQ is a document that
stipulates the qualitative and quantitative aspects of every constituent parts of a proposed
construction project. Similarly, it is a book containing the all the list of items needed for
construction; and these items are complete with description in terms of materials, labour and
workmanship for the work and its quantity (NSW Legislative Council, 1991 and Marsden, 1998).
Willis (2002) adds that the BOQ is document with in-depth information on the type, nature and
quantities of the finished works in a construction. The BOQ is prepared together with the form of
tender, specification, preliminary bill and list of drawings to form a tender document. According
to Adnan et al. (2011) the BOQ is a document that itemizes the quantities of materials and labour
in a construction project. It is usually prepared by a professional quantity surveyor of the client
or the contractor (David & Baccarini, 2002) provide the quality control, cost analysis, cost
planning and to provide basis for financial reporting/cash flow.
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4.8.3 Uses of the Bills of Quantities
Chan, (2003) has identified various purposes of the BOQ to include: to avoid unnecessary effort
from multiple Contractors to prepare the bill, to According to Rashid et al. (2006), the BOQ is
used for cost planning; projected cash flows and budget, for valuation of interim payments and
variation orders and for settlement of final account; and are used for preparing materials
schedules or bills of materials in the contractors’ organization (Wainwright & Whitrod, 1980;
and Molloy, 2001). Other uses of the BOQ include bid evaluation (Rashid et al., 2006); are part
of the tender and documentation process; a tool for obtaining bids and maintaining cost control
during the contract (Rashid et al., 2006). According to El-Mashaleh (2010); the BOQ is useful in
making decision during bidding. It is also used for post-tender works such as cost planning,
projected cash flow and budget, valuation of interim payments and variation orders and for
settlement of final account (Kodikara et al., 1993). Numerous studies have identified the various
uses of BOQ and these include It enables the contractor to insert suitable rates to the list of
descriptive quantitative items( Adnan et al., 2011); the BOQ helps contractors at the pre-tender
stage in the formulation of their tenders (Davis & Baccarini 2004); it breaks down works in
formal detailed and structured manner for tendering (Adnan et al., 2011); the BOQ helps in the
observation, and analysis of risks for monitoring and controlling of construction process (Bu-
Qammaz et al., 2009); it assists in the valuation and payments of progress payments (Davis &
Baccarini , 2004); the BOQ provides a financial structure for contract administration (Adnan et
al., 2011); and it provides information for on-site checking (Jaggar, et al., 2002).
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4.8.4 Challenges Confronting BOQ Usage
Royal Institution Chartered Surveyors (RICS, 1991); in a study conducted revealed that the
usage of BOQ in the building construction sector has decline by 10% between 1984 and 1989.
The study also suggested that BOQ usage may totally disappear from the construction industry in
the future (Rashid et al., 2006). The use of non-traditional form of contracting such as the
turnkey, design and build, management contracting and build-operate-transfer contracts account
for this phenomenon of abandoning the use of BOQs (Rashid et al., 2006). Other reasons
adduced for abandoning the use of the include inability of the project team to fully utilized the
BOQ (Ing, 1984); many are not able to relate to the BOQ for everyday project development
process (Rashid et al., 2006); the use of the BOQ usually come to an end when the contractor
signs the contract (Rashid et al., 2006).
4.8.5 The Relevance of BOQ in Modern Construction Industry
The relevance of the BOQ in today’s construction industry needs to be examined in spite of the
challenges that confront the usage of the BOQ. Thus to the contractor; any project that involves
tendering will demand the preparation of a BOQ by the owner’s quantity surveyor or the
contractor’s quantity surveyor; in doing so the BOQ serve as a source of information effective
carry out the project management process (Rashid et al., 2006). The descriptions in the BOQ in
help the contractor to accurately arrive at a tender price; prepare project budget and cash flow;
compute the quantities of materials for the project; prepare labour requirements and schedules;
and to prepare claims (Rashid et al., 2006). Furthermore, Rashid et al. (2006) asserted that the
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BOQ helps the contractor’s planner to prepare the master programme for the project which helps
in the determination of project duration.
To the client, the relevance of the BOQ lies in the fact that it is a source of information for
monitoring cost, time and quality which are the concerns of every clients; furthermore, the
information in the BOQ helps in the preparation of cash flows, periodic project account and cost
variation for project management processes (Rashid et al., 2006). To the consultant, the BOQ
contains invaluable description and quantitative financial information for the use of the
consultant in project cost management right from the pre-construction to construction phase;
tender evaluation and selection of contractors for a project (Rashid et al., 2006).
4.9 AN EXPOSITION OF QUANTITY SURVEYING PRACTICE IN GHANA
Badu and Amoah (2004) in their work on Quantity surveying education in Ghana revealed that
the quantity surveying profession is a received profession from the British colonial masters as a
building accounting course incorporated. The QS profession in Ghana received the much needed
boost by the promulgation of Professional Bodies Registration Decree 1973 (National
Redemption Council Decree No. 143, Section 18:20) which give the nod to only qualified
members of the Quantity Surveying Division of the Ghana Institution of Surveyors to practice
the profession (ibid). Entry into the quantity surveying profession in Ghana is by written and
practical training examination where in the latter nomenclature candidates are expected to be
affiliated to seasoned quantity surveying firms for practical training (c.f. Badu & Amoah, 2004;
Laryea & Hughes, 2011).
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In a related development, a study conducted by Addai et al. (2009) on the “the Ghanaian quantity
surveyor and the emerging oil and gas industry” remains the most current existing research work
on quantity surveying practice in Ghana. The paper published in “The Quantity Surveyor” was
very in-depth and its review will be very crucial to this study. According to Addai et al. (2009),
it is very necessary for practitioners of the quantity surveying profession to “reinvent” the
profession of quantity surveying in order to meet the current global trend.
Knowledge and skills set of Ghanaian quantity surveyors encompasses technical skills,
knowledge and training project controls and contract procurement services (ibid). Traditional
services provided by Ghanaian quantity surveyors comprise of preparation of bills of quantities;
cost planning, estimating, bid and contract documentation and contract administration; non-
traditional services include feasibility studies, mediation, expert witness, appraisal, valuations,
project/construction management and facilities management; emerging services which Ghanaian
quantity surveyors must take advantage of in the oil and gas industry include estimating, cost
planning, cost control and procurement services (Addai et al., 2009). In order to provide services
efficiently, quantity surveyors ought to improve their soft skills in terms of communication,
leadership, teamwork and time management which are acknowledged by Addai et al. (2009) as
overlooked in Ghana (ibid).
Numerous challenges confronting the quantity surveying profession in Ghana as identified by
Addai et al.(2009) to be currently the most worrying include computing and information
systems; in this regard, quantity surveyors are “generally” conservative in the adoption and usage
of information technology(ibid); globalization and stiff completion as most of the services
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provided by quantity surveyors are no longer restricted to the QS practitioner; the higher level of
client expectation currently pervading the built environment fraternity will require quantity
surveyors to upgrade their skills and capabilities in meeting the demands of their clients in order
to stay in control of the market (c.f. Addai et al., 2009). The need to re-brand the quantity
surveying profession is the pragmatic step to take in resuscitating the profession; in this
direction, core expertise and competencies; usage of information technology, development of
new knowledge areas through research and development; specialization and diversification are
key steps to take in salvaging the quantity surveying profession (ibid). In concluding, Addai et
al. (2009) asserted that quantity surveyors need to quiver their risk averse attitude to become
more enterprising and change agent.
4.10 APPRAISAL AND SYNTHESIS OF THE LITERATURE REVIEW
From the review of extant literature on quantity surveying practice, Anago (2006); Olawale
(2006); Westcott and Burnside (2003); and RICS (1991) agreed quantity surveying profession is
a financial management position endowed with critical duties of measurement or quantification
inter alia. Identifiable roles of quantity surveyors has been variously and extensively identified
and recognized as one of the important roles provided by the professions in the built
environment. This position was strongly made clear in the literature by Olawale (2006); Eke
(2006); McGaw (2007); Burnside and Westcott (1999) and Bonnar (2007) who variously
identified the roles of quantity surveyors in their work. The changing roles of quantity surveyors
was espoused by the literature review notably in Ashwoth (1981) noting that quantity surveying
roles has significantly changed; a position strongly affirmed by the works of RICS (1991);
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Ashworth (1994) and reinforced by Keel et al. (1994) that 80% of clients perceive the roles of
quantity surveyors to be changing.
Numerous quantity surveying services were identified in the review of extant literature on
quantity surveying practice from various jurisdiction of the world. For instance Olatunde (2006)
was very extensive in this regard classifying quantity surveying services rendered to clients in
contract stages as pre- contract stage and post contract stage services; and further went on to
categorize the quantity surveying services in managerial nomenclature as project management
services; facilities management; and programme management. The classification of services of
the quantity surveying profession in Olatunde (2006) is largely similar to the works of
Anago(2006); Olawale (2006); Burnside and Westcott( 1999); Seely (1997); Davis et al. (2007)
except a slight difference in the works of Canadian Institute of Quantity Surveyors, CIQS(2002)
classification with variations notably mortgage monitoring and verification of borrower
payments. Pricing is the vehicle through which quantity surveyors recover the cost incurred and
earning reward for risk taken in providing services to clients. Varied dimensions of quantity
surveying consultancy pricing exist; some based on the stages of construction viz pre-contract
and post contract; in this case quantity surveyors price services actually provided at each stage of
construction project execution.
The review of extant literature uncovered percentage pricing/fee of the cost of construction as
the main quantity surveying consultancy pricing strategy; this is very clear in the works of Fees
Bureau (2011) and the Alberta Infrastructure and Transportation (2005) and The South African
Council for the Quantity Surveying Profession (2010). The phenomenon of percentage
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pricing/fees has the inherent deficiencies of under-pricing and over pricing as extensively
espoused in Owusu-Manu et al. (2012). This dilemma of under-pricing and over pricing raises
the issue fair pricing which is the focus of this research study. Hoxley (1998); Cruywagen and
Snyman (2005) alluded to massive consultancy services pricing/fee reduction leading to loss of
profit and overhead by quantity surveyors as a challenge confronting the profession. Odeyinka
(2006) added to the challenges of the quantity surveying profession identified by earlier works of
Hoxley(1998) inter alia; and supported by Cartlidge (2002) proffering by a sum up, the
mounting challenge confronting quantity surveying practitioners that they ought to get into the
head of their client to figure out their expectation.
Professional misconduct and unethical practices are part of most professional organizations;
recent misconducts in quantity surveying practice abounds in literature and include falsification
of reports to favour selfish interest; exaggeration of services rendered to deceive clients to better
pricing position; bribery and cartel formation to dupe clients especially when pricing consultancy
services were unanimously raised by Ferrell and Weaver (1978); McDonald and Zepp (1988);
Olatunji (2007); Newstom and Ruch (1975); Albratt et al. (1992); Olatunji (2007); Dubinsky et
al. (1980); and Dolecheck and Dolecheck (1984). The non-adoption of ICT in quantity surveying
practice has been underscored by the literature review with all the reviewed works pointing to
the fact that the quantity surveying profession is lagging behind.
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CHAPTER FIVE
RESEARCH METHODOLOGY
5.0 INTRODUCTION
This chapter discusses the research methodology adopted for this research study. It delves into
the principles upon which the research process is based leading to the adoption of survey
instrument for data collection and analysis. In this chapter the “what is done”, “why” and “how it
was done” aspects of the research will be the cardinal point of this chapter. In this thinking, the
research methodological terms and concept will be thoroughly discussed followed by the
exposition of their application in the research process.
5.1 PHILOSOPHICAL TRADITIONS AND CONSIDERATIONS
Guba and Lincoln (1994, 1998) categorize research paradigms into four namely positivism, post
positivism, critical theory and constructivism. According to Guba (1990), a paradigm is a basic
set of beliefs that guide an action. Denzin and Lincoln (1998) were of the view that a paradigm
consists of three main elements namely: epistemology, ontology and methodology. According to
Jacob (1987), epistemology is how we know the world; ontology is about the reality of nature;
and methodology is about how we gain knowledge of the world. Epistemology is a research
philosophy branch which controls the structure and processes of social research (Sarantakos,
2005). Epistemology informs the methodologies about the nature of knowing or about what
counts as a fact and where knowledge is to be sought (Campana, 2010). Simply put,
epistemology is the science of knowing (Babbie, 1995). Gall et al. (2003) added that
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epistemology is about studying the nature of knowledge and the process of acquiring knowledge
and its validation.
Babbie (1995) asserted that the concept of knowing is positivism. Positivist researchers develop
knowledge by collecting numerical data on observable behaviours of samples and then
subjecting these data to numerical analysis (Campana, 2010). Researchers over the years have
clearly indicated that the aim of positivism is to explain, predict and control a phenomenon
(Guba & Lincoln, 2004). Positivism concerns epistemological doctrine that physical and social
reality are independent of those who observe it; the observation of this reality is unbiased and
constitute scientific knowledge (Gall et al., 2003). According to Weber (2004) positivist
philosophy assumes that theoretical based predictions can be tested with data collected from the
objective world. Quantitative research is taken as identical to positivist research since it
contains epistemological characteristics that show how the methodology should control the
research (Sarantakos, 2005). Sarantakos (2005) pointed out that positivist research paradigm
consist of realist or objectivist ontology that guides the strategy of quantitative methods.
In consonance with the tenets of epistemology which is about where knowledge is to be sought;
and leaning greatly towards positivism, the researcher distributed the questionnaires to only
practitioners of quantity surveying consultancy as they have in-depth knowledge of what was
being investigated. In doing this only what counts as facts were collected as data for analysis in
order to churn out reliable and workable results. The survey instruments administered were
designed using key variables from the theoretical framework and the statistical tools which are
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mathematical and scientific in nature of analysis were adopted for data analysis. This clearly
positions the study within the positivist tradition.
Similarly, idealism branch of philosophy is cardinal to this research as the research seeks to
establish existing truth about pricing phenomenon using statistical analysis which is the cardinal
point of idealism. In this direction, the research endeavor to establish preexisting unchangeable
facts about consultancy pricing. Idealist believed that contemporary problems are deeply rooted
in the past hence the need to give the past prominence in the diagnosis of current pricing
phenomena. Idealism lays much emphasis or pertinence on past literature to chart a new path. In
this direction, this research study conducted a very elaborate literature review of pertinent issues
of pricing ranging from theoretical issues of pricing to the practice of general consultancy and
quantity surveying.
5.1.1 METHOD OF SCIENTIFIC INQUIRY AND REASON
Having adopted the positivism, it is appropriate to reason along the line of deductive logic in the
conduct of this research in attempt to unravel the phenomenon of pricing which is a social and
quantitative dynamic in nature. This is because, social issues and intrinsic (psychological) issues
affect pricing which is numerically communicated. Deductive reasoning operates from a general
to specific perspectives drawing conclusions based on facts (Burney, 2008); pricing is the
anticipation of reward for services rendered, this position is supported by adoption of deductive
reasoning, a stance advocated by Collis and Hussey (2003) that deduction allows the expectation
of a phenomenon; likewise, Robson (2002) sequentially outlined deductive logic in research as
deduction of hypothesis from theory; operationalization of the hypothesis (how the variables are
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to be tested) to determine the relationship between specific concepts and variables; testing the
hypothesis; confirmation or modification of the outcomes; and verification of the theory using
the findings.
Based on the above, the theoretical framework (refer to chapter two) was adopted in which
various concepts and theories of pricing were reviewed and synthesized leading to the
postulation of twelve (12) key hypothesis with fifty-three(53) independent variables and the
dependent variable mainly was pricing. The Chi Square test was adopted using the SPSS in
testing the hypothesis. The Chi Square test of independence was the specific type of chi Square
test used because to the nature of the hypothesis, they were composed of Dependent variables
(DV) and independent variables (IV). The conventional p-value of 0.005 was adopted in
determining the existence of relationship between the dependent and independent variables of
testing the hypotheses. The chi square value denoted by X2 and the p-value were used to accept
or reject the null hypothesis and to determine relationship between DV and IV. Where the X2cal
(calculated) > X2α (value from chi square table) the null hypothesis is rejected and when the p-
value ≤ 0.005, this indicate that a significant relationship exist between the DV and the IV.
5.2 RESEARCH STRATEGY AND DESIGN
5.2.1 Quantitative Research Paradigm
According to Wadsworth (1997), quantitative research is the systematic scientific investigation
of quantitative properties and their relationships. Quantitative studies are concerned with
behaviours consisting of measures or observation scales (or both) and they focus on the cause-
and-effect relationship between two variables (Krathwohl, 2004). Wadsworth (1997) stated that
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quantitative research is about “how many; to what extent, or how much aspect which involves
counting and other data analysis. The objective of quantitative research is to develop and employ
mathematical models, theories, hypotheses concerning the natural phenomena (Sarantakos,
2005). Measurement process is key to quantitative research because it provides the basis for
connection between empirical observation and mathematical expression of quantitative
relationships (Gall et al., 2003). The quantitative research generally uses critical approaches
such as the generation of models, theories and hypotheses; the development of instruments and
measurement; experimental control and manipulation of variables; collection of empirical data;
modeling and analysis of data; and evaluation of results (Gall et al., 2003). A positivist,
objectivist and realist approach (quantitative research) investigate and explain how one variable
affects another (Creswell, 2005). According to Creswell (2005), variables are the attributes that
the researcher studies. Sarantakos (2005) argued that as a strategy the quantitative research
(hinged on positivist, objectivist and realist approach) consist of vital criteria such as the use of
empirical methods; objectives; clarity in design and reliance on methods and procedures;
distance between the researcher and the participants; measurement and quantification; validity,
reliability, accuracy and precision; and ethical considerations. Quantitative research is an
appropriate educational research approach in which the researcher is free to choose what to
study, especially what is of interest to the research, asks specific and narrow questions, collects
numeric data from participants, analyses the data using statistics in an objective and unbiased
manner (Creswell, 2005).
5.2.1.1 Objectivism and Realism
Campana (2010) opined that realism is a feature of quantitative method because it perceives
reality to be objective, simple and fixed. Sarantakos (2005) adds that reality comprises of sense
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of impressions, which is what is perceived through the senses. Researchers perceive the features
of the social environment as having both social and physical reality. Objective reality means that
these features must exist independently of the individual who created or is observing them (Gall
et al., 2003). According to Guba and Lincoln (2004), a researcher who adopts the positivist
position believe that scientific inquiry must form the basis for the study of multiple social reality,
which means different individuals interacting with the social environment. Sarantakos (2005)
asserted that objectivism is significantly linked to reality as reality and truth exist objectively,
and can be discovered and adequately measured. Also, Creswell (2005) opined that the
observance of objective detachment, value neutrality, and unbiased approach must be taken by
researchers to quantitative research.
Drawing on from the above works cited, quantitative research studies explore behaviours with
much emphasis on the cause-and-effect relationship between variables; positivist researchers are
concerned about collecting data on numerical behavior of individuals for analysis. The art of
pricing borders heavily on consumer behavior and meaningful assessment of the variables
underlying pricing behavior and this can be identified quantitatively. Again, quantitative
research permits an objective and fair data analysis using statistics. The issue of fairness in
pricing is highly fundamental to this research and it is the basis upon which the research study is
hinged. This issue of fairness in pricing has made the adoption of the quantitative research
approach a non-negotiable issue and the most apposite method to be adopted as far as the
research is concerned. The quantitative research method adopted for the research is positioned in
philosophical paradigms such as epistemology (what is the fact and where the fact is to be
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sought); positivism (explaining, predicting, and controlling phenomenon); and objectivism and
realism (perception through the senses and social phenomenon).
The researcher adopted the quantitative approach to test the hypotheses postulated. The
presentation of results collected using tables and other visual techniques for ease of
comprehension and assimilation of the results are all features of the quantitative method of
analysis. In adopting the quantitative approach to this research, the objective perspectives of the
research was both descriptive and correlation in nature determined by the testing of hypotheses
using chi-square test. The correlational (i.e. relational in this case) aspect of the research borders
on the postulation and testing of hypotheses to determine the relationship between pricing as a
dependent variable (DV) and the independent or explanatory variables (IV) that can influence or
alter pricing levels. This is because the study seeks to investigate the attitude of consultants
concerning decisive factors that influence the pricing of their services.
The adoption of this strategy of testing hypothesis is crucial in order to generalize the findings of
the research since pricing is a universal phenomenon. The decision of pricing services by
quantity surveying consultants is individualistic hence it is pertinent for the researcher to be
detached from the study of this phenomenon to be able to identify the dynamics that are
independent in nature without the feelings and sentiments of the researcher. This assertion gives
much impetus to the adoption of the quantitative approach in this study. Pricing is a multifaceted
phenomenon which is expressed quantitatively hence the adoption of the quantitative method
with its attendant philosophical underpinnings is espoused in the research process as follows:
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5.2.1.2 The Survey Process
Cohen et al. (2005) observed that researchers who adopt positivist perception use a range of
traditional options such as surveys and questionnaires. According to Isaac and Michael (1997),
survey research is an avenue for answering questions that have been raised, to solve problems
that have been posed or observed, assess needs and goals set, to determine whether or not
specific objectives have been met, to establish baselines against which future comparisons can be
made, to analyze trends across time, and generally to describe what exist, in what amount and in
what context. Kraemer (1991) opined that survey research is used to quantitatively describe
specific aspects of a given population which consist of relationship between variables. Kraemer
(1991) further pointed other characteristics of survey research by asserting that the data required
for the survey research are collected from people by using certain portion of the population from
which findings can later be generalized back to the population. According to Glasow (2005)
independent and dependent variables are used to define the scope of survey research; and that
before the commencement of the research, the researcher must predicate a model of relationship
existing among the variables.
Survey design consist of two steps namely development of sampling plan and obtaining
population estimate from the sample data. The sampling plan involves the selection of sample;
determination of an adequate sample size; and the choice of media through which the survey will
be administered which comprises of telephone interview, face-to-face interviews and mailed
surveys using postal or electronic mail (Levy & Lemeshow, 1999 and Salant & Dillman, 1994).
In keeping with the above works demonstrated in extant literature, the rationale for adopting
the survey process for this study is embedded in the philosophy of the researcher that the survey
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process enables data to be gathered from large number of respondents in order to generalize the
results of the study. Again, the survey process was adopted because of its ability to allow for the
aggregation of the opinions and attitude of respondents on the various facets of quantity
surveying pricing under investigation. The sample for this study involves professionals
categorized as quantity surveyors by training and education and are working in firms. Survey is
appropriate for because of the intention to ascertain the relationship between key variables of the
researcher. Also the use of the survey process provided the basis for the testing hypothesis by chi
square test of independence; ranking of variables by relative importance index and the
classification and reduction of variables based on the common factors by the use of factor
analysis.
5.2.1.2 .1 Research Scope and Boundaries
The research was conducted in Accra the administrative and political capital of the Republic of
Ghana. The population of Accra constitute 16.3 per cent of the population of Ghana (Ghana
Statistical Service, 2012). Accra is also the capital of the Grater Accra region of Ghana bounded
by the Central Region, Volta Region, Eastern Region and the Gulf of Guinea. Accra is the key
industrial hub of Ghana, being home to every aspect of the Ghanaian economy ranging from
agriculture to tertiary services like the consultancy industry. Construction is one of the key
industrial sectors in Accra. This phenomenon is underpinned by its industrial nature and the
concentration of job seekers in the construction sector by people migrating from the rural areas.
As construction activities boom in Accra, it implies that more professionals including quantity
surveyors in the construction industry will gravitate towards the Greater Accra.
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Figure 5.1: Map of Greater Accra Region (Source: UN-HABITAT, 2009)
5.2.1.2 .2 Sampling Techniques and Sample Frame
Salant and Dillman (1994) pointed out that sample selection is hinged on population size; the
sample media and its cost of use; and the degree of precision required. Participants in the sample
must be selected at random with equal chance (ibid). A prerequisite to sample selection is to
define the target population as narrowly as possible (Salant & Dillman, 1994). On the contrary, it
is sometimes not possible to know the true population hence Attewell and Rule (1991) proposed
that a theoretical sample may be used; theoretical sample purposively selects organizations that
demonstrate the desired characteristics that are the focus of the researcher’s study.
According to Ghana Institution of Surveyors, GhIS (2012), the membership of the quantity
surveying division of consist of 68 firms; 37 fellows; 282 professionals; and 53 technicians; this
sum up to 372 members and 68 firms. Therefore the sampling frame for this research is 372
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quantity surveyors operating in 68 quantity surveying firms and other institution but are
performing QS functions. Having determined the sampling frame for this study, the researcher
adopted the Kish (1965) formula which is popularly used in most empirical works as evidenced
in the works of Bolstein and Crow (2008) as follows:
n¹
n =
1+ n¹/ N
Where;
n = sample size
N = total population size
s2
n¹ = v2
s = maximum standard deviation in the population element at a
confidence interval of 95%
s2 = p (1-p)
p = the proportion of population elements
v = standard error of the distribution at 0.05
s2 = 0.5(1- 0.5)
s2 = 0.25
0.25
n¹ = 0.052
n¹ = 100
Now N = 372
100
Therefore, sample size, n = 1 + 100/ 372
n = 78.8
Hence, Sample Size, n = 79
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Therefore the appropriate sample size for the study was 79 respondents (quantity surveyors).
This means that questionnaires should be distributed to 79 respondents to achieve 95%
confidence interval.
5.2.1.2 .2 .1 Sampling Technique Adopted
Consistent with the assertion of Salant and Dillman (1994), the respondents for the research were
selected by using simple random sampling technique to give each respondent an equal chance of
being selected as active participant of the survey process. This is necessary because the roll of
QS practitioners is available. Similarly, the adoption of simple random sampling will enable the
generalization of the research findings to be easier than the utilization of other sampling
methods. In order to pursue randomization in the selection process, a random number table (see
Appendix 2) was utilized in that regard. Using the rules of simple random sampling, and the
information available to the researcher: 372 of registered professional quantity surveyors, 79 QS
were selected (i.e. sample size) to participate in the survey. Hinged on the rule that each member
of the survey population (sampling frame) must have an equal chance of being selected to
participate, the random table in appendix two was the main tool for the execution of the task of
selecting 79 respondents from a survey population randomly. Based upon the above data and the
random table available, 3-digit numbers are required. It is also necessary to enter the random
number table randomly. This was accomplished by pulling out one of the Ghana Cedi notes from
pocket which turned out to be twenty Ghana Cedis (GH₵ 20.00) with a serial number of
VL7745452. The last two digits being 52 were selected as entry point. Now the row and the
column would have to be determine randomly, therefore a twenty pesewa (20p) coin was tossed,
a head showing implies the first digit is 5 which was designated as the entry column and 2 was
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designated as the entry row and vice versa. With this procedure, the researcher tossed the twenty
pesewa coin and a tail showed which means the second digit designated the column which is 2
and 5 designated the row. Hence the random table was entered as indicated with arrows in
appendix two. The names of all members of the target population were arranged alphabetically
and serialized. With this, the random selection began by using the first random number of 3114,
this number was separated to 31 and 14, and reading from the right to left on the random table,
the QS with number 31 was selected to be the first respondent. Moving down the column, the
next number was 2463 and separating this random number because the sample size was a two-
digit number and reading from the right to the left of the table, the QS with serial number 24 was
selected. Numbers selected which were not within the sample size range of 1 to 79 were ignored
and the next number within the column was considered. The process continued until the sample
size was exhausted. Numbers already selected were crossed out from the survey population list.
5.2.1.2.3 Data Collection Methods
A data collection strategy that quantitative researchers mostly prefer is survey or questionnaires
(Sarantakos, 2005). Surveys questionnaires are the most frequently used method of data
collection in the social sciences and are mostly mistaken as a method of social research
(Sarantakos, 2005). Cohen et al. (2005); Creswell (2005); and Krathwohl (2004) asserted that
survey questionnaires are used in diverse ways as an instrument for data collection. Survey
questionnaires are excellent techniques (method) of data collection with closed and open ended
questions (Sarantakos, 2005). Creswell (2005) opined that quantitative research uses an
instrument to measure variables in a study; this instrument consists of specific questions and
response alternatives or possibilities that the researcher has established as a priori to the study.
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According to Campana (2010), survey questionnaires are adopted to generalize the results
collected from a smaller number to a larger number. Survey questionnaires are recognized as the
suitable method of data collection from a large number of participants when the researcher is
able to clearly convey the appropriate information of interest across with suitable measures of
variables (Creswell, 2005; Gall et al., 2003; Krathwohl, 2004; and Sarantakos, 2005).
Survey questionnaires also aim at one or more groups of people in obtaining their opinions and
attitudes concerning a phenomenon under study (Funnell, 1996). Survey questionnaires have
numerous advantages consisting of the ability to access a large number and geographically
dispersed population; gathering of data by means of voluntary participation devoid of
compulsion or force; reduction of researcher bias; and minimization of time requirement for the
respondent and the researcher (Creswell, 2005). A good questionnaire consists of questions that
elicit different types of information from respondents (Gall et al., 2003). Questionnaires must be
kept short, questions organized in easy manner and avoiding double-barreled questions (Gall et
al., 2003). According to Creswell (2005), quantitative investigators use both ordinal and interval
scales; of these, interval scales provide the most variation of responses and lend themselves to
stronger statistical analysis. Sarantakos (2005) and Creswell (2005) suggest that the Likert scale
is particularly suitable for studying attitudes; Cohen et al. (2004) adds that the use of Likert scale
gives the researcher the opportunity to build differences, measure attitudes, and generate hard
data on the respondents; and it also offers information such as frequency, flexible responses and
linkage between opinion and quantity. The Likert scale is a five point response scale used to
measure responses to a set of statements; and permits the measurement of degrees of difference
but not the specific amount of difference (Kapadia-Kundu & Dyalchand, 2007). Attitudes and
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perceptions have traditionally been measured on a five point Likert scale and its variants
(O’Keefe, 1991).
The design of an effective survey questionnaire is hinged on four critical pillars namely question
wording, categorization, coding of variables and general acceptance (Sarantakos, 2005). Survey
instrument design must be preceded by firstly defining clearly the focus of the study; and
secondly, translating the study objectives into measureable factors that contribute to the focus of
the research (Salant & Dillman, 1994). According to Fowler and Floyd (1995) a good question is
one that produces answers that are reliable and valid measures of something that we want to
describe. McIntyre (1999) observed that survey questions must use words that commensurate the
educational levels of respondents. Fowler and Floyd (1995) added that both the question and the
response options must be clear to both the respondent and the researcher. The wording should
prevent alternative interpretations or incomplete sentences that would allow misinterpretation
(Browne & Keeley, 1998; Fowler & Floyd, 1995; and Salant & Dillman, 1994). Survey
questions should not be combined where the respondent might wish to answer affirmatively for
one part, and negatively for the other part (Glasow, 2005).
Survey questions must be feasible to answer and respondents must be willing to answer them
(Fowler, 1995). Questions must be civil and ethical (McIntyre, 1999); questions that ask
respondents for data they do not have must be avoided and those questions that assume the
respondent knows something about the subject must not be asked; personal questions,
objectionable statements that reflects the researcher’s bias and questions that require difficult
calculations must be avoided; and Undefined abbreviations, acronyms, and jargons should not be
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used (Salant & Dillman, 1994). Onerous questions, double negatives questions and long
questions that lose the respondents in the reading must be avoided (McIntyre, 1999).
In questionnaire type of data collection, standards such as validity and reliability are very crucial
in which researchers look for two types of responses at group level and individual level (Gall et
al., 2003). According to Cohen et al. (2005) validity can be achieved by choosing an appropriate
time frame; selecting an appropriate methodology; selecting and designing an appropriate
instrument to collect data; and ensuring that the study comply with its original hypothesis.
Sarantakos (2005) supported the assertion of Cohen et al. (2005) on validity by suggesting that
validity in quantitative research is hinged on the instrument that measures relevance; precision;
accuracy and compliance with the research hypothesis. Burns (2000); Cohen et al.(2003); Gall et
al.(2003) and Sarantakos (2005) all agree that internal validity is necessary for ensuring validity
in a research; thus internal validity refers to internal study mechanisms that ensure research
design, method and approach do not have impact on the results of the study. According to
Campana (2010), instrument design; instrument changes during the study; diverse methods of
data collection over the study periods; changes in personnel in the study; and inconsistent
recording techniques will affect the outcomes of the study. Campana (2010) clearly pointed out
that validity and reliability are critical to conduct and data collection of a research study. In this
thinking Campana (2010) identified validity broadly as content and construct. Content validity is
ensured by piloting the questionnaire with qualified practicing personnel to ascertain details
concerning wording of questions and industry relevance while construct validity is address by
ensuring statistical procedures; tabulation of results; and application of non-statistical results in
examining, discussing and interpreting the scores align to the questions (Campana, 2010). The
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key issues of validity and reliability were achieved by the adoption of factor analysis in which
the KMO values and Barlett test of sampling adequacy were used to ascertain validity and
reliability (refer to factor analysis in chapter 6 and section 5.3 of this chapter).
Sarantakos (2005) clearly pointed out nine keys for ethical consideration consisting of:
explanation of research purpose; risk assessment; confidentiality and privacy; informed consent;
data access and ownership; data collection; advice; mental harm; and research approvals through
ethics committees. Creswell (2005) opined that a cover letter should accompany the
questionnaire soliciting responses from respondents to assure them of confidentiality and
anonymity. Similarly, Cohen (2005); Creswell (2005); and Gall et al.(2003) all agree that the
cover letter is key to the research project and enhances a positive view if the study and fulfilling
the principles of ethics at the in addition. Glasow (2005) suggests the respondent is a source of
error; and responses to survey questions may not reflect the actual beliefs, attitudes or behaviours
of respondents. Browne and Keeley (1998) added that respondents may intentionally provide
false responses to invalidate the survey results or choose not to reveal their true insight for
personal reasons, which reasons may not be rational or even understood by the respondent. Isaac
and Michael (1997) identified two errors of measurement as the tendency to agree with a bias
inherent in the wording of a question to the extent that the respondent more readily agrees with
positively worded questions; and respondents may consistently give high or low ratings,
reflecting a rater bias that depart from the validity of the results.
Drawing on from the above existing works extensively, the source of data for this study was
primary as a result of the adoption of idealist perspective that issues be holistically examined. In
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this research, idealism was fulfilled as a result of elaborate literature review conducted within the
general consultancy practice milieu, quantity surveying practice environment and a theoretical
framework on the general pricing theories that are widely acceptable. This review culminated
into the identification of key variables for the research study. The data was ordinal in nature as a
result of the five point Likert scale adopted to measure the perception of respondents.
