Entrepreneurial orientation in turbulent environments: The moderating role of absorptive capacity

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Entrepreneurial orientation in turbulent environments: The moderating role of absorptive capacity Andreas Engelen a,∗ , Harald Kube a,1 , Susanne Schmidt a,2 , Tessa Christina Flatten b,3 a b

Department of Strategic and International Management, TU Dortmund, Martin-Schmeisser-Weg 12, 44227 Dortmund, Germany Centre for Entrepreneurship, RWTH Aachen, Kackertstrasse 7, 52072 Aachen, Germany

a r t i c l e

i n f o

Article history: Received 19 November 2012 Received in revised form 4 March 2014 Accepted 5 March 2014 Available online xxx Keywords: Entrepreneurial orientation Absorptive capacity Survey research

a b s t r a c t The literature on entrepreneurial orientation (EO) has confirmed the positive relationship between EO and firm performance and that relationship’s dependence on several contingencies. The present study connects the resource-based view and its dynamic capability extension to introduce absorptive capacity (ACAP) as a moderator of the relationship between EO and firm performance. This theoretically derived research model is empirically validated using survey data from 219 small and medium-sized enterprises in Germany. Our empirical findings are that ACAP strengthens the EO–performance relationship in turbulent markets. © 2014 Elsevier B.V. All rights reserved.

1. Introduction Entrepreneurial activity in both start-up and corporate contexts has been identified as a major engine for the generation of employment and the creation of economic growth and welfare (Wong et al., 2005). Accordingly, there is a strong interest in what entrepreneurial behavior looks like and in its antecedents and concrete consequences. In the corporate context, the literature has examined the construct of entrepreneurial orientation (EO), a strategic posture that reflects the specific processes, practices, and behaviors that allow a firm to act in an entrepreneurial way (Covin and Slevin, 1991; Lumpkin and Dess, 1996). In 1983, Miller introduced EO into the academic literature, conceptualizing the construct along three firm-level dimensions: innovativeness, proactiveness, and risk-taking. Since then EO has developed into one of the most established constructs in the entrepreneurship literature (Wales et al., 2011). A major tenet is that firms with strong EO outperform other firms. However, while many studies and a meta-analysis (Rauch et al., 2009) largely confirm the positive performance contribution of EO,

∗ Corresponding author. Tel.: +49 163 461 35 46. E-mail addresses: [email protected] (A. Engelen), [email protected] (H. Kube), [email protected] (S. Schmidt), fl[email protected] (T.C. Flatten). 1 Tel.: +49 231 755 3150. 2 Tel.: +49 231 755 3460. 3 Tel.: +49 241 80 96222.

a few studies find no positive relationship between EO and performance (e.g., Ireland et al., 2003). Extant research is more consistent in showing that the strength of the EO–performance relationship depends on various contingencies (Lyon et al., 2000), including external conditions (e.g., Zahra and Covin, 1995) and internal variables (e.g., Covin et al., 2006). In terms of the latter, recent research finds that firm-level resources and capabilities, both tangible (e.g., financial resources; Wiklund and Shepherd, 2005) and intangible (e.g., leadership styles; Engelen et al., 2013a), moderate the EO–performance relationship, pointing out the general importance of firm-level resources and capabilities in facilitating the EO–performance relationship. The present study extends research on how EO interacts with firm-level capabilities to increase firm performance by arguing that dynamic capabilities play a central role in converting EO into improved performance. Dynamic capabilities differentiate from “ordinary” resources and capabilities, as they allow the firm to reconfigure its existing resource and capability base (Teece et al., 1997). We argue that, in order to implement inherently uncertain entrepreneurial activities smoothly, a reconfiguration of the existing resources or capabilities that dynamic capabilities can provide is necessary, as the inertia of stable, “ordinary” resources and capabilities may not allow the full potential of an EO to be realized (Eisenhardt and Martin, 2000). The strategic management literature discusses which capabilities qualify as dynamic and has largely agreed that the firm’s absorptive capacity (ACAP) is a major dynamic capability (van den Bosch et al., 1999; Floyd and Lane, 2000; Zahra and George, 2002). ACAP, which refers to “an ability to recognize the value of new information, assimilate it, and

