Entrepreneurial locus of control and competitive strategies – The moderating effect of environmental dynamism
Introduction
Research in the past decades into the impact of the chief executive’s personality has revealed that the locus-of-control trait – i.e., the disposition of perceived control – is a stable predictor of a small firm’s performance (e.g., Anderson, 1977, Boone et al., 1996, Brockhaus, 1975, Brockhaus, 1980, Brockhaus, 1982, Kets de Vries, 1977, Lee and Tsang, 2001, Miller and Toulouse, 1986a, Miller and Toulouse, 1986b, Pandey and Tewary, 1979, Powell, 1992). Several scholars show that the locus-of-control personality trait relates to action orientation, proactiveness, transformational leadership, high information-processing abilities, and a proclivity for complex and unstructured tasks (see, for detailed overviews, Boone et al., 1996, Boone et al., 2005, Miller et al., 1982, Spector, 1982). Accordingly, persons with a high level of perceived control (internals) have been associated with entrepreneurial behavior and a preference for innovative strategies (Boone et al., 1996, Brockhaus, 1975, Hansemark, 2003, Kets de Vries, 1977, Miller, 1983, Miller and Toulouse, 1986a, Miller and Toulouse, 1986b, Miller et al., 1982, Mueller and Thomas, 2001), whereas those with a low level of perceived control (externals) have been associated with conservative behavior and a preference for low-cost strategies (Baron, 1968, Boone et al., 1996, Govindarajan, 1989, Spector, 1982). The central thesis of the current study is that these strategy preferences driven by the locus-of-control personality trait may well produce unconventional strategy–environment (mis)matches.
An in-depth examination of why unconventional strategy–environment (mis)matches occur is important, since strategy contingency theorists (Burton and Lauridsen, 2002, Miller, 1988, Miller, 1991, Porter, 1985) claim that firms with misaligned strategies are likely to fail.1 In the present paper, we focus on dynamic versus stable environments, where dynamism is defined with reference to the nature of and speed at which consumer preferences and producer offerings change. Dynamic environments are characterized by major and rapid changes in consumer preferences and producers’ offerings, and stable environments by gradual changes in consumer preferences and producers’ offerings (Miller, 1988). This implies that future consumer preferences and competitor actions are harder to predict in dynamic environments, due to the disruptive and fast nature of changes in the firm’s environment, than they are in stable environments. For instance, firms competing in dynamic industries such ICT or life sciences face tremendous uncertainties about the viability of their competing technologies and products. When sudden changes occur in customer preferences or in their competitors’ core technologies, these companies may face disastrous consequences (Tushman & O’Reilly, 1996). Therefore, strategy contingency scholars suggest that a product innovation strategy is an effective strategy in a dynamic environment in order to meet or anticipate the changes. In contrast, they suggest that such a strategy does not align well with a stable environment. This is because in stable environments there is not much demand for product changes. Pursuing a product innovation strategy in stable environments increases the chance that the company can ultimately not recoup the costs of its product innovations. Accordingly, this strategy–environment misalignment exposes the firm to the risk of failure. Another strategy–environment misalignment occurs when the firm employs a low-cost strategy in a dynamic environment. Products and methods that help to produce against low costs cannot be altered quickly, which exposes the firm’s current products to the risk of obsolescence. Taking the principles of the strategy–environment (mis)alignment argument into account, financers may face high risks when funding entrepreneurs who fail to match their strategies with the extent of dynamic change in their environments.
So far as we know, just a few studies (Miller and Toulouse, 1986a, Miller and Toulouse, 1986b) examined the influence of environmental dynamism on the locus-of-control trait–product innovation strategy relationship. Miller and Toulouse, 1986a, Miller and Toulouse, 1986b report high correlations between internal entrepreneurs and components of product innovation strategies for both high and low perceived environmental dynamism subgroups. However, they do not analyze interaction effects by using moderated regression techniques. Even though their subgroups show quite similar correlations between the locus-of-control trait and product innovation strategies, the form (or slope) of these relationships could be significantly different otherwise (see Cohen & Cohen, 1975, p. 66; Podsakoff, MacKenzie, & Lee, 2003, p. 430). Therefore, the present study takes competitive strategies as a function of the entrepreneur’s locus-of-control personality trait and environmental dynamism in the context of an interaction-effect model. Specifically, we examine the locus-of-control – competitive strategy relationship for two strategic dimensions – i.e., product innovation and low-cost strategies – using objective measures for the moderator environmental dynamism variable.
