Entrepreneurship and Performance: An Antithetical … · Entrepreneurship and Performance: An Antithetical View Of ... personality characteristics of ... The social embeddedness theory

DBA Africa Management Review 2012, Vol 2 No 3, pp 1-24

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Entrepreneurship and Performance: An Antithetical View Of Mcclelland’s Ideological “Need for Achievement”

Robert Kemepade Moruku, PhD.1

The present researcher raised the question whether the well-known high mortality rate of SMEs was due only to poor motivation on the part of owner-managers or not. To provide an answer to this question, I evaluated the performance of SMEs in three states of the South-South geopolitical zone of Nigeria. In particular, I first positioned the latent motivation as well as its indicators as direct antecedents and second as ultimate antecedents to performance through locus of control (LC) and entrepreneurial orientation (EO). The multivariate cross-sectional data generated from the survey were analyzed using the canonical correlation statistic. It was found that latent motivation did not make a statistically significant impact on performance but the perceived environment did make a statistically significant impact on performance, particularly, employment growth. It seemed that the external business environment dampened the impact of motivation on performance, suggesting that motivation can find expression only within the opportunities of the domineering business environment. The findings led to questioning whether the entrepreneurs in McClelland’s Achieving Society were not products of their environment. In view of “achievement-based vulnerabilities” I also question whether the “need for achievement” should be recommended as a universal value irrespective of context. Thus, it was recommended that the state should support entrepreneurial performance by adapting the business environment to the performance of SMEs. It was also recommended that SMEs should acquire dynamic capability to fit in to the dynamic business environment. Future researchers may wish to extend on this study in different contexts and use longitudinal design.

Keywords: Subjective environment; objective environment; locus of control; entrepreneurial orientation; entrepreneurial performance; resources; motivation

1 Senior Lecturer, Faculty of Management Sciences, Delta State University, Asaba Campus, Nigeria - [email protected]


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INTRODUCTION Until a few decades ago, entrepreneurs were a despised lot. This was even the case in the Western world despite the idealization of entrepreneurship in the “Western cultural account” (Brandl and Bullinger, 2009) and the existence of entrepreneurship from antiquity (Johnson et al., 2001). It was just in the 1980s, in the US, that Bill Gates, Sam Walton, and others brought charm, fame, status, and respect to entrepreneurship by their extraordinary successes and wealth. Every country has its entrepreneurial icons. In Nigeria, these include Chief Alex Ibru, Alhaji Aliko Dangote, late Alhaji Aminu Dantata, and others (see also Forrest, 1994). In 2011, Alhaji Aliko Dangote was honoured with the title, Grand Commander of the Order of the Niger (GCON), which is normally reserved for the vice president of the Federal Republic of Nigeria for the contributions the Presidency or award committee thought he made to the Nigerian economy.

The extraordinary successes of entrepreneurs have attracted the attention of scholars, who seek to identify the defining characteristics of these entrepreneurs (Envick and Langford, 2000) with a view to teaching them to, and making entrepreneurs out of, ordinary people. In this effort, entrepreneurs have been compared and contrasted with managers to see whether there exist differences between the two groups (see Kikooma, 2010). In many studies (e.g., Carraher et al., 2003; Envick and Langford, 2000; Garsombke

and Garsombke, 2000), entrepreneurs were found to be different from managers and from one another (Rogoff and Lee, 1996).

So, it may be asked, “What was it that made these entrepreneurs to achieve success?” For David McClelland, it was the “need for achievement” (nACH) that is the psychological vehicle driving entrepreneurial performance and economic development in the Western world. In his book, The Achieving Society, and other publications, David McClelland postulated that people in the Western industrialized countries had high motivation to achieve, which explained the disparity in economic development between those Western countries and the developing countries (see also Jha, 2010).

In contrast, Lumpkin and Erdogan (1999) do not subscribe to a parsimonious explanation of the entrepreneur. In a similar vein, Rogoff and Lee (1996), for example, suggested that entrepreneurs are more different from one another than they are alike, which makes them “defy aggregation”.

