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TITLE OF THE PAPER RELATIONAL EMBEDDEDNESS AND PERFORMANCEOF SMALL AND MEDIUM ENTERPRISES INSOUTHWESTERN NIGERIA

NAME OF AUTHORS: ALARAPE, Aderemi Ayinla.Management Consultant/Lecturer

Centre for Industrial Research and DevelopmentObafemi Awolowo University, Ile-Ife, Nigeria

NASSAR, Moshood LanreProfessor of Business AdministrationDepartment of Management and Accounting,Faculty of Administration,Obafemi Awolowo University, Ile-Ife, Nigeria

Corresponding Author: ALARAPE, Aderemi Ayinla.

Telephone: +2348034090821

Email: [email protected] or [email protected]

Keywords : Business Networks, relational embeddedness, SME’s performance, Nigeria

mailto:[email protected]






RELATIONAL EMBEDDEDNESS AND PERFORMANCE OF SMALL AND

MEDIUM ENTERPRISES IN SOUTHWESTERN NIGERIA

ABSTRACT

The paper examined the impact of relational embeddedness on the performance of SMEs.The primary data were collected through questionnaire and analyzed using descriptive andinferential statistics. 279 firms were selected for the study. The relational embeddednesswas operationalised based on (i) strong ties and (ii) weak ties and the performance of thefirm were contrasted on the basis of growth in assets. The result of the study showed that

personalised “strong ties” do not automatically translate to better performance, atimes,“weak ties” enhance firm’s performance due to removal of unnecessary pressure,obligations and expectations associated with strong relation.

Introduction

The concept of relational embeddedness assumes that firms are closely linked to

their local production environments in a world of increasing globalisation. Relational

embeddedness emphasises the importance of trust-based networks in firm’s development

and explain why under the same market condition some firms perform better than others.

Literature on relational embeddedness in term of effect of degree of relations a firm

cultivated with members of its business networks on the firm’s performance is not only

scarce but there is controversy among the available literature on the effect of strong and

weak ties on firm’s performance.

Strong and weak ties have direct effects on individual economic action (Granovetter

1990). Strong ties enhance firm’s performance directly through trust building, information

transfer and joint problem solving arrangement (Uzzi, 1997). Whereas, (Burt, 1992)

hypothesized that weak ties are performance boosting devices because they provide that

crucial freedom to act upon opportunities and the entrepreneurs are likely to gain most when

not bound by expectations and obligations.



In this paper, the concern is not to engage on the debate whether is better for firm to

cultivate strong relations with the member of is business network or not but provide

empirical information on the effects of strong and weak ties on entrepreneurial performance

of SMEs as it relates to the Nigeria Business environment. Further, this study is a follow-up

to a previous study that found the performance of entrepreneurs who are members of

business associations to be significantly higher than those who did not belong to business

association.

Theoretical Perspective of Effect of Relational Embeddedness on the Performance of

Firms

Embeddedness plays an important role in social relations among economic actors.

There are many theoretical approaches to the study of firms’ relations, such as transaction

cost approach (TCA), resource dependence approach (RDA) and social network approach

(SNA). These theories look at firms relations with social, cultural and economic

environments from different perspectives and provide insights into the causes as well as the

structure of small enterprise relationship. The TCA analyses firm’s relations from an

economic point of view, while the management point of view is the basis of the RDA and

the SNA explains firm’s relations from a sociological point of view.

The Transaction cost approach (TCA) provides a rationale for enterprise networks

rather than analyzing the direction of the relations. The focal point of the TCA is

transactional event rather than any other relationships. The TCA provides a better basis for

analyzing the organizational integration. However, formal integration of small firms among

themselves is not a general phenomenon in less developed countries (LDCs). What is

commonly found in LDCs are informal relations with other supporting organizations and

other firms, because small firms in developing countries are generally seeking for support



rather than looking for avenues to reduce their transaction costs (Ring and Van de Ven

1994).

The Resource Dependency Approach is an organizational ecology perspective that

looks into the behaviour of an organization in relation to its external environment.

According to the RDA, successful performance of a firm depends on resources and

supporting networks. The resources and supports are, particularly for small firms, control by

outside actors of the firms. Thus, in order to access these resources and supports at a

relatively low cost, firms are linked by federations, associations, customer-supplier

relationships, competitive relationships, and a social-legal apparatus that define and control

the nature and limits of these relationships (Butler and Sohod 1995, Pfeffer and Salanick

1978).