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apply it to commercial ends” (Cohen and Levinthal, 1990; p. 128), is a dynamic capability that appears particularly relevant to EO since a major obstacle in effectively and efficiently implementing entrepreneurial activities is the handling of uncertain situations in which typically established knowledge and information are missing (Lumpkin and Dess, 1996). In order to develop a nuanced understanding of how EO and ACAP interact, we also examine how the turbulence of the market in which the firm operates is related to the interaction of EO and ACAP. We argue that the facilitating role of ACAP on the EO–performance relationship should be strongest in turbulent markets based on the assumption that dynamic capabilities like ACAP are most valuable in dynamic environments (Zahra et al., 2006). In these environments, the generation of new information and knowledge appears particularly important for entrepreneurial firms, as does a timely response to new circumstances. In order to validate our theoretical arguments empirically, we analyze survey data from small and medium-sized companies. The empirical findings provide support for our core expectation that the link between the interaction of EO and ACAP to firm performance strengthens, as market turbulence increases. We contribute to the EO and dynamic capabilities literatures in two major ways. First, in terms of EO literature, we develop a theoretical rationale for how EO interacts with ACAP as a major dynamic capability that is required in order to increase firm performance. In so doing, we link EO to the theory of dynamic capabilities and address Miller’s (2011) call to embrace theories of related disciplines, such as strategic management, in order to clarify which resources and capabilities foster a robust entrepreneurial process. Dynamic capabilities, which have been conceptually expected to be the “key means for linking EO to firm opportunity exploitation and subsequent performance” (Covin and Lumpkin, 2011; p. 861), still require examination in this context. Second, we contribute to the literature of dynamic capabilities. Barreto’s (2010) recent review of the dynamic capability literature claims that it is centrally important to determine whether dynamic capabilities like ACAP lead directly to performance consequences and to understand the dynamic capabilities’ boundary conditions. We establish theoretical arguments and provide empirical validation that the dynamic capability of ACAP interacts with a strategic posture (i.e., EO) in order to reap the full performance benefits of EO and that the degree of market turbulence determines the strength of ACAP’s role. In so doing, we add market turbulence as an important boundary condition to the dynamic capability literature.

2. Theoretical background and research model This study is based on Miller’s (1983) definition of EO as a strategic posture that primarily applies to entry into new businesses. Miller conceptualizes EO as the simultaneous presence of the three dimensions of innovativeness, proactiveness, and risk taking (e.g., Wiklund and Shepherd, 2005). Innovativeness describes a firm’s propensity to experiment with new ideas in order to activate a process that results in new products, services, or technological progress (Covin and Slevin, 1991). Proactiveness is characterized by a high level of opportunity-seeking, ideally ahead of competitors and combined with anticipation of future customer demands. Risk taking refers to bold moves into unknown business areas and/or the commitment of significant resources to business activities under conditions of uncertainty (Lumpkin and Dess, 2001). EO is understood as a firm-wide construct, so most, if not all, firm members are involved in implementing this strategic posture (Wales et al., 2011). There is also agreement that implementing EO is a complex task that requires repeated trial-and-error and experimentation (Covin et al., 2006).