A sobering reality, however, is that the search for the defining personality characteristics of entrepreneurs has been met with lingering frustration, resulting in an interminable definitional and identity debate. For every finding which suggests that there is a relationship between entrepreneurial traits and performance, there is also one that counters it


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(Sonfield et al., 2001). For Jones and Spicer (2005), the deep and inconvenient truth is that entrepreneurship is an empty signifier or an impossible and incomprehensible object.

In the light of the multitudinous influences impacting on the performance of the entrepreneur, I here pose the key research question that guides this study, namely, “Does the ‘need for achievement’ alone provide a sufficient explanation for entrepreneurial performance?” Besides pluralism, causation may be non-linear (see Anderson, 1962 [1938], as cited in Hibberd, 2010), which requires continuous re-evaluation of the relationship. The modest objective for this paper, therefore, is to find the answer to this question. The study uses multivariate cross-sectional data to evaluate entrepreneurial performance, taking cognizance of the complexity of the entrepreneur; doing so by positioning motivation as just one among other key latent antecedents to performance.

After this introductory section, which defines the problem and sets the objective for the study, the rest of the paper is structured as follows. A review of the extant literature is made in the second section to develop the hypotheses and lay the theoretical foundation; doing so recursively and iteratively. This is followed by a description of the research strategy or methodology in section three. In the succeeding section, I describe the empirical findings, which are then discussed in section five. The final section concludes the paper with policy

recommendations and suggestions for future research.

THEORETICAL FOUNDATION The social embeddedness theory is employed to serve as the theoretical foundation upon which the discourse on entrepreneurial performance is erected. The theory, as developed by Mark Granovetter (1985, as cited in Greenwood and Meyer, 2008), suggests that economic activities take place in a social context. This context is a shaping mould.

The social context is a melange of the political, economic, technological and cultural influences. In general, it consists of the influences that shape the cognition or world view of the entrepreneur. The cultural context sets the social and behavioural norms, gives legitimacy and recognition to business entrepreneurship, and permits or encourages the entrepreneur to take to entrepreneurship (see Garsombke and Garsombke, 2000; Kikooma, 2010). It structures inter-actor ties, which makes possible the formation of meaningful relationships and social networks for acquiring social capital; structures governance institutions for regulation of entrepreneurship and related services such as the approval, registration, issuance and revocation of business permits or operating licenses (Yang, 2004).

As the embeddedness framework suggests, the entrepreneur’s firm does not operate invacuo; it is embedded in a complex total environment system.


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Based on the resource dependence theory (Pfeffer & Salancik, 1978, as cited in Davis, 2010), the firm engages in exchanges with the environment; dependent on resources from the external business environment. Based on the new institutional theory, the environment exerts isomorphic pressures on the firm (Meyer and Rowan, 1977 as cited in Greenwood and Meyer, 2008), which then impacts on the operations of the entrepreneur.

It can be seen, therefore, that firms are shaped by the national as well as the global business environment, both of which they need for their survival and prosperity. The impact of the global environment may be demonstrated with the operation of the phenomenon of distant correlation (Shelton and Darling, 2001) on an economy, which shows up in the collapse of one economy as a result of environmental jolts from another country. For example, the financial crisis in the US snowballed into a global financial meltdown of 2007 and many firms and economies around the world collapsed in consequence despite the high capability and motivation of their entrepreneurs.

EMPIRICAL STUDIES

When it comes to entrepreneurial performance, every discipline emphasizes its approach as the route to salvation, which makes entrepreneurship a perspectival and multidisciplinary phenomenon and subject of enquiry. For example, psychologists advance “psychological determinism”, suggesting

that motivation provides the big picture in performance. Strategic management theorists (for example, Porter, 1996; Rothschild cited in Day and Wensley, 1995:144; Thompson and Strickland, 1995:19;) suggest that “strategy” is the driver of performance. For Porter (1996), strategy is the only basis for securing sustainable competitive advantage. Population ecologists (as cited in Wahlgren, 1999) underscore “environmental determinism” as explanatory framework for entrepreneurial performance. Fortuitous factors have also been recognized to play a role in entrepreneurial performance.