Despite, this support from businesses’ federations and associations, individual firms

develop different degrees (strong or weak) of relationship with their customers, suppliers,

bankers, larger firms, consultants that cause variance in their performance. Granovetter

(1990) stated that relational embeddedness has typically quite direct effects on individual

economic actions that is constrained and facilitated by history of interactions and

consequent mutual expectations.

Therefore, relational quality as preconditioned affects sharing of knowledge and

pertinent information essentials for firms development. Specifically, coping with increasing

globalization, promoting technology transfer, achieving economies of scale, internalising

specialised functions (such as training, marketing intelligence, logistics and technical

innovation) and overcoming the problem of poor physical infrastructure which adversely

affect their operation and competitive positions of the firm in the market. Strong ties

enhance firm performance directly through trust building, information transfer, and joint

problem solving arrangements (Uzzi, 1997).



Relational trust and closeness as indicators of relational quality have been found

significantly related to managerial sales and innovation performance (Galunic & Moran,

1999). Therefore, the relational quality has effect on firm performance by directly affecting

the access to physical and financial resources of the firm. Hence, the study hypotheses are:

1(a) Firms that have strong ties with their Bankers perform better than firms that have

weak ties with their Bankers.

1(b) Firms that have weak ties with their Bankers perform better than firms that have

strong ties with their Bankers.

2(a) Firms that have strong ties with their business counsellor perform better than firms

that have weak ties with their business counsellor.

2(b) Firms that have weak ties with their business counsellor perform better than firms

that have strong ties with their business counsellor.

3(a) Firms that have strong ties with their competitors perform better than SMEs that

have weak ties with their competitors.

3(b) Firms that have weak ties with their competitors perform better than firms that have

strong ties with their competitors.

4(a) Firms that have strong ties with larger firms perform better than firms that have

weak ties with larger firms.

4(b) Firms that have weak ties with larger firms perform better than firms that have

strong ties with larger firms.



The Conceptual Framework for the Study

In explaining entrepreneurship and small business firms, the SNA applies network

concept in four different manners. These are: (1) the effect of social forces that increase the

density of networks, (2) the role of brokers and other persons or organizations that increase

the accessibility of networks, (3) the importance of linkage diversity to the question of

which positions in networks are most likely to produce entrepreneurs, and (4) the

importance of the social resources embedded in entrepreneur’s network. However, these are

based on the premises that (i) the entrepreneurial process involves the gathering of scarce

resources (finance, and other material resource like information, ideas, advice, customers

among others and (ii) resources are usually obtained through the entrepreneur’s personal

network.

In this aspect, a social network provides the entrepreneur with information, support,

contact, and credibility. Hence, the SNA is necessary for the analysis of business relations

because economic actions are infused and mixed with social context and the embedded

business relations is a focal issue in social network analysis (Granovetter 1985, Johannisson

1990, Uzzi 1997). However, since it reveals how actors such as entrepreneurs use their

social relations to obtain necessary resources in carrying out economic activities, it

complements the resource-based view.

The foci of RBV are competitive advantages generated by the firm, from its unique

set of resources (Wernerfelt, 1984; Barney, 1986, 1991; Peteraf, 1993). The RBV is based

on the assumptions that: (i) firm resource heterogeneity - firms can be thought of as bundles

of productive resources and that different firm possesses different bundles of these

resources (Penrose, 1959, Barney 1991); and (ii) resource immobility - some of these

resources are either very costly to copy or inelastic in supply (Richardo, 1966).



Therefore, the RBV describes a firm in terms of the resources that firm integrates.

Thus, for a firm to take high levels of performance and a sustained competitive advantage, it

needs to integrate variant resources that should be difficult to create, to substitute or to

imitate by other firms. These resources can be tangible or intangible in nature. Tangible

resources include capital, access to capital and location (among others). Intangible resources

consist of knowledge, skills and reputation, entrepreneurial orientation, among others

(Runyan et al ., 2006). In this sense, this theory defends that, under imperfection of markets

exists a diversity of firms and a variation in the specialisation degrees that provokes a

limited transfer of resources, which present type, magnitude and different nature (Amit and

Schoemaker, 1993).

Therefore, the main reason for firms grow and success is inside of the firms, that is,

firms with resources will build up a basis for gaining and sustaining competitive advantage

(Peteraf, 1993; Ferreira and Azevedo 2007). The SNA thus provide the explanation for the

ways the firm utilised the personalised relations to gain access to this resources and have

sustained competitive advantage in the markets. The firm with the greater resources due to

the strong ties it has with the members of its social networks will be more equipped with

necessary physical and financial resources. Hence, have higher performance compared to

firms with weak ties that cannot equally access the resources.