The tool for data collection was a survey questionnaire fitted onto four pages of A4 sheets
measuring various aspects of the research of interest to the researcher. There were eleven
questionnaires addressing key aspects of the research notably the aim and objectives of the
research which sought to tackle the general pricing milieu in quantity surveying practice and
these questions touched on price and value; just price; objectives of pricing; pricing strategies
and parameters; criteria for consultancy bid price success; dynamics of pricing risks; taxation
and inflation; components of quantity surveying consultancy services pricing; challenges
confronting QS consultancy practice and the QS consultancy services. Questions on the profile
of respondents bordered on the status of their firms; working experience; rate of work acquisition
and sectors of operation. These questions were necessary to ensure internal validity of the data
collected. Questionnaires are suitable for survey processes to gather data on social phenomenon
on individuals, groups and institutions located within large geographical areas. In using
questionnaire as a tool for gathering data in this study, care was taken in the construction of
questions. In the first place, the questions were closed-ended requiring respondents to provide
responses on key variables. Standardization was carefully observed in order to ensure all
respondents answer the same questions with the same responses; this is one of the reasons for
using questionnaire as a tool because control is of essence in survey process unlike laboratory
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research where samples are under control in confinement and conditioning. In ensuring
uniformity, same wording of questions were maintained throughout the questionnaire and the use
of jargons or technical words were minimal. In terms of ethics and communication, an
introduction was provided bordering on the title of the research, the aim and objectives of the
research and respondents were highly assured of their confidentiality. The sequence of the
questions were such that they draw the respondents gradually into the interaction with the
questionnaire beginning with issues that respondents are very familiar with by graduating the
questions from simpler to thought provoking professional issues in practice. The questions were
devoid of sensitive issues and the privacy of respondents was highly respected. Practicality and
relevance of questions were achieved by crafting questions that are of much interest to
respondents in the practice of quantity surveying consultancy services pricing. To aid
respondents’ responses to avoid measurement errors, tables were used to profile the variables to
majority of the questions to help in ticking appropriate boxes based on the instructions provided
in the introductory section of the questionnaire; this will also make the recording, aggregation,
analysis and organization of data into standardized format easier for the researcher.
The questionnaire was self-administered to respondents by the researcher. Respondents were
given time to respond to the questions within four (4) weeks. The questionnaires were later
retrieved after four weeks by which time majority of the respondents had considered and
responded to the questionnaire. In all a total of 110 questionnaires were distributed in order to
achieve the appropriate sample size of 79. At the end of the four week field work of
questionnaire administration to respondents, 79 questionnaires were retrieved producing a
response rate of 71.8 per cent.
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5.3 DATA ANALYSIS METHODS
A variable’s measurement scale determines which statistical methods are appropriate (Agresti,
2002). A variable is a characteristic that is measured on individuals (Tebbs, 2006). According to
Ryan (2004) a variable depict the characteristics of a population which can contain different
values. According to Agresti (2002) variables are suitable for measuring attitudes and opinions;
and the subjective evaluation of certain characteristics. In a research, response scales measure
attitudes, attributes, client satisfaction, cultural beliefs and values; they are means of collecting
responses from people on an instrument (Kapadia-Kundu & Dyalchand, 2007).
5.3.1 Descriptive Analysis
After the collection of data using the questionnaire, there exist an enormous data that needs to be
presented to audience. As a matter of fact, the data collected require summarization in order to
deduce meaningful information from it. The descriptive statistics is the analytical tool for this
agenda. According to Ryan (2004), descriptive statistics consists of methods for presenting and
summarizing data. The descriptive statistics in the analysis of data as a priori to easy digestion
and understanding of large quantities of data; and provision of opportunity to communicate the
research results to others (Ryan, 2004).
5.3.2 Data Presentation Using Tables
Good tables are integral part of packaging and presenting data to audience. Tables help to
minimize the amount of data values in a text; and aid in eliminating less important variables in
discussing the data (UN, 2009). According to Miller (2004), good tables must aid audience to
find and understand numbers within the table; and both the layout and labeling must be
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straightforward and unobtrusive in order to draw substantive attention to the data which is
conveying information to audience. Tables should contain concise and well-organized data that
supports the analysis to be made (ibid, 2009). The UN (2009) clearly pointed out that tables
should be able to stand on their own; and should contain descriptive title; indicate source. The
UN (2009) identified the five support components needed to describe data presented in a format
to include the table title (should give a clear and accurate description of the data, it should
answer the three questions “what”, “where” and “when.”); column headers (at the top of the
table, should identify the data presented in each column of the table and provide any relevant
metadata (e.g. unit of measurement, time period or geographic area); row stubs (in the first
column of the table, should identify the data presented in each row of the table); footnotes(at the
bottom of the table, may provide any additional information needed to understand and use the
data correctly (e.g. definitions); and the source line (at the bottom of the table, should provide
the source of the data, i.e. the organization that produced the data and the data collection method
(e.g. population census or labour force survey).
Drawing on from the above, the data collected from the field through the use of questionnaire
was presented in table format which belong to the demonstration or presentation categories of
tables in order to highlight key figures and as this research is analytical. The results were
presented in table format as it will aid in the analysis of key and critical results. The tables were
corresponding to the number of questions from 1 to 11 in the questionnaire and the number of
hypothesis tested and the each case of factor analysis. The tables were designed to suit the five
components of table design identified by UN (2009) as follows; table title which comprised of
legal status; firm’s years of experience; rate of work acquisition; sectors of operation; concept of
price and value; project pricing(consultancy pricing); concept of risk; concept of taxation and
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inflation; quantity surveying consultancy services pricing components; challenges confronting quantity
surveying consultancy practice; and quantity surveying consultancy services; the column headers
comprised of the weighting, Relative Importance Index(RII) and rankings; the row stubs consisted of key
variables encapsulated in the respective table titles; and the source line indicated.
5.3.3. Relative Importance Index (RII)
According to Soofi et al. (2000), the relative importance index refers to quantities that compare
the contribution of individual explanatory variables to a response variable. Carpio et al.(2007)
asserted that the relative importance index is used for determining the relative significance of
attributes in a decision maker’s choice of one out of several alternatives in the revealed
preference setting. Carpio et al. (2007) opined that the determination of the relative importance
of attributes is required for the construction of an index summarizing the overall effect of a group
of attributes; the calculated indexes are then used to compare and rank the attributes. According
to Carpio et al.(2007), the RII proposed by Soofi et al.(2000) is one of the measures that can be
used to gauge the relative importance of variables. The Likert scale is a five point response scale
used to measure responses to a set of statements (Kapadia-Kundu & Dyalchand, 2007). Attitudes
and perceptions have traditionally been measured on a five point Likert scale and its variants
(O’Keefe, 1991).
The frequently used measure of relative importance is the unstandardized coefficients (Carpio et
al., 2007); these unstandardized coefficients signify the impact of “one- unit” difference in the
independent variable on the dependent variable (Carpio et al., 2007). As a panacea to this one-
unit paucity in use of unstandardized coefficients; Menard (2004) strongly advocated for the use
of standardized coefficients in the determination of relative importance for two main reasons:
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firstly, for variables with no natural metric such as (1= strongly disagree, 2 = disagree, 3 =
neutral, inter alia) a “scale free” standardized coefficient may be more significant than
unstandardized coefficient; and for variables measured in natural metric, it is unclear whether a
one unit-change, or a 0.1 unit change, is “big” or “small” with respect to the scale.
Indeed, the relative importance index (RII) has been widely used by numerous researchers
notably Badu et al. (2013); Nkado (2001); Johnson (2000); and Jeyamathan and Rameezdeen
(2005) in identifying the significance of variables of different dimensions in their research work,
hence the adoption of the RII is appropriate for this study as it has been used by other seasoned
researchers in built environment as indicated above. Another justification for using the RII lays
in the fact that the relative importance analysis can be performed for groups of variables and not
for only individual variables (Carpio et al., 2007). According to Wilen and Abbott (2006)
relative importance serves as useful measures of significance.
Hinged on the above works cited, and in keeping with the advocacy of Menard (2004) the
Relative Importance Index (RII) was used to ascertain the perception of respondents on critical
pricing variables since pricing is attitudinal it is therefore necessary to measure the significance
of the key pricing variables in order to be fully aware of their vitality in the determination of
quantity surveying consultancy services pricing.
The RII was determined by:
Σ W
RII =
A*N
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Where W = weight given to each pricing variable by respondents ranging from 1 to 5 on a likert
scale; A = highest response integer, 5; and N= total number of respondents (c.f. Badu et al.,
2013).
5.3.4 Inferential Analysis: Hypothesis Testing
Inferential analysis intends to make generalizations from a sample to the wider population
(Gabrenya, 2003). Inferential analysis largely dwells on the deployment of statistical techniques
in testing hypothesis to derive implications from a research (Baddie & Halley, 1995; Kolawole,
2001). Inferential analysis have been categorized into two main streams namely parametric
analysis consisting of t-test, analysis of variance and Pearson Product Moment Correlation
Coefficient; and non-parametric analysis comprising chi-square test, the kolmogorov-Sminov
test, Mann-Whitney U test, Sign test, Wilcoxon matched-Pairs Signed–ranks test and the
Lambda symmetrical/ asymmetrical test (Adeyemi, 2009; Berenison, & Levine, 1979). The
choice of these two types analysis(parametric and non-parametric) is dependent on key factors
associated with the study instrument which were used by the researcher or the nature of the study
which will later manifest in the type of data collected for analysis. In this regard, Adeyemi
(2009) pointed out factors which determine the choice of parametric or non-parametric analysis
to include scale of measurement of data collection instruments, sampling method adopted,
sample size and the number of independent variables. Non-parametric tests are distribution-free
tests appropriate for samples drawn deemed to be not normal (Champion, 1970). They are
equally suitable for data obtained through the utility of nominal scale of measurement; ordinal
measurement and processed in ranked order of 1st, 2nd, 3rd, 4th and indefinitely. Non-parametric
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analysis is also suitable when the research does not have idea about the nature of the distribution
(Siegel, 1988).
Hypothesis testing is a technique adopted by researchers to draw conclusion on the results of a
data collected in a research investigation in order to make useful conclusions on a population of
interest (Deveries, 2007). Hun (2010) asserted that a hypothesis is an assumption about the
characteristic of a particular population of interest. Hun (2010) clearly noted that a first-class
hypothesis should be precise enough to be falsifiable to make it acquiescent to testing. A wide
range of procedures exist for the testing of hypothesis, notable among them are z-tests, t-tests,
correlations, ANOVAs, chi square inter alia (Deveries, 2007).
According to Deveries (2007), hypothesis testing is conducted by researchers to identify the
effect that a variable of interest will have on a particular population. Testing hypothesis for a
research study is also aimed at the utilization of the sample data and to infer from the results to
determine the level of real relationship between variables. According to Kochanski (2005),
hypothesis testing is apposite for critical application or for drawing conclusion. Hypothesis
testing results into either ‘null hypothesis (Ho)’ or the ‘alternative hypothesis (H1); for which the
p-value is the probability of obtaining a result as large as that observed in the sample if the null
hypothesis were true; and Alpha, the probability of falsely rejecting the null hypothesis
Typically, the alpha is set at .05 or .01( Anglim, 2007). The p-value is about the statement of
values that never occurred; it is computed based on the distribution of the test statistic assuming
the null hypothesis is true (Anderson et al., 2000). According to Anderson et al. (2000), the
appropriate interpretation of the p-value is based on the probability of the data given the null
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hypothesis is not the converse. The p-value indicates the degree of consistency of the data with
the null hypothesis (Ho) (Anderson et al., 2000). Similarly, the p-value is perceived as the degree
of risk that researchers take in rejecting the null hypothesis (Hun, 2010). When the p-value is less
than 1%, then there is an overwhelming evidence to infer that the alternative hypothesis is true
then conclude that the test is highly significant; p-values between 1% and 5% are deemed to
possess strong evidence to infer that the alternate hypothesis is true hence the result is
significant. Similarly, if the p-value is between 5% and 10% then there is a weak evidence to
support that the alternate hypothesis is true; when the p-value is greater than 5% then the test is
not statistically significant; and in the event that the p-value is greater than 10% then the there is
no evidence to infer the alternative hypothesis is true.
According to Anglim (2007), if the p-value is less than alpha (for instance .05), the probability of
the null hypothesis being true is low, hence reject the null hypothesis and accept the alternative
hypothesis. According to Anderson et al.(2000) a test statistic is first calculated from the
sampled data and judged against its hypothesized null distribution to assess the consistency of
the data with the null hypothesis; if the values of the test statistic are more extreme, then it
implies that the sample data are not consistent with the null hypothesis. In addition, an arbitrary
level (α) is set as a cutoff to serve as the basis for deciding statistically significant and
statistically non-significant results (Anderson et al., 2000).
5.3.4.1 Steps for Hypothesis Testing
Hypothesis testing which is part of the scientific method is conducted according to set criteria in
order to achieve a successful result; thus Deveries (2007) and Hun (2010) identified the criteria
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for hypothesis testing as stating the hypotheses (the null hypothesis(H0) must be stated which
intends that there is no change as a result of the study. The null hypothesis (Ho) postulates that
the independent variables will have no effect on the dependent variables which makes the
population mean to remain same. The alternate hypothesis (H1) which establishes that there will
be an amount of change in the population mean as a result of the study seeks to suggest the
independent variable will have an effect on the dependent variable. It is worthy to note, the
alternate hypotheses are not meant to determine the direction of change, and they can
demonstrate that a change is either positive or negative).
The second criteria is setting the critical region ( this involves defining the alpha level and the
critical region which consist of two extreme scores that are very difficult to obtain if the null
hypothesis(H0) is true. Indeed the result has to be beyond these two extreme scores for them to
be statistically significant. The alpha level in this instance is a probability value and it sets the
critical region indicating that the probability that a result occurs beyond the critical region is by
chance). Collecting data and computing statistics (the researcher conducts study collects data
and manipulate the data using statistical test; the statistical test results are then used to determine
if the null hypothesis should be accepted or rejected). Making a decision (this involves the
rejection of the null hypothesis which implies that the is a significant change in the population
mean this goes to explain that the alternate hypothesis must be accepted; and failing to reject the
null hypothesis which means that there was no change in the population mean). The null
hypothesis is rejected in order to avoid the result of the study from being falsified through further
research (Deveries, 2007).
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5.3.4.2 Approaches/Criteria to Hypothesis Testing
Hun (2010) also added to the approaches to testing hypothesis by advocating test statistic
approach; p-value approach; and Confidence Interval(CI) approach (state H0 and H1; determine
test size α or 1- α, and a hypothesized value; construct the (1- α)100% confidence interval; reject
Ho if a hypothesized value does not exist in CI; and substantive interpretation). According to Hun
(2010), the test statistic approach calculates a test statistic from the empirical data and compares
it with the critical value and a test statistic larger than the critical value leads to the rejection of
the null hypothesis; in adopting the p-value approach, researchers compute the p-value on the
basis of a test statistic and then compare it with the significance level(test size), if the p-value is
smaller than the significance level, the null hypothesis is rejected; and finally, the confidence
interval approach create confidence interval and check if the hypothesized values fall within this
interval, if the hypothesized value cannot be found within the confidence interval, the null
hypothesis is rejected. Figure 5.2 below demonstrates the methods for hypothesis testing as
advocated by Cohen (2010).
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Statistical Testing Confidence Intervals
Figure 5.2: Methods for hypothesis testing ( Adapted from Cohen, 2010)
5.3.4.3 Interpretation of Hypothesis Test Result
The results of a hypothesis test ought to be interpreted to give optimum meaning to the outcome
of the test. The kind of interpretation or inference drawn depends on the test approach adopted;
in the case of statistical testing approach, whenever the p-value is greater than α, the null
hypothesis is not rejected and the inference is that the difference or the association of observed
groups is likely due to chance; and in using the confidence interval approach, a null hypothesis is
not rejected if the confidence interval encloses the pre-established null value and in this instance
it is proper to infer that the difference or the association of observed groups is likely due to
chance (Cohen, 2010).
Set α
Compare p-value to α
p > α
Obtain test statistic and
Corresponding p-value
Conduct Statistical test
p < α
Reject H0
Set confidence limits and
establish null value
Calculate point estimate and
confidence interval (CI)
Determine if confidence
interval includes null value
Null is not
included in
CI
Null is
included in
CI
Do not reject H0
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5.3.4.4 Some Key Statistical Tools for Hypothesis testing
5.3.4.4.1 ANOVA
Tang et al. (2008) pointed out that the ANOVA is used to test the perceptions of respondents
concerning the phenomenon being investigated. The higher the F value; the significant the
difference in perception among respondents. According to Underwood (1997), analysis of
variance (ANOVA) provides tremendous and powerful tool for statistical tests of factors and
their interactions in experiments. Anderson (2006) opined that the fundamental nature of analysis
of variance is to compare variability within groups versus variability among different groups,
using the ratio of the F-statistic. The larger the value of F, the more likely it is that the null
hypothesis (H0) of no differences among the group means (i.e. locations) is false (Anderson et
al., 2006).
5.3.4.4.2 Correlation
According to Varalakshmi et al. (2005), correlation is an analytical tool that measures the extent
of relationship between two or more variables. Correlation expresses the inter-dependence of two
sets of variables upon each other. Correlation involves measuring relationships between price
and quantity; costs, sales and price; income and expenditure, price and supply, demand and
supply; and it serves as the basis for the concept of regression.
5.3.4.4.3 Regression
According to Varalakshmi et al.(2005), regression is the measure of the average relationship
between two or more variables in terms of the original units of a data. Sykes (2000) asserted that
regression analysis is a statistical tool for investigating the relationship between variables in
which the investigator intends to seek the causal effect of one variable upon another variable.
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According to Sykes (2000), a key fundamental requirement for a regression study is the
formulation of hypothesis about the relationship between variables of interest. Sykes (2000)
opined that multiple regression techniques allow additional factors to enter the analysis
separately so that their effect can be estimated. Multiple regression is valuable for quantifying
the impact of various simultaneous influences upon a single dependent variable even when the
investigator is only interested in the effects of one of the independent variables. After identifying
the relationship that exists between two or more variables, there may be the need to predict the
value of one variable given the value of the other variable (Varalakshmi et al., 2005). The
prediction is hinged on the average relationship derived statistically by regression analysis
(Varalakshmi et al., 2005). Regression has several uses including the establishment of functional
relationship between two or more variables; a viable tool in economics and business research as
a result of its potential to establish cause and effect relationship; and the prediction values of
dependent variables from values of independent variables (Varalakshmi et al., 2005).
5.3.4.5 Adoption of Chi Square Test for Hypotheses Testing
Two key underlying assumptions of the Chi-square test state that the sample size must not be less
that 5 (Champion, 1970); and samples must be achieved through independent observation
(Adeyemi, 2009). Chi-square test is appropriate for an entire population irrespective of whether
the data fits normal distribution (Adeyemi, 2009). The three main types of Chi-square test
include Chi-square Goodness of Fit Test; One-Dimensional Chi Square; and Chi square Test for
Two Independent Samples (ibid, 2009). The Chi-Square test is a non-parametric test of
significance targeted at testing the differences or relationship between two variables (Adeyemi,
2009). According to ITS (2010) the chi-square test is an analytical tool used to examine the
differences between nominal or categorical variables; it analyzes whether the observed frequency
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distribution of a categorical or nominal variable is consistent with the expected frequency
distribution. It is normally useful for estimating how close an observed distribution matches with
expected distribution; testing hypothesis; and determining whether two random variables are
independent.
Scheaffer (1999) observed that the chi square test indicates the relationship in data. According to
Zibran (2007), the chi-square test is appropriate for data in frequencies; and the most common
use is to ascertain the probability of association or independence of facts. The key ingredients of
the chi-square test identified by Zibran (2007) consist of the population, sample being the subset
of the population; parameter which is the value generated from or applied to a population;
variable which is anything that can be codified; and can have value from a set (domain) of more
than one values; nominally scaled variable; and contingency table. According to Zibran (2007)
the chi-square test is given by:
(Oi - Ei)2
X2 = ;
Ei
where Oi= observed frequencies; Ei= expected frequencies; i= 1, 2, 3…….n, and n= number of
cells in the contingency table. The use of the chi-square test is restricted to large samples (ibid,
2007). Zibran (2007) concludes that the chi-square test helps in ascertaining whether the
classifications on a given population are dependent on each other or not.
Drawing on from the above extant literature extensively, the Chi-Square test is adopted for this
research as a result of the scale of measurement adopted in data collection which is mainly
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ordinal. Another reason for using the chi square to test hypothesis is the objective of ascertaining
the relationship between pricing as the main dependent variable and independent variables which
have the potential of affecting pricing to cause changes in price levels. Chi-square Test was
conducted using the SPSS to determine if significant relationships exist between dependent and
independent pricing variables. Pricing is the main dependent variable and factors relating to
pricing are independent variables; in this case independents variables are all variables within the
concept of price and value; pricing strategies; project pricing(consultancy pricing); concept of
price and risk; taxation and inflation in pricing; and components of consultancy services pricing.
In the conduct of this research, the Chi-Square test result was reported by first stating the X2
(Chi-Square value), followed by the chi square value from the chi square distribution table( Xα);
the degrees of freedom (df); and the significance level represented by p-value in a bracket.
Therefore, the Chi-Square test results for hypotheses tested in this research were reported in the
format (X2, Xα, df, and p-value). The exact significance levels were reported but in
circumstances where they are less than .001, they were denoted as p < .001. In this research, a
pricing variable was considered to be significant if its significance level represented by p-value
on the hypothesis result table is less than the conventional or the alpha value (α) = 0.005 which
was adopted for the test using the SPSS. The assumptions underlying the Chi-Square Test for
Independence adopted for this research are that: the respondents were randomly selected;
expected frequencies are grater or equal to 1 (E ≥1); and not more than 20% of expected
frequencies are less than 5. The null hypotheses were denoted by Hoi while the alternative
hypotheses were denoted by H1i; where i represent the serial number of the hypothesis being
tested.
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5.3.4.6 Framework Development: Utilizing Factor Analysis
For factor analysis to be suitable, the number of variables in a study must in the range of 20 to 50
(Po-Yi & Chen, 2004). Factor analysis is conducted for varied purposes including the quest for
improving measures; evaluation of construct validity; hypothesis testing; development and
enhancement of instrument’s scales (McCauley et al., 1994); and reduction of data and the
comprehension of its intrinsic characteristics and constructs (Conway & Huffcutt, 2003;
Williams et al., 2012). The reasons for factor analysis are to reduce the number of variables; to
determine the relationship between variables; to discover and evaluate the unidimensionality of a
theoretical concept; to examine the validity of a scale; to ensure the simplification and
effectiveness of analysis and interpretation; to address phenomenon of high correlation between
two or more variables; to develop theoretical frameworks (which is the focus of this particular
research); and to confirm or reject theories ( Williams et al., 2012).
According to Po-Yi and Chen (2004), factor analysis must be conducted in accordance with
these procedures: Bartlett’s Test of Sphericity to test for the existence of common factors within
a collected data to necessitate the conduct of the factor analysis. Estimation of common factors
to ascertain the suitability of the sampled questionnaire for the factor analysis, the principal
component factor analysis is adopted as it has assumed popular usage (Po-Yi & Chen, 2004).
Most studies adopt ‘1’ as the common factor for value for the diagonal line of the matrix;
extraction of components, exploratory factor analysis is adopted for the identification of new
attributes or variables to develop a framework, the method of principal axes is used to extract
common factors; factor extraction is categorized as common factor model and component model
also christened principal component analysis (PCA) (Gorsuch, 1983). Common factor models
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are used for the identification of dormant variables responsible for relationship between
measured variables in a study; and the target of the PCA is to reduce the number of variables by
linear combination to uphold essentially original measures (Conway & Huffcutt, 2003).
Deciding common factor number, the factor analysis combine variables that are highly
correlated and the representation of their meanings, for instance Po-Yi and Chen (2004) adopted
the value of ‘1’ as the benchmark for the selection of common factors in their study on
evaluating the performance of VE study using factor analysis and AHP.
Other means of determining the number of factors in factor analysis include the scree test,
parallel analysis; a priori theory; and the retention of variables that produce high proportion of
variance explanation (Conway & Huffcutt, 2003). The scree plot is irrelevant in most cases as it
allows for the subjectivity of the researcher in the interpretation of the plotted line to determine
the number of factors; hence an alternative to the scree plot is the deployment of parallel analysis
by comparing correlation matrices to eigenvalues and in this case of parallel analysis factors
derived from the real data must be greater than the eigenvalues ( Fricker et al., 2012). The
common factor model is suitable for deriving meaning for the variables observed (Conway &
Huffcutt, 2003). Selection of rotation method is necessary when the factors are more than one
to acquire deduce solution (Conway & Huffcutt, 2003) to curtail the problems associated with
interpretation. The main rotation methods include the orthogonal rotation method and oblique
rotation method, the oblique method was adopted by Po-Yi & Chen (2004). Oblique rotations
are more favoured than orthogonal rotations. A simple structure approach is advocated by
Fabrigar et al. (1999) in which each factor has a set of variables with high loadings and the other
set of factors with low loadings.
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5.3.4.6.1 Interpretation of Results Produced by Factor Analysis
The interpretation of the results churned out by factor analysis output is guided by the following
criteria, common degree which is determine by the conduct of the Barlett test in which the KMO
value is used to ascertain the suitability of the variables for factor analysis. A KMO value above
0.5 implies that the Bartlett’s test is appropriate reinforcing the suitability of the original
variables (Po-Yi & Chen, 2004); factor characteristics and variable explanation values larger
than ‘1’ for respective variables under consideration are considered. Interestingly, factor rotation
does not change the characteristic value and variable explanation hence a careful study of the
factor characteristic value and variable explanation would translate into the identification of the
common characteristic among factors (variables). Factor name, for common factors, a group
name would have to be obtained by the observation of the common characteristic among the
group of factors.
Dwelling extensively on information provided by extant literature above, the factor analysis
was adopted for data analysis to reduce the large amount of data involved in the study and to
classify the variables of the same underlying characteristics. The factor analysis aided in the
development of the grand pricing framework emanating from the systematic development of
subclass framework. The deployment of factor analysis helped in utilizing the KMO to compare
the correlation between variables to identify potential factors. In all the cases of applying the
factor analysis the KMO values were above 0.5 which demonstrated the sampling adequacy of
the research. Similarly, the KMO was used to measure the strength of relationship between
dependent variables (DV) and independent variables (ID) in this study. The KMO values in this
regard proved that the magnitude of partial correlation is significant as a result of KMO values
148
above 0.5 in all cases. This explained that the factors identified in this study are potential pricing
variables in the quantity surveying consultancy services pricing milieu. The KMO values
provided the needed validity for this study which gave the research results the needed impetus
for generalization.
5.4 Summary of the Research Process
The research methodology first of all reviews the existing environment regarding the
philosophies, methods and statistical tools to be adopted for the research. This is then followed
by the justification for the choice of a particular process. Once the key characteristics of the
research philosophies, methods and analytical tools have been examined and justified, the
researcher proceeded with a detailed description of how they were applied in the conduct of this
research study. The methodology adopted for the research process is summarized in figure 5.2
below.
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Figure 5.3: Research Approach Adopted
Review of
Research problem,
research objectives
and framework
Descriptive
: RII
Grand
Generic QS
Consultancy
Services
Pricing
Framework
Research Problem
Research Aim and
Objectives
Research Philosophies
Positivism Epistemology
Quantitative
Method
Survey
Process
Instrument: Questionnaire Design
Data Analysis
Inferential:
Chi Square
test of
Independence
Factor
Analysis: Data
reduction,
classification
and subclass
framework
development
Tripartite
Discussion
involving RII,
Chi Square
test of
Hypotheses
and Factor
Analysis
Theoretical
Framework:
Pertinent Pricing
Theories/concepts
Review of Pertinent
Literature: General
and QS consultancy
Milieu
Postulation of
12 Key Pricing
Hypotheses
112 Operationalized Variables
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CHAPTER SIX
ANALYSIS OF DATA AND DISCUSSION OF RESULTS
6.0 INTRODUCTION
This chapter of the research details the analysis and the discussion of the results realized after the
administration of the key research instrument, the questionnaire which churn data to provide the
basis for this chapter. The data collected using the questionnaire provide the information on the
critical pricing variables under investigation within the context of this research work; the data
also provided other key information which are very crucial for the analysis and will improve the
validity and acceptability of the research. The data in this chapter will provide the manifestations
(Leedy & Ormrod, 2005) of the key pricing variables hitherto unexplored within the arena of the
marketing mix. The data within the analysis and discussion of this chapter will give better
insights on pricing variables that are neglected during the pricing of economic activities
especially services in the nature of those provided by quantity surveying practitioners and other
services providers. The analysis is applicable to other practitioners especially consultants in the
built environment for the fact that pricing is a universal language understood by all.
The nature of data analysed in this chapter is purely primary data; primary data is significant in
this domain of pricing investigation because of their ability to be closer to the layer of truth
(Leedy & Ormrod, 2005). The logical reasoning in this analysis is purely deductive relying on
the data collected using the questionnaire crafted as a result of the general review of extant
literature and critical pricing theories or concepts to postulate critical pricing hypotheses to be
tested to enable inferences to be made for generalization.
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6.1 DESCRIPTIVE ANALYSIS
6.1.1 Respondents Profile
This aspect of the analysis seeks to delve into the background of respondents in order to ascertain
the degree of credible information they have acquired as a result of quantity surveying practice.
It consists of the status of firms; years of experience; rate of work acquisition; and the sectors of
operation. Earlier researchers analysed these critical phenomenon on respondents; for instance
Dogbegah (2009), Otu-Nyarko (2010); Osei-Hwedie (2010); and Saleh (2008) all explored these
aspects of respondents in their study to give much credence to the data behind the results being
analysed and discussed.
6.1.2 Legal Status of Respondent’s firms
Statutory regulations have made it a ritual for all firms to regularize their operations by
registration with statutory authorities in most jurisdictions for socio-economic reasons. The legal
status of firms is crucial as clearly indicated by Owusu-Manu (2008) that the legal character of
the firm depicts the caliber of activity they undertake. Table 6.1.1 demonstrates the legal entities
that respondents in this study belong. It is clear that majority of respondents representing 56
percent practice in private limited firms; while sole enterprise/sole proprietorship;
partnership/joint venture; and other category of firms were represented by respondents below 20
percent. This explains that nature of firms in the construction industry is largely private owned
hence majority of QS practitioners found themselves in these caliber of firms. This result is in
consonance with Otu-Nyarko (2010) and other previous works conducted in similar cases in
Ghana. The reason for the private limited company being in the majority in this regard as far as
Ghana is concerned relates to the fact that QS practitioner firms belong to the construction
industry in which the government is the largest employer operating with procurement regulations
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which do not recognize sole proprietorship. Similarly, most enterprising individuals prefer
owning their businesses as a result of prestige and enjoyment of profits.
Table 6.1.1 :Firm Status
Firms Status Frequency Percent Valid Percent Cumulative Percent
Valid Enterprise/Sole proprietorship 10 12.7 12.7 12.7
Private Limited Company 44 55.7 55.7 68.4
Partnership/Joint Venture 13 16.5 16.5 84.8
Others 12 15.2 15.2 100.0
Total 79 100.0 100.0
6.1.3 Years of Existence of Firms (Age)
The years of existence for that matter the age of firms has been recognize as a critical factor in
the life of every business establishment including quantity surveying firms as well. In this regard,
Stinchcombe (1965) suggested that older firms are more experience; have learned more over
time and are not susceptible to the liabilities of newness and have the benefits of better
performance. Drawing on from Table 6.1.2, 37 percent of respondents practice in firms that are
under 10 years and between 10 to 20 years of establishment respectively. The age of the firm will
determine the experiences of its employees in the acquisition of knowledge and know how in the
pricing of their consulting services.
Table 6.1.2: Years of existence
Years of Experience
Frequency Percent Valid Percent
Cumulative
Percent
Valid Under 10 years 29 36.7 37.2 37.2
10-20 years 29 36.7 37.2 74.4
21-30 years 7 8.9 9.0 83.3
Over 30 years 13 16.5 16.7 100.0
Total 78 98.7 100.0
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Missing Missing 1 1.3
Total 79 100.0
6.1.4 Rate of Work Acquisition
The rate of work acquisition is necessary for the learning throughout the life cycle of a firm. The
more frequent a firm acquires work or consulting engagements, the better their experiences and
sharpness in pricing skills hence their information becomes reliable and more valid than firms
that do not acquire work frequently. From Table 6.1.3, majority of respondents’ firms have work
acquisition rate of 42 percent, while the next significant work acquisition rate is moderately
frequent with 33 percent.
Table 6.1.3: Rate of Work Acquisition
Work Acquisition
Frequency Percent
Valid
Percent
Cumulative
Percent
Valid Not frequent 7 8.9 9.1 9.1
Moderately frequent 26 32.9 33.8 42.9
Frequent 33 41.8 42.9 85.7
Very frequent 11 13.9 14.3 100.0
Total 77 97.5 100.0
Missing Missing 2 2.5
Total 79 100.0
6.1.5 Sectors of Operation
It is also important to examine the sectors that consulting QS practitioners operate in order to
identify the areas that they are well-informed. It will also serve as the direction and identification
of opportunities yet untapped in the economy. For instance Olatunji et al. (2009) acknowledged
that the quantity surveying discipline is an important profession in the construction industry. In
furtherance of this assertion and to compare with other allied sectors in the construction industry
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where the role of the quantity surveying profession may be required, this research explored
sectors such as civil and structural engineering; Mechanical building and engineering services;
petro-chemical; mineral extraction; and urban planning. In the construction sector, the frequency
of operation is 35 percent; civil and structural engineering is 15 percent frequent; mechanical
building and engineering services is 5 percent frequent; petro-chemical is 4 percent frequent;
mineral extraction is 1 percent frequent and 5 percent very frequent; and urban planning had 6
percent frequent and 3 percent very frequent as demonstrated in Tables 6.1.4a, b, c, d, e and f
below.
From the result above, it is clear that QS professionals operate in the building construction
sector more than the other sectors examined in this research; this result is in consonance with the
earlier assertion of Olajunji et al. (2009). On the contrary, the low level of operation by QS
practitioners in other sectors examined including petro-chemical is an opportunity for
enterprising QS practitioners to venture into since those sectors are unsaturated with QS
practitioners hence their services will be in dire need in those sectors.