In the rest of this section, these various disciplinary perspectives are examined in some detail in an attempt to link them up as a theoretical explanatory model. The Motivation Perspective Psychologists contend that the emergence and performance of entrepreneurs can be explained by “psychological determinism”, which consists of the psychological drives of the entrepreneur (see Akeredolu-Ale, 1975: 8-9; Hisrich and Peters, 2002:72).

I here focus attention on McClelland’s learned needs theory, particularly, the need for achievement component of the theory. According to McClelland, humans have three basic needs. These are the need for achievement (nACH), need for affiliation (nAFF) and the need for power (nPWR).


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The need for achievement component of this theory is often cited among the theories of psychologists even though it is deeply ideological to the extent that it is used to explain the underdevelopment of the underdeveloped countries (Cf Rodney, 1978). Overall, however, research evidence on the association between need for achievement and performance is inconclusive. The Resource-Based Perspective The resources that impart performance benefits, according to the resource-based view (RBV), are skills, core competencies, and culture. They must be heterogeneous, difficult or impossible to copy or substitute; and have “causal ambiguity” (Foss and Ishikawa, 2007). The theory suggests that the enterprise can achieve strong performance through the building or acquisition of these resources.

Important to building skills, knowledge or expertise, is “learning”, particularly, lifelong learning. So, the “learning entrepreneur” (Gielen et al., 2003) and “learning organization” or organizational learning (Ferguson-Amores et al., 2005) constructs have been developed in recent times.

The Strategy Perspective

The strategic adaptation theory advances the role of strategy in fitting the internal capabilities of the firm to the attractive opportunities and significant threats in the external business environment. The internal capabilities include the

knowledge, skills, attitudes and other factors (KSAOs), which are internal to the firm (Bacon and Hofer, 2003).

Strategy is a tool for achieving firm-environment fit or adaptation; the business environment is the source of information for formulating strategy; adaptation is the action (behavioural, structural, and ideological) issuing from strategy and fitting the firm to the environment; and learning is the capability used to improve on the strategy formulating process.

The Population Ecology Perspective

The external business environment consists of the perceived (subjective) environment and the industry (objective) environment, which embed and shape the firm. Thus, population ecologists attribute organizational performance to “environmental determinism” or environment selection, meaning that the environment exerts a “domineering” impact on organizational or entrepreneurial performance such that managerial options in the face of environmental constraints are limited.

The theoretical background laid above, enables the researcher to state the two path null hypotheses below:

H0a: There is no statistically significant direct impact of the motivation of owner-managers/entrepreneurs on the performance of SMEs.

H0b: There is no statistically significant indirect impact of the


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motivation of owner-managers/entrepreneurs on the performance of SMEs.

These are omnibus path hypotheses on the canonical relationship between the latent variables, which are motivation and performance. Hypothesis H0a tests the direct canonical relationship between the two variables while H0b tests the indirect canonical relationship between the two variables mediated by entrepreneurial orientation (EO) and locus of control (LC).

As stated before, the study takes cognizance of the complexity of the entrepreneur by positioning motivation as one among other key latent antecedents to performance in the conceptual framework as proposed and shown below. The other latent antecedent variables are the industry environment, perceived environment, resources. In addition, EO and LC are considered useful for possibly mediating the link between the antecedent variables and performance (Covin and Slevin, as cited in Quince and Whittaker, 2003; Gray, 1999).

Industry

PerceivedEnvironment

Resources

Attitude

Entrepreneurial Orientation

Locus of Control

Performance

x1x5

x2

x3

x4x6

Y

Fig. 1: Conceptual framework

The null hypotheses made above are here used to develop the conceptual frame work presented in Fig. 1. The arrows indicate the hypotheses. Each of the three dimensions of performance will be tested with the latent motivation

variable. Thus, three path sub-hypotheses based on the direct relationships and another three path sub-hypotheses based on the indirect relationships between the canonical variable and each of the three indicator


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variables of performance are formulated as follows:

H0a1: There is no statistically significant direct impact of motivation on sales growth of SMEs.