The Research Methods

The data for the study were collected from 279 firms from a sample frame of one

thousand and forty seven (1,047) SMEs. The two hundred and seventy nine firms are

selected using proportionate stratified random sampling procedure. The questionnaire was

drawn to collect relevant information on the growth performance of SMEs, the forms of



relationship in the SMEs networks and the state of the physical and financial resources in

the SMEs.

The performance of the firms was measured using the growth rate in total assets

calculated based on Gilbrat’s rule. Mathematically, the growth rate is expressed as:

X t1 = X t0 (1+g) t1-t0

Then, g = X t1 1/t1-t0 − 1X t0

g refers to growth rate(GR), i.e. the annual growth rate

X t1 refers to the value of the unit of measure (i.e. assets, employee as at

inception).X t0 refers to the value of the unit of measure (i.e. assets, employee as

present).

The relational embeddedness is expressed in terms of the nature of relevant actors in

the networks, such as: (i) the Bank manager, (ii) the Business Counsellor, (iii) Competitors,

and (iv) the relations with larger firms.

Furthermore, relationship that is at acquaintance’s level is regarded as weak ties and

the one friendly is regarded as strong ties.

The data collected were analysed using descriptive and inferential statistics

The frequencies distribution and percentages are employed for describing the sample

population. The t-test is employed in comparing the mean-values of performance of firms

having personalised strong ties to firms having weak ties. The Kruskal-Wallis’s test

compares the rank the mean performance of the firms based on the extensiveness of

utilising relationship with members of network. The Correlation test is employed to test the

significance of the relationship in firm’s network on performance.



Result and Discussion

The Description of the Relational Embeddedness among the Sample population

In general, the majority of the firms have weak ties with the members of their

networks. For examples: more than seventy percent (i.e. 72.6%) have weak ties with bank

mangers, seventy seven percent (77%) have weak ties with business counsellor, eighty four

percent (84.4%) have weak ties with fellow firms in the same business (i.e. competitors)

and eighty five percent (85%) have weak ties with larger firms. Whereas, only twenty seven

percent (i.e. 27.4%) have strong ties with their bank managers, twenty-three percent (i.e.

22.9%) have strong ties with business counsellor, fifteen percent have strong ties with

competitors and another fifteen percent have strong ties with larger businesses (see Table

1).

Furthermore, less than twenty percent moderately, quite extensively or very

extensively utilized their relations with bank managers. While, twenty six percent and

thirty-one percent do not used or sparingly utilized the relationship they have with their

bank managers. The above pattern is replicated in terms of the utilization of relationship

with business counsellors by the firms. Eighteen percent, twenty percent and three percent

of the firms moderately, quite extensively and very extensively utilized their relationship

with their business counsellors, While, more than fifty percent of the firms do not utilize or

sparingly utilize their relationship with business counsellors. In addition, more than sixty

percent of the firms do not utilize or sparingly utilize relationship with their fellow firms,

whereas, only thirty-eight percent moderately or quite extensively utilize their relationship

with fellow firms. However, no firms extensively utilize the relationship with fellow firms.

With respect to having relationship with larger firms: seventy two percent do not utilize or

sparingly utilize their relationship with larger firm in their network but thirteen percent,

eight percent and seven percent moderately, quite extensively and very extensively utilize

their relationship with larger firms in their network (see Table 2).

The Effect of Relational Embeddedness on the Performance of Firms

The mean value of the performance measure growth in assets of the firms is

generally low. The annual growth rate of firms with weak ties is .03 percent and the growth

rate of firms with strong ties is -.27 percent. This implied that the performance of small and



medium enterprises in Southwestern Nigeria is generally poor in terms of growth in total

assets.

The statistical significance test (t-test) show that there is no significant differences

between the mean performance measure of firms with weak ties and strong ties with their

bank managers. Therefore, developing strong relationship or having weak relationship with

the Bank mangers does not have significant effect on the performance (i.e. total growth in

assets) of firms (see Table 3). However, the nonparametric test (kruskal-wallis test) based

on how extensively the firms utilized their relationship with bank managers vis-à-vis their

performance showed that the mean rank of firms that very extensively utilized their

relationship with their bank managers, significantly is the highest (see table 4).