Table 6.1.4a: Building construction
Responses Frequency Percent Valid Percent
Cumulative
Percent
Valid Not frequent 3 3.8 3.8 3.8
Less frequent 4 5.1 5.1 9.0
Moderately Frequent 23 29.1 29.5 38.5
Frequent 27 34.2 34.6 73.1
Very frequent 21 26.6 26.9 100.0
Total 78 98.7 100.0
Missing Missing 1 1.3
Total 79 100.0
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Table 6.1.4b : Civil and structural engineering
Responses Frequency Percent Valid Percent
Cumulative
Percent
Valid Not frequent 9 11.4 11.4 11.4
Less frequent 23 29.1 29.1 40.5
Moderately Frequent 30 38.0 38.0 78.5
Frequent 12 15.2 15.2 93.7
Very frequent 5 6.3 6.3 100.0
Total 79 100.0 100.0
Table 6.1.4c : Mechanical building and engineering services
Responses Frequency Percent Valid Percent
Cumulative
Percent
Valid Not frequent 46 58.2 58.2 58.2
Less frequent 24 30.4 30.4 88.6
Moderately Frequent 5 6.3 6.3 94.9
Frequent 4 5.1 5.1 100.0
Total 79 100.0 100.0
Table 6.1.4d: Petro-chemical
Responses Frequency Percent Valid Percent
Cumulative
Percent
Valid Not frequent 68 86.1 86.1 86.1
Less frequent 7 8.9 8.9 94.9
Moderately Frequent 1 1.3 1.3 96.2
Frequent 3 3.8 3.8 100.0
Total 79 100.0 100.0
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Table 6.1.4e: Mineral extraction
Responses Frequency Percent Valid Percent
Cumulative
Percent
Valid Not frequent 65 82.3 82.3 82.3
Less frequent 8 10.1 10.1 92.4
Moderately Frequent 1 1.3 1.3 93.7
Frequent 1 1.3 1.3 94.9
Very frequent 4 5.1 5.1 100.0
Total 79 100.0 100.0
Table 6.1.4f: Urban planning
Responses Frequency Percent Valid Percent
Cumulative
Percent
Valid Not frequent 30 38.0 38.0 38.0
Less frequent 27 34.2 34.2 72.2
Moderately Frequent 15 19.0 19.0 91.1
Frequent 5 6.3 6.3 97.5
Very frequent 2 2.5 2.5 100.0
Total 79 100.0 100.0
6.2 RANKING OF KEY PRICING VARIABLES
This section of the descriptive analysis of data employs the Relative Importance Index (RII) in
the ranking of pricing variables. The RII has been preferred over the mean and standard
deviation as they are not credible and reliable tools for examining the overall ranking of key
attributes (Chan & Kumaraswamy, 1997). In a different dimension, Ferguson (1978) contended
that relevant attributes must be identified by imagination and common sense; Chan &
Kumaraswamy (1997) supported Ferguson by indicating that the identification of significant
variables from a vast amount of variables should be guided by sensibility and reasonability; and
157
to improve these ranking and identification of attributes hypothesis testing must be objective and
robust (Beeston, 1983 and Gilchrist, 1984). In view of the above revelation by earlier researchers
on the ranking of variables, the art of ranking pricing variables in this research observed the rule
of falsifiability (underpinning discussions with solid facts and stating other works that contradict
the findings), validity(drawing sensible conclusions), parsimony (keeping it simple; “getting the
job done with the simplest tool” ) (Levine, 1996). The analysis and ranking of key pricing
variables were within the context of price and value; project pricing (consultancy pricing);
concept of risk; concept of taxation and inflation; quantity surveying consultancy services
pricing components; challenges confronting quantity surveying consultancy practice; and
quantity surveying consultancy services.
6.2.1 Concept of Price and Value
According to Ramirez (1999) value is the parameter for the measurement of worthiness. Value is
assessed through the anticipated results balanced against cost. Table 6.2.1 demonstrates variables
for achieving realistic pricing. These variables are crucial in the 21st century to the extent that
business organizations that intend to break-even ought to price within the framework of these
variables in order to achieve realistic prices for services provided to clients. The problem
bedeviling QS practice borders on the inability to recover cost incurred in the provision of
services to their clients. Drawing on from Table 6.2.1, price and value concepts that affect
pricing were categorized into price and value which consist of: value of a product or service
(RII= 0.78), affordability (RII= 0.71); just price concepts consisting of the government (RII=
0.58); seller’s profit (RII= 0.67); customer’s intrinsic value (RII= 0.63); customer’s affordability
(RII= 0.71); media action and pressure group had RII fairly below the significant level of 0.5.
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Another aspect examined was the role of the firm in price setting and this includes the goals,
importance and objectives of pricing. In this category key significant variables include: firm’s
image (RII= 0.77); firm’s objectivity (RII= 0.76); firm’s success ( RII = 0.76); and firm’s failure
(RII= 0.64). The pricing strategy category as indicated by the results in Table 6.2.1 is one of the
most pricing and value concepts considered by respondents as variables within this category
were demonstrated to be very significant consisting of demand (RII= 0.79), cost(RII= 0.79),
profit (RII= 0.78) and competition (RII= 0.77).
Drawing on from the above results, extant literature has placed much emphasis on the concept of
price and value thus in their works, Cannon (1998) perceived price and value to be equable or
comparable; and Farese et al.(1991) considered price as value placed on services rendered to
clients. Perreault and McCarthy (2002) noted price is the money placed on value while
Pontiskoski (2009) advocated that the gateway to successful pricing is understanding the value
clients place on the service provided. Other research studies that have underscored the role of
value in price setting include Zhilin and Robin (2004); and Grahame and Mark (1997)
conceptualize value to be anticipated satisfaction derived from a service or product. Within the
context of the above literature and empirical results, it is clear that price and value concepts are
important ingredients in gauging price, as it is evident that the key variables value of product or
service and affordability were clearly above the higher order of significant. It is therefore
imperative for QS practitioners to ensure that clients have value for their services. This will aid
them in setting realistic prices for their services because if the value is greater than affordability,
the service provider (consultant) and the client will gain.
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Some aspects of the just price have not been observed fully over the years as indicated in the
empirical results of this research (see Table 6.2.1). Among them seller’s profit and customer’s
intrinsic value were fairly above the middle order of pricing variables; on the contrary,
customer’s affordability was above the high order of significance while others were insignificant.
The underlying dynamics for relegating key just price concepts notably the government, media
action and pressure group is democratization and the dominance of capitalism over socialism as
governments do not interfere directly in the capitalist market by setting minimum prices to affect
goods and services.
From the above discussion, the main role of the quantity surveyor is to be successful in gauging
the price of services provided to clients to sustain the business of consulting. Within the domain
of pricing roles, the image of the firm; the objectives of the firm; and firm’s desire to be
successful are all active roles in consultancy services price gauging. The objectives of the firm
regarding pricing include cost recovery, profit margin maximization, profit maximization,
revenue maximization, quality leadership, quantity maximization, status quo and survival
(Channon, 1986; Cannon and Morgan, 1990; Bonnici, 1991; Payne, 1993; Palmer, 1994;
Bateson, 1995; Woodruff, 1995; Drake and Llewellyn, 1995; Ansari et al., 1996; Lovelock,
1996; Meidan, 1996; Zeithaml and Bitner, 1996; Hoffman and Bateson, 1997; Langeard, 2000;
and Owusu-Manu et al., 2012). One limitation of this research is that these specific pricing
objectives were not explored in detail; a further research agenda to explore the detail dynamics
of pricing objectives with much emphasis on their influence on price levels will be a novel
undertaking in research.
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Pricing strategies considered by respondents to be higher order pricing variables include demand,
cost, profit and competition were raked first, second, third and fourth with RII above 0.7
respectively. It is clear that among the price and value concepts, pricing strategies are the most
significant in the fixing of quantity surveying consultancy services prices. Quantity surveyors
just like any other professionals as well as business entities intend to make profit, recover cost
incurred in rendering services to clients. These must be attained within the challenges of
competition and accurate estimation of demand for quantity surveying services. Several
strategies have been adopted in pricing over the decades to achieve pricing quality (Owusu-
Manu et al., 2012) some of which include competitive pricing and multiple pricing. Pricing
strategies affect profitability in the sense that a particular pricing strategy adopted might not
yield the needed profit level required to stay in business. A recent study by Hinterhuben and
Liozu (2012) revealed that both researchers in the academia and industry practitioners adopt key
pricing strategies of cost-based pricing; competition-based pricing; and customer value-based
pricing which are in tandem with the pricing strategies identified in this study as cost,
competition and demand.
Table 6.2.1: Concept of Price and value
Concept of Price and Value
A. PRICE AND VALUE N SUM RII RANKING MISSING
1. Value of a product or service 79 287 0.73 8
2. Affordability
79 280 0.71 10
B. JUST PRICE 1. The Government 79 231 0.58 14
2. Media action 79 171 0.43 16
3. Pressure Group 79 175 0.44 15
4. Seller’s profit 79 263 0.67 11
5. Customer’s intrinsic value 79 249 0.63 13
6. Customer’s affordability
78 277 0.71 9 1
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C. IMPORTANCE, OBJECTIVES AND GOALS OF PRICING(ROLE OF THE FIRM) 1. Firm’s objectivity 79 300 0.76 6
2. Firm’s failure 79 254 0.64 12
3. Firm’s success 79 299 0.76 7
4. Firm’s image
79 304 0.77 5
D. PRICING STRATEGIES
1. Cost 79 313 0.79 2
2. Profit 79 309 0.78 3
3. Demand 79 313 0.79 1
4. Competition 79 305 0.77 4
6.2.2 Project Pricing (Consultancy Pricing)
Quantity surveying practitioners are in the business of rendering services in the construction and
its allied sectors. Projects are not manufactured products hence their related services such as
consultancy services which QS practitioners render are for a fixed duration. Similarly, services
provided in the construction sector are tailor made, therefore require different pricing approach.
In addition, the requirements for engaging QS consultants are different from suppliers or
providers of manufactured products. Table 6.2.2 demonstrates the key issues of consultancy
services provision during project execution. These consultancy pricing variables have been
classified into pricing parameters/ criteria and bid price success (c.f. Table 6.2.2). From Table
6.2.2, the variables relating to pricing criteria and bid price success are all within the higher order
pricing variable category with RII above 0.70 except business development and overhead and
profit while technical capacity and materials used on the project have RII above 0.80 and were
ranked first and second respectively.
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Table 6.2.2: Consultancy Pricing
Project Pricing (Consultancy Pricing)
A. PRICING PARAMETERS/ CRITERIA
N SUM
RII
RANKING
MISSING
1. Time taken to solve the problem 79 314 0.79 3
2. Materials used on the project 79 315 0.80 2
3. Good financial control system 79 298 0.75 10
4. Record of past project costs 79 288 0.73 12
5. Accurate forecast of future cost 79 289 0.73 11
6. Production of timely reports
79 302 0.76 9
B. BID PRICE SUCCESS 1. Financial capacity 79 310 0.78 5
2. Technical capacity 79 319 0.81 1
3. Firm’s experience 79 311 0.79 4
4. Duration to render the service 79 303 0.77 8
5. Firm’s reputation 78 300 0.77 7 1
6. Business development 79 271 0.69 13
Overhead and profit 79 308 0.78 6
6.2.3 Concept of Risk
Risk is any event related to a consulting engagement that has the potential of making the
consulting endeavor a failure. Risk is related to consultancy services pricing in two main ways:
the risk associated with the project being undertaken; and the risk associated with pricing. It is a
fact that if the project has elapsed prematurely then the whole of the consultation period has
come to an end. It is therefore clear that consulting engagement is complimentary to project
execution in the built environment. Risk in their nature can occur at different stages of the
project and those associated with consulting pricing can affect consultancy services pricing.
Table 6.2.3 has categorized risks investigated in this research into price associated risks; and
risks likely to occur at the various stages of projects that will have impact on consultancy
services pricing. From Table 6.2.3 risk at the various stages of projects affecting consultancy
services pricing were highly ranked by respondents; notable among these variables include
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financial risk (RII = 0.73); legal risk (RII = 0.70); regulatory risk (RII= 0.70); political risk (RII
= 0.69) are all in the higher order variables. Similarly, pricing risks relate to the activities of the
consultant during pricing. These risks include financial risk (RII= 0.73); market related risk
(RII=0.68); associated business risk (RII=0.68); technological risk (RII= 0.67) and
organizational risk (RII = 0.63). Among these direct risks of consulting, financial risk is
perceived to be a higher order pricing variable while the rest comprising of market related risk
inter alia are perceived to be marginally above the middle order ( Chappel, 1994 and Doloi,
2008) pricing variables with average RII= 0.60. Similarly, risks at the various stages of projects
or consulting engagements affecting price levels which are indirect risks to the consulting entity
were professed to be in higher order pricing variables comprising of financial risk (RII= 0.73,
ranked first); legal risk (RII= 0.70, ranked third); regulatory risk (RII= 0.70, ranked fourth);
political risk (RII= 0.69, ranked fifth); and force majeure risks (RII= 0.61, ranked twelfth).
The indirect risks associated with projects are apparently significant pricing variables that can change the
levels of consultancy services pricing. It is clear from the result that financial risk is both direct and
indirect consultancy services pricing risk of significant proportion. The economic crisis being experience
globally has brought serious financial risks to the consulting industry, for instance Adendorff et al. (2012)
clearly asserted that the current global crisis has intensified the risks of completed projects and decreased
the amount of work completed in the built environment. This assertion has demonstrated the gravity of
indirect risks to consultancy services pricing. In view of the above result, it is important for price setters
in the consulting industry to envisage the probability of any of the category of the risks identified
occurring in the execution of projects for which consulting services are emanate. It is therefore important
to be vigilant and resourceful in environmental analysis to identify the potential risk as far as pricing
consulting services are concerned.
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Table 6.2.3: Concept of Risk
Concept of Risk
A. PRICE AND RISK(Direct risks)
N SUM RII RANKING
MISSING
1. Associated business risk 79 268 0.68 7
2. Financial risk 78 298 0.73 1 1
3. Market related risk 79 269 0.68 6
4. Logistical and infrastructural risk 78 240 0.62 11 1
5. Managerial and operational risk 79 261 0.66 9
6. Technological risk 79 263 0.67 8
7. Organizational and societal risk 79 248 0.63 10
B. RISKS AT VARIOUS STAGES OF PROJECTS AFFECTING CONSULTANCY
PRICE LEVELS(Indirect risks) 1. Financial risk 79 287 0.73 2
2. Legal risk 79 277 0.70 3
3. Regulatory risk 79 276 0.70 4
4. Political risk 79 273 0.69 5
5. Force majeure risks 79 239 0.61 12
6.2.4 Concept of Taxation and Inflation
Economic activities notably manufacturing and economic services provision are subject to
taxation in many countries globally to generate revenue for governments. In pursuant of this
agenda, numerous nomenclature of taxes exist which are burdens imposed on service providers
and clients. These taxes are factored into the price formulation of services provided by
consultants in order to recover their invested resources into service delivery to clients. Table
6.2.4 examines the various forms of taxes, inflation and subsequently inflationary causes
affecting change in consultancy price levels that consulting entities may encounter in the
delivery of their services to clients and setting of appropriate prices. Inflationary causes affecting
consultancy price levels are perceived to be potential price altering agents in any economic
activity. It is clear from Table 6.2.4 that in this category of variables, effects of input market (RII
= 0.70, ranked third); government policies (RII = 0.69, ranked fourth); international trade and
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trade barriers (RII = 0.68, ranked fifth); and production shortfall (RII = 0.68, ranked sixth) have
in most cases demonstrated that they are marginally significant except effects of variable inputs
affecting the levels of consultancy services pricing. It is a fact that these phenomena affect the
commercial transactions of consultancy firms in the purchase of materials and other relevant
supplies to aid them in delivering services to clients. The two variables in the inflation category
were ranked high by respondents; thus inflation (RII = 0.77, ranked first); and input prices (RII =
0.75, ranked second) were in higher order variables. Though respondents acknowledge operating
and pricing within the framework of inflation, inflationary causes affecting change in
consultancy price levels and various tax obligations are marginally considered in pricing, the
only notable case is VAT/NHIL. This phenomenon could be attributed to non-payment of taxes
or tax evasion as a result of the inability of the tax authorities to locate consultants to fulfill this
statutory obligation as a result of improper planning and layout policies of offices. However,
consulting entities rendering services to government establishment may not escape the tax net
because of the regulations of the Procurement Act 663. This finding is a pearl for the tax
authorities to dwell on in expanding their tax net to mobilize more revenue for government
coffers for development. It is equally important for the consulting entities to take cognizance of
inflation and its causes that will affect consultancy services pricing.
Table6.2.4: Concept of Taxation and inflation
Concept of Taxation and inflation
TAXATION
N
SUM RII
RANKING
MISSING
1. Personal income tax 79 239 0.61 8
2. VAT/ NHIL 79 252 0.64 7
3. Corporate tax 79 218 0.55 11
4. Profit tax 79 221 0.56 10
5. Local rates 79 224 0.57 9
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6. Property tax 79 218 0.55 12
B. INFLATION 7. Input prices 79 297 0.75 2
8. Inflation 79 302 0.77 1
C. INFLATIONARY CAUSES AFFECTING CHANGE IN CONSULTANCY PRICE
LEVELS 9. Production shortfall 79 267 0.68 6
10. Effects of input market 79 275 0.70 3
11. Government policies 79 273 0.69 4
12. International trade and trade barriers 79 267 0.68 5
6.2.5 Quantity Surveying Consultancy Services Pricing Components
Inflation and taxation policies in Table 6.2.4 above have the potential of affecting the major consultancy
services pricing components notably materials for report preparation and training programmes; travel and
transport; supplies and equipment; and communication. Table 6.2.5 clearly demonstrate the various
components of quantity surveying consultancy services pricing comprising of profits (RII = 0.76); travel
and transport (RII = 0.75); staff allowances (RII = 0.74); consultant staff remuneration (RII = 0.74);
report preparation and contingencies (RII = 0.72) respectively; and taxes and duties; and mobilization and
demobilization (RII = 0.71) respectively. Other variables demonstrated in Table 6.2.5 are largely above
the middle order of significance with average ranking of 0.68. These components except profits and
contingencies represent the cost component of consulting entities in the delivery of their services to
clients (Washburn et al., 2002; JICA, 2006; The World Bank, 2002; CEBC, 2011 and TRF,
2011). In reference to earlier analysis on concept of price and value (See Table 6.2.1 ), cost
(RII= 0.79, ranked second) was in the higher order pricing variables among pricing strategies
variables. Juxtaposing this against the performance of pricing components, it is proper to assert
that when cost of consultancy services is high all components of consultancy services pricing will
be proportionally high except profit and contingencies.
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Table 6.2.5: Quantity surveying consultancy services pricing components
Quantity surveying consultancy services pricing components
PRICING COMPONENTS N SUM RII RANKING
1. Profits 79 302 0.76 1
2. Travel and transport 79 295 0.75 2
3. Staff allowances 79 294 0.74 3
4. Consultant staff remuneration 79 293 0.74 4
5. Report preparation 79 285 0.72 5
6. Contingencies 79 284 0.72 6
7. Taxes and duties 79 282 0.71 7
8. Mobilization and demobilization 79 281 0.71 8
9. Communications 79 272 0.69 9
10. Supplies and equipment 79 272 0.69 10
11. Insurance 79 272 0.69 11
12. Office rent 79 266 0.67 12
13. Training programmes 79 260 0.66 13
6.2.6 Challenges confronting quantity surveying consultancy practice
There are numerous challenges that quantity surveying consultancy practitioners encounter in the
delivery of services to clients. These challenges are classified as general challenges and those
that are price-related. Referring to Table 6.2.6 below, the critical general challenges confronting
the quantity surveying profession perceived to be in higher order by respondents include impact
of competition ( RII= 0.72, ranked first); changing nature of client demands (RII= 0.71, ranked
second); slow response to information and communication technology revolution (RII= 0.70,
ranked third); and complexity of modern construction( RII= 0.70, ranked fourth). Other
challenges notably inability to integrate applied research outputs into practice; slow response to
changing contractual arrangements; and challenge of appropriate response to emerging services
were ranked with RII ranging from 0.65 to 0.69.
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From the above, the identifiable general challenges confronting quantity surveying practitioners
are serious, and though some of these challenges are perceived to be general they can also affect
pricing. These challenges include the impact of competition; slow response to information and
communication technology; complexity of modern construction projects inter alia. Specifically,
Odeyinka (2006) identify key modern construction project arrangements that the quantity
surveyor will face as challenging to include Private Finance Initiative (PFI) and Public Private
Partnership (PPP); supply chain management; partnering and alliancing; prime contracting; and
performance based contracting. Other emerging areas that the quantity surveyor will face
challenges which will subsequently affect consultancy services pricing comprise of facilities
management, project management, value management, commercial management and risk
management; these challenges Odeyinka (2006) averred that the quantity surveyor will have to
be prepared in the areas of business and management competence to be equipped to properly
deliver in these project nomenclature. Based on the assertion of Odeyinka (2006) and the above
result of this research, it is appropriate that quantity surveying professional bodies and
educational institutions notably universities and polytechnics begin training students in business
management and entrepreneurial pedagogy.
The price-related challenges were within the middle order variables implying that their effect is
averagely influential when pricing services. The dominance of capitalism has weakened the
power of professional bodies in price determination and control leading to haggling between
demand (client) and supply (consultant) to set their price levels hence price-related challenges
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are deemed to be moderately significant in the pricing of quantity surveying consultancy services
except in the cases of market forces.
Table 6.2.6: Challenges confronting quantity surveying consultancy practice
A. GENERAL CHALLENGES
N SUM RII RANKING
1. Slow response to changing contractual arrangements 79 262 0.66 7
2. Challenge of appropriate response to emerging
Services
79 257 0.65 8
3. Slow response to information and communication
technology revolution
79 277 0.70 3
4. Inability to integrate applied research outputs into
practice
79 273 0.69 5
5. Changing nature of clients’ demand 79 280 0.71 2
6. Impact of competition 79 286 0.72 1
7. Complexity of modern construction projects 79 275 0.70 4
B. PRICING/FEES CHALLENGES
1. Reducing fees to loss-making territory 79 251 0.64 10
2. Exposure to risks 79 266 0.67 6
3. Decrease in project value 79 257 0.65 9
4. Fluctuation in professional tariff of fees 79 240 0.61 11
6.2.7 Quantity surveying consultancy services (Seeley, 1997; Olatunde, 2006)
Services rendered are priced in the services industry to rope in revenue to recover cost and to
provide reward for the efforts of service providers via profits. In quantity surveying professional
practice, numerous services exist that practitioners can render and price accordingly. These
services were acknowledged variously in literature by notable authorities namely Seeley (1997);
Olatunde (2006) inter alia. This research classified quantity surveying services as traditional and
non-traditional (emerging) services (See Table 6.2.7a and Table 6.2.7b) below. Traditional
services are the most dominant services rendered by QS consultants while the non-traditional
services or the emerging services remain the less dominant within the framework of services
provided by QS consultants to clients. The demonstration of the results From the Tables6.2.7a
and Table 6.2.7b below implies that traditional services are the most significantly priced while
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the non-traditional services remain the less priced. It is worthy to note that one of the key non-
traditional service sectors that the quantity surveyor can explore which is not yet saturated by
other QS practitioners is the oil and gas sector. The competition in the non-traditional service
sectors of QS practice is not intensive hence innovative QS practitioners venturing into the oil
and gas and other non-traditional services of quantity surveying have the opportunity of making
substantial profit and are open to the prospect of enjoying some significant level of monopoly for
some considerable period of time.
Table 6.2.7a: Quantity Surveying Traditional Services
Quantity Surveying Consulting Services N Sum RII Ranking
1. Preparing tender documents 79 318 0.81 1
2. Interim valuations and payments 79 308 0.78 2
3. Valuation of construction work 79 306 0.77 3
4. Valuation of variations 79 301 0.76 4
5. Cost control of projects 79 296 0.75 5
6. Final account preparation and
agreement 79 296 0.75 6
7. Claims preparation 79 286 0.72 7
8. Financial statements 79 285 0.72 8
9. Cost planning and cost checking 79 280 0.71 9
10. Advice on contracting methods 79 279 0.71 10
11. Preliminary cost advice 79 278 0.70 11
12. Participating in contract administration 78 274 0.70 12
13. Preparing cash flow forecasts 79 273 0.69 13
14. Advice on construction procurement
systems 79 272 0.69 14
15. Negotiating contract prices 79 260 0.66 15
16. Project management 79 248 0.63 16
17. Value management 79 239 0.61 17
18. Arbitrations and disputes resolution 79 183 0.46 18
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Table 6.2.7b:Non-Traditional (Emerging) Services
NON-TRADITIONAL(EMERGING) SERVICES
Quantity Surveying Consulting Services N Sum RII Ranking Missing
1. Advice on procurement strategy 78 175 0.45 1 1
2. Contract administration 78 175 0.45 2 1
3. Project management 78 174 0.45 3 1
4. Construction management 77 168 0.44 4 1
5. Procurement management 78 169 0.43 5 1
6. Development and facilities management 78 169 0.43 6 1
7. Construction management 78 168 0.43 7 1
8. Program management 78 167 0.43 8 1
9. Expertise in maintenance programme 78 166 0.43 9 1
10. Cost planning and budgeting 78 162 0.42 10 1
11. Procurement and supply chain
management 78 156 0.40 11
1
12. Whole life cycle cost management 78 152 0.39 12 1
13. Cost and business planning 78 151 0.39 13 1
14. Risk and value management 78 151 0.39 14 1
15. Commercial management 78 150 0.38 15 1
16. Management of capital expenditure 78 146 0.37 16 1
17. Facilities management of stations 78 146 0.37 17 1
6.3 INFERENTIAL ANALYSIS: HYPOTHESES TESTING
Inferential analysis deals with parameter estimation and hypothesis testing. Several statistical
techniques are employed in these cases to manipulate data for analysis and interpretation. In this
research work, inferential analysis is solely limited to hypothesis testing (see chapter three for
more details) by adopting Chi-Square test. Utilizing the relative importance index (RII) which is
a descriptive technique is not enough to generalize the result to the population, as some results
may be due to chance. In order to ascertain the significance of the results, hypothesis testing has
been adopted to achieve this goal. The Chi-Square test was adopted because of its admissibility
of all types of scale (nominal, ordinal, interval and ratio) used in collecting data. Also, the ranked
nature of the preliminary results analysed above has made the Chi-Square test apt for this test of
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significance. The hypothesis tested were crafted from a carefully constructed theoretical
framework covering key pricing concepts notably price and value; just price; role of the firm
(importance, objectives and goals of pricing); pricing strategies; pricing parameters; bid price
success; price and risk concepts; risks associated with various stages of projects affecting
pricing; taxation and inflation; and quantity surveying consultancy services pricing components.
6.3.1 Price and Value Hypotheses
Ho1: A significant key to successful pricing is not dependent on: (H1a) value of a product or
service and (H1b) affordability.
H1 1: A significant key to successful pricing is dependent on: (H1a).value of a product or service
and (H1b). affordability
A chi-square test conducted to determine the relationship between successful pricing (a
dependent variable) and pricing variables (independent variables) as demonstrated in Table H1
below revealed that there was significant relationship between the value of a product (X2 =
61.190, X2α = 14.860, df = 4, p < 0.001); and affordability ( X2 = 52.329, X2α = 14.860, df = 4, p
< 0.001). Since X2cal
> X2α at p < 0.05, reject the null hypothesis. The results clearly suggest that
there is relationship between the independent variables and the dependent variable hence the
alternate hypothesis holds implying that the successful pricing of quantity surveying consultancy
services is dependent on the value of the service provided to clients and the ability of clients to
afford for the services (ability to pay the services). These pricing variables, “value of a product
or service” and “affordability” were higher order pricing variables with RII of 0.73 and 0.71
respectively. The hypothesis testing of these variables further gives much statistical credence to
the relative ranking of these variables. This result clearly suggests that the value of the services
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that QS consultants provide to clients has significant bearing on the prices they charge. Poor
services in value will require low prices being attained while quality services provided to clients
will definitely require sustainable pricing that will result in break-even. In another vein,
providing value services alone will not inure to realistic pricing or successful pricing being
chalked but the ability of the client to afford or pay for a price determined based on the value of
the services provided. It is therefore necessary to determine the parameters for ascertaining the
value of services provided by QS consultants to their clients. However, this phenomenon has not
been addressed by this study hence a research agenda to explore the criteria for value of QS
services will be novel and apt. Similarly, a study to determine the willingness to afford or pay
(WTP) for consultancy services will be a step in the right direction.
Table H 1: Test Statistics
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. Value of a product or service 61.190a 4 0.000
2. Affordability 52.329a 4 0.000
a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.-
Ho2: The achievement of just price levels is not significantly dependent on: (H2a). the
government. (H2b) media action. (H2c) pressure group (H3d). Seller’s profit. (H3e). customer’s
intrinsic value. (H3f) customer’s affordability.
H12: The achievement of just price levels is significantly dependent on: (H2a). the government.
(H2b). media action. (H2c). pressure group (H3d). seller’s profit. (H3e). customer’s intrinsic
value. (H3f). customer’s affordability.
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The chi-square test conducted with respect to hypothesis 2 is demonstrated in Table H2 below.
The test result revealed that there is significant relationship between media action ( X2 = 34.861,
X2α = 14.860, df = 4, p < 0.001); pressure group ( X2 = 36.886, X2α = 14.860, df = 4, p < 0.001);
Seller’s profit ( X2 = 28.278, X2α = 14.860, df = 4, p < 0.001); customer’s intrinsic value ( X2 =
27.899, X2α = 14.860, df = 4, p < 0.001); and customer’s affordability ( X2= 76.359, X2α =
14.860, df = 4, p < 0.001). Since X2cal
> X2α at p < 0.005, reject the null hypothesis in terms of
these group variables, hence there is significant evidence that these group variables are related to
the achievement of just price levels. However there is significant evidence that the variable ‘the
government’(X2 = 1.316, X2α = 14.860, df = 4, p = .859). Since X2cal
< X2α at p > 0.005, accept
the null hypothesis in terms of this group variable (the government). The media has been
powerful since the emergence of democratization in Ghana. The media can influence price level
to the extent that the consultant’s objective of making profit can be achieved or dashed.
Customer’s/clients intrinsic value can also be influenced by the media and this will subsequently
affect the decision of the client on the services being acquired leading to the determination of a
price level that will be beneficial to the consultant or vice versa. It is therefore important for
practitioners of QS consultancy to be mindful of media action when setting price for their
services. QS consultancy price setters hence forth ought to consider the media landscape and
other pricing variables when fixing prices for clients.
Table H 2: Test Statistics
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. The Government 1.316a 4 .859
2. Media action 34.861a 4 .000
3. Pressure Group 36.886a 4 .000
4. Seller’s profit 28.278a 4 .000
5. Customer’s intrinsic value 27.899a 4 .000
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6. Customer’s affordability 76.359b 4 .000
a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.
b. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.6.
Ho3: The role of the firm in setting price levels is not significantly dependent on: (H3a)
objectivity. (H3b) failure. (H3c) success. (H3d) image.
H1 3: The role of the firm in setting price levels is significantly dependent on: (H3a). objectivity.
(H3b). failure. (H3c). success. (H3d). image.
The Chi-Square test conducted with regards to Hypothesis 3 above is demonstrated in Table H3
below; the result revealed that there is significant relationship between the role of the firm in
setting prices and firm’s objectivity ( X2 = 49.544, X2α = 14.860, df = 4, p < 0.001); firm’s
failure (X2 = 14.861, X2α = 14.860, df = 4, p = 0.005); firm’s success (X2= 68.658, X2α = 14.860,
df = 4, p < 0.001); and firm’s image (X2 = 42.456, X2α = 14.860, df = 4, p < 0.001) and the role
of the firm in setting prices. Since, X2cal > X2α (14.860) at p < 0.005 in all the cases of the group
variables, we reject the null hypothesis H0 at a significance level of 0.005. Therefore there is
significance relationship between the role of the firm in setting price levels and the objectives of
the firm’s objectivity; firm’s failure; firm’s success; and the firm’s image). It has been
statistically evident that the role of the firm in fixing consultancy prices would result in the
failure of the firm; prices set by the firm would have impact on their image before their clients;
and this leads to the success of the firm. It is imperative to note that the determinant of the three
key variables above is pricing objectives. QS consultancy firms must determine their objectives
prudently in within the parameters of the above pricing outcomes ( image, success and failure).
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Table H 3: Test Statistics
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. Firm’s objectivity 49.544a 4 .000
2. Firm’s failure 14.861a 4 .005
3. Firm’s success 68.658a 4 .000
4. Firm’s image 42.456a 4 .000
a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.
Ho 4: The fundamentals of pricing strategy of a firm are not dependent on: (H4a). Cost. (H4b).
Profit (H4c). Demand (H4d). Competition
H1 4: The fundamentals of every pricing strategy of a firm are dependent on: (H4a). Cost. (H4b).
Profit (H4c). Demand (H4d). Competition
The Chi-Square result for hypothesis 4 in Table H4 below demonstrates that a significant
relationship exist between the pricing strategy and group variables( independent variables)
namely cost (X2 = 42.873, X2α = 12.838, df = 3, p < 0.001); profit ( X2 = 59.038, df = 4, p <
0.001, X2α = 14.860 ); demand ( X2 = 33.354, df = 3, p < 0.001, X2α = 12.838 ); and competition
( X2 = 40.557, df = 4, p < 0.001, X2α = 14.860 ). Since the X2cal > X2α at p < 0.005 in all the
cases of the group variables, reject the null hypothesis H0 at a significance level of 0.005.
Therefore, there is significant evidence to suggest that pricing strategy is dependent on cost,
profit, demand and competition. This will mean that consultancy services pricing must take
cognizance of these variables of cost, demand, competition and profit. Having established the
evidence of these variables (demand, cost, competition and profit) as the fundamentals of
pricing, it is novel that a further research at advanced level to conduct an in-depth study to
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investigate on the dynamics of each of these variables in influencing consultancy services
pricing.
Table H 4: Test Statistics
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. Cost 42.873a 3 .000
2. Profit 59.038b 4 .000
3. Demand 33.354a 3 .000
4. Competition 40.557b 4 .000
a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 19.8.
b. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.