H0a2: There is no statistically significant direct impact of motivation on profit growth of SMEs

H0a3: There is no statistically significant direct impact of motivation on employment growth of SMEs

H0b1: There is no statistically significant indirect impact of motivation on sales growth of SMEs.

H0b2: There is no statistically significant indirect impact of motivation on profit growth of SMEs

H0b3: There is no statistically significant indirect impact of motivation on employment growth of SMEs

In addition, there are thirty other hypotheses which are not stated but will be tested. They relate to the industry environment, perceived environment, and resources (Table 2). The stated and tested hypotheses are those relating motivation to performance (Table 2).

METHODOLOGY

This section describes the research design and the strategies used to gain access to data sources, generate, and analyze the data generated.

Research Design

The ex-post facto design was considered appropriate for this study because the study was meant to evaluate the performance of SMEs which have long been operating in the Nigerian business environment, prior to the time of conducting the present study.

Instrument and Measures

The instrument was derived from Wiklund (1998: 315-342). A pilot study was carried out in Benin City in November 2006, outside the three states selected for the full study. This was done to avoid practice or maturity effects among the participants of the study.

The survey instrument was statistically validated and adapted to the Nigerian business environment via factor analysis, using the varimax rotation technique, which ensured that variables loaded high (r ≥ .70) on relevant axes but with low cross-loadings (in most cases r ≤ .40) on irrelevant axes, which suggests that the latent variables attained orthogonality or discriminant validity. Thus there was no threat of multicolinearity.

Further, the instrument was tested for reliability, using the Spearman Brown split-half reliability statistic and


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its equivalents such as the Gutman’s split-half and Cronbach’s alpha statistics. Variables were selected based on a reliability score specified above along with item-total correlations. Consequently, many constructs lost several dimensions in this item purification process. For example, locus of control lost two of four dimensions. The final instrument consisted of 23 variables distributed over eight theoretical constructs. Except the resource variables, the reliability coefficients of most of the variables ranged from .60 to .92, thus meeting or exceeding the reliability coefficient recommended by Nunnally and Bernstein (as cited in Miller et al., 2007). As such, the study attained methodological rigor, in the positivist tradition, in terms of achieving construct validity (the constructs used are established as relevant to the study), internal consistency or validity (the research process is reproducible), and external validity (the findings are generalizable beyond the sample to the population).

Data Sources and Analysis

Primary data for the study were generated via the survey instrument administered in 2007 to MDs/CEOs of 800 SMEs in three states of the South-South geopolitical zone of Nigeria. The sampling frame (population) consisted of 1,245 SMEs, which was created by combining the directories of SMEs of the three states selected for the study.

Trained research assistants were employed to distribute copies of the instrument. The survey was accompanied with a covering letter, which explained to the informants the purpose of the research and assured them of the strict anonymity of their identity and responses.

Of the 800 copies of the survey that were distributed, 640 copies were retrieved out of which 463 were usable. Retrieval was stopped as soon as the required minimum usable responses were obtained. This met the threshold sample size of 460 cases for the 20 cases per item required for accurate reporting of the first root of a canonical correlation analysis (Stevens, 2001: 475). The survey achieved 80% retrieval rate, which exceeded the 10 to 27 percent rate of response accepted for mail surveys with MDs/CEOs as respondents (Ghobadian and O’Regan, 2008).

The research model was based on cross-sectional, multivariate data. As such, the structural equation modelling approach was used to analyze the data, using the canonical correlation statistic. A structural equation model permits simultaneous estimation of the complicated relationships among the variables and control Type I error (Huck et al., 1974: 184; StatSoft Inc, 1984).

EMPIRICAL FINDINGS

The preliminary findings were obtained from the analysis of the data from the pilot study, which are summarized in


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Appendix Tables 1 and 2. Table 1 reports the results of testing thirty-three (33) unstated hypotheses on the relationship between 11 indicators of motivation each with the three dimensions of performance.