Therefore hypotheses 1(a) and 1(b) is rejected and introduce another dimension and

proposition that strong ties with bank managers may not lead to better performance in firms,

if the relationship is not extensively utilized. This result does not contradict the view of

(Uzzi, 1999) that personalized relations between entrepreneurs and their bankers lead to

improved performance, it only brings out the importance of extensive utilisation of

personalized relationship.

The result of the t-test of the effect of having strong ties or weak ties with business

counsellor on performance show that mean growth rate in total assets of firm with weak ties

with business counsellors in their network is higher than firm with strong ties with business

counsellor in their network. The mean growth rate for firms with weak ties is .08 percent

while the mean growth rate of those having strong ties is -.56 percent (see Table 5). This is

further confirmed by the non parametric kruskal wallis test that returns lower mean rank

values for those who extensively utilize business counsellor compare to those who do not or

sparingly utilize their relations with business counsellor (see Table 6).



In addition, the non-parametric bivariate correlation further confirmed the above

trend. There is a significant negative relationship (i.e. Kendall’s tau b = -.180 and rho =

-.250) between the extensiveness of utilizing business counsellor and the growth

performance of firms at 99 percent confidence level (Table 7). Hypotheses 2(a) is rejected

and 2(b) is upheld that firms with weak ties with their business counsellor perform better

than firms that have strong ties with their business counsellor. This support the findings of

Burt (1992) that Weak ties are also performance boosting devices because vaguely defined

relationships provide that crucial freedom to act upon opportunities and entrepreneurs are

likely to gain most being not bound by expectations and obligations.

The analysis of the relational effect of weak ties or strong ties with fellow firms (i.e.

competitors) shows that both types of relationships return negative growth rates in total

assets of the firms. However, the t-test of the effect of the relations on performance shows

that they are not significant (see Table 8). The nonparametric Kruskal-Wallis’s test shows

that the extensiveness of utilizing the relations with fellow firms in the same business does

not have significant effect on the performance of the firms 9see Table 9). Thus, hypotheses

3(a) and 3(b) is rejected. The non significance of the effect of the modes of relationship firm

has on other competitively related firms is because competitively related firms see one

another as rivals and do not cultivate the required networking relationship that could

significantly reduce the cost of transactions by internalizing the advantages of economics of

scale as postulated by Nassar and Remi Alarape (2007).

The result of test of the personalized relationship of small firms with larger firms

shows that the mean performance value of firms with weak ties is significantly higher than

mean performance value of firms with strong ties with larger firms (see Table 10). The

nonparametric test of the extensiveness of utilizing personalized relations with larger firms

shows that the mean rank of the performance measure (growth in total assets) of those who



do not utilize or sparingly utilize the personalized relations is higher than those who quite

and very extensively utilize the personalized relations with larger firms (Table 11).

This is further confirmed through nonparametric correlation test. The result of the

correlation test show that the extensiveness of utilizing the personalized relations is

significantly negative related to performance (see Table 12).Therefore, hypothesis 4(a) is

rejected and hypothesis 4 (b) is upheld. This implies that firms with weak ties with larger

firms perform better than firms that have strong ties with larger firms. This may result from

lack of what Uzzi (1997) describes as trust building, information transfer, and joint problem

solving arrangements in the relationship between firms.

Conclusion

This study contributes to the literature on the empirical effect of relational embeddedness on

performance of SMEs by investigating the effect of strong ties and weak ties of small firms

with selected members (bank managers, business counsellor, competitors and larger firms)

of its network on growth performance of SMEs. Study of this nature is scarce in this part of

the world, thus, it is of high relevance to researchers interested in explaining firm

performance from a sociological perspective.

The results of this study complement existing studies, and it suggests that

personalised strong ties with members of firm’s network is not sufficient to lead to high

performance, it has to be extensively utilised. This is because weak ties or non-extensive

cultivation of personalised relations can also lead to high performance due to the removal of

unnecessary pressure, obligations and expectations that can adversely affect the

performance of firms as previously explained by Burt (1992).

Therefore, firms need not only cultivate strong informal relationship with member

of its business network but it should be extensively utilised for the good of the business.

Firms should be very careful in developing strong informal relations because not all such

relations contributed positively to performance.

Despite the fact that the study does not provide information on those factors that

may make developing strong or weak informal relations with members of the firm’s



network to be injurious or catalyst for improved performance, this may be focus of future

research. However, this has not limit its relevance and application by researchers, trainers,

owner-managers of SMEs and other practitioners because it highlights the effects of

personalised relationship on performance of firms and the importance of well-cultivated

informal relationship on growth performance of SMEs. Thus, the study has enhanced the

understanding of the relevance of firm’s social relations with the members of its business

network in the explanation of the dynamism of firm’s performance.