Ho5: The successful criteria for consultancy services pricing is not dependent on: (H5a). time
taken to solve the problem. (H5b). materials used on the project. (H5c). good financial control
system. (H5b). Record of past project costs. (H5c). accurate forecast of future cost; and (H5d).
production of timely reports.
H1 5: The successful criteria for consultancy services pricing is dependent on: (H5a). time taken
to solve the problem. (H5b). materials used on the project. (H5c). good financial control system.
(H5b). Record of past project costs. (H5c). accurate forecast of future cost; and (H5d).
production of timely reports.
The Chi-Square test conducted for hypothesis 5 above has its result depicted in Table H5 below.
The results revealed that there was a significant relationship between successful criteria for
pricing consultancy services and the independent variables namely time taken to solve the
problem ( X2 = 62.722, df = 3, p < 0.001, X2α = 12.838); materials used on the project ( X2 =
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34.468, df = 3, p < 0.001, X2α = 12.838); good financial control system ( X2= 17.456, df = 3, p =
0.001, X2α = 12.838); record of past project costs (X2 = 50.177, df = 4, p < 0.001, X2α =14.860);
accurate forecast of future cost ( X2 = 55.873, df = 4, p < 0.001, X2α =14.860); and production
of timely reports (X2 = 43.722, df = 4, p < 0.001, X2α =14.860). Since the X2cal > X2α at p <
0.005 in the case of the group variables, reject the null hypothesis H0 at a significance level of
0.005. Therefore, there is a statistical evidence to advocate that the success criteria for
consultancy services pricing is significantly dependent on the time taken to solve the problem;
materials used on the project; good financial control system; record of past project costs;
accurate forecast of future cost; and production of timely reports. Drawing from the result of
hypothesis 5, practitioners of QS consultancy services must operate within the framework of
these success criteria in order to be successful in pricing their services. Theoretically, pricing of
services within the consultancy services provision has been improve as this provides enough
scientific bases for consideration these variables in future pricing development.
Table H 5: Test Statistics
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. Time taken to solve the problem 62.722a 3 .000
2. Materials used on the project 34.468a 3 .000
3. Good financial control system 17.456a 3 .001
4. Record of past project costs 50.177b 4 .000
5. Accurate forecast of future cost 55.873b 4 .000
6. Production of timely reports 43.722b 4 .000 a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 19.8.
b. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.
Ho 6: The success of a bid price is not dependent on: (H6a). financial capacity, (H6b). technical
capacity, (H6c). experience, (H6d). duration, (H6e). reputation, (H6f). business development
and (H6g) profit and overhead.
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H1 6: The success of a bid price is dependent on: (H6a). financial capacity, (H6b). technical
capacity, (H6c). experience, (H6d). duration, (H6e). reputation, (H6f). business development,
and (H6g) profit and overhead.
The Chi-Square test result for Hypothesis 6 above is demonstrated in Table H6 below, the results
supports the existence of significant relationship between the dependent variable bid price for
consultancy services pricing and the independent variables namely financial capacity ( X2 =
44.734, df = 4, p < 0.001, X2α =14.860); technical capacity ( X2 = 69.165, df = 4, p < 0.001, X2α
=14.860); firm’s experience( X2 = 69.671, df = 4, p < 0.001, X2α =14.860); duration to render the
service ( X2 = 52.456, df = 4, p < 0.001, X2α =14.860); firm’s reputation ( X2 = 59.692, df = 4, p
< 0.001, X2α =14.860); business development ( X2 = 12.595, df = 3, p = .006, X2α =12.838); and
profit and overhead ( X2 = 41.443, df = 4, p < 0.001, X2α =14.860). Since X2cal < X2α, and the p
> 0.005, accept the null hypothesis Ho for the group variable business development, hence bid
price success for consultancy services is not dependent on the business development agenda of
the firm. However, the result demonstrates that in the case of other independent variables X2cal >
X2α at p < 0.005, at this instance, reject the null hypothesis Ho at a significance level of 0.005.
Hence there is statistical evidence to suggest that bid price success for consultancy services is
significantly dependent on financial capacity; technical capacity; firm’s experience; duration to
render the service; firm’s reputation; and profit and overhead. The rejection of the null
hypothesis is a testament that bid price success which is the focus of most consultancies is
important and reinforces the application of the independent variables in the examination of bid
price quotations from consultants. The acceptance of the null hypothesis in terms of business
development underpins the fact that in spite of business development strategies adopted by
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consultancies if they do not adhere to successful bid pricing criteria, they are bound to fail in the
pricing of their services.
Table H 6: Test Statistics
Independent Variables Chi-Square ( X2) df Asymp. Sig.
1. Financial capacity 44.734a 4 .000
2. Technical capacity 69.165a 4 .000
3. Firm’s experience 69.671a 4 .000
4. Duration to render the service 52.456a 4 .000
5. Firm’s reputation 59.692b 4 .000
6. Business development 12.595c 3 .006
7. Overhead and profit 41.443a 4 .000
a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.
b. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.6.
c. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 19.8.
Ho 7: Consultancy services price levels are not dependent on financial risks.
H1 7: Consultancy services price levels are dependent on financial risks.
A Chi-Square test was conducted to find out whether consultancy services price levels are
dependent on associated financial risk. The results demonstrated that there is significant
relationship between consultancy price levels and financial risks (X2= 78.532, df = 4, p < 0.001,
X2α =14.860). Since X2cal > X2α at p < 0.005, reject the null hypothesis. Hence there is
significant evidence statistically to advocate that consultancy services price levels are dependent
of financial risks. Hitherto financial risks do not feature in the price composition of consultancy
services provisions. The test of this hypothesis would practically improve the pricing of
consultancy services by ensuring that financial obligations are shared among project
stakeholders. However, it is important to explore the nature of consultancy financial risks to
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establish its true level of influence and other associated encumbrances in pricing in a future
study.
Table H 7: Test Statistics
Independent Variable Chi-Square (X2) df Asymp. Sig.
Financial risk
78.532a
4
.000 a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.
Ho 8: The robustness of consultancy pricing is not dependent on the: (H8a).Market related risks
(H8b). Logistical and infrastructural risks (H8c). Managerial and operational risks (H8d).
Technological risks (H8e). Organizational and societal risks.
H1 8: The robustness of consultancy pricing is dependent on: (H8a).Market related risks (H8b).
Logistical and infrastructural risks (H8c). Managerial and operational risks (H8d).
Technological risks (H8e). Organizational and societal risks.
The Chi-Square result conducted revealed that the robustness of consultancy services pricing is
significantly dependent on market related risks ( X2 = 35.076, df = 3, p < 0.001, X2α =12.838);
logistical and infrastructural risk ( X2 = 57.769, df = 4, p < 0.001, X2α =14.860); managerial and
operational risk ( X2= 29.405, df = 3, p < 0.001, X2α =12.838); technological risk( X2 = 14.924,
df = 3, p = 0.002, X2α = 12.838); and organizational and societal risk ( X2= 37.646, df = 4, p <
0.000, X2α =14.860). Since the X2cal > X2α at p < 0.005, reject the null hypothesis H0 and
conclude that the robustness of consultancy services pricing is dependent on market related risks;
logistical and infrastructural risks; managerial and operational risks; technological risks; and
organizational and societal risks. The ingredients for consultancy price robustness have eluded
practitioners over the decades. The test result of this hypothesis has the potential of creating the
awareness of price robustness among consultancies and contributing to theory development by
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setting the tone for in-depth studies in this area in consultancy pricing and other disciplines as
well.
Table H 8: Test Statistics
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. Market related risk 35.076a 3 .000
2. Logistical and infrastructural risk 57.769b 4 .000
3. Managerial and operational risk 29.405a 3 .000
4. Technological risk 14.924a 3 .002
5. Organizational and societal risk 37.646c 4 .000 a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 19.8.
b. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.6.
c. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8
Ho 9: The level of consultancy pricing is independent of: (H9a). Financial risk (H9b). Legal risk
(H9c). Regulatory risks (H9d). Political risk and (H9e). Force majeure risks.
H19: The level of consultancy services pricing is dependent on: (H9a). Financial risk (H9b).
Legal risk (H9c). Regulatory risks (H9d). Political risk and (H9e). Force majeure risks.
The Chi-Square result for Hypothesis 9 above as demonstrated in Table H9 below disclosed that
there is significant relationship between the level of consultancy pricing and financial risk ( X2 =
58.795, df = 4, p < 0.001, X2α = 14.860); legal risk (X2 = 37.266, df = 4, p < 0.001, X2α
=14.860); regulatory risk ( X2= 38.911, df = 4, p < 0.001, X2α =14.860); political risk ( X2=
22.962, df = 4, p < 0.001, X2α =14.860); and force majeure risks ( X2 = 19.165, df = 4, p = 0.001,
X2α =14.860). Since the X2cal > X2α at p < 0.005, reject the null hypothesis Ho and conclude that
the level of consultancy services pricing is significantly dependent on financial risk; legal risk;
regulatory risk; political risk; and force majeure risk. This implies that consultants must price
their services within the framework of these risks in order to realize appreciable price levels for
their services. Theoretically, the relationship between risk and pricing levels are least
investigated in consulting and other fields as well, this revelation has the potential of igniting
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novel studies in the research community towards unfolding deeper dynamics regarding price
levels and risk.
Table H 9: Test Results
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. Financial risk 58.795 4 .000
2. Legal risk 37.266 4 .000
3. Regulatory risk 38.911 4 .000
4. Political risk 22.962 4 .000
5. Force majeure risks 19.165 4 .001
a. 0 cells (0%) have expected frequencies less than 5. The minimum expected frequency is 15.6.
b. 0 cells (0%) have expected frequencies less than 5. The minimum expected frequency is 15.8.
Ho 10: The level of consultancy prices is not dependent on these taxes: (H10a). personal income
tax (H10b). VAT/ ‘NHIL’ (H10c). Corporate tax (H10d). Profit tax (H10e). local rates (H10f).
Property tax.
H1 10: The level of consultancy prices is dependent on these taxes: (H10a). personal income tax
(H10b). VAT/ ‘NHIL’ (H10c). Corporate tax (H10d). Profit tax (H10e). local rates (H10f).
Property tax.
The Chi-Square result of Hypothesis 10 above depicted in Table H10 revealed that there is
significant relationship between the level of consultancy services prices and personal income tax
( X2 = 20.051, df = 4, p < 0.001, X2α =14.860); VAT/ NHIL ( X2 = 27.519, df = 4, p < 0.001, X2α
=14.860); corporate tax ( X2 = 36.506, df = 4, p < 0.001, X2α =14.860); profit tax ( X2= 31.063,
df = 4, p < 0.001, X2α =14.860); local rates ( X2 = 22.203, df = 4, p < 0.001, X2α =14.860); and
property tax ( X2= 22.835, df = 4, p < 0.001, X2α =14.860). Since the X2cal > X2α at p < 0.005 in
all cases of the variables, reject the null hypothesis Ho and conclude that the level of consultancy
services price is dependent on personal income tax; VAT/ NHIL; corporate tax; profit tax; local
rates; and property tax. The phenomenon of taxes in pricing is least investigated theoretically
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especially in QS consultancy services pricing, the result of this hypothesis implies that awareness
would be created to engender the consideration of taxes in the development of consultancy
services pricing theories especially in the determination of price levels. Practically, price setters
would henceforth consider the various tax burdens that they encounter in the delivery of services
to clients.
Table H 10: Test Results
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. Personal income tax 20.051 4 .000
2. VAT/ NHIL 27.519 4 .000
3. Corporate tax 36.506 4 .000
4. Profit tax 31.063 4 .000
5. Local rates 22.203 4 .000
6. Property tax 22.835 4 .000 a. 0 cells (0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8
Ho 11: Consultancy services price level is not dependent on: (H11a). input prices (H11b).
Inflation
H1 11: Consultancy services Price level is dependent on: (H11a). input prices (H11b). Inflation
The Chi-Square results of Hypothesis 11 above as demonstrated in Table H11 unveiled that there
is significant relationship between input prices ( X2= 43.722, df = 4, p < 0.001, X2α =14.860) and
inflation ( X2 = 43.154, df = 4, p < 0.001, X2α = 14.860). Since the X2cal > X2α at p < 0.005,
reject the null hypothesis Ho and conclude that consultancy services price level is dependent on
input prices and inflation. The result of this hypothesis underpins the consideration given to
components of consultancy services pricing which serve as inputs to the delivery of the services
to clients. These inputs include materials and supplies, communication expenses among others.
Practically, this hypothesis gives a scientific impetus to their inclusion in the development of the
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pricing framework. Inflation is not considered in the existing pricing of consultancy services
since majority of consultancies adopt percentage pricing where a percentage of the project cost is
normally taken to be the consultancy services price. This hypothesis also provides a further
reason for the consideration of inflationary rate in the pricing of service especially over long
project duration.
Table H 11: Test Results
Independent Variables Chi-Square (X2) df Asymp. Sig.
1. Input prices 43.722 4 .000
2. Inflation 43.154 4 .000 a. 0 cells (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.8.
b. 0 cell (.0%) have expected frequencies less than 5. The minimum expected cell frequency is 15.6.
Ho12: Changes in consultancy services price levels are independent of inflationary causes:
(H12a). production shortfall (H12b). Effects of input market (H12c). Government policies; and
(H12d). International trade and trade barriers.
H112: Changes in consultancy services price levels are dependent on inflationary causes:
(H12a). production shortfall (H12b). Effects of input market (H12c). Government policies; and
(H12d). International trade and trade barriers.
The Chi-Square test result of Hypothesis 12 as in Table H12 below revealed that there is
significant relationship between changes in consultancy services price levels and production
shortfall ( X2 = 27.266, df = 4, p < 0.001, X2α =14.860); effects of input market ( X2 = 40.304, df
= 4, p < 0.001, X2α = 14.860); Government policies ( X2 = 26.127, df = 4, p < 0.001, X2α
=14.860); and international trade and trade barriers ( X2= 23.595, df = 4, p < 0.001, X2α
=14.860). Since the X2cal > X2α at p < 0.005, reject the null hypothesis Ho and conclude that
changes in consultancy services price levels are dependent on production shortfall; effects of
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input market; government policies; and international trade and trade barriers. Globalization has
made the world to be closer in trade and its related issues. International trade has the potential of
altering the level of consultancy price levels. An increase in input prices in the world market in a
different jurisdiction can affect the pricing of services provided input materials are purchased
from the international market. In the light of this, pricing QS consultancy services must take due
cognizance of international trade dynamics especially in the delivery of services that are
international in nature.
6.4 FACTOR ANALYSIS
There are sixty-six (66) independent variables. In view of the numerous independent variables
involved in this research, it is possible there will be significant amount of variables measuring
the same pricing phenomenon. Hence factor analysis wass adopted to reduce the repeatability of
variables and to empirically aid in the development of the pricing framework by classifying key
pricing variables of the same characteristics.
6.4.1 Concept of Price and Value (Variables)
6.4.1.1Initial Consideration
The reliability of factor analysis is determined by the sample size as correlation coefficients
changes from one set of sample to another. From Table F 1 below using the Kaiser-Meyer-Olkin
(KMO) measure of sampling adequacy which is approximately 0.7 signifies the adequacy of the
sample size of the data for the factor analysis to be conducted. This implies that factor analysis
has been given a clean sheet to proceed. Similarly, communalities in Table F 2 after extraction
were above 0.5 (c.f. Po-Yi & Chen, 2004), and this further strengthen the adequacy of the sample
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size; hence the communalities in the Table F2 are significant. The Bartlett's Test of Sphericity is
also significant since the KMO is above 0.5. These phenomena of the data as demonstrated by
the KMO and the Bartlett's Test of Sphericity clearly indicate that there is a strong relation
among the pricing variables, this aspect of the result clearly dovetail into the objective of the
research of ascertaining the nature of relationship among the quantity surveying consultancy
pricing variables. After ascertaining the suitability of the data on price and value concepts, the
data was analysed using the Principal Component Analysis (PCA) and Varimax with Kaiser
Normalization. The communalities involved were ascertained as indicated in Table F 2 below to
account for the number of variables to be extracted finally. A critical examination of the
extraction column of Table F 2 indicated that the average of communalities extracted were above
0.60 indicating how well the extracted components represent the factors/ pricing variables hence
the extracted components are very good representation of the factors price and value factors.
Table F 1: KMO and Bartlett's Test (Price and value)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .673
Bartlett's Test of Sphericity Approx. Chi-Square 524.433
df 120
Sig. .000
Table F 2: Communalities (Price and Value)
Variables Initial Extraction
1. Value of a product or service 1.000 .704
2. Affordability 1.000 .643
3. The Government 1.000 .802
4. Media action 1.000 .837
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5. Pressure Group 1.000 .723
6. Seller’s profit 1.000 .866
7. Customer’s intrinsic value 1.000 .722
8. Customer’s affordability 1.000 .670
9. Firm’s objectivity 1.000 .736
10. Firm’s failure 1.000 .561
11. Firm’s success 1.000 .691
12. Firm’s image 1.000 .605
13. Cost 1.000 .662
14. Profit 1.000 .618
15. Demand 1.000 .741
16. Competition 1.000 .666
Extraction Method: Principal Component Analysis.
From Table F 3, five components have been extracted to represent the price and value factors or
variables. The total variance explained by each component extracted include, the first principal
component (component 1) version is 27.965% of the total variance; second principal component
(component 2) version is 15.216% of the remaining variance not accounted for by the first
component while the third principal component (component 3) version is 11.757% of the
remaining variance unaccounted for by the first and second component; the fourth principal
component (component 4) accounted for 8.197% of the remaining variance not explained by the
previous components; and finally, the fifth component (component 5) accounted for 7.15% of the
remaining variance not explained by the previous four principal components. In all, the five (5)
components extracted cumulatively accounted for 70.285% of the variation inherent in the data,
a phenomenon which is in compliance with the criterion that extracted components must explain
at least 50% of the variance. This therefore implies that five (5) principal components have been
extracted to represent key pricing variables or factors whose eigenvalues are greater than 1. The
remaining 11 factors or variables have their eigenvalues less than one hence they have been
189
ignored as a result of not being able to meet the criteria for selection which is eigenvalues greater
than 1. These factors with high eigenvalues explained about 70% of the variables, therefore the
factor (variables) can be reduced to these set of variables with a loss of 30% information.
Table F 3: Total Variance Explained (Price and value)
Comp
onent
Initial Eigenvalues
Extraction Sums of
Squared Loadings
Rotation Sums of
Squared Loadings
Total % of
Variance Cum. % Total
% of
Variance Cum. % Total
% of
Variance Cum. %
1 4.474 27.965 27.965 4.474 27.965 27.965 2.702 16.885 16.885
2 2.435 15.216 43.181 2.435 15.216 43.181 2.654 16.588 33.473
3 1.881 11.757 54.938 1.881 11.757 54.938 2.613 16.329 49.802
4 1.312 8.197 63.135 1.312 8.197 63.135 1.863 11.642 61.444
5 1.144 7.15 70.285 1.144 7.150 70.285 1.415 8.841 70.285
6 0.851 5.320 75.605
7 0.724 4.523 80.128
8 0.600 3.749 83.877
9 0.512 3.203 87.08
10 0.496 3.102 90.182
11 0.393 2.457 92.638
12 0.332 2.073 94.711
13 0.300 1.875 96.586
14 0.237 1.482 98.068
15 0.189 1.178 99.247
16 0.121 0.753 100
Extraction Method: Principal Component Analysis.
Table F 4: Rotated Component Matrixa ( Price and value)
Component
Variables 1 2 3 4 5
1. Value of a product or service .079 .038 .219 -.060 .803
2. Affordability .509 .175 .017 .194 .561
3. The Government .096 -.675 .234 .521 -.102
4. Media action -.114 -.085 -.032 .887 -.171
5. Pressure Group -.073 .220 -.071 .783 .225
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6.4.1.2 Components Extracted
The results of the factor analysis above are promising. The data was summarized to 70% of the
variance in the 16 factors with 5 components. Each component has at least 1 factor and at most 4
factors which can be represented as factors which are significant in pricing decision with regards
to price and value concepts. Table F5 below summarizes the components and their respective
factors of price and value. Factors are interestingly grouped according to their heading (themes).
Table F 5: Component Profile of the concept of Price and value
Description of Components and Variables Factor
Loading
Variance Explained
Component1: Pricing Strategies
1. Cost .692 27.965%
2. Profit .764
3. Demand .796
4. Competition .637
Component 2: Just Price
1. The government -.675 15.216%
2. Seller’s profit .919
6. Seller’s profit .035 .919 -.048 .035 -.126
7. Customer’s intrinsic value .281 .775 .036 .094 .179
8. Customer’s affordability .094 .664 .407 .094 .213
9. Firm’s objectivity .301 -.051 .779 .090 .165
10. Firm’s failure .269 .382 .519 .145 -.229
11. Firm’s success .001 -.034 .810 -.053 .176
12. Firm’s image .232 .089 .717 -.159 .060
13. Cost .692 .119 .151 -.246 .292
14. Profit .764 .157 .094 -.004 -.008
15. Demand .796 .094 .235 -.109 .179
16. Competition .637 -.134 .447 .032 -.204
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
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3. Customer’s intrinsic value .775
4. Customer’s affordability .664
Component 3:Pricing Roles
1. Firm’s objectivity .779 11.757%
2. Firm’s success .810
3. Firm’s image .717
Component 4: Social Influence
1. Media action .887 8.197%
2. Pressure group .783
Component 5: Value
1. Value of a product or service .803 7.15%
6.4.2 Project Pricing (Consultancy Pricing)
6.4.2.1 Initial Considerations
For this aspect of the analysis, there are 13 variables involved and it is likely there would be
variables that feature in various aspect of consultancy pricing. It is therefore necessary to
summarize the dataset for simplification and easy comprehension. This attempt is in tandem with
the overall objectives of the study which is to develop a framework. The reduction and
summarization of the data is organized into manageable and appreciable level. The first step in
the conduct of every factor analysis is to verify the adequacy of the survey data. The KMO test
and Bartlett's Test of Sphericity (see Table F 6) below are used to verify the adequacy of the data
for the factor analysis of consultancy pricing variables. From Table F 8, the adequacy of the data
is excellent since the KMO value is .855. The KMO statistic ranges from 0 to 1 and a KMO
value closer to 1 is considered better than KMO values far from 1.
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Table F 6: KMO and Bartlett's Test (Price and value)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .855
Bartlett's Test of Sphericity Approx. Chi-Square 462.501
df 78
Sig. .000
After ascertaining the suitability of the data on price and value concepts, the data was analysed
using the Principal Component Analysis (PCA) and Varimax with Kaiser Normalization. The
communalities involved were ascertained as indicated in Table F 7 below accounted for the
number of variables to be extracted finally. A critical examination of the extraction column of
Table F 7 indicated that the average of communalities extracted were slightly above 0.60
indicating an average extracted components representing the factors/ project pricing variables
hence the extracted components are to a larger extent an average representation of the factors of
project pricing.
Table F 7: Communalities (Project Pricing/consultancy pricing)
Variables Initial Extraction
1. Time taken to solve the problem 1.000 .642
2. Materials used on the project 1.000 .650
3. Good financial control system 1.000 .738
4. Record of past project costs 1.000 .564
5. Accurate forecast of future cost 1.000 .577
6. Production of timely reports 1.000 .614
7. Financial capacity 1.000 .548
8. Technical capacity 1.000 .613
9. Firm’s experience 1.000 .664
10. Duration to render the service 1.000 .671
11. Firm’s reputation 1.000 .599
12. Business development 1.000 .814
13. Overhead and profit 1.000 .582
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Table F 7: Communalities (Project Pricing/consultancy pricing)
Variables Initial Extraction
1. Time taken to solve the problem 1.000 .642
2. Materials used on the project 1.000 .650
3. Good financial control system 1.000 .738
4. Record of past project costs 1.000 .564
5. Accurate forecast of future cost 1.000 .577
6. Production of timely reports 1.000 .614
7. Financial capacity 1.000 .548
8. Technical capacity 1.000 .613
9. Firm’s experience 1.000 .664
10. Duration to render the service 1.000 .671
11. Firm’s reputation 1.000 .599
12. Business development 1.000 .814
13. Overhead and profit 1.000 .582
Extraction Method: Principal Component Analysis.
Drawing on from Table F 8 below, three (3) components of the total variance explained have
been extracted comprising of the first principal component christened component 1 accounted
for 45.587% of the total variance; component 2 explained 9.41% of the other components not
accounted for by component 1; and component 3 accounted for 8.673% of the variance not
explained by the first and second components of the remaining variation. In all, the three
extracted components cumulatively accounted for 63.67% which is well above the accepted
variance criterion that the cumulative extracted components must be at least 50% of the variance.
Table F 8: Total Variance Explained (Project Pricing/consultancy pricing)
Compo
nent
Initial Eigenvalues
Extraction Sums of
Squared Loadings
Rotation Sums of Squared
Loadings
Total
% of
Variance Cum. % Total
% of
Variance Cum. % Total
% of
Variance
Cum.
%
1 5.926 45.587 45.587 5.926 45.587 45.587 2.767 21.287 21.287
2 1.223 9.410 54.997 1.223 9.41 54.997 2.765 21.269 42.556
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3 1.127 8.673 63.670 1.127 8.673 63.67 2.745 21.114 63.670
4 0.938 7.212 70.882
5 0.697 5.362 76.244
6 0.589 4.528 80.771
7 0.485 3.729 84.501
8 0.472 3.634 88.135
9 0.409 3.146 91.281
10 0.368 2.834 94.116
11 0.309 2.375 96.491
12 0.294 2.26 98.751
13 0.162 1.249 100
Extraction Method: Principal Component Analysis.
Table F 9: Rotated Component Matrixa (Project pricing/consultancy pricing)
Component
Pricing Variables 1 2 3
1. Time taken to solve the problem 0.078 0.794 0.075
2. Materials used on the project 0.151 0.653 0.448
3. Good financial control system 0.272 0.805 0.123
4. Record of past project costs 0.303 0.618 0.300
5. Accurate forecast of future cost 0.512 0.517 0.217
6. Production of timely reports 0.127 0.172 0.754
7. Financial capacity 0.214 0.291 0.646
8. Technical capacity 0.454 0.331 0.546
9. Firm’s experience 0.648 0.266 0.417
10. Duration to render the service 0.709 0.162 0.376
11. Firm’s reputation 0.580 0.243 0.451
12. Business development 0.881 0.157 -0.116
13. Overhead and profit 0.086 0.066 0.755 Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 4 iterations.
6.4.2.2 Components Extracted
The results of the factor analysis are auspicious. The data was summarized to 64% of the
variance in the 13 factors with 3 components. Each component has three factors which represent
significantly project pricing/consultancy pricing variables. Using Table F9 above, Table F 10
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below clearly demonstrates the extracted components with their key variables. Factors are
grouped according to appropriate headings (themes).
Table F 10: Component Profile of Project pricing/consultancy pricing
Description of Components and Variables Factor Loading Variance Explained
Component 1: Business management
1. Firm’s experience 0.648 45.587%
2. Duration to render service 0.709
3. Business development 0.881
Component 2: Project/service cost management
1. Time taken to solve the problem 0.794 9.41%
2. Materials used on the project 0.653
3. Good financial control system 0.805
4. Record of past project cost 0.618
Component 3: Technical and financial
capabilities
1. Production of timely reports 0.754 8.673
2. Financial capacity 0.646
3. overhead and profit 0.755
4. technical capacity 0.546
6.4.3 Concept of risk
Pricing is affected by risks of various dimensions. The pricing of quantity surveying services is
not devoid of risks. The study examines various degrees of risk and it is important to critically
categorize or summarize these risks into their appropriate domain empirically. The factor
analysis has been adopted for the purposes of data reduction, summarization and framework
development.
6.4.3.1 Initial Considerations
The most important prelude to the conduct of factor analysis is the determination of the
suitability of the data set. Examining the Barlett test conducted to ascertain the existence of
196
common factors with regards to the concept of pricing risks in this study. Referring to the KMO
measure of sampling adequacy, it is clear that the sampling adequacy is deemed to be above
average; hence the factor analysis proceeds (see Table F11).
Table F 11: KMO and Bartlett's Test (Concept of risk)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .691
Bartlett's Test of Sphericity Approx. Chi-Square 324.155
df 66
Sig. .000
Having examined the suitability of the data using Table F11 above, the Principal Component
analysis PCA was used to establish the communalities for the factor analysis. Table F 12 below
presented the variables to be extracted. The average communalities to extract are marginally
above average (i.e. 0.607).
Table F 12: Communalities(Concept of risk)
Variables Initial Extraction
1. Associated business risk 1.000 .643
2. Financial risk 1.000 .526
3. Market related risk 1.000 .472
4. Logistical and infrastructural risk 1.000 .596
5. Managerial and operational risk 1.000 .605
6. Technological risk 1.000 .584
7. Organizational and societal risk 1.000 .629
8. Financial risk 1.000 .431
9. Legal risk 1.000 .582
10. Regulatory risk 1.000 .691
11. Political risk 1.000 .794
12. Force majeure risks 1.000 .731
Extraction Method: Principal Component Analysis.
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From Table F 13 below, three (3) components of the total variance explained have been
established for extraction. Component 1 accounted for 34.469% of total variation; component 2
version is 14.268% of the variation not explained by the component 1; and component 3
accounted for 11.972% of the total variance not explained by components 1 and 2. The three
components altogether accounted for 60.709% which is above the accepted criterion of
cumulative extracted components to be at least 50%.
Table F 13: Total Variance Explained (Concept of risk)
Compo
nent
Initial Eigenvalues
Extraction Sums of
Squared Loadings
Rotation Sums of Squared
Loadings
Total
% of
Variance Cum. % Total
% of
Variance Cum.% Total
% of
Variance Cum. %
1 4.136 34.469 34.469 4.136 34.469 34.469 3.108 25.903 25.903
2 1.712 14.268 48.737 1.712 14.268 48.737 2.446 20.385 46.288
3 1.437 11.972 60.709 1.437 11.972 60.709 1.731 14.422 60.709
4 0.838 6.985 67.694
5 0.801 6.673 74.367
6 0.759 6.321 80.688
7 0.678 5.648 86.336
8 0.438 3.652 89.988
9 0.43 3.587 93.575
10 0.319 2.657 96.232
11 0.262 2.185 98.417
12 0.19 1.583 100
Extraction Method: Principal Component Analysis.
Table F 14: Rotated Component Matrixa (Concept of risk)
Rotated Component Matrixa
Component
Concept of risk(variables) 1 2 3
1. Associated business risk 0.727 -0.188 0.281
2. Financial risk 0.709 0.152 -0.004
198
3. Market related risk 0.629 0.254 -0.11
4. Logistical and infrastructural risk 0.710 0.133 0.273
5. Managerial and operational risk 0.727 0.272 -0.049
6. Technological risk 0.485 0.564 -0.175
7. Organizational and societal risk 0.155 0.766 0.136
8. Financial risk 0.553 0.332 0.121
9. Legal risk 0.259 0.710 0.106
10. Regulatory risk 0.045 0.83 0.004
11. Political risk 0.115 -0.012 0.883
12. Force majeure risks 0.028 0.155 0.841
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
6.4.3.2 Components Extracted
The extracted components with their respective variables comprising component 1 with four (4)
variables; component 2 with three (3) variables; and component 3 consist of two (2) extracted
variables. In all nine (9) variables have been extracted cumulatively at 60.709%. Three variables
were eliminated because of the insignificance of their eigenvalues which are far below 1. The
respective components with their themes are demonstrated in Table F 15 below.
Table F 15: Component Profile of concept of risk
Description of Components and Variables Factor Loading Variance Explained
Component 1: Corporate internal risk
1. Associated business risk 0.727 34.469
2. Financial risk 0.709
3. Logistical and infrastructural risk 0.710
4. Managerial and operational risk 0.727
Component 2: Corporate external risk
1. Organizational and societal risk 0.766 14.268
2. Legal risk 0.710
3. Regulatory risk 0.830
Component 3: location risk
1. Political risk 0.883
2. Force majeure risks 0.841 11.972
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6.4.4 Concept of taxation and inflation
Taxes and inflation affect prices of services rendered to clients by consultants. In most cases,
these two indicators of prices have become the concerns of the business world. In this study,
varied form of taxation and inflationary forces were examined to ascertain the opinion of
respondents on these issues with regard to the pricing of QS consultancy services.
6.4.4.1 Initial Consideration
In view of the numerous taxes examined, it is important to summarize and classify them
appropriately hence the adoption of factor analysis for such a purpose. Prior to the conduct of
factor analysis, a preliminary test on the sample size adequacy of the dataset in order to proceed
with the analysis. Also required is the determination of the existence of common factors within
the data through the Barlett test. A critical examination of the KMO statistic in Table F 16
regarding the dataset of concept of taxation and inflation revealed that the adequacy of sampling
for factor analysis is above average since the KMO statistic is 0.726; hence the factor analysis
proceeds.
Table F 16: KMO and Bartlett’s Test (Taxation and inflation)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .726
Bartlett’s Test of Sphericity Approx. Chi-Square 420.665
df 66
Sig. .000
Table F 17 demonstrates communalities before and after extraction; before extraction the
communalities are all to be 1. The communalities in the extraction column of Table F 17
demonstrate the common variance existing in the data structure. Referring to the Table F17,
200
0.708 (70.8%) of the variance in relation to personal income tax is common (refer to Table F 17
for this information regarding other variables). The average of the communalities is 0.65.
From Table F 18 below, three (3) components of the total variance explained have been
established. Component 1 accounted for 34.444% of total variance explained; component 2
version produced 20.858% of the total variance not explained by component 1; and component 3
accounted for 9.708% of the total variance not accounted by component 1 and 2. The three
components together accounted for 65.010% which meets the criteria that cumulative extracted
components must be at least 50%.
Table F 18: Total Variance Explained (Taxation and inflation)
Comp
onent
Initial Eigenvalues
Extraction Sums of
Squared Loadings
Rotation Sums of Squared
Loadings
Total
% of
Variance Cum. % Total
% of
Variance Cum. % Total
% of
Variance Cum. %
Table F 17: Communalities (Taxation and inflation)
Variables Initial Extraction
1. Personal income tax 1.000 .708
2. VAT/ NHIL 1.000 .558
3. Corporate tax 1.000 .571
4. Profit tax 1.000 .560
5. Local rates 1.000 .554
6. Property tax 1.000 .720
7. Input prices 1.000 .727
8. Inflation 1.000 .788
9. Production shortfall 1.000 .651
10. Effects of input market 1.000 .758
11. Government policies 1.000 .686
12. International trade and trade barriers 1.000 .520
Extraction Method: Principal Component Analysis.