Taking these results along with those in Appendix 1 reveals a great

surprise. In particular, the results reveal that although owner-managers of SMEs were highly motivated, the impact of the high motivation on performance is significant for only five of the sub-variables of motivation (Table 1).

Table 1: Impact of Sub-Variables (indicators) of Motivation on Perform of SMEs

Manifest Variable Sales Growth

Profit Growth

Employment Growth

Entrepreneur’s Motivation (X 5)

(i) Goals

23b Profitability (V71)

23c Self-fulfilment (V72) 0.11 (.01) 0.12 (.01)

23d Time for family (V73)

23e Reap fruits of work (V74) 0.10 (.04)

(ii) Favoured Work -tasks

24a Contact existing customers (V75)

24b Developing new products (V76)

24c Sales (V77)

24d Board work (V78)

24e Marketing plans (V79) -0.11(.02)

24f Developing strategies (V80)

24g Developing new customers (V81) 0.10 (.02)

Note: Path coefficients are Pearson’s product moment correlation coefficients; levels of statistical significance are in brackets,

Source: SAS output based on authors’ survey data.


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The scores for the rest of the motivation sub-variables are high but their impacts on the three dimensions of performance are statistically insignificant (p > .05). As such, they are not reported.

These results may implicate the external business environment as imposing a domineering constraint on performance as suggested in Akeredolu-Ale (1975: 58-61) and by population ecologists (as cited in Wahlgren, 1999).

Table 2 summarizes the findings on the relationship between each of the independent variables with each dimension of the dependent (performance) variable and the overall multivariate statistics of eight models. Findings from the testing of the hypothesized (latent) models are summarized in Table 3.


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Table 2: Impact of Business Environment on Performance of SMEs in the Presence of Context Variables

Model and

Related

Hypothesis

Indep Vars with Path Coefficients DV Overall Multivariate Statistics

Industry

X1

P.Envir

X2

Resou.

X3

Motiv

X4

EO

X5

LC

X6

Per

Y i

Rc Adj. Rc R2c F Wilk’s λ

Model1 (H0a) Xc Yc 0.26 0.24 0.07 3.70 0.000٭

Model 2 (H0a1) y1 -0.02 0.03 -0.01 -0.05 1.00 (y1) 0.07 0.02 0.00 0.48 0.748

Model 3 (H0a2) y2 0.13** 0.03 -0.03 +0.07 1.00 (y2) 0.15 0.13 0.02 2.66 0.032

Model 4 (H0a3) y3 0.00 0.25*** +0.05 +0.02 1.00 (y3) 0.15 0.13 0.02 2.66 0.032

Model 5 (H0b) Xc Yc 0.32 0.29 0.10 3.81 0.000٭

Model 6 (H0b1) y1 -0.02 0.03 -0.01 -0.05 0.08 0.11** 1.00 (y1) 0.16 0.13 0.03 2.05 0.058

Model 7 (H0b2) y2 0.13** 0.03 -0.03 +0.07 0.07 0.00 1.00 (y2) 0.16 0.13 0.03 2.05 0.058

Model 8 (H0b3) y3 0.00 0.25*** +0.05 +0.02 0.08 -0.04 1.00 (y3) 0.31 0.30 0.10 8.20 0.000

Notes: (1) ٭ First canonical function or root; Yc = Variate canonical (performance) variable; Xc = Covariate canonical (environ) variable.

(2) Coefficients are path coefficients which are Pearson’s product moment correlation coefficients.


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(3) Significance: *- p < .05; **- p < .01; ***- p < .001; Wilk’s λ = Pr>F.

(4) Models 1 to 4 are direct relationship models while models 5 to 8 are indirect (interaction effects) structural equation model

(5) y1 is Sales Growth; y2 is Profit Growth; and y3 is Employment Growth.

(6) Coefficients in bold print in the motivation column relate to the stated and tested hypotheses.

Source: SAS output (pp. 1- 39) as computed from Researcher’s survey data.