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App endix

Table 1: The Distribution of the Relational Strength of the Firms with Selected

Members of the its Network

Bank manager Frequency PercentValid

PercentCumulative

PercentValid weak 199 71.3 72.6 72.6

strong 75 26.9 27.4 100.0Total 274 98.2 100.0

Missing 99 5 1.8Total 279 100.0

Business counsellor Frequency PercentValid

PercentCumulative


strong 63 22.6 22.9 100.0Total 275 98.6 100.0

Missing 99 4 1.4Total 279 100.0

Competitor Frequency Percent

ValidPercent

CumulativePercent

Valid weak 232 83.2 84.4 84.4strong 43 15.4 15.6 100.0Total 275 98.6 100.0

Missing 99 4 1.4Total 279 100.0

Larger firms Frequency PercentValid

PercentCumulative


strong 41 14.7 14.9 100.0Total 275 98.6 100.0

Missing 99 4 1.4Total 279 100.0

Source: Field survey 2008



Table 2: The Distribution of the Extensiveness of Utilisation of Firm’sPersonalised Relations with Selected members of its Network

Bank Manager Frequency Percent Valid PercentCumulative

PercentValid Not used at all 72 25.8 26.3 26.3

Used sparingly 86 30.8 31.4 57.7Used moderately 41 14.7 15.0 72.6Used quite extensively 45 16.1 16.4 89.1Used very extensively 30 10.8 10.9 100.0Total 274 98.2 100.0

Missing 99 5 1.8Total 279 100.0

Business Counsellor Frequency Percent Valid PercentCumulative


Used sparingly 79 28.3 28.7 59.6Used moderately

48 17.2 17.5 77.1Used quite extensively 56 20.1 20.4 97.5Used very extensively 7 2.5 2.5 100.0Total 275 98.6 100.0

Missing 99 2 .7System 2 .7Total 4 1.4

Total 279 100.0

Competitors Frequency Percent Valid PercentCumulative


Used sparingly48 17.2 17.5 62.2Used moderately 61 21.9 22.2 84.4

Used quite extensively 43 15.4 15.6 100.0Total 275 98.6 100.0

Missing 99 4 1.4Total 279 100.0

Larger Firms Frequency Percent Valid PercentCumulative


Used sparingly 31 11.1 11.3 72.0Used moderately 36 12.9 13.1 85.1Used quite extensively

23 8.2 8.4 93.5Used very extensively 18 6.5 6.5 100.0Total 275 98.6 100.0

Missing 99 4 1.4Total 279 100.0

Source: Field survey, 2008



Table 3: The Result of the T-Test of Effect of Firm Relationship with Bank

Managers on Performance of Firms Group Statistics

Bank manager N Mean Std. DeviationStd. Error

MeanGrowth in Asset Weak 175 .0303 2.13425 .16133

Strong 74 -.2714 2.03898 .23703

Independent Samples Test

Levene's Testfor Equality of

Variances t-test for Equality of Means

F Sig. t Df Sig. (2-tailed)

MeanDifference

Std. Error Difference

95% ConfidenceInterval of the

Difference

Lower Upper Growthin

Asset

Equalvariancesassumed

1.616 .205 1.033 247 .303 .30165 .29210 -.27367 .87698

Equalvariances notassumed

1.052 143.397 .295 .30165 .28672 -.26510 .86840

Table 4: Kruskal –Wallis Mean Ranks Test of Performance of SMEs andthe Extensiveness of Utilising the Relationship with Bank Managers

Bank Managers N Mean Rank

Growth in Asset Not used at all 60 144.00Used sparingly 76 114.84Used moderately 28 102.27Used quite extensively 44 72.61Used very extensively 25 153.38Total 233

Test Statistics(a,b)

Growth in AssetChi-Square 37.435Df 4

Asymp. Sig. .000a Kruskal Wallis Testb Grouping Variable: Bank manager

Table 5: The Result of the T-Test of Effect of Firm Relationship with



Business Counsellors on Performance of Firms

Group Statistics

Business counsellor N Mean Std. DeviationStd. Error


Strong 56 -.5576 .47411 .06336




F Sig. T df Sig. (2-tailed)