201
1 4.133 34.444 34.444 4.133 34.444 34.444 3.689 30.741 30.741
2 2.503 20.858 55.302 2.503 20.858 55.302 2.813 23.439 54.180
3 1.165 9.708 65.010 1.165 9.708 65.010 1.300 10.830 65.010
4 .980 8.167 73.177
5 .838 6.986 80.163
6 .600 5.003 85.166
7 .430 3.587 88.752
8 .405 3.378 92.130
9 .316 2.630 94.760
10 .235 1.959 96.720
11 .220 1.831 98.551
12 .174 1.449 100.000
Extraction Method: Principal
Component Analysis.
Table F 19: Rotated Component Matrixa (Taxation and inflation)
Component
Variables 1 2 3
1. Personal income tax .824 .169 .016
2. VAT/ NHIL .730 -.007 .158
3. Corporate tax .724 -.035 .212
4. Profit tax .738 .106 -.063
5. Local rates .735 .015 .120
6. Property tax .812 .110 -.221
7. Input prices .272 .293 .753
8. Inflation .153 .659 .574
9. Production shortfall .019 .799 .108
10. Effects of input market -.064 .868 .025
11. Government policies .145 .816 .006
12. International trade and trade barriers .294 .425 -.503
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
202
6.4.4.2 Components Extracted
Referring to Table F 19 above, six (6) variables were extracted from component 1. Component 2
had four (4) variables extracted; and component 3 consist of only one (1) extracted variable. In
all, eleven (11) variables were extracted while one (1) variable was ignored because its
eigenvalue is low in all the three components. The three components with their interpretation are
demonstrated in Table F 20 below.
Table F 20: Component Profile (Taxation and inflation)
Description of Components and Variables Factor Loading Variance Explained
Component 1: Taxes 1. Personal income tax
.824
34.444
2. VAT/ NHIL .730
3. Corporate tax .724
4. Profit tax .738
5. Local rates .735
6. Property tax .812
Component 2:Price catalysts
1. Inflation .659 20.858
2. Production shortfall .799
3. Effects of input market .868
4. Government policies .816
Component 3: Input prices
1. Input prices .753 9.708
6.4.5 Quantity surveying consultancy services pricing components
After examining the parameters of consultancy pricing, it is important to delve into the various
components of quantity surveying (QS) consultancy services pricing. Varied forms of QS
consultancy pricing components exist which this study intends to classify appropriately using
factor analysis to eventually develop a robust framework for QS consultancy pricing.
203
6.4.5.1 Initial Consideration
The reliability of factor analysis is dependent on the adequacy of the sample size involved in the
data collection. It is in this direction that preliminary analysis using KMO statistic as depicted in
Table F 21 is vital. The KMO value is .786 which is above average hence the reliability of factor
analysis is guaranteed. The KMO value ranges from 0 to 1, the closer the KMO value to 1 the
more reliable the factor analysis. Similarly, the Barlett test conducted indicated the existence of
common factors in the data. Since the reliability of the factor analysis is assured; its conduct is
appropriate for data reduction and classification of quantity surveying consultancy services
pricing components variables to develop a framework.
Table F 21: KMO and Bartlett's Test (QS consultancy services pricing components)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .786
Bartlett's Test of Sphericity Approx. Chi-Square 413.503
df 78
Sig. .000
Table F 22 below contains the communalities before and after extraction, the communalities
before extraction are assumed to be 1 while communalities after extraction are above 1. The
loadings in the extraction column depict the amount of common variance present in the data as
far as each variable is concerned. The average communality (8.937/13) is 0.687.
Table F 22: Communalities (QS consultancy services pricing components)
Variables Initial Extraction
1. Consultant staff remuneration 1.000 .684
2. Travel and transport 1.000 .798
3. Mobilization and demobilization 1.000 .521
4. Staff allowances 1.000 .719
204
5. Communications 1.000 .672
6. Office rent 1.000 .682
7. Supplies and equipment 1.000 .714
8. Training programmes 1.000 .721
9. Report preparation 1.000 .617
10. Insurance 1.000 .743
11. Contingencies 1.000 .749
12. Taxes and duties 1.000 .620
13. Profits 1.000 .697
Extraction Method: Principal Component Analysis.
In Table F 23 below, four (4) components were established of the total variance explained.
Component 1 accounted for 37.889% of total variance explained; component 2 revealed
12.948% of the total variance not accounted for by component 1; component 3 depict 9.357% of
total variance unaccounted by the component 1 and component 2; and component 4 portray
8.571% of the total variance not demonstrated by the previous three components. The four
components together accounted for 68.765% of total variance explained which satisfy the criteria
that the cumulative extracted components must be at least 50% of the total variance explained.
Table F 23:Total Variance Explained (QS consultancy services pricing components)
Comp
onent
Initial Eigenvalues
Extraction Sums of
Squared Loadings
Rotation Sums of Squared
Loadings
Total
% of
Variance Cum. % Total
% of
Variance Cum. % Total
% of
Variance Cum. %
1 4.926 37.889 37.889 4.926 37.889 37.889 2.533 19.487 19.487
2 1.683 12.948 50.837 1.683 12.948 50.837 2.331 17.927 37.414
3 1.216 9.357 60.194 1.216 9.357 60.194 2.243 17.254 54.667
4 1.114 8.571 68.765 1.114 8.571 68.765 1.833 14.097 68.765
5 .842 6.476 75.241
6 .692 5.322 80.562
205
7 .564 4.336 84.898
8 .524 4.034 88.932
9 .375 2.884 91.816
10 .326 2.510 94.326
11 .294 2.258 96.584
12 .228 1.752 98.336
13 .216 1.664 100.000
Extraction Method: Principal
Component Analysis.
6.4.5.2 Components Extracted
From Table F 24 above, three (3) variables have been extracted with regard to component 1,
Table F 24: Rotated Component Matrixa (QS consultancy services pricing components)
Variables Component
1 2 3 4
1. Consultant staff remuneration .462 -.235 .315 .562
2. Travel and transport .223 -.120 .817 .258
3. Mobilization and demobilization .238 .371 .254 .512
4. Staff allowances .776 .004 .110 .323
5. Communications .500 .299 .555 -.158
6. Office rent .755 .295 .117 .104
7. Supplies and equipment .783 .244 .136 .152
8. Training programmes .074 .343 .771 -.055
9. Report preparation .058 .422 .616 .238
10. Insurance .350 .779 .102 -.058
11. Contingencies .138 .828 .195 .086
12. Taxes and duties .028 .546 .185 .536
13. Profits .164 .024 -.052 .817
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 11 iterations.
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component 2 and component 4 respectively except component 3 which had four (4) variables
extracted. It is worthy to note that consultant staff remuneration; mobilization and
demobilization; communications; and taxes and duties had their eigenvalues marginally above
0.50 hence the extraction of these variables can be deemed to be mediocre. Table F 25 below
demonstrates the components, their descriptions with respective variables extracted.
Table F 25:Component Profile (QS consultancy services pricing components)
Description of Components and Variables Factor Loading Variance Explained
Component 1: Office management
1. Staff allowances .776 37.889 2. Office rent .755
3. Supplies and equipment .783
Component 2: Overheads
1. Insurance .779 12.948 2. Contingencies .828
3. Taxes and duties .546
Component 3: Administration and training
1. Travel and transport .817 9.357 2. Communications .555
3. Training programmes .771
4. Report preparation .616
Component 4: Reimbursement and payments
1. Consultant staff remuneration .562 8.571 2. Mobilization and demobilization .512
3. Profits .817
6.4.6 Challenges Confronting QS Consultancy Practice
Every professional practice has its own challenges and QS consultancy practice is not an
exception. The QS profession has been confronted with numerous challenges that need urgent
examination and redress. The study examine key challenges undermining QS professional
207
practice and intends to categorize them based on some underlining factors that are common to
them using factor analysis.
6.4.6.1 Initial Consideration
In the conduct of factor analysis, the sample size affects the reliability of the output hence
preliminary analysis is required using the KMO statistic. Table F 26 clearly reflects the KMO
statistic for the data on the challenges of QS practice. A KMO value of .664 provides an average
basis for the reliability of the factor analysis hence the factor analysis proceeds.
Table F 26: KMO and Bartlett’s Test (QS consultancy challenges)
Kaiser-Meyer-Olkin Measure of Sampling Adequacy .664
Bartlett’s Test of Sphericity Approx. Chi-Square 227.777
df 55
Sig. .000
Table F 27 below contains the communalities before and after extraction, the communalities
before extraction are assumed to be 1 while communalities after extraction are above 1. The
loadings in the extraction column represent the amount of common variance existing in the data
as far as each variable is concerned. The average of communalities (7.482/11) is 0.680.
Table F 27: Communalities (QS consultancy challenges)
Variables Initial Extraction
1. Slow response to changing contractual arrangements 1.000 .630
2. Challenge of appropriate response to emerging services 1.000 .661
3. Slow response to information and communication technology revolution 1.000 .686
4. Inability to integrate applied research outputs into practice 1.000 .536
5. Changing nature of clients’ demand 1.000 .577
208
6. Impact of competition 1.000 .794
7.Complexity of modern construction projects 1.000 .609
8. Reducing fees to loss-making territory 1.000 .755
9. Exposure to risks 1.000 .714
10.Decrease in project value 1.000 .686
11. Fluctuation in professional tariff of fees 1.000 .834
Extraction Method: Principal Component Analysis.
From Table F 28 below, four (4) components of total variance explained were established for
extraction. Component 1 accounted for 27.385% of total variance explained; component 2
portrays 18.966% of total variance not accounted for by component 1; component 3
demonstrates 12.172% of total variance not portrayed by components 1 and component 2; and
component 4 accounted for 9.497% of total variance explained not accounted for by components
1, 2 and 3. The four components accounted for 68.021% of the total variance explained which is
well above with the acceptable criteria of cumulative extracted components to be at least 50%.
Table F 28: Total Variance Explained(QS consultancy challenges)
Comp
onent
Initial Eigenvalues
Extraction Sums of
Squared Loadings
Rotation Sums of Squared
Loadings
Total
% of
Variance Cum. % Total
% of
Variance Cum. % Total
% of
Variance Cum. %
1 3.012 27.385 27.385 3.012 27.385 27.385 2.512 22.837 22.837
2 2.086 18.966 46.351 2.086 18.966 46.351 2.054 18.677 41.514
3 1.339 12.172 58.523 1.339 12.172 58.523 1.630 14.821 56.334
4 1.045 9.497 68.021 1.045 9.497 68.021 1.285 11.686 68.021
5 .821 7.463 75.484
6 .649 5.897 81.381
7 .540 4.905 86.287
8 .504 4.578 90.865
209
9 .411 3.736 94.600
10 .341 3.100 97.700
11 .253 2.300 100.000
Extraction Method: Principal
Component Analysis.
Table F 29: Rotated Component Matrixa (QS consultancy challenges)
Variables Component
1 2 3 4
1. Slow response to changing contractual arrangements .735 -.224 .191 -.054
2. Challenge of appropriate response to emerging services .803 -.044 .099 -.070
3. Slow response to information and communication technology
revolution .755 .282 .169 .084
4. Inability to integrate applied research outputs into practice .719 .101 -.088 .042
5. Changing nature of clients’ demand .412 .127 .618 -.091
6. Impact of competition -.064 .076 .886 .011
7. Complexity of modern construction projects .218 .070 .565 .487
8. Reducing fees to loss-making territory .113 .840 .071 -.176
9. Exposure to risks -.010 .842 .008 .074
10. Decrease in project value -.026 .686 .236 .398
11. Fluctuation in professional tariff of fees -.068 .028 -.036 .910
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 5 iterations.
6.4.6.2 Components Extracted
From Table F 30 above, four (4) variables have been extracted for component 1; component 2
had three ( 3) extracted variables while component 3 is represented by two (2) variables; and
component 4 had only one (1) extracted variable. Table F 30 below demonstrates the
components and their descriptions with respective variables extracted.
210
Table F 30: Component Profile (QS consultancy challenges)
Description of Components and Variables Factor Loading Variance
Explained
Component 1: Contractual and technology challenges
1. Slow response to changing contractual
arrangements
.735 27.385
2. Challenge of appropriate response to
emerging services
.803
3. Slow response to information and
communication technology revolution
.755
4. Inability to integrate applied research
outputs into practice
.719
Component 2: Pricing challenges
1. Reducing fees to loss-making territory .840 18.966 2. Exposure to risks .842
3. Decrease in project value .686
Component 3: Market forces challenges
1. Changing nature of clients’ demand .618 12.172 2. Impact of competition .886
Component 4: Professional fees challenges
1. Fluctuation in professional tariff of fees .910 9.497
6.5 DISCUSSION AND INTERPRETATION OF RESULTS
This section focuses on the discussion and interpretation of the results. It combined the
descriptive analysis utilizing the RII (relative importance index) for ranking of variables; the
inferential analysis results using chi square to test hypotheses; and the factor analysis meant to
classify and reduce variables for development of the generic framework. This section would
adopt the procedure of Leedy and Ormrod (2005) for the discussion and interpretation of results
by relating the findings of the research to the hypotheses advanced; relating the findings to extant
literature, concepts, theories and research studies; determining if the findings have practical and
statistical significance; and identifying the limitations of the research.
211
It is important to recap the problem statement of the research within the context of this
discussion and interpretation in order to be well guided. The problem statement confronting this
research include the need to offer competitive consultancy pricing; setting pricing within
perceived risk factors; the phenomenon of overpricing and under-pricing syndrome which can
cause substantial loss to consultants hence their extinction; existence of serious pricing
challenges confronting built environment consultants in the form of non-payment on the part of
clients for services rendered to them; prices set by professional bodies to which built
environment consultants belong (QS) do not achieve value ( that is absence of value in pricing);
and finally absolute lack of apposite and reliable framework for consultancy services pricing.
6.5.1 Concept of price and value
6.5.1.1 Component 1: Pricing strategies
Pricing strategies are very important in all pricing endeavours. Pricing strategies hinged on cost,
profit, demand and competition have factor loadings of .692, .764, .796 and .637 respectively.
These pricing strategies were in higher order ranking by respondents, having obtained RII above
0.80 respectively. Verifying the statistical significance of these pricing strategies in this study by
employing the chi square test of independence, it is crystal clear there is a significant relationship
between cost, demand, competition and profit hence the acceptance of the hypothesis that cost,
demand, competition and profit are fundamentals of pricing strategies. Extant literature is in
consonance with the acceptance of the above hypothesis in terms of the pricing strategies hence
Robert (2001) advocated that a sound pricing strategy must give much consideration to the
pricing variables of cost, demand, competition and profit.
212
In developing a realistic framework for quantity surveying consultancy pricing, it is crucial to
consider the recovery of cost incurred in providing services to clients; the profit that will accrue
as a reward; the competition from other quantity surveyors in terms of pricing (c.f. Rahim et al.,
2013); and the nature of demand from the perspective of clients. Drawing on from the above, a
sub class pricing framework will be appropriate and novel as demonstrated in figure 6.5.1.1
below.
Figure 6.5.1.1: Pricing Strategies sub framework
Practically, cost oriented strategy and profit oriented strategy are mostly adopted in pricing than
others because most price setters think first of cost recovery to stay in business, and profit to
reward their effort. However, it is appropriate to consider infusing all these strategies in to the
pricing agenda whenever pricing. Each of the above pricing strategies identified namely, demand
oriented; competition oriented; profit oriented; and cost oriented have their own nature and
dynamics which will require a future research study to thoroughly examine their characteristics.
6.5.1.2 Component 2: Just Pricing
The pricing variables classified under this component comprise of seller’s profit; customers
intrinsic value; customer’s affordability; and the government. The eigenvalues of the government
Pricing Strategies
Profit Oriented Competition
Oriented Cost oriented
Demand
oriented
213
and customer’s affordability are slightly above average (-.675 and .665 respectively) hence are
mediocre but examining these variables practically, the two variables are critical in the dynamics
of QS consultancy. The chi square test result revealed that there is no significant relationship
between the government and the achievement of just price; similarly, the variable ‘the
government’ was ranked with an RII of 0.58 which is also mediocre hence it is deemed
eliminated, likewise, the chi square test result revealed that the variable ‘the government’ is not
significantly related to the achievement of just price. However, the chi square test result proved
that just price is significantly dependent on seller’s profit; customer’s intrinsic value; and
customer’s affordability. Practically, the role of governments regarding pricing in capitalist and
democratic economies is very minimal; however, their actions or decisions can indirectly affect
the manner in which demand (client) and supply (consultant) interact in setting a just price or an
equilibrium price.
From the above discussion, the sub pricing framework for just price achievement for the
establishment of equilibrium in consultancy pricing between the client and the quantity surveyor
is demonstrated below in figure 6.5.1.2.
Figure 6.5.1.2: Just/equilibrium pricing sub framework
Just Price
Seller’s profit Customer’s
affordability
Customer’s
intrinsic value
214
A perusal of figure 6.5.1.1 and figure 6.5.1.2 revealed a special relationship between just price
and pricing strategies. In this relationship, profitability exists in both just pricing and pricing
strategies. This phenomenon produces another pricing framework depicted in figure 6.5.1.2a
below.
Figure6.5.1.2a: Pricing strategy and just price relationship
6.5.1.3 Component 3: Pricing Roles
The variables extracted under component 3 include firm’s objectivity; firm’s success; firm’s
image, and firm’s failure with eigenvalues of .779, .810, .717 and .519 respectively; referring to
the ranking by respondents the RII of these variables are above 0.70; similarly, the chi square
result indicated that the role of the firm is significantly dependent on the objectivity, success
image and failure of the firm. The sub pricing framework is demonstrated in figure 6.5.1.3
below.
Pricing
Strategies Just Price
Demand
oriented
Competition
Oriented
Cost
oriented
Customer’s
intrinsic
value
Customer’s
affordability
Profitability
215
Figure 6.5.1.3: Pricing roles sub framework
Practically, the objective of the firm determines the pricing strategy to be adopted in setting
prices hence QS consultancy practitioners must be mindful of their roles and bear in mind that
setting price for clients will either affect their image and ultimately their success in consultancy
business. Comparing figure 6.5.1.3 and figure 6.5.1.2a above, pricing objectivity has created a
relationship between pricing roles and pricing strategies; hence the sub class framework is
depicted in figure 6.5.1.3a.
Figure 6.5.1.3a: Grand sub pricing framework
Pricing Roles
Outcome
Failure
Success
Image
Pricing Objective
Pricing
Roles
Pricing
Objective
Pricing
Strategy
Outcome
Failure
Success
Image
Just Price Profitability
Customer’s
intrinsic
value
Customer’s
affordability
216
6.5.1.4 Component 4: Social influence
Social influence affect pricing; and prominent among them are media action and pressure group.
Media action and pressure group after extraction have factor loading of .783 and .887
respectively. The ranking by respondents also revealed that media action and pressure group
have their RII below 0.50. The chi square test result also produced a p-value below .005 hence
there is significant statistical evidence that social influence is related to quantity surveying
consultancy pricing. Therefore, the sub pricing framework is demonstrated in figure 6.5.1.4
below.
Figure 6.5.1.4: Social influence, sub pricing framework
6.5.1.5 Component 5: Value
Value is important to pricing; component 5 has an extracted variable ‘value of a product or
service’ with factor loading of .803 and an RII of 0.73 in higher order of variable ranking.
Considering the chi square test results of hypotheses in this regard, value of a product or service
has a p-value less than .005 which makes it statistically significant. Equally linked to value is
intrinsic value which is innate to the customer and has the potential of influencing whether the
customer will afford the service. It therefore implies that a relationship is created between value
and just price by intrinsic value and customer affordability. Similarly, social influence can affect
the value system of the client through media advertising, marketing and the actions of consumer
Social
influence
Pressure
group
Media
action
217
protection groups to exert pressure on QS consultancy price setters. In this direction, the grand
sub pricing framework will be represented in figure6.5.1.5 below.
Figure 6.5.1.5: Grand sub pricing framework
This study has not critically examine the key aspects of value pricing in detail, it is novel to
conduct a future study to explore the dynamics of value pricing as far as QS consultancy services
pricing is at stake.
6.5.2 Project Pricing (Consultancy Pricing)
6.5.2.1 Component 1: Business management
Business management has the tendency to affect pricing. Component 1 comprises of firm’s
experience in pricing; duration of service provision; and business development with factor
loadings of .648, .708 and .881 respectively. The ranking of these variables revealed that
duration of service provision (RII= 0.77); firm’s experience (RII= 0.79); and business
development (RII= 0.69) are above average ranking. The chi square test of independence
adopted for testing hypothesis indicated the null hypothesis relating to business development was
Outcome
Failure
Success
Image
Pricing
Roles
Social influence
Pricing
Strategy
Just Price Pricing
Objective
Profitability
Value Systems
Intrinsic value
Affordability
218
accepted hence business development is not dependent on the success of bid price of QS
consultants. A perusal of the ranking of business development is clearly in consonance with the
hypothesis, therefore, there is no statistical evidence to suggest that business development is
dependent on pricing success. However, per the ranking and hypothesis testing, there is statistical
evidence to advocate the dependency of bid price success on duration to render service and
firm’s experience. Practically, clients are interested in the duration of service delivery and the
experience of the consultant to ensure value for money; these would be met by the consultant
based on sound business management practices. Figure 6.5.2.1 demonstrate the sub pricing
framework in terms of achieving realistic QS consultancy services pricing.
Figure 6.5.2.1: Business management, sub pricing framework
6.5.2.2 Component 2: Service cost management
The manner in which the consultant manages cost, value and client attraction (demand) will
reflect the pricing strategy leading to the determination of price levels for clients. The variables
in component 2 comprises of time taken to solve a problem; materials used on the project; good
financial control system; and record of past project cost with factor loadings of .794, .653, .805
and .618 respectively. The ranking of these variables by respondents indicated that time taken to
solve a problem (RII= 0.79); materials used on the project (RII= 0.80); and good financial
control system (RII= 0.75) were in higher order of ranking. The chi square test of hypothesis
Business Management
Duration to render
service
Firm’s Experience
219
relating to these variables revealed a statistical evidence to suggest, a successful criteria for QS
consultancy pricing is significantly dependent on the time taken to solve the problem; materials
used on the project; and good financial control. In view of the above dynamics, the sub pricing
framework is depicted in figure 6.5.2.2 below.
Figure 6.5.2.2: Service cost management, sub pricing framework
Observing figure 6.5.2.1 and figure 6.5.2.2, time taken to solve a problem; and duration to render
service have created a relationship between business management and service cost management.
Hence, the combined framework is depicted in figure 6.5.2.2a as:
Figure 6.5.2.2a: Consultancy (service) management, sub pricing framework
Service Cost
Management
Time taken to
solve problem Good financial
control
Materials used
on the project
Consultancy
(service)
Management
Business
management
Service cost
management
220
6.5.2.3 Component 3: Technical and financial capabilities
The art of pricing is dependent on key elements. Component 3 clearly captures them as
production of timely reports; financial capacity; overhead and profits; and technical capacity
with eigenvalues of .754, .646, .755 and .546 respectively. Equally, the ranking of these
variables, production of timely reports (RII= 0.76); financial capacity (RII=0.78); overhead and
profit (RII= 0.78); and technical capacity (RII= 0.81) are deemed to be in higher order. The chi
square test of hypothesis on these variables indicated that there is significant evidence to suggest
that bid price success is dependent on production of timely reports; financial capacity; overhead
and profit and technical capability. Hence figure 6.5.2.3 demonstrates the sub class framework
for technical and financial capabilities below.
Figure 6.5.2.3: Technical and financial capabilities
6.5.3 Concept of Risk
6.5.3.1 Component 1: Corporate internal risk
Corporate internal risks are directly related to the consultancy firm and affects pricing of services
provided to clients. Component 1 comprises of associated business risk; financial risk; logistical
and infrastructural risk; and managerial risk and operational risk with factor loadings of .727,
.709, .710 and .727 respectively. Similarly, the ranking of these variables revealed associated
business risk (RII= 0.68); financial risk (RII= 0.73); logistical and infrastructural risk (RII=
0.62); and managerial and operational risk (RII= 0.66). The chi square test hypothesis result of
Technical and financial capabilities
Technical
capacity
Overhead
and profits
Production of
timely reports
Financial
capacity
221
these variables demonstrates that there is significant statistical evidence to claim that the
robustness and levels of consultancy services pricing is dependent on financial risk; logistical
and infrastructural risk; and managerial and operational risk. The sub pricing framework is
demonstrated in figure6.5.3.1 below.
Figure 6.5.3.1: Corporate internal risk sub pricing framework
6.5.3.2 Component 2: Corporate external risk
Corporate external risks are not directly related to the core activities of the QS consultancy firms
but they have the potential of affecting the manner in which services are priced. Component 2
comprises of organizational and societal risk; legal risk; and regulatory risk with their
eigenvalues of .766, .710 and .830 respectively. Respondents rank these risks as follows:
organizational and societal risk (RII= 0.63); legal risk (RII= 0.70); and regulatory risk (RII=
0.70). The chi square test of hypothesis revealed enough statistical evidence to suggest that QS
consultancy robustness is dependent on organizational and societal risk; legal risk; and
regulatory risk. In the light of the above, the pricing sub framework is demonstrated in in figure
6.5.3.2 below.
Corporate internal
risk
Financial risk
Managerial and
operational risk
Logistical and
infrastructural risk
222
Figure 6.5.3.2: Corporate external risk
6.5.3.3 Component 3: Location Risk
Location risk occurs as a result of the geographical positioning of the pricing entity. This risk
manifests in various forms like political upheavals and acts of God which may lead to the
disruption of the consultancy process. Component 3 comprises of political risk; and force
majeure risk with associated factor loadings of .883 and .841 respectively. Referring to the
ranking of these risks, political risk (RII = 0.69); and force majeure risk (RII = 0.61). The chi
square test of hypothesis revealed that there is statistical significance to claim that the level of
consultancy pricing is dependent on political risk and force majeure risk. Therefore, the sub
pricing framework is demonstrated in figure 6.5.3.3 below.
Figure 6.5.3.3: Location risk sub pricing framework
Corporate External Risk
Organizational
and societal risk
Regulatory
Risk Legal risk
Location Risk
Force majeure risk Political risk
223
Considering the sub pricing frameworks in figures 6.5.3.1, 6.5.3.2 and figure 6.5.3.3 for
corporate internal risk, corporate external risk and location risk respectively, it is clearly
demonstrated that QS consultancy pricing robustness and level is affected by corporate internal
risk; corporate external risk; and force majeure risk. Hence the sub grand framework for risk
when considering QS consultancy pricing is depicted in figure 6.5.3.3a below.
Figure 6.5.3.3a: Sub grand Pricing risk framework
6.5.4 Concept of Taxation and Inflation
6.5.4.1 Component 1: Taxes
Component 1 consists of taxes which the consultant has to honour as part of statutory duty.
These taxes are considered in this study as pricing variables because they have the capacity to
alter the level of prices set by consultants whom the client has to pay. These taxes include
personal income tax; corporate tax; profit tax; local tax and property tax with factor loading of
.824, .730, .724, .738, .735 and .812 respectively. The ranking of these variables revealed
personal income tax (RII= 0.61); corporate tax (RII= 0.55); profit tax (RII= 0.56); local rate
(RII= 0.57); and property tax (RII= 0.55). The rankings by respondents demonstrated a mediocre
consideration attached to the issues of taxation when pricing consultancy services. The chi
square result of hypothesis testing revealed that there is significant statistical evidence to suggest
Pricing
Robustness and
Level
Location risk Corporate internal
risk
Corporate external
risk
224
that a relationship exist between QS consultancy services levels and the tax variables since their
p-values < .005. Therefore, the sub pricing framework is demonstrated in figure6.5.4.1 below.
Figure6.5.4.1: Taxes sub pricing framework
6.5.4.2 Components 2 and 3: Price catalysts
Some circumstances precipitate QS consultancy price levels and robustness remotely. This
research study christened those price hastening circumstances as price catalysts. The price
catalysts are categorized in components 2 and 3 comprising of inflation, production shortfall,
government policies and input prices with factor loadings of .659, .799, .868 and .816
respectively. The ranking of these price variables revealed inflation (RII= 0.77), production
shortfall (RII= 0.68); effects of input market (RII= 0.70); government policies (RII= 0.69; and
input prices (RII= 0.75). The consideration given to these pricing variable by respondents
through ranking is fairly higher. It is therefore necessary to consider the chi square test of
hypothesis which demonstrated clearly that QS consultancy services price levels are significantly
dependent on inflation, production shortfall, effects of input market and government policies. In
the light of the above, the pricing sub framework is depicted in figure 6.5.4.2 below.
QS Price
Levels
Profit tax Personal
income tax Local
rates
Property
tax
225
Figure 6.5.4.2: QS consultancy price catalyst sub framework
So far it has been realized that the QS consultancy price levels and robustness are affected by
risk and tax liabilities of the consultancy entities. These key variables of risk and tax liability will
depend on the location of the consultancy firm and the environment of the consultancy
engagement hence location has the potential of altering the gauge of QS consultancy services
pricing. Combining figures 6.5.3.3a, 6.5.4.2 and 6.5.4.2 above produces a combined pricing
framework for risk, taxes and price catalysts would produce a sub grand framework
demonstrated in figure 6.5.4.2a below.
Figure 6.5.4.2a: QS pricing level and robustness, sub grand framework
Government
Policies
Inflation
Price
Catalysts
Production
shortfall
Effects of
input market
Input prices
PRICE LEVELS
Taxes Pricing Risk
QS Price Levels and Robustness
Price Catalysts
Input Prices
226
6.5.5 Quantity Surveying Consultancy Services Pricing Components
Having considered the influential factors that relate to the generic pricing environment of QS
consultancy services provision, this section will concentrate on the various components of
consultancy pricing as follows:
6.5.5.1 Component 1: Office Management
Office management is important in every corporate organization. Costs are incurred in the
management of offices which must be recovered through pricing, Component 1 comprises of
staff allowances; office rent; and supplies and equipment with factor loadings of .776, .755 and
.783 respectively. Similarly, respondents ranking of these key variables unfolds as staff
allowance (RII= 0.74); office rent (RII= 0.67); and supplies and equipment (RII= 0.69). It is
clear that QS consultancy services pricing must appreciate office management in order to stay in
business. Hence the sub framework in this regard is depicted in figure 6.5.5.1 below.
Figure6.5.5.1: QS pricing sub framework for office management
6.5.5.2 Component 2: Overheads
Overheads are expenses incurred as a result of providing services to clients. They are
expenditure indirectly related to the core services of the consultancy engagement but are needed
to keep the consultancy machinery moving. Component 2 examines the composition of
overheads for QS consultancy pricing. It consists of insurance, contingencies; taxes and duties
Office
Management
Supplies and
equipment Staff
Allowances Office rent
227
with factor loadings of .779, .828 and .546 respectively. The ranking of these variables indicated
insurance (RII= 0.69); contingencies (RII= 0.72); and duties and taxes (RII= 0.71). In spite of
taxes and duties obtaining higher order ranking from respondents, its eigenvalue of .546 is
mediocre. In addition to the consideration given to taxes by respondents earlier, it is appropriate
to ignore the component related to taxes and duties to avoid double counting or taxation.
Therefore the pricing sub framework is depicted below in figure 6.5.5.2 below.
Figure 6.5.5.2: Overheads pricing sub framework
6.5.5.3 Component 3: Administration and Training
Consultants are often engaged for the training of individuals of corporate organizations or
professional bodies. The expenses incurred in providing the training services must be recovered
for the consultant to stay in business. Component 3 is designated administration and training. It
comprises of variables: travel and transport; communications; training programmes and report
preparation with factor loadings of .817, .555, .771 and .616 respectively. It is also necessary to
refer to the ranking of these variables by respondents which unfolded as travel and transport
(RII= 0.75); communication (RII= 0.69); training programme (RII= 0.66); and report preparation
(RII= 0.72). Observing the factor loading and the ranking of these variables, it is appropriate to
ignore communication because it has a mediocre eigenvalue and ranking but in practical sense, it
Overheads
Contingencies Insurance
228
is impossible to successfully render consultancy services without employing various forms of
communication with the client. Therefore, it is appropriate to include communication in the
framework, hence the sub pricing framework for this component is demonstrated in figure
6.5.5.3 below.
Figure 6.5.5.3: Administration and training sub pricing framework
6.5.5.4 Component 4: Reimbursement and Payments
It is important to reimburse or reward the consultant for services provided to clients. Component
4 comprises of consultant staff remuneration; mobilization and demobilization; and profits with
eigenvalues of .562, .512 and .817 respectively. Referring to respondents ranking of these
variables, consultant staff remuneration (RII= 0.74); mobilization and demobilization (RII=
0.71); and profits (RII= 0.76). Examining the eigenvalues, it is novel to ignore consultant staff
remuneration and mobilization and demobilization because most consultancy engagements are
activities are operated in an office, this is the reason office rent is crucial to the running of
consultancies. Similarly, consultant staff remuneration was considered under the component
office management. In an international engagement, the consultancy would have to relocate to a
different geographical area hence pricing for mobilization and demobilization will be appropriate
in that regard but within the purview of this study, mobilization and demobilization will be
Administration and Training
Training
programme
Communication Report
Preparation
Travel and
transport
229
ignored. The sub pricing framework in terms of reimbursement and payments is demonstrated in
figure 6.5.5.4 below.
Figure 6.5.5.4: Reimbursement and payments sub pricing framework
6.5.6 Challenges confronting Quantity Surveying Consultancy Practice
Every professional practice has its own challenges. In like manner, quantity surveying practice
has its own challenges bedeviling the profession in diverse ways. It is therefore appropriate to
examine the critical challenges inimical to the vivacity of QS professional practice.
6.5.6.1 Component 1: Contractual and technology challenges
This component comprises of variables: slow responses to changing contractual arrangements;
lack of appropriate response to emerging services; slow response to information and
communication technology revolution; and inability to integrate applied research outputs into
practice with eigenvalues of .735, .803, .755 and .719 respectively. The ranking of these
challenges by respondents indicated an average RII of 0.70 which demonstrated that the severity
of these QS practice challenges is slightly above average. Practically, the QS profession is noted
for being conservative to the application of information technology and research integration.