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Of the eight models in Table 2, model 8 has the second highest association between motivation and performance, after the indirect canonical association between the latent motivation and performance variables.

The figure below is used to show the complex relationships in a graphic manner which transcends verbalization with a better depiction than any other descriptive device. It also represents the theoretical framework of the study.

Industry

PerceivedEnvironment

Resources

Attitude

Entrepreneurial Orientation

Locus of Control

Employment growth

x1x5

x2

x3

x4x6

y3

.16

-.06

-.04

.08

-.00

-.17

-.07

.18

-.08

.26

- .17.44

-.05

-.01

. 33

.08

.00.25

.05

.02

-.04

R = .31c

R = .33c

* **

***

***

***

***

***

***

*** ***

***

Significance: *-p<.05; **-p<.01; ***p<.001

Fig. 2: Tested Model of the impact of Environment on employment growth

The figure reveals that perceived environment contributes most (r = .44***) to the explanation for locus of control (LC) and second best explanation for entrepreneurial orientation (EO) (r = .08***), only after resources (r = .26***). Motivation (attitude) has the least explanation for both LC (-.01, p > .05) but surprisingly, the best explanation for EO (r = .26***). All four latent variables combined before accounting for an appreciable amount of LC (r = .47***) and EO (r = .33***) before explaining

employment growth (r = .31***). The point here established is that motivation alone is incapable of accounting for performance.

The most promising (‘critical’) path to entrepreneurial performance, clearly, is the one that links perceived environment to locus of control (r = .44***) to entrepreneurial orientation (r = .33***) and finally to employment growth (r = .08) (see the figure).

Rc = .47***


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Table 3: Summary of Results of Stated and Tested Hypotheses

Hypothesis

Hypothesized Path *Path

Coeffs.

Decision

From Thro To

H0a Motivation Performance +0.26*** Reject

H0b Motivation LC-EO Performance +0.32*** Reject

H0a1 Motivation (Direct) Sales growth(y1) -0.05 Accept

H0a2 Motivation (Direct) Profit growth (y2) +0.07 Accept

H0a3 Motivation (Direct) Employment growth (y3) +0.02 Accept

H0b1 Motivation

(Indirect)

Sales growth(y1) -0.05 Accept

H0b2 Motivation

(Indirect)

Profit growth (y2) +0.07 Accept

H0b3 Motivation

(Indirect)

Employment growth (y3) +0.02 Accept

Note: (1) * First canonical root

(2) Path coefficients are Karl Pearson’s (r ) bivariate correlation coefficients; stated as

Prob. > Under H0i: Rho = 0;

(3) Significance: * - p < .05; ** - p < .01; ***- p < .001


DISCUSSION

The results of this study question the “superfactor” status accorded to motivation in accounting for performance. Owner-managers had high levels of motivation to achieve performance but it did not convert to commensurate levels of

performance. This is evident in the high mean scores of the motivation sub-variables (see Appendix 1).

The low and insignificant link between motivation and performance


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while the perceived environment made a statistically significant impact appears to suggest that the business environment had a dampening impact on performance despite the high achievement motivation of owner-managers. This finding is puzzling and needs some explication. First, it is at variance with theoretical expectations formed in both McClelland’s learned needs theory, particularly, its need for achievement, (Hisrich and Peters, 2002: 67) and Locke’s goal-setting theory (Locke, 2007).

Second, it is consistent with the view of population ecologists as highlighted in Akeredolu-Ale (1975: 57-61) and Wahlgren (1999) regarding the failure of entrepreneurial capacity to lead to performance. This may well vindicate their perspective that the environment exerts a “domineering” impact on organizational or entrepreneurial performance such that managerial options in the face of environmental constraints are limited.

Akeredolu-Ale (1975) showed how indigenous entrepreneurs in Nigeria were frustrated from striving for entrepreneurship during the colonial era, arguing, therefore, that motivation can only make sense within the context of the external business environment. This is particularly relevant to the Niger Delta sub-region of Nigeria in which the present study was carried out, an area without the minimum basic infrastructures required for operating business successfully. Yet, research indicates that entrepreneurship is significantly related to access to road networks and Internet connections (Low et al., 2005).