MeanDifference



Difference

Lower Upper Growthin

Asset


6.551 .011 2.014 248 .045 .63847 .31709 .01394 1.26299


3.535 234.740 .000 .63847 .18062 .28262 .99431

Table 6: Kruskal –Wallis Mean Ranks Test of Performance of SMEs and theExtensiveness of Utilising the Relationship with Business Counsellor

Business Counsellor N Mean Rank

Growth in Asset Not used at all 75 145.37Used sparingly 76 131.30Used moderately 43 124.59Used quite extensively 49 86.23Used very extensively 7 130.00Total 250


Growth in

AssetChi-Square 20.649Df 4

Asymp. Sig. .000a Kruskal Wallis Testb Grouping Variable: Seek advice of a Consultant in managing biz

Table 7: The Result of the Correlation Test of the relationship of Extensiveness of Utilising the Relationship with Business Counsellor and Performance of Firms



Growth in

Asset

Seek advice of a Consultant inmanaging biz

Kendall 's tau_b Growth in Asset Correlation Coefficient 1.000 -.180(**)

Sig. (2-tailed) . .000N 254 250

Seek advice of aConsultant inmanaging biz

Correlation Coefficient -.180(**) 1.000Sig. (2-tailed) .000 .

N 250 275

Spearman's rho Growth in Asset Correlation Coefficient 1.000 -.250(**)Sig. (2-tailed) . .000N 254 250

Seek advice of aConsultant inmanaging biz

Correlation Coefficient -.250(**) 1.000Sig. (2-tailed) .000 .

N 250 275

** Correlation is significant at the 0.01 level (2-tailed).

Table 8: The Result of the T-Test of Effect of Firm Relationship with

Competitors on Performance of Firms

Group Statistics

Competitor N Mean Std. DeviationStd. Error

MeanGrowth in Asset Weak 214 -.0129 2.24201 .15326

Strong 36 -.3554 .87837 .14640




F Sig. T df Sig. (2-tailed)

MeanDifference



Difference

Lower Upper Growth in

Asset


1.614 .205 .904 248 .367 .34259 .37899 -.40386 1.08903


1.616 128.415 .108 .34259 .21194 -.07677 .76194

Table 9: Kruskal–Wallis Mean Ranks Test of Performance of SMEs and theExtensiveness of Utilising the Relationship with Competitors



Competitors NMeanRank

Growth in Asset Not used at all 114 134.65Used sparingly 45 121.53Used moderately 55 114.06Used quite extensively 36 118.96Total 250


Growthin Asset

Chi-Square 3.633df 3

Asymp. Sig. .304a Kruskal Wallis Testb Grouping Variable: relations with Competitors

Table 10: The Result of the T-Test of Effect of Firm Relationship

with Larger firms on Performance of Firms

Group Statistics

Contractual Relations N Mean Std. DeviationStd. Error


Strong 37 -.5466 .40807 .06709


Levene'sTest for

Equality of Variances t-test for Equality of Means

F Sig. t df Sig. (2-tailed)

MeanDifference



Difference

Lower Upper Growth

in Asset

Equal

variancesassumed 4.559 .034 1.522 248 .129 .56854 .37358 -.16726 1.30434Equalvariances notassumed

3.366 247.684 .001 .56854 .16891 .23585 .90122

Table 11: Kruskal –Wallis Mean Ranks Test of Performance of SMEs and the

Extensiveness of Utilising the Relationship with Larger firms



Relations with larger firms N Mean Rank

Growth in Asset Not used at all 152 140.01Used sparingly 28 115.80Used moderately 33 93.23Used quiteextensively 20 92.53Used very extensively 17 113.18Total 250


Growth in

AssetChi-Square 17.861Df 4

Asymp. Sig. .001a Kruskal Wallis Testb Grouping Variable: Develop contractual relations with larger firms

Table 12: The Result of the Correlation Test of the relationship of Extensiveness of Utilising the Relationship with Business Counsellor and Performance of Firms

Growth in

Asset

Developcontractual

relations withlarger firms

Kendall's tau_b Growth in Asset Correlation Coefficient 1.000 -.189(**)Sig. (2-tailed) . .000N 254 250

Develop contractualrelations with larger firms

Correlation Coefficient -.189(**) 1.000Sig. (2-tailed) .000 .N 250 275

Spearman's rho Growth in Asset Correlation Coefficient 1.000 -.249(**)Sig. (2-tailed) . .000N 254 250

Develop contractualrelations with larger firms

Correlation Coefficient -.249(**) 1.000Sig. (2-tailed) .000 .N 250 275

** Correlation is significant at the 0.01 level (2-tailed).

alarape and nassar

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