However, the current wave of research revolution on building information modeling (BIM) gives
much hope to overcoming these challenges.
Reimbursement and
payments
Profits Consultant staff
remuneration
230
6.5.6.2 Component 2: Pricing Challenges
QS consultants are confronted with pricing challenges. These are categorized in component 2 as
reducing fees to loss making territory; exposure to risk; and decrease in project value with
eigenvalues of .840, .842, and .686 respectively. The respondents consider these challenges as
having moderate impact on the pricing of services. In a situation where fees are tied to the total
cost of the entire project, the fluctuation or the unstable nature of the project as a result of
variations introduced will affect the level of consultancy pricing.
6.5.6.3 Component 3: Market forces
Market forces influence pricing and should not be ignored. From Table F31, these market forces
have been categorized under Component 3 as the changing nature of demand; and impact of
competition with eigenvalues of .618 and .886 respectively. The perception of respondents on the
impact of these challenges on pricing indicated that changing nature of clients’ demand (RII=
0.71); and impact of competition (RII= 0.72). From these, it can be deduced that the impact of
market forces on Qs consultancy services pricing is much higher than other challenges explored
in this research study. It is therefore vital for practitioners to be very cautious of market forces.
QS professionals are also facing challenges from other professionals who are venturing into QS
practice. This scenario looks ugly for the traditional practitioners of the QS profession as it is
bound to create stiffer competition within the QS consultancy market. For instance, Rahim et al.
(2013) clearly pointed out that the scarcity of projects in the construction industry is a catalyst
for competition among quantity surveying practitioners. Another phenomenon of competition in
the quantity surveying profession is fee competition (Rahim et al., 2013).
231
6.5.6.4 Component 4: Professional fees
In most cases, professional fees in the construction industry especially quantity surveying fee in
many jurisdiction are determined by professional bodies and political authorities(Rahim et al.,
2013), which are not left to the forces of demand (client) and supply (consultant) as it pertains in
other consulting nomenclature like management consultancy. Component 4 contain only
fluctuations in professional tariff of fees with eigenvalue of .910 with respondent ranking its
impact as RII= 0.61. The ranking by respondents revealed that no matter the severity of this
challenge in other jurisdiction, it is a mediocre issue as far as the scope of this study is concerned
because, in practical terms authorities do not interfere in to the gauging of consultancy fees in
Ghana.
A Generic Framework for Pricing QS Consultancy Services
Having examined the pricing issues empirically through the development of sub frameworks
above, it is now time to develop the generic (all-embracing) framework that will reflect the
realities of pricing quantity surveying services. This generic (all-embracing) framework
metamorphosed from figure 6.5.1.3a; figure 6.5.2.3; and figure 6.5.4.2a respectively is
demonstrated in figure 6.6 below.
232
Administration and management
Overheads
Profits
Office management
Reimbursements and Payments
Client QS Consultant
Figure 6.6: A framework for pricing quantity surveying consultancy services
Supply
Supply
Pricing
Strategies
Pricing Catalyst
-Pricing risks
-Taxes
-Input prices
Demand
Value
-Intrinsic
nature of
clients
-Client’s
affordability
-Social
influence
Just Price
Pricing
Management
Pricing
Objectives
Clie
nt E
xp
ec
ta
tio
n
Outcome
-Robust price level
-Image
-Success
-Failure
Pricing S
pine
Client-Consultant Relationship
233
CHAPTER SEVEN
CONCLUSION AND RECOMMENDATIONS
7.1 INTRODUCTION
This research study commenced with the target of extensively delving into the dynamics of
quantity surveying consultancy services pricing. It has become necessary to engage in this
important venture because of the absolute lack of a generic framework for pricing the services
rendered by professional quantity surveyors for their clients as pertaining to other corporate
establishments like manufacturing companies. The six chapters undertaken hitherto the
commencement of this chapter have concentrated on theoretical framework for the research;
literature and conceptual milieu of the research agenda; the methodological dimensions including
philosophical underpinnings of the research; and analysis and discussion of results leading to the
development of framework for pricing.
This chapter ties the knot on the research endeavor by addressing only the main points
throughout the study. It commences by reviewing the objectives of the research study; findings;
recommendations; and limitations of the research. The curtain to this research journey so far
would be drawn on future research agenda emanating from this research.
7.2 REVIEW OF RESEARCH OBJECTIVES
The main aim of this research was to explore Quantity Surveying (QS) practice in Ghana, and to
develop a generic framework for pricing QS professional consulting services in Ghana. To
achieve this novel aim of the research, four key specific research objectives were set to
effectively drive the agenda as follows:
234
Objective 1: To conduct a critical literature review on quantity surveying and consulting
practice
Critical issues concerning the consultancy services pricing environment of the quantity surveying
profession were reviewed to identify the trends in practice. The review was also necessitated by
the need to be abreast with the current quantity surveying and research environment to take
sound decisions concerning what should be investigated. The review aided in the identification
of the knowledge gap and research gap as far as this research is at stake. The review of extant
literature concentrated on key issues notably general consultancy practice; quantity surveying
practice; and a theoretical framework on pricing and its allied concepts which are needed in the
development of a robust pricing framework. The theoretical framework culminated in to the
postulation of key hypothesis in which the dependent variables (DV) were pricing, price
robustness and price levels and several independent variables (IV) (refer to chapter two for more
details). The literature review revealed a gap in research as far as the pricing of quantity
surveying consultancy services are concerned. This lacuna in knowledge and research in quantity
surveying practice alone but in other consulting practices. Similarly, the literature also unfolded
a scarcity of research conducted on quantity surveying practice in Ghana.
Objective 2: To explore the potential challenges confronting Quantity Surveying (QS)
consultancy in Ghana
Challenges confronting corporate organizations would affect their business transactions
culminating into weak pricing strategies which can cause the collapse of business entities if they
are not able to recover the cost of operation among others in the provision of goods and services.
Quantity surveying practice is no exception as far as challenges confronting business entities are
235
concerned. This study explored the challenges confronting quantity surveying consultancy
practice and found changing nature of clients’ demand; impact of competition; complexity of
modern construction projects and slow response to information and communication technology
revolution as the general challenges confronting quantity surveying consultancy practice. On
pricing challenges, the study revealed exposure to risks; and decrease in project value by
inflation. However, price-related challenges are perceived to be moderately significant in the
pricing of quantity surveying consultancy services except in the cases of market forces. This
therefore implies that the general challenges are the most severe challenges confronting quantity
surveying practice. Risk of various dimensions posing as challenges to quantity surveying
consultancy services pricing identified by the study have been categorized as directly related to
the activities of the consulting firm include financial risk; market related risk; and technological
risk. Indirect risk which are risks occurring at the various stages of the project implementation
were identified by the study as financial risk; legal risk; political risk; and regulatory risk. Using
the factor analysis, these risks were further classified as corporate internal risk; corporate
external risk; and location risk (political risk and force majeure).
Objective 3: To establish the key determinants (indicators) in pricing QS consultancy service
practice
The study also sought to identify the key determinants of quantity surveying consultancy
services pricing. The study unfolded the key determinants as demand for quantity surveying
services; taxes and inflation; amount of cost incurred in service provision; various forms of risks
as identified in objective 2 above; inflation; effects of input market; service cost management;
value; social influence (media and pressure groups); pricing strategies adopted; profit; and
duration of service provision.
236
Objective 4: To develop a generic framework for pricing QS consultancy services based on the
identified indicators
In achieving the above objective which is the grand agenda of this study, the researcher
combined the results and discussion conducted using statistical tools: relative importance index,
chi-square test of hypothesis to ascertain the relationship between the dependent variables and
independent variables; and the factor analysis to identify the underlying common factors among
these pricing variables. The discussions led to the development of the generic framework
depicted in figure 7.1 below.
237
Administration and management
Overheads
Profits
Office management
Reimbursements and Payments
Client QS Consultant
Figure 7.1: A generic framework for pricing quantity surveying consultancy services
Pricing Catalyst
-Pricing risks
-Taxes
-Input prices
Just Price
Value
-Intrinsic
nature of
clients
-Client’s
affordability
-Social
influence
Pricing
Management
Outcome
-Robust price level
-Image
-Success
-Failure
Pricing S
pine
Clie
nt E
xp
ec
ta
tio
n
Pricing
Strategies
Pricing
Objectives
Demand Supply
Supply Client-Consultant Relationship
238
7.3 FINDINGS
In addition to the findings under the review of research objectives above, other findings
identified by the research study which are crucial to the pricing of quantity surveying
consultancy services include:
indirect risks associated with projects are significant pricing variables that can change the
levels of consultancy services pricing;
financial risk is both direct and indirect consultancy services pricing risk of major
proportion;
when cost of consultancy services is high all components of consultancy services pricing
will be proportionally high except profit and contingencies;
the dominance of capitalism has weakened the power of professional bodies in price
determination and control leading to haggling between demand (client) and supply
(consultant) to set consultancy services price levels hence price-related challenges are
deemed to be moderately significant in the pricing of quantity surveying consultancy
services except in the case of market forces;
traditional QS consultancy services are the most significantly priced while the non-
traditional services remain the less priced;
QS consultancy price levels and robustness are affected by risk and tax liabilities of the
consultancy entities;
corporate external risks are not directly related to the core activities of the QS
consultancy firms but they have the potential to affect QS consultancy services pricing;
239
social influence affect the value system of the client through media advertising,
marketing and the actions of consumer protection groups will exert pressure on price
setters;
intrinsic values of clients have the potential of influencing the affordability of QS
consultancy services; and
QS consultancy price levels and robustness are affected by risk and tax liabilities of the
consultancy entities.
7.3.1 Special Relationships Identified
The tripartite discussion of the results involving the three main statistical tools employed for this
research study in section 6.5 of chapter six culminating into the above generic framework for
quantity surveying consultancy services pricing has led to the creation of key relationships
among some of the variables involved in the study by other variables equally involved in the
study. These relationships were discovered during the development of the various subclass
frameworks and include the following:
1. A relationship has been created between profitability and pricing strategies. This means
that the type of pricing strategy adopted by the quantity surveying consultant would
determine the level of profit to be enjoyed from services rendered to clients;
2. There is a relationship between pricing objectivity and pricing strategy. This implies that
the objective of pricing would determine the pricing strategy to be adopted;
3. Time taken to render service to clients has a bearing on business management and
service cost management. This means that the cost of service provision is proportional to
the duration of the service provision; however, adoption of appropriate business
240
management practices would determine whether higher or minimal service cost would be
incurred; and
4. Production of timely reports is related to business management, service cost
management, technical and financial capabilities.
7.4 CONTRIBUTION TO KNOWLEDGE
The relevance of a research is measured in terms of its contribution. All over the world higher
education institutions set their parameters for contribution to knowledge. Thus what counts as a
contribution to knowledge may slightly differ from institution to institution but there are
commonalities among these parameters for determining contribution to knowledge by a research
work. For instance, Gray (2011) identified five criteria for determination of contribution to
knowledge as:
literature review to demonstrate what counts as knowledge in the area of discourse and
establishing what is currently known in the area of research study;
development of frameworks (models);
publications;
contributions to methodology; and
formulas.
Within this study, extensive literature review had been conducted covering the key areas of
general consultancy; quantity surveying practice; and a theoretical framework of the general
pricing milieu. These reviews demonstrated that much work has not been done in the areas of
quantity surveying practice in Ghana especially in terms of research which is entirely focus on
241
QS services pricing. The review revealed that even though QS practitioners publish papers in
Ghana, they rather focus mostly on other areas such as project management which are not their
core areas of operation. This research also contributed to knowledge by publication of papers in
international journals of repute. It is estimated that this research study has the potential of
yielding more than three academic publications.
The generic framework for pricing consultancy services contributes to knowledge in diverse
ways by the combination of the various facets of pricing dynamics into a simpler, manageable,
and comprehensive entity for price setters of consultancy services and others alike. The key
findings of the research regarding value emphasized the need for ensuring value in pricing QS
services which hitherto pricing knowledge transmission has not been robust. This is very
significant in the case of knowledge transmission to provide value pricing in consultancy
services provision to clients especially in the arena of quantity surveying. The pricing catalysts
comprising pricing risks, taxes and input prices have added to the dimension of pricing
consultancy services especially in terms of potential risks that can alter the robustness and level
of consultancy services pricing. A pricing knowledge in area of the identified pricing catalysts by
this research provides solid foundation for understanding pricing situations faster. This leads to
quick analysis of consulting engagements to price effectively. In addition, this study identified
special pricing relationships among key pricing variables of profitability and pricing strategy;
pricing objectivity and pricing strategy; and the concept of consultancy duration and its bearing
on business and service cost management. The knowledge of these special pricing relationships
improves the knowledge base of consultancy services price setters. The systematic manner of
developing the generic framework through the development of subclass pricing frameworks has
242
added to the understanding of consultancy services pricing phenomenon that pricing within the
QS consultancy practice should be systematic and methodical.
7.5 RECOMMENDATIONS FOR PRACTITIONERS
In view of the findings of this research, it is appropriate to recommend vital issues for
consideration by consultancy practitioners and other stakeholders as far as consulting practice is
concerned. These recommendations include the following:
it is important for price setters in the consulting industry to envisage the risks in relation
to consulting engagements for which they are employed to provide services;
the low ranking of various taxes except VAT/NHIL means non-payment of taxes or tax evasion
by consultants dealing with private sector clients as a result of the inability of the tax authorities
to locate consultants to fulfill this statutory obligation due to improper planning and layout of
offices. This finding is a pearl for the tax authorities to dwell on in expanding their tax net to
mobilize more revenue for government coffers for development;
it is equally important for consulting entities to take due cognizance of inflation and its
causes that will affect consultancy services pricing;
competition in the non-traditional service sectors of QS practice is not intensive hence
innovative QS practitioners venturing into facilities management; oil and gas and other
non-traditional services of quantity surveying have the opportunity of making substantial
profit; and have the prospect of enjoying some significant monopoly for some
considerable period of time;
practically, clients are interested in the duration of service delivery, the consultant can
only meet this expectation by deploying experience in sound business management to
243
ensure value for money thereby meeting timelines, cost and quality expectations of
clients;
the objective of the firm determines the pricing strategy to be adopted in setting prices
hence QS consultancy practitioners must be mindful of their roles and bear in mind that
setting price for clients will either affect their image and ultimately their success in
consultancy business; and
the impact of market forces on QS consultancy services pricing is much higher than other
challenges. It is therefore vital for practitioners to be very wary of the market.
7.6 FUTURE RESEARCH AGENDA
This study has its own shortcomings as it cannot cover all aspects of the consultancy services
pricing agenda. It is therefore appropriate to turn these shortcomings into future research to be
undertaken; these future researches as far as this study is concerned evolved from the analysis
and discussion of the research results (see for instance chapter six) include:
a further research agenda to explore the in-depth dynamics of pricing objectives with
much emphasis on their influence on price levels will be a novel research undertaking;
it is therefore necessary to determine the parameters for the ascertainment of value of
services provided by QS consultants to their clients, this phenomenon has not been
addressed by this study hence a research agenda to determine the parameters for value of
services will be novel and apt;
Similarly, a study to determine the willingness to afford or pay (WTP) by clients for
consultancy services will be a step in the right direction;
244
having established the evidence of these variables (demand, cost, competition and profit)
as the fundamentals of pricing, it is novel that a further research at advanced level be
conducted in an in-depth manner on the dynamics of each of these variables in
influencing consultancy services pricing;
it is important to explore the nature of consultancy financial risks, to establish its true
level of influence and other associated encumbrances in pricing;
this study has not critically examine the key aspects of value pricing, it will be necessary
to conduct a future study to explore the dynamics of value pricing as far as QS
consultancy services pricing is at stake; and
a further empirical study on the relationship between economic development and demand
for consultancy services would be a novelty to undertake at a higher level of research.
7.7 CONCLUSIONS
It is important to examine the various aspects of the generic framework developed from this
research work viz-a-viz the circumstances surrounding a particular consulting engagement
during service delivery to clients. It should be noted that the utilization of this framework is
subject to the manipulation of the quantity surveying services price setter since practitioners
would operate under different ambiance all the time. In short, the framework should be used in
relation to the circumstances of the consultancy service price setter.
The adoption of this framework for practice has the potential of providing consultancy
practitioners the opportunity to estimate realistic prices based on the nature of their service
delivery. The generic framework also provides an opportunity for reflections on consultancy
245
engagements in order to engage in the right caliber of practices that would inure to the
profitability and sustenance of consultancy firms.
246
REFERENCES
Abrahamson, E. (1996). Management Fashion, Academy of Management Review, Vol.21, No.1,
pp.254–85.
ACENZ. (2004). Guideline on the Briefing and Engagement for Consulting Engineering
Services. Wellington NZ: The Association of Consulting Engineers NZ.
Addai, J.P; Nkuah, M and Amoah, P. (2009). The Ghanaian quantity surveyor and the emerging
oil and gas industry, The Quantity Surveyor, Iss. 2, 2009.
ADB. (2010). Guidelines on the Use of Consultants by Asian Development Bank and Its
Borrowers. Mandaluyong City, Philippines: Asian Development Bank, 2010.
Adebola, O. (2006). The Quantity Surveyor in Highway Development. Nigerian Institute of
Quantity surveyors. 22nd Biennial Conference of Nigerian Institute of Quantity
Surveyors, Calabar Nigeria, 22-25th November, 2006.
Adendorff, C., Botha, B., van Zyl, C and Adendorff, G. (2012). Financial implications for built
environment consultants working at risk in South Africa, Acta Structilia, Vol. 19, No. 1
Adeoye, A.A. (1996). Computerized Information System for Surveyors, Information
Management Consultants, Lagos.
Adeyemi, T.O. (2009). Inferential Statistics for Social and Behavioural Research, Research
Journal of Mathematics and Statistics, Vol. 1, No.2, pp. 47-54.
Adnan,H; Nawawi, A.H.M; Akhir,S.M.M; Supardi, A and Chong, H.(2011). Bills of
Quantities: Perspectives of Contractor in Malaysia, Australian Journal of Basic and
Applied Sciences, Vol. 5, No.11, pp. 863-873.
AERC. (1998). Tax Reform and Revenue Productivity in Ghana. Nairobi, Kenya: The African
Economic Consortium.
Aguilar, M.A, Gill, J.B.S and Pino, L. (2000). Preventing Fraud and Corruption in World Bank
Projects: A Guide for Staff. The World Bank, Washington, D.C.
Ahadzie, D.K. (2007). A Model for Predicting the Performance of Project Managers in Mass
House Building Projects in Ghana. PhD Thesis, University of Wolverhampton.
Akintoye, A. (2001). Quantity Surveying; An art or Science? A researchers’ Perspective, in:
Moneke, G.O. (Ed.): Quantity Surveying and Total Cost Management, Lagos: The Nigerian
Institute of Quantity Surveyors, pp. 19 – 41.
Al-Bahar, J and Crandall, K. (1990). Systematic Risk Management Approach for Construction
Projects. ASCE Journal of Construction Engineering and Management, Vol. 116,
No.3, pp533-546.
Albratt, R, Nel, D and Higgs, NS (1992). An examination of the ethical beliefs of managers
using selected scenarios in a cross-cultural environment. Journal of Business Ethics,
Vol.11, pp. 29- 35.
Alberta Infrastructure and Transportation. (2005). Guidelines for Calculation of Fees for Cost
Consultant Services.
Alexis J. A. (1990). Horizontal Concentration and European Merger Policy. European
Economic Review, Vol. 34 , pp. 539-550.
Allison, G; Braidford, P; Houston, M; Robinson, F and Stone, I. (2011). Business Dupport for
social enterprises: Findings from a longitudinal study. Policy Research Group,
University of Durham.
Amstrong, J.S and Green, K.C. (2011). Demand Forecasting: Evidence-Based Methods. Oxford
Handbook in Managerial Economics.
247
Andam, Z.R. (2003). E-Commerce and e-Business. E-ASEAN Task Force, UNDP-APDIP
Anderson, M.J. (2006). A new method for non-parametric multivariate analysis of variance,
Austral Ecology, Vol. 26, pp. 32–46.
Anderson, W.L and Ross, R.L.(2005). The Methodology of Profit Maximization: An Austrian
Alternative. The Quarterly Journal of Austrian Economics, Vol. 3 No. 4, pp.31-44.
Anderson, D.R; Burnham, K.P and Thompson, W.L. (2000). Null Hypothesis Testing: Problems,
Prevalence and an Alternative, Journal of Wildlife Management, Vol. 64, No. 4,
pp 912-923.
Andrea, M.B.(2011). Public Sector Marketing: Importance and Characteristics. Journal of
Economics Practices and Theories, Vol.1, No.2 .
Anglim, J. (2007). Cluster Analysis and Factor Analysis, 325-711 Research Methods,
Email: [email protected], Office: Room 1110 Redmond Barry Building,
Website: http://jeromyanglim.googlepages.com/
Agresti, A. (2002). Categorical Data Analysis, 2nd edition, Hoboken, New Jersey: John Wiley&
Sons.
Anago, I. (2006). The Quantity Surveyor and Road Map to the Future. Nigerian Institute of
Quantity Surveyors. 22nd Biennial Conference of Nigerian Institute of Quantity
Surveyors, Calabar, Nigeria, 22-25th November, 2006.
Ansari, A., Siddarth, S. and Weinberg, C.B. (1996). Pricing a bundle of products or services: the
case of nonprofits, Journal of Marketing Research, Vol. 33 No. 1, pp. 86-93.
Antolin, P and Stewart, F. (2009). Private Pensions and Policy Responses to the Financial and
Economic Crisis. OECD Working Papers on Insurance and Private Pensions,
No.36, OECD Publishing
APEGGA. (2006). Guideline for Selecting Engineering, Geological and Geophysical
Consultants. Draft 1.5, June 2006.
Appelbaum, S.H and Steed, A.J. (2004). The critical success factors in the client-consulting
Relationship. Journal of Management Development, Vol. 24 No. 1, pp. 68-93.
Argyris, C. and Schön, D. (1978). Organizational Learning: A theory of action perspective.
New York, NY: Addison-Wesley.
Arnaud, G. (1998). The obscure object of demand in consultancy: a psychoanalytic perspective.
Journal of Managerial Psychology, Vol. 13 No. 7, pp. 469-484.
Association of South African Quantity Surveyors (ASAQS). (2006). History of Quantity
Surveying in South Africa.
Ashford, M. (1998).Con Tricks: The World of Management Consultancy and How to make it
Work for You. London: Simon & Schuster.
Ashok, J, Carmen, S and Joice, G. (2008). Applying Customer Relationship Valuation.
The Journal of Professional Pricing, Third Quarter 2008.
Ashworth, A and Hogg, K. (2000). Added value in design and construction: Pearson Education Ashworth, A. (1994). Education and Training of Quantity Surveyors. Construction papers, 37. Ashworth, A. (1981). Progress in Quantity Surveying 1960-1980. Quantity Surveyor, 37(1), pp.6-7.
Attewell, P and Rule, J.B. (1991). Survey and other methodologies applied to IT impact
research: experiences from a comparative study of business computing, Paper Presented at
the Information Systems Research Challenge: Survey Research Methods.
Awal, S.M. (2010). Contractor Selection in Ghana. Masters Dissertation, Kwame Nkrumah
University of Science and Technology.
Ayeni, A.A. (1989). Computers Making your choice, Lagos Q.S. Digest, Vol.3, No. 2, pp.4-5.
248
Babalola, B. (2006). Harnessing the opportunities at the Grassroots to make Quantity
Surveying Profession Competitive at the National and International Markets.
Nigerian Institute of Quantity Surveyors. 22nd Biennial Conference of the
Nigerian Institute of Quantity Surveyors, Calabar, Nigeria, 22-25th November,
2006.
Babbie, E. (1995). The Practice of Social Research, 7th Ed, Belmont: Wadsworth Publishing.
Baddie, E and Halley, F. (1995). Advantages in social research: data analysis using SPSS for
Windows. The Thousand Oaks, California: Pine Forge Press; a Sage Publications
Company.
Badu, E and Amoah, P. (2004). Quantity Surveying Education in Ghana, Kwame Nkrumah
University of Science and Technology, Ghana.
Ball, D. (2009). Regulation of Mark-ups in the Pharmaceutical Supply Chain. WHO/HAI
Review Series on Pharmaceutical Pricing Policies and Interventions, Working
Paper 3.
Ball, L and Mankiw, N.G. (1994). Asymmetric Price Adjustment and Economic Fluctuations.
The Economic Journal, 104(March), 247-261.
Barker, J, Sedik, D and Nagy, J.G. (2008). Food Price Fluctuations, Policies and Rural
Development in Europe and Central Asia. FAO Regional Office for Europe and
Central Asia UNDP Regional Bureau for Europe and CIS. FAO-UNDP Europe
and Central Asia Consultation, Budapest, Hungary, 5-6th December, 2008.
Barrringer, H.P.E. (2003). A Life Cycle Cost Summary. Maintenance Engineering Society of
Australia. International Conference of Maintenance Societies, Sheraton Hotel, Perth,
Western Australia, May 20-23, 2003.
Bateson, J.E.G. (1995).Managing services marketing: texts and readings, 3rd ed., Orlando, FL:
The Dryden Press.
Beeby, M., Broussine, M., Grisoni, L., James, J., and Shuttle, A-M. (1998). Consulting to a
“hurt” or “upset” Organization, The Leadership & Organization Development Journal,
Vol. 20 No. 2, pp. 61-69.
Beechy, T.H and Conrod, J.E.D. (1998). Intermediate Accounting. Canada: McGraw-Hill
Ryerson Limited.
Beeston, D.T. (1983). Statistical method for building price data, London, UK: E&FN Spon.
Bedoucha, L. (2010). Risk Assessment and Mitigation in Infrastructure Projects. Multilateral
Investment Guarantee Agency (MIGA). First Meeting of the Working Group
on Infrastructure Finance in Iraq, February, 18, 2010.
Belkin, P. (2008). The European Union’s Energy Security Challenges. CRS Report for
Congress. Congressional Research Service.
Berenison, M.L and Levine, D.M. (1979). Basic business statistics: concepts and applications,
London: Prentice-Hall International Inc.
BIS. (2010). Financing a private sector recovery. The Stationery Office Limited, UK: Crown
Copyright.
Bloch, B. (1999). How they put the ‘con’ in consulting. Managerial Auditing Journal, Vol. 14
No. 3, pp. 115-117.
Blunsdon, B.J. (2002). Beneath fashion: Why is there a market for management consulting
services? Professional service Firms workshop, university of Alberta,
Edmonton, Canada. Available http://canback.com/blunsdon.pdf
249
Boisnier, A and Chatman, J.A. (2002). The Role of Subcultures in Agile Organizations. Haas
School of Business, University of California, Berkeley.
Bolstein, A.R and Crow, M.(2008). Statistical Formulas and Citations for EPA’s 2007 ERP
Sample Planner and ERP Results Analyzer, EPA Contract Number EP- W-04-023, Work
Assignment 3-61, May 12, 2008.
Bonnar, I. D. (2007). “Not As Cool As Fighter Pilots”: An exploration of identity and learning
for full-time Quantity Surveying students. EdD Thesis May 2007, EdD Programme:
Cohort 3, University of Stirling.
Bonnici, L.H. (1991). Pricing dimensions in health-care service, Journal of Professional Services
Bouchaud, J.P and Potters, M. (2003). Theory of Financial Risk and Derivative Pricing: From
Statistical Physics to Risk Management. 2nd Edition, The Pitt Building,
Trumpington Street, Cambridge, United Kingdom: Cambridge University Press
Marketing, Vol. 8 No. 1, pp. 92-8.
Bower, M. (1982).The forces that launched management consulting are still at work. Journal of
Management Consultancy, Vol. 1 No. 1, pp. 4-6.
Braithwaite, A. (2003). The Supply Chain Risks of Global Sourcing. LCP Consulting, The
Stables, Ashlyns Hall Chesham Road, Berkhamsted HP4 2ST, United Kingdom.
Brand, M. (1998). New Product Development for Microfinance: Design, Testing and Launch.
ACCION International, Microenterprise Best Practices (MBP) Project.
Brizz, M. (1998). The Ultimate Advantage: Forging Stronger Partnerships with your Clients.
Journal of Management Consulting, Vol.10, No.1, pp.18–21.
Brodie, I. (2009). The consultancy industry. Presentation to MMU BS Placement Fair &
Career development Day, 4 February, 2009.
Browne, M.N and Keely, S.M. (1998). Asking the right questions: a guide to critical thinking,
5th edition, Upper Saddle River, NJ: Prentice Hall.
Brunsson, N. (2000). A World of Standards. Oxford: Oxford University Press.
Buehler, K, Freeman, A and Hulme, R. (2008). The Risk Revolution. Mckinsey Working
Papers on Risk.
Bu-Qammaz, A.S.; Dikmen, I and Birgonul, M.T .(2009). Risk assessment of international
construction projects using the analytic network process, Canadian Journal of Civil
Engineering, 36(7): 1170-1181.
Burney, S.M.A. (2008). Inductive and Deductive Research Approach. Department of Computer
Science, University of Karachi.
Burns, R. (2000). Introduction to research methods, 4th edition, Melbourne: Longman Cheshire.
Burnside, K. and Westcott, A. J. (1999). Market Trends and Developments on QS services
Proceedings of COBRA, 1999, The University of Salford, UK, September 1-2, 1999,
pp.88-102.
Burnett, J. (2008). Core Concept of Marketing. Zurich, Switzerland; Global Text.
Butcher, N and Demmers, L. (2003). Cost Estimating Simplified. Libris Design Project.
Byrne, J.A. (2002). Inside McKinsey. Business Week, July/08, pp. 54–62.
Campana, J. (2010). The soft Skills of Project Management: A view from Diploma Graduates,
Master Thesis, Faculty of Education, Queensland University of Technology.
Canadian Institute of Quantity Surveyors (CIQS). (2002). Quantity Surveying and Cost
Consulting Services: Schedule of Services and Recommended Charges, 4th edition: CIQS.
Canback, S. (1999). The Logic of Management Consulting, Part 2. Journal of Management
250
Consulting, Vol.10, No. 3, pp. 3-12.
Canbäck, S. (1998).Transaction cost theory and management consulting: why do management
consultants exist? Working paper Henley Management College.
Cannon, T. (1998). Marketing: Principles and Practice, 5th Edition. Wellington House 125
Strand, London WC2R 0BB: Cassell Publishers Limited
Cannon, H.M. and Morgan, F.W. (1990). A strategic pricing framework, Journal of Services
Marketing, Vol. 4 No. 2, pp. 19-30.
Carpio, C; Sydorovych, O and Marra, M.(2007). Relative Importance of Environmental
Attributes Using Logistic Regression, Selected paper prepared for presentation at the
Southern Agricultural Economics Association Annual Meetings Mobile, Alabama,
February 4-7, 2007.
Cartlidge, D. (2009). Quantity Surveyor’s Pocket Book. Linacre House, Jordan Hill, Oxford
Cartlidge, D. (2002). New Aspects of Quantity Surveying Practice: Butterworth Heinemann.
Cartlidge, D. (2000). New Aspects of Quantity Surveying Practice. Oxford: Butterworth-
Heinemann.
CAS. (2003). Overview of Enterprise Risk Management. Enterprise Risk Management
Committee Report. Available online: www.casact.org/area/erm/overview.pdf. [Accessed
14/6/2013].
CEBC. (2011). Consulting Engineers Fee Guidance. Available online: www.cebc.org.
[Accessed 3/1/2012].
Champion, D.J. (1970). Basic statistics for social research, Tennessee, USA: Chandler
Publishing Company.
Chan, Y.H. (2005). Discriminant analysis. Singapore Med Journal, Vol. 46, No. 2, pp.55.
Chan, Y.C. (2003). “Pre-Qualification Structured Learning (PQSLs) Series – Schedule of Rates
vs. Bills of Quantities.” The Hong Kong Institute of Surveyors. http://www.hkis.org.hk.
[Assessed: 14/3/2013].
Chan, DW.M and Kumaraswamy, M.M. (1997). A comparative study of causes of time overruns
in Hong Kong construction projects, International Journal of Project Management, Vol.
15, No. 1, pp. 55-63.
Channon, D.F. (1986). Bank strategic management and marketing, Chapter 8, Chichester: John
Wiley& Sons.
Chapman, J. (1998). Do process consultants need different skills when working with
nonprofits? Leadership and Organization Development Journal, Vol. 19 No. 4, pp.
211-215.
Chappel, D. (1994). Architects legal position on D&B, The Architect’s Journal, 9 March, pp. 43.
Chidambaram, S, Whitman, L and Cheraghi, S.H. (1999). A Supply Chain Transformation
Methodology. Proceedings of the 4th Annual International Conference on
Industrial Engineering Theory, Applications and Practice, San Antonio,
Texas, November 17-20, 1999.
Chinyio, E. (2011). The cost of tendering. In: Toole, T.M. (ed.) 2011. Working Paper Series
Proceedings of the Engineering Project Organizations Conference, Estes Park,
Colorado 9-11 August.
Chomitz, K.M and Gray, D.A. (1996). Roads, Land use and Deforestation: A Spatial Model
Applied to Belize. The World Bank Economic Review, Vol. 10, No. 3 487-512.
251
Cicchetti, C.J and Haveman, R.H. (1972). Optimality in Producing and Distributing Public
Outputs. Paper Presented at the December 1971 Meetings of the American
Economic Association, Institute for Research on Poverty, University of
Wisconsin
CIDB. (2005). Applying the Procurement Prescripts of the CIDB in the Public Sector.
September, 2005. Fourth Edition of CIDB Document 1002.
CIDB. (2005). Preparing procurement documents. September 2005 Second edition of CIDB
document 1009.
Clark, P.I. 2012. “Meeting the requirements of the CDM Regulations: 10 tips for architects.”
[online]. Available Online:
<http://www.ciob.org.uk/sites/ciob.org.uk/files/RIBA%20Ten%20Tips%20for%20CDM%
20Rev%2000_0.pdf.> [Accessed 30th June 2013].
Cohen, L; Manion, L and Morrison, K. (2005). Research methods in education, 5th edition
London: Routledge.
Cohen, S.G and Bailey, D.E. (1997). What makes Teams work: Group Effectiveness Research
The Shop Floor to the Executive Suite, Journal of Management, Vol.23, No. 3,
pp.239-290.
Cohen, S. (1972). Folk Devils and Moral Panics. London: MacGibbon and Kee.
Consultancy Development Centre. (2006). Export promotion of consultancy and management
services from India. Ministry of Commerce and Industry Government of India New
Delhi.