Third, it also suggests that David McClelland appears to have overlooked

the complexity of the entrepreneur and the multiple influences on his/her performance. As Bates et al. (2007) suggest, performance is like a “black box”, given its multiple explanations and causal influences, all of which are not clearly understood (Moruku, 2010: 104).

Fourth, David McClelland’s thesis is inconsistent with the human capital theory that has been put forward to explain why developing countries lag behind the Western industrialized countries in economic development (see Psacharopoulos and Patrinos, 2002).

Fifth, recent research highlighted in Hunter and O’Connor (2003) reveal the incidence of “achievement-based vulnerabilities” such as depression and suicidality among people with high expectations and standards of performance (and fail to achieve them). SMEs experience failure (Inang and Ekpeyong, 1992), and their owner managers face discouragement, frustration, learned helplessness (Askim and Feinberg, 2001) and possible “achievement-based vulnerabilities”.

Sixth, and finally, the lack of performance despite achievement motivation may reflect the contention that the need for achievement alone cannot guarantee performance; the owner-manager must also possess entrepreneurial skills to do well (Akeredolu-Ale, 1975: 21). In the present study, it was found that these skills were not updated through continuous training. Consistent with McMahon (1998), the findings of this study demonstrated that the performance (growth) factors of SMEs are a gestalt. This implies that performance is a complex and multidimensional phenomenon. As such, no single theory or practice can


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provide an adequate explanation of the performance (growth) phenomenon.

CONCLUSION

The findings of the present study make important contributions to the literature on entrepreneurship. These findings inform the researcher to question the conventional wisdom on entrepreneurial capability and the psychological antecedents to entrepreneurial performance, as suggested in the need for achievement and goal-setting theories, which are divorced from environmental influences. Thus, it is necessary to apply caution in employing these theories.

In particular, throughout the world, entrepreneurs are known to fail in large numbers (Inang and Ekpeyong, 1992) despite their putative possession of entrepreneurial capability and need for achievement. Consequently, the findings of the present study lead to the questioning of the mythicization, or painting a larger-than-life image, of entrepreneurs (Jackson et al., 2001) as to whether entrepreneurs are peculiarly or uniquely innovative, courageous, efficient, and being able to thrive in chaos or adversity.

Also, the incidence of depression and suicidality related to “achievement-vulnerabilities” among high achievement-

oriented people strengthen the need to question whether the need for achievement should be recommended as a universal value irrespective of context.

In light of the findings of the present study, it is here recommended that the environment be adapted to the performance of SMEs. In connection with this, Meyer-Stamer (1997) had correctly observed that SMEs cannot achieve performance on their own without support from the state. I suggest that this support needs to include, first and foremost, the policy actions of the state towards the adaptation of the business environment for performance. It is also recommended that SMEs learn and acquire dynamic capability to fit in to the dynamic business environment.

The context of the study may well be a limitation. Thus, studies similar to this one should be conducted in other environment contexts. Cross-sectional designs present problems when it comes to prediction of results. Future researchers may, therefore, wish to test the research model with a longitudinal design.

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APPENDICES

Appendix 1: Descriptive Statistics of Latent and Manifest Variables (Scale Properties)

Variable Mean Std. Dev. Min. Max.

Independent Variables (Xi)

Industry (X 1)

1 Customer concentration (V1) 3.28 1.11 0 6.00

2 Supplier concentration (V2) 3.57 1.25 0 6.00

Perceived Environment (X2)

22a Survival hostility (V64) 3.70 1.88 1.00 7.00

22b Price hostility (V65) 3.67 1.70 1.00 7.00

22c Quality hostility (V66) 3.49 1.79 1.00 7.00

Resources (X3)