Strategy contingency theory has produced robust findings as to which type of strategies fit with what type of environment (see above). Similarly, Rotter’s social learning theory (Rotter & Hochreich, 1975) and a great number of empirical studies inspired by this theory have produced robust findings as to which locus-of-control type fit with what type of task environment. This paper argues that the components of Rotter’s social learning theory perfectly align with the very nature of strategy contingency theory, particularly environmental fit reasoning. In essence, Rotter’s social learning theory holds that the individual’s expectancy that certain actions will lead to successful outcomes depends upon the predictability of the task environment (Krovetz, 1974, Rotter, 1966). The level of predictability is an important distinction between stable and dynamic environments. Dynamic environments are less predictable than stable environments, because changes in future consumer preferences and competitor actions are often disruptive, occurring at a fast speed, whilst changes in stable environments occur more gradually over time (Miller, 1988, Tushman and O’Reilly, 1996).
By integrating Rotter’s social learning theory with strategic contingency logic this paper produces a novel perspective on the impact of environmental dynamism on the locus-of-control trait–product innovation strategy relationship. That is, we argue that internal entrepreneurs may perceive that their actions and abilities are more bounded in dynamic environments than in stable environments, because outcomes are more difficult to control due to a higher level of unpredictability in customer preferences and producer offerings. Particularly in environments that are less predictable or more dependent upon chance, social learning theorists suggest that internal individuals tend to perceive that outcomes are less contingent upon their own behavior or more beyond their own control (Krovetz, 1974, Rotter, 1966). In all, this implies that we integrate the personality – environment fit argument from Rotter’s social learning theory into the strategy contingency tradition in a full-blown interaction-effect model. As a result, we introduce a novel theoretical argument, producing new hypotheses that explain the occurrence of unconventional (mis)matches between personality, strategy and environment. The ability to predict the formation of such potentially maladaptive strategies could help both investors and at-risk entrepreneurs to prevent them from happening, and to develop adaptive strategies instead.
Section snippets
Social learning theory
Rotter’s social learning theory holds that a person’s behavior stems from this person’s motivation, regarding behavior to be goal directed (Rotter & Hochreich, 1975, p. 94). Social learning theorists who are studying the locus-of-control personality trait, are generally concerned with the individual’s problem-solving skills as a function of generalized expectancies – i.e., internal versus external control of reinforcement across situations. Internals, those who belief that what happens to them
Data collection procedure
This paper concentrates on small and medium-sized enterprises (SMEs) that are funded by venture capital, where SMEs are defined as firms employing 250 employees or less. Competitive strategy is a highly relevant issue for these firms. Nesheim (2000, p. 46) finds that about 25% of the entrepreneur’s time is spent on raising secondary rounds of capital from the venture capitalist during 1–4 years. Therefore, it is very likely that the entrepreneur is frequently engaged in strategic planning
Results
Table 2 reports the results for our main and product-term effect analyses.9 As is clear from Table 2 step 2, Hypothesis 1 is supported (p < 0.05) for the bi-linear interaction effect of the entrepreneur’s locus-of-control personality trait and environmental dynamism on pursuing product innovative strategies. The estimate of the product term of the entrepreneurial locus-of-control score and the ICT/life sciences dummy
Discussion
Porter took the view in his 1985 book that a company must make a clear choice as to which type of strategy – differentiation or cost leadership – it will pursue in order to achieve above-average performance. This view is widely supported in a number of studies (e.g., Dess and Davis, 1984, Kim and Lim, 1988, Miller, 1988, Miller, 1991, Miller and Friesen, 1986, Robinson and Pearce, 1988), particularly when the firm’s competitive strategy aligns with the environment (e.g., Burton and Lauridsen,
Conclusion
This study shows that personality-environment congruency combinations derived from Rotter’s social learning theory explain the occurrence of unconventional strategy–environment (mis)matches. That is, internal entrepreneurs tend to prefer product innovation strategies in stable environments, whereas external entrepreneurs are likely to opt for low-cost strategies in dynamic environments. Rotter’s social learning theory suggests that internal entrepreneurs who operate in stable industries prefer
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