Costello, A.B and Osborne, J.W. (2005). Best practices in exploratory factor analysis: Four
Recommendations for getting the most from your analysis. Practical Assessment
Research & Evaluation, Vol.10, No.7, July, 2005.
Creswell, J. W. (2005). Educational research: planning, conducting, and evaluating quantitative
and qualitative research, 2nd edition, Upper Saddle River, NJ: Prentice Hall.
Crotty, M. (1998). The foundation of social research: meaning and perspective in the research
process, Sydney: Allen and Unwin.
Crucini, C. and Kipping, M. (2001). Management consultancies as global change agents?
Evidence from Italy. Journal of Organizational Change Management, Vol. 14 No. 6, pp.
570-589.
Curtain, R. (2000). Good Public Policy Making: How Australia Fares. Agenda: a Journal of
Policy Analysis and Reform, Volume 8, No. 1, 2000, pp. 33 - 46.
Cruywagen, H and Snyman, E. (2005). Affordability of Quantity Surveying Services on
Construction Projects in South Africa. Queensland University of Technology.
The Queensland University of Technology Research Week International
Conference. Conference Proceedings. Brisbane, Australia, 4-8th July, 2005
Czander, W. (2001). A Failed Consultation. Consulting to Management 12(2), pp. 26–31.
Dana, J. (2005). Managing Commodity Price Risks: A Technical Overview, The World Bank
Commodity Risk Management Group.
Danso, F.O, Badu, E and Ahadzie, D.K. (2011). Casual Workers Preference of Occupational
Health and Safety Items on Building Construction Sites in Ghana; A Kumasi
Study. Proceedings of the WABER 2011 Conference. Reading, UK: West
Built Environment Research (WABER) Conference.
Date, H. (2009). Public Sector Knowledge Management: A Generic Framework. Public Sector
252
ICT Management Review. January-June, 2009. Vol. 3.
Davis, R; Watson, P and Man, C.L. (2007). Knowledge Management for the Quantity
Surveying Profession. Strategic Integration of Surveying Services FIG Working Week
2007 Hong Kong SAR, China 13-17 May 2007.
Davis, P.R. and Baccarini, D. (2004). “The Use of Bills of Quantities in Construction Projects–
An Australian Survey”. http://www.rics-foundation.org/publish.Assessed: 03/06/2011.
Davis, P and Baccarini, D. (2002). Bills of Quantities-A literature review, The Building
Economist, 10-17.
De Burgundy, J. (1998). Management consultancy: a modern folly? Management Decision,
Vol. 36 No. 3, pp. 204-205.
De Burgundy, J. (1995). Working daze: uncertainty and ambiguity in consulting. Management
Decision, Vol. 33 No. 8, pp. 51-55.
DeCoster, J. (1998). Overview of factor analysis. Department of Psychology, University of
Alabama.
Dehn, J. (2000). Commodity Price Uncertainty in Developing Countries. WPS/2000-12, Centre
for the Study of African Economies, University of Oxford.
De Jong, J.A. and Van Eekelen, I.M. (1999). Management Consultants: What do they do? The
Leadership and Organizational Development Journal, Vol. 20 No. 4, pp. 181-188.
Denzin, N. K and Lincoln, Y. S. (1998). Collecting and Interpreting Qualitative Materials,
London: Sage.
Department of Energy. (2011). Cost Estimating Guide. DOE G 413.3-21. U.S. Department of
Energy, Washington, D.C. 20585.
Department of Finance. (2011). Value for Money and Policy Review of the Construction
Procurement Reform Initiative, United Kingdom.
DevComm. (2005). A Toolkit for Procurement of Communication Activities in World Bank-
Financed Projects. The Development Communication Division (DevComm) External
Affairs Vice Presidency, The World Bank, 1818 H Street, N.W. Washington, D.C., 20433,
U.S.A.
DeVeries, J. (2007). About Hypothesis Testing, University of Guelph.
Dogbegah, R.K. (2009). Project Management Competency Requirements: The Case of Project
Managers on Large Construction Projects in Ghana. Master’s in Business Administration
Dissertation [Unpublished], Faculty of Business and Law, Demontfort University, (DMU)
Leicester, United Kingdom.
Dohring, B. (2008). Hedging and Invoicing Strategies to Reduce Exchange Rate Exposure: a
Euro- area perspective. Brussels: Office for Infrastructures and Logistics in Brussels.
Dolecheck, MM and Dolecheck, CC (1987). Business ethics: a comparison of attitudes of
managers in Hong Kong and the United States. The Hong Kong Manager, April/May,
pp. 38-43.
Doloi, H. (2008). Analysing the novated design and construct contract from the client’s design
team’s and contractor’s perspectives, Construction Management and Economics, Vol. 26,
pp1181- 1196.
Drake, L. and Llewellyn, D.T. (1995). The pricing of bank payments services, International
Journal of Bank Marketing, Vol. 13 No. 5, pp. 3-11.
Drucker, P.F. 1979. Why management consultants? The Evolving Science of Management,
475- 478. New York: AMA COM.
Dubinsky, A; Berkowitz, E and Rudelius, W. (1980). Ethical problems of field sale personal,
253
MSU Business Topics, Summer, pp 11 - 16.
Dwyer, F.R and Tanner, J.F. (2006). Business Marketing: Connecting Strategy, Relationship
And Learning, 3rd Edition, 1221 Avenue of the Americas, New York, NY,
10020: McGraw- Hill/Irwin.
Economic Commission for Africa. (2001). Enhancing the Competitiveness of Small and
Medium Enterprises in Africa: A Strategic Framework for Institutional Support.
Edler, J. (2010). Public Procurement of Innovation: An Introduction. Manchester institute of
Innovation Research, MBS, University of Manchester.
Eisen, M. (1999). Cluster 3.0 Manual, Stanford University 1998-99 updated in 2002 by
de Hoon, M, University of Tokyo, Human Genome Center.
Eke, T.(2006).Overview of Quantity Surveyors Role in Engineering Infrastructure Projrects.
NIQS 22nd Bienniel Conference, Calabar, Nigeria, 22nd–25th November,2006. Theme:
“Quantity Surveying in the 21st Century– Agenda for the Future.”
Elliott, D.C. (2009). UNFC, User Manuals, and Working Groups. Discussion Paper for the 6th
Session, Ad Hoc Group of Experts on Harmonization of Fossil Energy and Mineral
Resources Terminology Geneva, 25-27, March 2009.
El-Mashaleh, M.S. ( 2010). Decision to bid or not to bid: a data envelopment analysis approach,
Canadian Journal of Civil Engineering, Vol. 37, No. 1, pp. 37-44.
Elwell, C.K. (2011). Economic Recovery: Sustaining U.S Economic Growth in a Post-Crisis
Economy. Congressional Research Service.
ESCAP. (2009). Globalization of Production and the Competitiveness of Small and Medium
Sized Enterprises in Asia and the Pacific: Trends and Prospects. United
Nations Building Rajadamnern Nok Avenue, Bangkok 10200, Thailand: United Nations.
Essel, A.E. (1996). “Points to consider when pricing a product.” Virginia State University.
National Small Farm Conference, September 10-13th, 1996.
European Union.(2010). Free Movement of Goods: Guide to the Application of Treaty
Provisions Governing the free movement of goods, Luxembourg: Publications
Office of the European Union.
European Union. (2010). Risk Management in the Procurement of Innovation. Luxembourg:
Publications Office of the European Union.
Everitt, B. S. (1998). The Cambridge Dictionary of Statistics: Cambridge University Press.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C and Strahan, E. J. (1999). Evaluating the use
of exploratory factor analysis in psychological research, Psychological Methods, Vol.4,
pp. 272-299.
Farese, L, Kimbrell, G and Woloszyk, C. (1991). Marketing Essentials. 15319 Chatsworth
Street, Missions Hills, CA: Glencoe Division, Macmillan/McGraw-Hill.
FEWS NET. (2009). Adjusting Prices for Inflation and Creating Price Indices. FEWS NET
Markets Guidance, No.3.
Ferguson, R. (1978). Linear regression in geography: concepts and techniques in modern
geography, No. 15 Norwich, UK: Geo Abstract Limited.
Ferrell, O.C and Weaver, K.M. (1978). Ethical beliefs of marketing managers. Journal of
Marketing, Vol. 42, pp.69-73.
Finon, D and Perez, Y. (2008). Investment Risk Allocation in Restructured Electricity Markets.
The need for vertical arrangements. Working Paper No.12
254
Fischer, A.M and Orr, A.B. (1994). Monetary Policy Credibility and Price Uncertainty: The
New Zealand Experience of Inflation Targeting. OECD Economic Studies, No. 22
Spring 1994.
Flouris, T and Yilmaz, A.K. (2010). The Risk Management Framework to Strategic Human
Resource Management. International Research Journal of Finance and Economics, Vol.5,
pp. 237- 264.
Flyvbjerg, B, Holm, M.K.S and Buhl, S.K. (2003). How common and how large are cost
overruns in transport infrastructure projects? Transport Reviews, 2003, Vol.23,
No.1, 71-88.
Fowler, J and Floyd, J. (1995). Improving survey questions: design and evaluation, Vol.38,
Thousand Oaks: Sage Publications.
Fricker, Jr., R.D; Kulzy, W.W and Appleget, J.A. ( 2012). From Data to Information: Using
Factor Analysis with Survey. Data Naval Postgraduate School.
Froeb, L and McAfee, P. (1998). Deterring Bid Rigging in Forest Service Timber Auctions.
Economic Analysis Group Discussion Paper.
FTC. (2005). Gasoline Price Changes: The Dynamic of Supply, Demand and Competition.
Federal Trade Commission, June, 2005.
Fullerton, J. and West, M.A. (1996). Consultant and Client – Working Together? Journal of
Managerial Psychology, Vol. 11, No. 6, pp. 40 – 49.
Funnell, R. (1996). A handbook for research in adult and vocational research, Adelaide, SA:
NCVER.
Gabrenya, W.K. (2003). Inferential Statistics: Basic Concepts. In Research Skills for Psychology
Majors: Everything You Need to Know to Get Started. Version: 1.0. Available Online:
my.fit.edu/~gabrenya/IntroMethods/eBook/inferentials.pdf. [Accessed: 20th January, 2013].
Gale, B.T and Swire, D.J. (2006). Value-Based Marketing and Pricing. Customer Value Inc.
217 Lewis Wharf, Boston, MA 02110 USA.
Gall, M; Gall, J and Borg, W. (2003). Educational Research: An introduction, 7th ed. , Boston:
Allwyn and Bacon.
Gattiker, U.E. and Larwood, L. (1985). Why do clients employ management consultants?
Consultation, Summer, pp. 119-29.
Ghana Statistical Service .(2012). 2010 Population and Housing Census. Summary Report of
Final Results.
Ghemawat, P.(2006). Zara: Fast Fashion. Harvard Business Review, December 21, 2006.
GhIS .(2012). Roll of Quantity surveyors, 7th Surveyors Week and 43rd Annual General Meeting,
Infrastructure Development for Economic Growth: Get it right, use a surveyor, Accra,
Ghana , 18th-26th February, 2012.
Gill, J. and Whittle, S. (1993). Management by Panacea: Accounting for Transience. Journal of
Management Studies, Vol.30, No.2, pp.281–95.
Gilchrist, W. (1984). Statistical modeling, Chichester, Sussex, UK: John Wiley& Sons.
GIZ. (2010). Information event for consulting companies on 27 September 2010 at GIZ. Open
questions – Notes – Suggestions.
Glasow, P.A (2005). Fundamentals of Survey Research Methodology, MITRE, Washington, C 3
Center.
GNPC. (2009). Natural Gas Transportation and Processing Project; Resettlement Policy
Framework Terms of Reference. EDM/GNPC/2009.
255
Gorsuch, R. L. (1983). Factor analysis, (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
Goyal, M.L. (1991). Information Technology in Everyday Life, New Delhi: Tata McGraw Hill
Publishing Co. Ltd.
Grabel, I. (2002). Regulating Global Capital II: Capital Account Controls and Currency Taxes.
Mott Foundation and the Boell Foundation. Conference of the coalition New
Rules for Global Finance, Washington, D.C, May 23-24, 2002.
Grahame, R.D and Mark, U. (1997). Do Customer Programs Really work? Sloan Management
Review, 38(4), (1997), pp.71-82.
Gray, P and Irwin, T. (2003). Exchange Rate Risk: Allocating Exchange Rate Risk in Private
Infrastructure Projects. The World Bank Group Private Sector Development.
Gray, C. (2011). “How can you tell when there has been contribution to knowledge (in a
doctoral research study)?” Available Online:
www.supervisorsfriend.wordpress.com/2011/05/17. [Accessed: 21/10/2013].
Grehalva, R. (2004). Unleashing the Power of Consultative Selling: Selling the way your
Customer wants to buy….Not the way you like to sell: P2P People to People
Communications Media.
Greiner, L. and Metzger, R. (1983). Consulting to Management. Englewood Cliffs, NJ: Prentice-
Hall.
Grosskurth, L.K. (2008). Marketing Architectural Services: The role of the internet in Marketing
Architectural services in the Western Cape. CPUT Theses and Dissertations. Paper 11.
Master of Technology Thesis, Cape Peninsula University of Technology.
Guba, E and Lincoln, Y. (2004). Approaches to qualitative research design: a reader on theory
and practice, New York: Oxford University Press.
Gupta, P, Lamech, R, Mazhar, F and Wright, J. (2002). Mitigating Regulatory Risk for
Distribution Privatization- The World Bank Partial Risk Guarantee. Energy and Mining
Sector Board Discussion Paper Series. Paper No.5 Nov., 2000
Guo, W. (2004). Development of a Framework for preliminary risk analysis in transportation
Project. Master’s Thesis, Worcester Polytechnic Institute.
Hackett, M. and Robinson, I. (2003). Pre-Contract Practice and Contract Administration.
Oxford: The Aqua Group and Blackwell Science.
Haider, T. (2009). Financial management of Construction contracts (constructability and its
Relation with TQM, cost shifting risk and cost/benefit). International Research Journal of
Finance and Economics, ISSN 1450-2887, Issue 28(2009).
Hamilton, B. (2008). Taking the Efficiency Utility Model to the Next level. Paper presented at
the ACEEE summer study on energy efficiency in buildings, Pacific Grove, Calif.,
August 17-22, 2008.
Harris, C.(2003). Private participation in infrastructure in developing countries: Trends, impact
Policy lessons. World Bank Working Paper No.5.
Heitzmann, K, Canagarajah, R.S and Siegel, P.B.(2002). Guidelines for assessing the sources
of risk and vulnerability social protection Discussion Paper Series, No. 0218.
Helmlinger, T.A. (2005). The Essence of Centennial Campus: A Public/Private Strategic
Alliance that Responds to Corporate Core Values of Innovation. A Ph.D Dissertation,
North Carolina State University.
Hinterhuben, A and Liozu, S. (2012). Is it time to rethink your pricing strategy? MIT Sloan
School of Management Review, Vol. 5, No. 3, pp. 70-71.
256
Hillson, D.A and Hulett, D.T. (2004). Assessing Risk Probability: Alternative Approaches. 2004
PMI Global Congress Proceedings- Prague, Czech Republic.
Hoffman, K.D and Bateson, J.E.G. (1997). Essentials of services marketing, Orlando, FL.: The
Dryden Press.
Holland, R. (1998). Selling Price, Gross Margin and Mark-up determination. Agricultural
Development Center, Agricultural Extension Service, University of Tennessee.
Hovland, I. (2003). Knowledge Management and Organizational Learning: An International
Development Perspective. London: Overseas Development Institute.
Hoxley, M. (1998). The impact of competitive fee tendering on construction professional service
quality. COBRA conference , 1998.
Huang, J and Wang, J. (1997). Market Structure, Security Prices, and Informational Efficiency.
Macroeconomic Dynamics, 1, 1997, 169-205.
Huczynski, A. (1993). Explaining the Succession of Management Fads. International Journal of
Human Resource Management, Vol.4, No.2, pp.443–63.
Hun, M. P.(2010). Hypothesis Testing and Statistical Power of a Test, University Information
Technology Services, Indiana University.
IDB. (2011). Policies for the Selection and Contracting of Consultants Financed by the
Inter- American Development Bank GN-2350-9.
IFAD. (2010). Project Procurement Guidelines. 100th Session in September 2010.
IFC. (2007). Stakeholder Engagement: A Good Practice Handbook for Companies Doing
Business in Emerging Markets. Washington, D.C: IFC.
IMCA. (2010). IMCA Standards of Practice. Available Online: www.IMCA.org. [Accessed
19/12/2011].
IMP. (1982). International marketing and purchasing of industrial goods: an interaction
approach, Ring wood, Hampshire, USA: John Wiley & Sons Ltd.
Inerst, G. (2009). Pension Fund Investment in Infrastructure. OECD working Papers on
Insurance and Private pensions, No.32, OECD Publishing.
INSEAD. (2011). Consulting Club Handbook: ICC.
Ioannis, K. (2002). Product Life Cycle Management. Urban and Regional Innovation Research
Unit, Faculty of Engineering, Aristotle University of Thessaloniki.
Isaac, S and Michael, W.B. (1997). Handbook in research and evaluation: a collection of
principles, methods, and strategies useful in the planning, design and evaluation of
studies in educational and behavioural sciences, 3rd edition, San Diego: Educational and
Industrial Testing Services.
Islamic Development Bank. (2005). Guidelines for the use of consultants under Islamic
Development Bank financing.
ITS. (2010). Chi-Square and ANOVA. California State University, Los Angeles.
Jaatmaa, J. (2010). Financial Aspects of Cloud Computing Business Models. Master’s Thesis
School of Economics, Department of Business Technology, Aalto University.
Jaffee, S; Siegel, P and Andrews, C. (2008). Rapid Agricultural Supply Chain Risk
Assessment, Agriculture and Rural Development Department, The World Bank.
Jaggar, D., Ross, A; Smith, J and Love, P. (2002). Building design cost management: Blackwell
publishing.
257
Janes, A. (2011). Developing expertise and social standing in professional consulting. In: A.F.
Buono, R. Grossmann, H. Lobnig, K. Mayer (Editors), The Changing Paradigm of
Consulting: Adjusting to the Fast-Paced World, Information Age Publishing, Inc.
Charlottte, North Carolina, 2011.
Jenkins, N.(2006). “ A project management primer”. Available Online:
www.nickjenkins.net/prose/projectPrimer.pdf. [Accessed 20th June, 2013].
Jeyamathan, J and Rameezdeen, R. (2006). Skills and Competencies of Quantity Surveyors: The
case of Sri Lanka. In Customizing the Quantity Surveyor to Face Challenges in Year 2020,
Rameezdeen, R. & Seneviratne, I., ed. University of Moratuwa: Department of Building
Economics, Colombo, 26 January 2006.
JICA. (2009). Guide for Evaluation Procedures for employment of Consultants under Japanese
ODA Loans December 2009.
Jobeus, A and Martin Sikorski, M. (2000). Strategic action in the Swedish internet consulting
Industry- A study of motives behind integration. Uppsala University, Department of
Business studies.
Johnson, A.J.J. (2000). Project manager which services characteristics and skills are essential
and could it be a quantity Surveyor? Unpublished dissertation (BSc). University of
Moratuwa.
Johnston, J.W and Lebreton, J.M. (2004). History and Use of Relative Importance Indices in
Organizational Research, Organizational Research Methods, Vol. 7, pp. 238-257.
Kakabadse, N.K, Louchart, E and Andrew Kakabadse, A. (2006). Consultant’s Role: A
Qualitative Inquiry from the Consultant’s Perspective. Journal of Management
Development, 25(5) pp. 416- 500.
Kapadia-Kundu, N and Dyalchand, A. (2007). The Pachod Paisa Scale: A Numeric Response
Scale for Health and Social Sciences. Institute of Health Management, Pachod, India.
Kapila, S. (2006). Unleashing the Entrepreneurial Potential of Micro and Small Enterprises in
Kenya: Some Experiences and Directions. A Thematic Working Paper prepared For the
Commission on Legal empowerment of the poor. Presented at UNHABITAT, Nairobi,
Kenya, 28th November, 2006.
Kaplan, R.S. (2006). The Demise of Cost and Profit Centers. Management Control Systems
(MCS) Working Paper. Keel, D; Douglas, I and Coleman, M. (1994). Client value system: a scoping study. London: RICS.
Kefela, G.T. (2010). Knowledge-Based Economy and society has become a vital commodity to
Countries, International Journal of Educational Research and Technology, Vol.1, No.2,
pp. 68-75.
Keidel, A. (2007). China’s Financial Sector: Contribution to Growth and Downside risks.
Networks Financial Institute. China’s Changing Financial System: Can it Catch up with or
even drive economic growth? Conference, Indiana State University, January 25, 2007.
Kieser, A. (1997). Rhetoric and Myth in Management Fashion. Organization, Vol.4, No.1,
pp.49–74.
KIPPRA. (2010). A comprehensive study and analysis on energy consumption patterns in
Kenya. Final Report Nairobi, Kenya.
258
Kiriga, J.M; Sambo, L.G; Aldis, W and Mwabu, G. (2002). The burden of natural and
Technological disaster-related mortality on gross domestic product (GDP) in the WHO
Africa Region, African Journal of Health Sciences, Vol. 9, No. 3-4, July-December,
2002.
Kish, L. (1965). Survey Sampling, New York, NY: John Wiley & Sons, Inc.
Kitay, J and Wright, C. (2004).Take the Money and Run? Organizational Boundaries and
Consultants’ Roles. The Service Industries Journal, Vol.24, No.3, pp.1–18.
Klenter, G. and Möllgard, N. (2006). Selection and Evaluation of Consultants. Mering: Hampp.
Kochanski, G. (2005). Confidence Intervals and Hypothesis Testing, http://kochanski.org/gpk.
[ Accessed 6th August, 2013].
Kodikara, G.W., Thorpe, A and McCaffer,R. (1993). The use of Bills of Quantities in building
Contractor Organisations, Construction Management and Economics, Vol. 11, No.4,
pp.261-269.
Koomey, J.G; Belady, C; Patterson, M; Santos, A and Lange, K.D. (2009). Assessing trends
over time in performance, costs and energy use for servers. Final Report to Microsoft
Corporation and Intel Corporation.
Kojima, M.(2009). Changes in End-user petroleum product prices. A Joint service of the World
Bank and IFC. Extractive industries and development series2, February, 2009.
Kolawole, E.B. (2001). Tests and measurement, Ado- Ekiti: Yemi Printing Services.
Kosar, K.R. (2011). The Quasi-Government: Hybrid organizations with both government and
Private sector legal characteristics. Congressional Research Service.
Kraemer, K.L. (Ed.) (1991). The Information Systems Research Challenge: Survey Research
Methods (Vol. 3), Harvard Business School, Boston, MA.
Krathwohl, D. (2004). Methods in educational and social research: an integrated approach, 2nd
edition, Illinois, USA: Waveland Press.
Kreydieh, A. (1996). Risk management in BOT project financing. Master’s Thesis.
Massachusetts Institute of Technology.
Kubr, M. (1996). Management consulting: A guide to the profession. International Labour
Office, Geneva. Langeard, E. (2000). Specificity of the Pricing Policy in Service Activities, Innovations and
Perspectives, In: The International Research Seminar in Service Management, Le Londe Les
Maures, June, pp.243-256. Larsson, M. (2007). Services Producer Price Indices for Business and Management Consultancy
activities. SPPI Report No. 25, Service Producer Price Indices, Price Statistic Unit,
Statistics Sweden, November, 2007.
Laryea, S and Hughes, W. (2011). Negotiating access into firms: obstacles and strategies, 6th
Nordic Conference on Construction Economics and Organization, 13-16th April, 2011,
Copenhagen, Denmark.
Leamer, E.E. (1995). The Heckscher-Ohlin Model in Theory and practice. Priceton Studies
International Finance, No.77, February 1995.
Leedy, P.D and Ormrod, J.E. (2005). Practical research: planning and design, 8th ed., New
Jersey: Pearson Prentice Hall.
Lee, H.L, Padmanabhan, V and Whang, S.91997). The Bullwhip effect in supply chains. Sloan
Management Review, Spring 1997, Vol. 38, Iss. 3, pp.93-102.
Levine, J. H. (1996). Introduction to data analysis: the rules of evidence, Department of
Mathematical Social Sciences, Dartmouth College.
259
Levy, P.S and Lemeshow, S. (1999). Sampling of populations: methods and applications, 3rd
edition, New York: John Wiley & Sons.
Lewis, B. (2011). Visionary Marketing . Leadership Forum Report. Vol. 3, No.8, August, 2011.
Lewis, R.C and Shoemaker, S.(1997). Price-Sensitivity measurement: A tool for the hospitality
Industry. Cornell Hotel and Restaurant Administration Quarterly, Vol. 38, April, pp. 44-7.
Liang, B.A. (2008). A Dose of Reality: Promoting Access to Pharmaceuticals, Intellectual
Property Law Journal, Vol. 8 No.3.
Likosky, M. (2009). Contracting and regulatory issues in the oil and gas metallic minerals
Industries. Transnational Corporations, Vol.18, No.1 (April 2009).
Lippitt, G. and Lippitt, R. (1986). The consulting process in action (2nd ed.), San Diego, CA:
Pfeiffer & Company.
Lister, E.D. and Pirrotta, S. (1996). The Art and Science of Using Consultants, Physician
Executive Vol. 22, No.11, pp. 29-33.
Lovelock, C.H. (1996). Services marketing, 3rd ed., Englewood Cliffs, NJ: Prentice-Hall
Lundberg, C.C. and Young, C.A. (2001). A note on emotions and consultancy, Journal of
Organizational Change, Vol. 14, No. 6, pp. 530-538.
Lynden, G.W.J.V. (2008). Guidelines for the assessment of soil degradation in Central and
Eastern Europe. FAO and ISRIC Report 97/08b (Revised edition).
Malhotra, Y. (2005). Integrating knowledge management technologies in organizational
Business process: getting real time enterprises to deliver real business Performance,
Journal of Knowledge management, Vol.9, No.1, pp.7-28.
Malkiel, B.G. (2003). The efficient market hypothesis and its critics. CEPS working Paper
No.91, Princeton University.
McAfee, R.P. (2008). “Price discrimination.” California Institute of Technology. Available
Online: www.mcafee.cc/Papers/PDF/ABAPriceDiscrimination.pdf. [Accessed 20th
October, 2012].
Mccue, D and Belsky, E.S. (2007). Why do house prices fall? Perspectives on the historical
Drivers of large nominal house price declines. Joint Center for housing studies, Harvard
University.
McDonald, GM and Zepp, R.A. (1988). Ethical perceptions of Hong Kong Chinese business
managers. Journal of Business Ethics, Vol. 8, pp.835-845.
McGaw, H. (2007). Marketing of the Quantity Surveying Profession in Australia. A Paper
nominated by the Australian Institute of Quantity Surveyors in 2007 for the Kenneth K.
Humphreys Award Competition.
McIntyre, L.J. (1999). The practical skeptic core concepts in sociology, Mountain View, CA:
Mayfield Publication.
McTaggart, J.M and Kontes, P.W. (1993). The governing objective: Shareholders versus
Stakeholders. 1-3 Strand London WC2N 5HP United Kingdom.
Meidan, A. (1996). Marketing financial services, London: Macmillan Business Press.
Meijerink, G and Roza, P. (2007). “The role of agriculture in economic development.” Markets,
Chains and sustainable development strategy policy paper No. 4. Available Online:
http://www.boci.wur.nl/UK/Publications/ [Accessed 30th November, 2012].
Meissner, J. and Strauss, A.K. (2010). Improved bid prices for choice-based network revenue
Management. Department of Management Science, Lancaster University Management
School.
260
Menard, S. (2004). Six Approaches to Calculating Standardized Logistic Regression
Coefficients, The American Statistician, Vol. 58, pp 219-223.
Meyer, K.E. (2009). Corporate Strategies under Pressures of Globalization: Initiating a
Forward-looking Debate, University of Bath, School of Management, Working Paper
Series.
Micco, A and Perez, N. (2002). Determinants of maritime transport cost. Inter-American
Development Bank. Research Department Working Paper Series 441.
Miller, J.E. (2004). The Chicago Guide to Writing about Numbers, Chicago: University of
Chicago Press.
Mills, G.T. (1996). The impact of inflation on capital budgeting and working capital. Journal
of Financial and Strategic Decisions, Vol.9 No.1, Spring 1996.
Moavenzadeh, F and Rossow, J.A.K. (1976). The Construction Industry in Developing
Countries. Technology Adaptation Program, Massachusetts Institute of Technology.
Molloy, J.B. (2001). Destroying the Purpose of Bills of Quantities, HKIS Newsletter, Vol. 10,
No.8, Sept 2001.
Morduch, J and Haley, B. (2002). Analysis of the effects of microfinance on poverty reduction
NYU Wagner Working Paper No. 1014, issued June 28, 2002.
Morrison, J, Morikawa, M, Murphy, M and Schulte, P.(2009). Water scarcity and climate
Change: Growing risks for business and investors. The Pacific Institute. A Ceres Report,
February, 2009.
Morrison, W.M and Labonte, M. (2008). China’s currency: Economic issues and options
For U.S trade policy. CRS Report Prepared for Members of Congress, USA.
Mungofa, M.F. (2009). Supply chain resilience. Master’s Thesis, Turku School of Economics,
Tilburg University.
Murray, M., Nkado, R and Lai, A. (2001). The Integrated Use of Information Technology
In the Construction Industry. Proceedings of CIB 78 conference: IT in Construction in
Africa, Pretoria, South Africa.
Musa, N.A, Oyebisi, T.O and Babalola, M.O. (2010). A Study of the Impact of Information and
Communication Technology (ICT) on the Quality of Quantity Surveying Services in
Nigeria, The Electronic Journal on Information Systems in Countries, Vol.42, No. 7,
pp.1-9.
Musa, N.A.; Oyebisi, T.O and Babalola, M.O. (2010). A Study of the Impact of Information and
Communications Technology (ICT) on the Quality of Quantity Surveying Services in
Nigeria. EJISDC (2010) 42, 7, 1-9.
Naarmala and Tuomi, V. (2006). Product Oriented Thinking and Expert Knowledge
In Consulting Services. University of Vaasa.
Nagy, A, Elias, J and Podolny, J. (2006). Defining Success Was Both the Change and the
Opportunity. Yale Case, 06-017, November 17, 2006.
Nair, G and Yescombe, E.R. (2008). Financing Ghana’s infrastructure needs: A public-private
Partnership/private finance approach. National PPP/PFI workshop, November, 21-22,
2008.
Nees, D. B. and L. E. Greiner. 1985. Seeing Behind the Look-Alike Management Consultants.
Organizational Dynamics, Vol.13, pp. 68-79.
Newstom, J.W and Ruch, W. A. (1975). The ethics of management and the management of
ethics. MSU Business Topics, Winter, pp. 29-37.
Nippa, M.C and Petzold, K. (2002). Economic functions of management consulting firms – an
261
integrative theoretical framework. Freiberg University of Technology and Mining
D-09596 Freiberg, Germany.
Nkado, R. (2001).Competencies of a professional Quantity Surveyor: A South African
perspective, Construction Management and Economics, Vol. 19, pp.481-491.
NPA. (2007). Consulting Services Manual. National Procurement Agency, Democratic Socialist
Republic of Sri Lanka.
Nwokeji, G.U. (2007). The Nigerian National petroleum corporation and the development of
The Nigerian oil and gas industry: History, strategy and current directions. A Research
paper, The Joint Baker Institute/Japan Petroleum Energy Center Policy Report.
Obolensky, N. (2001). Management Consultancy: A Handbook for Best Practice, 2nd edition,
London: Kogan Page.
Odeyinka, H.A.(2006). The Role of the Quantity Surveyor in Value Management. NIQS 22nd
Bienniel Conference, Calabar, Nigeria, 22nd–25th November, 2006. Theme: “Quantity
Surveying in the 21st Century – Agenda for the Future.”
OECD. (2000). “The Service Economy.” Business and Industry Policy Forum Series. Available
Online: www.oecd.org/industry/ind/2090561.pdf. [Accessed 2nd Novenber, 2012]
Oforeh, E.C. (2006). The Nigerian Institute of Quantity Surveyors as an agent of Economic
Development. Nigerian Institute of Quantity Surveyors. 22nd Biennial Conference of
Nigerian Institute of Quantity Surveyors, Calabar, Nigeria,
Ofori, G. (2012). Developing the Construction Industry in Ghana: the case for a central agency.
A concept paper prepared for improving the construction industry in Ghana. National
University of Singapore.
OFT. (2008). Unfair contract terms guidance. Guidance for the unfair terms in consumer
Contracts regulations 1999, Iss. No. 2, 22-25th November, 2006.
OGC. (2006). Consultancy Value Programme. UK Office of Government Commerce, 1 Horse
Guards Road, London SW1A 2HQ.
Ogechukwu, A.D, Latinwo, H.K. (2010). Entrepreneurial development and small scale industry
Contribution to Nigerian national development- A marketing interface, Information
Management and Business Review, Vol.1, No.2, pp.51-68.
Ogunsemi, D.R and Saka, N. (2006). The NEPAD Initiative and the Challenge of Efficient
Cost Management of Infrastructure Development in Nigeria. Nigeria Institute of Quantity
Surveyors. 22nd Biennial Conference of Nigerian Institute of Quantity Surveyors, Calabar,
Nigeria, 22-25th, November, 2006.
O’Keefe, D.J.(1991). Persuasion theory and research, Newbury Park, CA: Sage Publication.
Oladapo, A.A. (2006). The Impact of ICT on Professional Practice in the Nigerian Construction
Industry, The Electronic Journal on Information Systems in Developing Countries, Vol.
24, No. 2, pp.1-19.
Olatunde, J. (2006). New Opportunities for Quantity Surveyors in Nigeria Business
Environment. NIQS 22nd Bienniel Conference, Calabar, Nigeria, 22nd–25th November,
2006. Theme: “Quantity Surveying in the 21st Century – Agenda for the Future.”
Olatunji, O. A., Sher, W and Gu, N. (2009). Building Information Modeling and Quantity
Surveying Practice, Emirates Journal for Engineering Research, Vol.15, No.1,
Olatunji, O. A. (2007). Conflict of Interest within Construction Practitioners: Quantity
Surveying, Case Study, Surveying and Built Environment, Vol 18, No.1pp. 35-50.