(i) Resources of the Entrepreneur

12 Management experience (V32) 0.55 1.20 0 7.00

13 Large firm experience (V33) 21.69 137.00 0 1,500.00

14 Rapid growth firm experience (V34) 1.51 1.02 0 9.00

15 Tenure as CEO (V35) 14.08 11.14 0 90.00

16 Age (V36) 41.55 12.26 9.00 76.00

17 Education (V37) 12.30 2.89 6.00 15.00

18 Management training (V38) 2.40 1.31 1.00 6.00

7 Being founder (V11) 2.86 1.22 0 12.00

(ii) Resources of the Enterprise

3 Firm size (employ) in 2007 (V3) 43.96 92.07 3.00 1,000.00

4 Firm size (employ) in 2006 (V4) 29.25 76.06 0 700.00

9 Management team size (V14) 3.50 5.01 0 29.00


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20h Capital availability (V51) 4.04 2.00 1.00 7.00

8 Board size (V12) 6.54 6.87 0 60.00

(ii) Resources of the Entrepreneur’s Network (Network Resources)

19a Bank contact (V39) 4.64 1.70 0 6.00

19b Customers (V40) 5.23 1.21 0 6.00

19c Employees (V41) 4.67 1.45 0 6.00

19d Board (V42) 4.14 1.69 0 6.00

19e Lawyers (V43) 3.48 1.75 0 6.00

Entrepreneur’s Motivation or Attitude (X 5)

(i) Goals

23b Profitability (V71) 4.36 0.83 0 5.00

23c Self-fulfilment (V72) 3.66 1.21 0 5.00

23d Time for family (V73) 3.78 1.00 0 5.00

23e Reap fruits of work (V74) 4.27 0.86 1.00 5.00

Note: (1) Synthetic Variables are in bold print (2) Manifest variables are in tiny print



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Appendix 2: Descriptive Statistics of Latent and Manifest Variables (Scale Properties)

Variable Mean Std. dev. Min. Max.

Independent Variables (Xi)

(ii) Favoured Work-tasks

24a Contact existing customers (V75) 3.69 1.12 0 5.00

24b Developing new products (V76) 3.97 1.11 0 5.00

24c Sales (V77) 4.03 1.08 0 5.00

24d Board work (V78) 3.25 1.29 0 5.00

24e Marketing plans (V79) 3.86 1.01 1.00 5.00

24f Developing strategies (V80) 4.03 1.14 0 5.00

24g Developing New customers (V81) 4.21 1.00 0 5.00

Entrepreneurial Orientation (X 5)

20a Risk-taking 1 (V44) 3.93 1.56 1.00 7.00

20b Risk-taking 2 (V45) 4.01 1.65 0 7.00

20c Pro-activity 1 (V46) 4.15 1.83 0 7.00

20d Pro-activity 2 (V47) 4.35 1.75 0 7.00

20e Pro-activity 3 (V48) 4.20 1.86 0 7.00

20f Innovation 1 (V49) 3.91 1.51 1.00 7.00

20g Innovation 2 (V50) 4.43 1.83 1.00 7.00

Locus of Control (X6)

21a Owner’s beliefs in performance (V60) 3.80 1.66 0 7.00

21b Owner’s improvement on perform. (V61) 3.93 1.73 0 7.00

Entrepreneurial Behaviour

25a Marketing to new customers (V82) 4.03 1.22 0 5.00

25b New marketing practices (V83) 3.82 1.09 0 5.00


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25c Intro new line of products (V84) 3.92 1.20 0 6.00

25d Invest. In new products now in mkt (V85) 3.54 1.33 0 5.00

25e Invest. In new products not in mkt (V86) 3.11 1.39 0 5.00

25f Intro new product ahead of compet. (V87) 3.70 1.39 0 5.00

25g New operating procedures (V88) 3.82 1.12 0 5.00

25h Reorganized firm (V89) 4.02 1.18 1.00 5.00

Dependent Variables (Yi)

Sales Growth (Y1) 172.24 924.17 -99.76 11011

Profit Growth (Y2) 125.41 318.44 -99.50 2400.00

Employment Growth (Y3) 17.31 50.82 -93.33 250.00

Note: (1) Synthetic Variables are in bold print (2) Manifest variables are in tiny print


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