262
Olatunji, O.A, Aje, I.O and Ogunsemi, D.R. (2006).An Overview of Ethical Imbalance in the
Construction Industry. Accepted for presentation and publication at the International
Seminar on Civil and Infrastructure Engineering (ISCIE 06), 13-14 June 2006. Universiti
Teknologi Mara, Shah Alam, Malaysia.
Olawale A.(2006). The Quantity Surveyor in Highway Development. NIQS 22nd Bienniel
Conference, Calabar, Nigeria, 22nd–25th November,2006. Theme: “Quantity Surveying
in the 21st Century – Agenda for the Future.”
Opoku-Afriyie, K.J. (2007). Elements of Economics. KNUST, Kumasi: Faculty of Distance
Learning.
Ormerod, R.J. (1997). The design of organizational intervention: choosing an approach.
Omega, Vol. 25 No. 4, pp. 415-435.
Osei-Hwedie, M. (2010). Strategic Issues of Innovative Financing Of Infrastructure Project
Delivery. MSc Dissertation [Unpublished], Department of Building Technology, KNUST,
Ghana.
O’Shea. J. and Madigan, C. (1997). Dangerous Company: the consulting powerhouses and the
businesses they save and ruin, New York: Random House.
Othoman, A.A.E, Hassan, T.M and Pasquire, C.L. (2005). Analysis of factors that drive brief
Development in construction, Engineering, Construction and Architectural Management,
Vol.12, No.1, 2005, pp.69-87.
Otu-Nyarko, D. (2010). Corporate Social Responsibility: The Perspective of the Ghanaian
Construction Industry. EMBA Dissertation [Unpublished]. IDL, KNUST, Kumasi.
Owusu-Afriyie, E. (2009). An Assessment of the Impact of Tax Reforms on the Tax System of
Ghana. A Bank of Ghana Working Paper Series.
Owusu-Manu, D., Badu, E., Edwards, D.J., Adesi, M and Holt, G.D. (2012). Conceptualisationof
the consultancy pricing paradox, Structural Survey, Vol. 30 Iss: 4 pp. 357 – 378.
Owusu-Manu, D. (2008). Equipment Investment Finance Strategy for Large Construction Firms
in Ghana, PhD Dissertation submitted to the Department of Building Technology, Kwame
Nkrumah University of Science and Technology, Kumasi- Ghana.
Oyegoke, A.S. (2006). Managing clients expectations in project delivery: a comparative study of
delivery systems. Nigerian Institute of Quantity Surveyors. 22nd Biennial Conference of
Nigerian Institute of Quantity Surveyors, Calabar, Nigeria 22-25th November, 2006.
Page, M., Pearson, S. and Pryke, S. (2004). Innovative and Current Practice in Large UK
Quantity Surveying firms, RICS Foundation Research Paper Series, Vol.4, No.25.
Palmer, K. (2000). Contract issues and Financing in PPP/PFI (Do we need the ‘F’ in DBFO
projects), UK: Institute for Public Policy Research (IPPR) Commission of Public Private
Partnerships.
Palmer, A. (1994). Principles of services marketing, London: McGraw-Hill.
Panayotou, T, Peterson, A and Sachs, J. (2000). Is the Environmental Kuznets Curve Driven by
Structural Change? What Extended Time Series May Imply for Developing Countries.
CAER II Discussion Paper No. 80 August 2000.
Papaioannou, M.G. (2006). Exchange rate risk measurement: Issues and approaches for firms,
South-Eastern Europe Journal of Economics, 2006, pp. 129-146.
Papulová, Z and Mokroš, M. (2007). Importance of managerial skills and knowledge in
management for small entrepreneurs. Department of Strategy and Entrepreneurship Faculty
of Management, Comenius University, Bratislava, Slovakia.
263
Paroush, J. (1985). Notes on Partnerships in the Service Sector. Journal of Economic Behavior
and Organization, No. 6, pp.79-87.
Patsula, P.J. (2007). The Entrepreneur’s Guidebook: Patsula Media. Available Online:
www.smbtn.com/books/gb46.pdf [Accessed 13th November, 2012].
Payne, A. (1993). The essence of services marketing, London: Prentice-Hall.
Peansupap, V. (2004). An Exploratory Approach to the Diffusion of ICT in a Project
Environment, Thesis submitted to School of Property, Construction and Project
Management RMIT University.
Perreault, W.D.J and McCarthy, E.J. (2002). Basic Marketing: A Global-Managerial Approach,
1221 Avenue of Americas, New York, NY 10020: McGraw-Hill/Irwin.
Perry, N. (1987). A Consulting firm too hot to handle? Fortune, Vol. 27, pp.91–98.
Piermartini, R and Teh, R. (2005). Demystifying modeling methods for trade policy, Geneva,
Switzerland: WTO Publications.
Pinault, L. (2000). Consulting Demons: Inside the Unscrupulous World of Global Corporate
Consulting. New York: Harper Business.
Pilsbury, S and Meaney, A. (2009). Are horizontal mergers and vertical integration a
problem? Analysis of the rail freight market in Europe. Discussion Paper No. 2009-4 for
the Round Table of 5-6 February 2009 on Vertical Relations between Transport and
Logistics Businesses.
Pirog, R. (2005). World oil demand and its effect on oil prices. CRS Report for US Congress.
Available Online: www.fas.org/sgp/crs/misc/RL32530.pdf [Accessed 17th July 2013].
Pissas, N. (2007). Corruption in the procurement process/outsourcing government functions:
Issues, case studies, implications. Report to Institute of Fraud Prevention, Northeastern
University, Boston.
Pittinsky, T.L and Poon, B. (2005). Upward Advice Transmission to Leaders in Organizations:
Review and Conceptual Analysis. RWP05-007, Faculty Research Working Papers Series,
John F. Kennedy School of Government, Harvard University.
Pontiskoski, E. (2009). Business markets and business buyer behavior. Helsinki School of
Economics
Porter, M.E. (2008).The Five Competitive Forces That Shape Strategy, Harvard Business
Review, January 2008.
PPB. (2003). Consultant Services Complex Time-Based Assignments Large Lump-Sum
Assignments. Public Procurement Board, Accra, Ghana.
Pricewaterhousecopers. (2008). A Quick Guide to Taxation in Ghana. 2008 Facts and Figures.
Pringle, E. (1998). Do Proprietary Tools Lead to Cookie Cutter Consulting? Journal of
Management Consulting, Vol.10, No.1, pp.3–7.
Productivity Commission. (2008). Review of Australia’s Consumer Policy Framework. Locked
Bag 2 Collins Street East Melbourne VIC 8003: Productivity Commission.
Rahim, F.A; Abd-Rahman, H; Wang, C; Othman, N.D and Zainon, N. (2013). Quantity
Surveying Firms Survival of Fast Developing Economy, Journal of Surveying,
Construction & Property Vol.4 Iss. 1, pp. 2.
Rajneesh, S and Kent, B.M. (2003). The effects of time constraints on consumers’ judgments
of prices and products, Journal of Consumer Research Inc., Vol.30, June 2003
Ramamurti, R and Doh, J.P. (2003). Reassessing risk in developing country infrastructure, Long
Range Planning, Vol. 3, pp. 6337-353.
264
Ramirez, R. (1999). Value co-production: intellectual origins and implications for practice and
research, Strategic Management Journal, Vol. 20, pp. 49-65.
RAMP. (1998). Risk Analysis and Management for Projects, London: Thomas Telford.
Rappaport, A. (2005). The economics of short-term performance obsession. Financial Analysts
Journal, Vol. 61, No.3.
Rashid, R.A; Mustapa, M and Wahid. S.N.A. (2006). Bills of Quantities – Are they Still Useful
and Relevant Today? Paper presented at International Conference on Construction
Industry, Padang, Indonesia, 21st June – 25th June 2006.
Reguant, M. (2011). The welfare effects of complementary bidding mechanisms: An empirical
Analysis of the Spanish wholesale electricity market. MIT Job market paper.
Rich, P. (2011). Leadership Forum Report. Vol. 3 No. 8, August, 2011, Rothstein, Kaas and
Company.
Robert, M.G. (2001). The resource-based theory of competitive advantage: Implications for
Strategy formation, California Management Review, vol.4, No. 9, pp.34-71.
Roberts, M.J, Xu, D.Y, Fan, X and Zhang, S. (2011). Demand, cost and profitability across
Chinese exporting firms. The Pennsylvania State University and NBER.
Robinson, K. (2007). Fighting Inflation. A Master’s Thesis, University of Central Missouri.
Rodin-Brown, E. (2008). Integrated financial management information systems. A practical
Guide prepared for USAID.
Rodriguez-Rodriguez, O.M. (2008). Firms as credit suppliers: an empirical study of Spanish
Firms, International Journal of Managerial Finance, Vol. 4, No. 2, pp.152-173.
Romer, C.D and Romer, D.H. (2007). The macroeconomic effects of fiscal shocks. Department
of Economics, University of California, Berkeley.
Royal Institution of Chartered Surveyors (RICS). (1991). Market Requirements of the
Profession. London: RICS.
Rummler, G and Morrill, K. (2004). Know Your Client’s Business. Performance Improvement,
Vol. 43 No. 3.
Ryan, P. (2004). Introduction, Basics, Descriptive Statistics, University of Adelaide
Rynning, M. (1992). Successful consulting with small and medium-sized versus large
clients: meeting the needs of the client? International Business Journal, Vol. 11 No. 1,
pp. 47-60.
SACQSP. (2010). 2010 Tariff of Professional Fees by the South African Council for the
Quantity surveying profession. Available Online:
www.sacqsp.org.za/resource/collection/.../SACQSP_Feescale_2010.pdf. [Accessed 30th
June 2013].
SADC and ZRA. (2006). Integrated Water Resources Management Strategy for the Zambezi
River Basin. Inception Report, Phase 1. SADC-WD/Zambezi River Authority. SIDA,
DANIDA, Norwegian Embassy Lusaka, November 2006.
Salant, P and Dillman, D.A. (1994). How to conduct your own survey, New York: John Wiley &
Sons.
Saleh, S. A. S. (2008). Factors Affecting the Performance of Construction Projects in the Gaza
Strip. MSc Master’s Dissertation[Unpublished], Faculty of Engineering
ConstructionManagement, The Islamic University- Gaza.
Samuels, K. (2006). Rule of law reform in post-conflict countries: Operational initiatives and
Lessons learnt. Social development papers, paper No.37/October 2006.
265
Sanche, R and Lonergan, K. (2006). Variable Reduction for Predictive Modeling with
Clustering, Casualty Actuarial Society Forum, Winter, 2006.
Santomero, A.M. (1997). Commercial bank risk management: an analysis of the process. The
Wharton School, University of Pennsylvania.
Sarantakos, S. (2005). Social Research, 3rd ed, Melbourne, Victoria: Palgrave Macmillan.
Schaffer, R.H. (2002). High-Impact Consulting: How Clients and Consultants Can Work
Together to Achieve Extraordinary Results. San Francisco, CA: Jossey-Bass
Scheaffer, R. L.(1999). Categorical Data Analysis, NCSSM Statistics Leadership Institute,
July, 1999.
Schein, E.H. (1997). The concept of “client” from a process consultation perspective: A guide
for change agents. Journal of Organizational Change Management, Vol. 10 No. 3, pp.
202-216.
Schein, E.H. (1990). Process consultation,: its role in organizational development, Volume I
Reading, MA: Addison-Wesley.
Schnepf, R. (2006). Price determination in agriculture commodity markets: A primer. CRS
Report for Congress.
Seeley, I.H. (1997). Quantity Surveying Practice (Second Edition). London: Macmillan Press
Ltd.
Seidl, D and Mohe, M. (2007). The Consultant-Client Relationship: A Systems-Theoretical
Perspective. Discussion paper 2007- 06, Munich School of Management, University of
Shapiro, E. (1996). Fad Surfing in the Boardroom: Managing in the Age of Instant Answers.
Reading, MA: Addison-Wesley.
Shenson, H.L. (1990). How to select and manage consultants. Lexington Books, Lexington, MA.
Siegel, A.F. (1988). Statistics and data analysis, New York : John Wiley & Sons Inc.
Simon, H. A. (1976). Administrative Behavior. 3rd Ed. New York: Macmillan.
Munich.
Sinkin, J and Putney, T. (2011). Leadership Forum Report, Vol. 3, No 8, August, 2011
Accounting Transition Advisors.
Skees, J.R., Hazel, P and Miranda, M. (1999). New Approaches to Public/ Private Crop Yield
Insurance. EPTD Discussion Paper No.5. International Food Policy Research Institute,
Washington D.C.
Smith, M. (2009). Contingency: ‘Use and Misuse’. CMS ‘White paper series.’
Smith, P. (2004). Trends in the Australian quantity surveying profession: 1995 – 2003.
International Cost Engineering Council 4th World Congress, Cape Town South Africa.
Smith, M. (2002). What client employees say about consultants? Leadership & Organization
Development Journal, Vol. 23 No. 2, pp. 93-103.
Smith, V.L. (2000). Bargaining and Market Behavior: Essays in Experimental Economics.
The Edinburgh Building, Cambridge CB2 2RU, UK: Cambridge University
Press.
Snyman, E. (2004). Affordability of quantity surveying services on construction projects in
South Africa. Unpublished MSc (Real estate) dissertation, Department of Construction
Economics, University of Pretoria.
Soofi, E.S., J.J. Retzer and M. Yasai-Ardekani. (2000). A Framework for Measuring the
Importance of Variables with Applications to Management Research and Decision
Models, Decision Sciences, Vol. 31, pp. 595-625.
266
Sorge, A. and van Witteloostuijn, A. (2004). The (Non) sense of Organizational Change: An
Essai about Universal Management Hypes, Sick Consultancy Metaphors, and Healthy
Organization Theories. Organization Studies, Vol. 25, No.7, pp. 1205–1231.
Stanford, J. (2008). A “How-To” Guide: Understanding and Measuring Inflation. Canadian
Centre for Policy Alternatives.
Steele, F. (1975). Consulting for Organizational Change, Amherst, MA: University of
Massachusetts Press.
Stevenson, R.A and Bear, R.M. (1970). Commodity features: Trends or random walks?
Journal of Finance, Vol.25, Iss. 1, pp.65-81.
Steven A. Cohen, S.A. (2010). Hypothesis Testing, the Role of Chance, Common Statistical
Tests, OCW Epidemiology and Biostatistics, 2010, Tufts University School of Medicine.
Stinchcombe, A. L. (1965). Social Structure and Organizations, in J. G. March, ed, Handbook of
Organizations, Chicago: Rand McNally.
Strader, T.J and Shaw, M.J. (1998). Electronic markets: Impact and implications. Department
of Management, Iowa State University, Ames, IA, USA.
Stumpf, S.A. and Longman, R.A. (2000). The ultimate consultant: building long term,
exceptional value client relationship. Career Development International, Vol. 5 No. 3, pp.
124-134.
Stumpf, S.A. and Tymon, Jr, W.G. (2001). Consultant or entrepreneur? Demystifying the “war
for talent. Career Development International, Vol. 6 No. 1, pp. 48-55.
Suomi, E. (2008). The Link between HR Professionals and HR Consultants – A Study on Value
adding HR Professionals at HUS and Outokumpu. Master’s Thesis, Helsinki School of
Economics.
Swanson, M and Guttman, B. (1996). Generally accepted principles and practices for securing
Information Technology systems. NIST, Technology Administration. US Department of
Commerce.
Sykes, A.O. (2000). An Introduction to Regression Analysis, The Inaugural Coase Lecture,
Chicago Working Paper in Law & Economics.
Tang, W; Qiang, M; Duffield, C.F; Young, D.M and Lu, Y. (2008). Incentives in the Chinese
Construction Industry, Journal of Construction Engineering and Management, Vol. 134,
No. 7, pp. 457–467.
Taylor, M. (2011). Basis risk and (cross) Hedging. Ag Lenders Conference, Manhattan,
October 13, 2011.
Tebbs, J.M. (2006). Introduction to Descriptive Statistics, Department of Statistics, University of
South Carolina.
Teece, D.J, Pisano, G and shuen, A. (1997). Dynamic capabilities and strategic management,
Strategic Management Journal, Vol.18, No. 7, pp. 509-533.
The Fees Bureau. (2011). Quantity Surveyors Fees: A Survey of Fees Charged by Professional
Quantity Surveying Practices. Southdown House Ford, Arundel West Sussex BN18 0DE:
Mirza and Nacey Research Ltd.
The South African Council for the Quantity Surveying Profession. (2010). Amendment of Tariff
of Professional Fees Quantity Surveying Profession Act, 2000 (Act 49 of 2000).
The World Bank. (2002). Consulting Services Manual: A Comprehensive Guide to
Selection of Consultants. 1818 H Street, N.W. Washington, D.C. 20433, USA: USA
Thompson, B. (2005). The loyalty connection: Secrets to customer retention and increased
Profits. Customer Think Corporation.
267
Tommie, L.S, Sharon, P.K, Audrey, L.M, Marcia, W.J and John, C.M. (2008). Conducting
Local market research. Agricultural Marketing Resource Center, Iowa State University.
Touwen, A. (2001). Handbook for Projects: Development management and Fundraising.
International Federation of University Women.
Treacy, M and Wiersema, F. (1992). Customer information and other value disciplines.
Harvard Business Review, January- February 1993.
TRF. (2011). Guidelines for Procurement of Consultancy Services. Public Procurement
Regulatory Authority, Islamabad.
Trostle, R. (2008). Global agricultural supply and demand: Factors contributing to the recent
Increase in food commodity prices. Economic Research Service/USDA.
Tseng, Y, Yue, W.L and Taylor, M.A. (2005). The role of transportation in logistics chain.
Proceedings of the Eastern Asia Society for Transportation Studies, Vol.5, pp. 1657-1672.
Turner, A.N. (1988). Guiding managers to improve their own performance, Journal of
Management Consulting, Vol. 4 No. 4, pp. 8-12.
Turner, A.N. (1982).Consulting is more than giving advice, Harvard Business Review,
September/October, pp. 120-9.
Underwood, A. J. (1997). Experiments in ecology: their logical design and interpretation
using analysis of variance, Cambridge: Cambridge University Press.
UN.(2009). Making Data Meaningful Part 2: A guide to presenting statistics, United Nations
Economic Commission for Europe, CE/CES/STAT/NONE/2009/3. Available online:
www.unece.org/stats/documents/writing/MDM_Part2_English.pdf [Accessed 15th August,
2013].
UNCTAD. (2008). Cocoa study: Industry structures and competition study. Prepared by
The UNCTAD Secretariat UNCTAD/COM/2008/1. United Nations, New York and
Geneva, 2008
UNEP. (2004). Financial risk management instruments for renewable energy projects, Oxford,
UK: United Nations Publications.
UNEP. (2006). Assessment of Financial Risk Management Instruments for Re Projects in
Developing Countries. 1st Ed. UNEP/GEF Project. Available Online:
www.unep.org/pdf/75_Risk_Management_Study.pdf. [Accessed 14th December, 2012].
UN-HABITAT.(2009). Ghana: Accra Urban Profile, Nairobi, Kenya: UNON, Publishing
Services Section.
van Rijn, J. (2005). Procurement in the Construction Industry, INDEVELOPMENT, Edition
2005.
Varalakshmi, V; Sundaram, G.G; Indrani, B; Suseela, N and Ezhilarasi, S. (2005). Statistics,
Higher Secondary, Tamilnadu Textbook Corporation College Road, Chennai- 600 006
Vogl, A.J. (1999). Consultants in their clients’ eyes. Across the Board, September, pp. 26-32.
Wadsworth, Y. (1997). Do it yourself social research, 2nd edition, Sydney: Allen and Unwin.
Wahab, A.B and Lawal, A.F. (2011). An evaluation of waste control measures in construction
industry in Nigeria, African Journal of Environmental Science and Technology, Vol. 5(3),
pp.246-254.
Wainwright, W.H. and Whitrod, R.J.(1980). Measurement of Building Work, London:
Hutchinson and Co.
Ward, K. (1994). Financial Aspects of Marketing. Linacre House, Jordan Hill, Oxford OX2
8DP, UK: Butterworth-Heinemann Ltd.
268
Washburn, S.A, Scanlan, J and Shays, M.E. (2002). How to Hire a Management Consultant and
Get the Results You Expect. Institute of Management Consultants, USA.
Weber, R. (2004). The rhetoric of positivism versus interpretivism: a personal view, MIS
Quarterly, Vol. 28, No. 1, pp. 3-12.
Weller, J. (2001). Economic reforms, growth and employment: labour markets in Latin America
and the Caribbean, Chile, Santiago: ECLAC
Werr, A., Stjernberg, T., and Docherty, P. (1997).The functions of methods of change in
management consulting. Journal of Organizational Change Management, Vol. 10 No. 4,
pp. 288-307.
Westland, J. (2007).The Project Management Life Cycle.AEW Services, Vancouver, BC.
Westcott, A. J and Burnside, K. (2003). “Education for competency in construction economics
and management”, The Quantity Surveyor, Vol. 43 No. 2, pp. 33.
WHO. (2003). Social discriminants of health: The solid facts. 2nd Edition, Copenhagen,
Denmark: WHO Publications.
Wideman, R.M. (1987). Project Management of Capital Projects: An Overview. A paper
presented in Calcutta, January 1987, to the First Engineering Congress, The Institution of
Engineers, India.
Wilding, R. (2007). The mitigation of supply chain risk. Inside Supply Management, Vol.18,
Williams, B; Brown, T and Onsman, A. (2012). Exploratory factor analysis: A five-step guide
for novices, Australasian Journal of Paramedicine, Vol. 8, Iss.3.
Williams, R. (2003). ‘Consultobabble’ and the client-consultant relationship. Managerial
Auditing Journal, Vol. 18 No. 2 pp. 134-139.
Willis, C.J., Ashworth, A. and Willis, J.A. (2002). Willis’s Practice and Procedure for the
Quantity Surveyor, 11th
Ed. London: Blackwell Science.
Wilen, J and Abbott, J.(2006). An Assessment of Ecotrust’s Relative Importance
Indicators: Comparisons with Logbook Data for the Market Squid Fishery, Report
submitted to the California Marine Life Protection Act Initiative In partial fulfillment of
Contract #2006- 0014M No.8, August 2007, pp12-13.
Wind, Y. (1981). Marketing and the other business functions. Research in Marketing, Vol.9,
No.1, pp.7-28.
Witt, M and Lautenbacher, U. (2003). Institutional Strengthening of the Tax System in Ghana.
Dag-Hammarskjold-Weg 1-5 65760 Eschborn, Germany: Deutsche Gesellschaft Fur
Technische
Wittreich, H.F. (1966). How to buy / sell professional services. Harvard Business Review,
March-April, pp. 127-138.
Wooldridge, A. (1997).Trimming the Fat: A Survey of Management Consultancy. The
Economist, Vol. 22, pp.1–22.
Woodruff, H. (1995). Services marketing, London: Pitman Publishing.
World Bank. (2002). Consulting Services Manual: A Comprehensive Guide to Selection of
Consultants. 1818 H Street, N.W. Washington D.C. 20433, USA: Office of the Publisher
World Bank.
World Bank. (1998). Public Expenditure Handbook, Washington, D.C: The World Bank
WTO. (2004). “Canada-Measures relating to exports of wheat and treatment of imported grain.”
Reports of the Panel. WT/DS276/R. Available Online:
www.wto.org/english/tratop_e/dispu_e/276abr_e.pdf. [Accessed 6th August, 2013].
269
Ying, L. (2005). “U.S. Sole Proprietorships: A Gender Comparison, 1985-2000.” A Working
Paper by Small Business Administration Office of Advocacy, No. 263, Available on line:
www.sba.gov/advo/research/rs263tot.pdf. [Accessed: 4th March, 2013].
Young, A.F., Moon, J and Young, R. (2003). The UK Corporate Social Responsibility
Consultancy Industry: a phenomenological approach. No. 14-2003, ICCSR Research Paper.
Zackrison, R.E. and Freedman, A. (2003). Some Reasons Why Consulting Interventions Fail.
Organizational Development Journal, Vol. 21, No.1, pp. 72–74.
Zibran, M.F.(2007). CHI-Squared Test of Independence, Department of Computer Science,
University of Calgary, Alberta, Canada.
Zeithaml, V.A and Bitner, M.J. (1996). Services marketing, Singapore: McGraw-Hill.
Zhilin, Y and Robin, T.P. (2004). Customer perceived value, satisfaction, and loyalty: The role
switching costs, Psychology and Marketing, Vol. 2, No.10, pp. 799-822.
270
APPENDICES
APPENDIX 1: QUESTIONNAIRE
This research is a Postgraduate level research entitled “A Generic Framework for Consultancy Service
Pricing: The Case of Quantity Surveying Practice (QSP)” and intends to identify the challenges
confronting QSP; to establish the key determinants of pricing QS consultancy services; and to establish a
framework for pricing QS consultancy services. Please , kindly respond to the questions by
ticking(√) the appropriate box for each item. Please note that all information provided will be
strictly treated as confidential as this work is for academic purposes.
Firm Status
1. What is the status of your firm?
A. Enterprise / sole proprietorship [ ]
B. Private Limited company [ ]
C. Partnership / Joint venture [ ]
D. Other (Please specify) ……………………………………………………… [ ]
Years of Experience
2. How long has the firm been in existence?
[ ] under 10 years [ ] 11 – 20 years [ ] 21 – 30 years [ ] over 30 years
Rate of work acquisition
3. How frequent do you render consultancy services to clients?
[ ] Not frequent [ ] moderately frequent [ ] frequent [ ] very frequent
Sectors of operation
4. Which of the following sectors do you render services frequently? Use the key: 1= Not frequent 2=
Less frequent 3= Moderately frequent 4= Frequent 5= Very frequent.
Sectors 1 2 3 4 5
Building construction
Civil and structural engineering
Mechanical building and engineering services
Petro-chemical
Mineral extraction
Urban planning
Concept of Price and Value
5. How significant does your pricing decisions depend on the following factors? Use the key 1= Not
significant 2= Less significant 3= Moderately significant 4= Significant 5= Very significant
E. PRICE AND VALUE 1 2 3 4 5
Value of a product or service
Affordability
F. JUST PRICE
271
The Government
Media action
Pressure Group
Seller’s profit
Customer’s intrinsic value
Customer’s affordability
G. IMPORTANCE, OBJECTIVES AND GOALS OF PRICING
(ROLE OF THE FIRM)
Firm’s objectivity
Firm’s failure
Firm’s success
Firm’s image
H. PRICING STRATEGIES
Cost
Profit
Demand
Competition
Project Pricing (Consultancy Pricing)
6. How will the following influence your consultancy services pricing decisions? Use the key 1= Not
significantly 2= Less significantly 3= Moderately significantly 4= Significantly 5= Very significantly.
B. PRICING PARAMETERS/ CRITERIA
1
2
3
4
5
Time taken to solve the problem
Materials used on the project
Good financial control system
Record of past project costs
Accurate forecast of future cost
Production of timely reports
C. BID PRICE SUCCESS IS DEPENDENT ON
Financial capacity
Technical capacity
Firm’s experience
Duration to render the service
Firm’s reputation
Business development
Overhead and profit
Concept of Risk
7. To what extent does the following affect your pricing decision? Use the scale: 1= Not significant 2=
Less significant 3= Moderately significant 4= Significant 5= Very significant
B. PRICE AND RISK
1
2
3
4
5
Associated business risk
Financial risk
Market related risk
Logistical and infrastructural risk
272
Managerial and operational risk
Technological risk
Organizational and societal risk
C. RISKS AT VARIOUS STAGES OF PROJECTS AFFECTING
CONSULTANCY PRICE LEVELS
Financial risk
Legal risk
Regulatory risk
Political risk
Force majeure risks
Concept of Taxation and inflation
8. How significant would the following influence your pricing decisions? Use the key: 1=Not significant
2=Less significant 3= Moderately significant 4= Significant 5= Very significant
A. TAXATION
1
2
3
4
5
Personal income tax
VAT/ NHIL
Corporate tax
Profit tax
Local rates
Property tax
B. INFLATION
Input prices
Inflation
C. INFLATIONARY CAUSES AFFECTING CHANGE IN
CONSULTANCY PRICE LEVELS
Production shortfall
Effects of input market
Government policies
International trade and trade barriers
Quantity Surveying Consultancy Services Pricing Components
9. How significant are the following quantity surveying consultancy pricing components in your price
build-up? Use the key: 1= Not significant 2=Less significant 3=moderately significant 4= Significant
5=Very significant.
A. Pricing Components 1 2 3 4 5
Consultant staff remuneration
Travel and transport
Mobilization and demobilization
Staff allowances
Communications
Office rent
Supplies and equipment
Training programmes
Report preparation
Insurance
Contingencies
273
Taxes and duties
Profits
Challenges confronting quantity surveying consultancy practice (Odeyinka, 2006; Eke, 2006; cartlidge,
2002; Cruywagen and Snyman, 2005)
10. How would you rate the following challenges confronting quantity surveying consultancy practice?
Use the scale: 1= Not Severe 2=Less severe 3=Moderately severe 4=Severe 5= Very severe.
A. GENERAL CHALLENGES 1 2 3 4 5
Slow response to changing contractual arrangements
Challenge of appropriate response to emerging services
Slow response to information and communication technology revolution
Inability to integrate applied research outputs into practice
Changing nature of clients’ demand
Impact of competition
Complexity of modern construction projects
B. PRICING/FEES CHALLENGES
Reducing fees to loss-making territory
Exposure to risks
Decrease in project value
Fluctuation in professional tariff of fees
Quantity surveying consultancy services (Seeley, 1997; Olatunde, 2006)
11. What would you say about the rate at which you provide the following quantity surveying consultancy
services to clients? Use the key: 1= Not frequent 2= Less frequent 3= Moderately frequent 4= Frequent
5= Very frequent
A. TRADITIONAL SERVICES (SEELEY, 1997) 1 2 3 4 5
Preliminary cost advice
Cost planning and cost checking
Advice on contracting methods
Advice on construction procurement systems
Valuation of construction work
Preparing tender documents
Negotiating contract prices
Participating in contract administration
Preparing cash flow forecasts
Cost control of projects
Value management
Interim valuations and payments
Financial statements
Valuation of variations
Final account preparation and agreement
Project management
Claims preparation
Arbitrations and disputes resolution
B. NON-TRADITIONAL(EMERGING) SERVICES (OLATUNDE,
2006)
274
Oil and gas
Management of capital expenditure
Procurement management
Construction management
Rail network
Cost and business planning
Procurement and supply chain management
Commercial management
Facilities management of stations
Risk and value management
Whole life cycle cost management
Power sector
Cost planning and budgeting
Program management
Construction management
Expertise in maintenance programme
Advice on procurement strategy
Contract administration
Project management
Development and facilities management
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APPENDIX 2: Random Number Table used for sample selection
1 2 3 4 5 6 7 8 9 10
1 8450 6992 6563 0340 2649 6933 9446 6182 2601 7800 2 5952 1443 7100 8444 3904 0159 1849 2601 9763 9058 3 5711 6779 9388 9668 4167 1423 2744 4622 2179 8503 4 2681 8047 0494 7853 8411 5406 8127 9577 8530 2350 5 0739 3114 3997 3482 3226 2216 6874 0620 8521 2938 6 8985 2463 5054 3448 6357 0187 6342 4740 4064 5068 7 7644 9339 8375 4583 7715 6355 6827 2055 9328 3287 8 6277 6631 8797 3693 6370 1436 1599 6267 2758 0323 9 6355 7590 7628 9054 0022 4241 7499 3430 3644 6576
10 7828 0589 3075 1954 5972 2266 0055 1097 9706 9009 11 6026 4546 4119 1554 4895 3123 9849 2094 5062 6711 12 8416 1972 9345 1593 2943 2379 5062 4829 5952 8292 13 1433 8823 7706 5273 6160 2161 5510 8617 7894 0175 14 0622 4884 8113 4447 5735 6347 7280 2301 2330 0693 15 4104 7164 1184 3964 2119 6968 0469 3827 0845 8400 16 4272 4979 1471 0942 9573 4283 1557 0161 3957 2516 17 1225 4171 3433 8700 0042 5884 2508 3250 1520 6366 18 7442 6575 1927 7267 7182 3960 4341 0350 1126 5945 19 4911 9007 3048 0319 0916 3002 1466 4421 7246 7662 20 3143 7402 4486 0909 1858 7961 1211 6296 5545 4588 21 8055 9294 2578 0426 4322 6925 2487 5677 9491 4301 22 9240 5260 7134 8001 0140 3394 8437 4066 2855 0933 23 7923 8630 3654 2638 2868 1059 0903 3114 6351 8261 24 0020 5104 4344 3324 9214 6615 5926 7012 9052 9205 25 3312 5923 5469 9171 4877 5392 3394 5077 3750 5637 26 3466 4193 5330 4680 0456 5891 3175 5733 5678 0956 27 1677 1694 1697 8921 2520 2811 3597 1355 9605 3637 28 3846 6283 0969 0051 5857 1043 1671 2013 8955 7706 29 8084 2327 0550 7231 1087 4830 9742 5654 5458 8290 30 2715 2247 4504 1374 9236 7340 1773 0693 2749 1335 31 6537 5815 9312 1460 6593 7678 4312 7537 9360 7195 32 4263 8931 1642 6694 1925 2661 1274 7346 8234 3159 33 7468 4077 6691 3961 7640 2355 9938 8485 9398 8364 34 4884 3324 3690 7433 1245 0523 4483 5933 5634 0512 35 7222 7299 1346 8937 0933 1569 5562 3735 2982 5966 36 5040 0820 8606 4006 4743 6343 4873 1002 4757 1075 37 2980 4860 5694 1501 5791 9414 7246 1283 9766 7427 38 8660 5480 7436 9745 8869 3307 4916 6543 9830 6099 39 7627 4959 6417 3542 1877 0370 5464 9590 5184 7379 40 1890 7664 7144 3523 8465 0385 8174 4740 3654 5543 41 3175 2580 3919 7436 0796 1018 5565 1142 4577 0457 42 7616 9338 6304 0283 6502 9085 5443 1531 9724 4140 43 5223 4525 0895 9930 0050 2201 5270 6447 1850 2070 44 9384 9794 8418 0374 4119 2075 0067 4535 7769 4719 45 5862 9165 5302 9789 5771 9670 7523 9280 2604 0212 46 9450 9307 6597 7183 5243 8854 6735 2415 0364 3096
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