A major interest in the EO literature has concerned how EO improves firm performance. From a conceptual stance, Lumpkin and Dess (1996) argue that entrepreneurial firms achieve superior performance by recognizing new opportunities with potentially large returns, by targeting the most promising premium market segments, and by obtaining first-mover advantages. However, empirical tests of this performance-enhancing role of EO reveal contradictory results. While most studies confirm the performance-enhancing character of EO, a few studies could not determine a positive relationship (e.g., Ireland et al., 2003). Extant research on the EO–performance relationship has more consistently identified various moderating variables that facilitate or inhibit this relationship. Table 1 provides an overview of extant empirical research on these moderators.4 Whereas the first studies in the 1980s and 1990s focus on external factors like environmental turbulence as moderators (e.g., Covin and Slevin, 1989), more recent studies examine the moderating role of internal factors like strategic decision-making styles (Covin et al., 2006; Chririco et al., 2011). Most recently, internal resources and capabilities have gained attention and have been shown to impact the EO–performance relationship, which is in line with Kreiser’s (2011; p. 1026) view that entrepreneurial firms “are more dependent on their ability to fully utilize resources than other types of firms are.” These studies can be divided into research on tangible resources like financial capital (e.g., Wiklund and Shepherd, 2005) and intangible resources like leadership (e.g., Engelen et al., 2013a). The reasoning on why internal resources and capabilities are important for the EO–performance relationship is based on the resource based view (RBV). According to the RBV, firms are unequally distributed bundles of resources (Wernerfelt, 1984), creating resource heterogeneity that persists over time and provides a basis for firm performance (Barney, 1991). The “strategic fit” paradigm from strategic management states that, for each strategic posture (such as EO), there is a set of firm-level resources and capabilities that facilitate the performance effects of the strategic posture (e.g., Slater et al., 2006; Song et al., 2007; Desarbo et al., 2005). In other words, firms should allocate their investments in resources and capabilities consistent with their strategic postures (Teece, 2012). In keeping with this rationale, strategic orientation (in our case, EO) describes what a firm strategically does, and the capabilities capture how this strategy can be implemented and deployed (Slater et al., 2006). In terms of EO, Habbershon et al. (2010; p. 21) support the notion that an entrepreneurial firm requires specific resources since “resources and entrepreneurial orientation taken on their own are necessary but not sufficient conditions for long-term success. Without resources, entrepreneurial orientation lacks the means to be realized.” However, research has recognized certain shortcomings of the RBV, especially for firms that act in turbulent environments, which is likely to be the case for many entrepreneurially oriented firms (Covin and Slevin, 1989). Therefore, the dynamic capability perspective was developed to extend the RBV and to answer the question concerning what changes or recombines the resource base when the firm’s environment is characterized by constant change (Teece and Pisano, 1994; Barreto, 2010). Central to the definition of a firm’s dynamic capabilities are the organizational and strategic routines by which its existing resources base is reconfigured (Winter, 2003). However, these dynamic capabilities have largely been ignored in EO research, an observation recently confirmed by Covin and Lumpkin (2011), who speculate that dynamic capabilities

4 We identified this list of studies by first taking all studies of the meta-analysis on the EO-performance relationship from Rauch et al. (2009) into account and then studying the reviews on the EO literature from George and Marino (2011) and Wales et al. (2013) to add more recent studies.

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Dependent variables

Moderator variable

Findings

Covin and Slevin (1988)

• EO

• Firm performance

• Organizational structure

• EO top management style positively (negatively) affects performance of organically (mechanistically) structured firms.

Covin and Slevin (1989)

• Organization structure • Strategic posture

• Firm performance

• Environmental hostility

• Firms’ performance benefits from an entrepreneurial strategic posture when they face hostile environments. • Firms’ performance benefits from a conservative strategic posture when they face benign environments.

Covin and Covin (1990)

• Stage of industry life cycle • Strategic posture • Organization structure

• Firm performance • Strategic posture • Organizational structure

• Stage of industry life cycle

• Strategic postures vary significantly over the industry life cycle, with firms in emerging industries having the most entrepreneurial strategic postures. • Industry life cycle moderates the relationship between strategic posture and performance (stronger for emerging industries than for mature industries).

Covin et al. (1994)

• Strategic posture • Organizational structure • Competitive marketing tactics

• Firm performance

• Strategic mission

• Strategic mission moderates the relationship between management decisions and firm performance. • Performance consequences of entrepreneurial strategic postures are greater for more build-oriented strategic missions than for less build-oriented strategic missions.

Zahra and Covin (1995)

• Corporate entrepreneurship

• Firm performance

• Time • Environmental hostility

• Corporate entrepreneurship has a positive (and, over time, increasing) impact on financial performance. • Corporate entrepreneurship is particularly effective for firms in hostile environments.

Becherer and Maurer (1997)

• EO • Marketing orientation

• Firm performance • Marketing orientation

• Environmental turbulence • Environmental hostility

• Marketing orientation and EO are positively and significantly correlated. • EO positively impacts firm performance. • Environmental turbulence and hostility quasi-moderate the relationship between marketing orientation and EO.

Barrett and Weinstein (1998)

• EO • Firm flexibility • Market orientation

• Firm performance • Firm flexibility • Market orientation

• EO • Firm flexibility • Market orientation

• EO, flexibility, and market orientation are all positively correlated with each other and with firm performance.

Zahra and Garvis (2000)

• International corporate entrepreneurship (ICE)

• Firm performance

• Environmental hostility

• There is a positive relationship between EO and firm performance. • Environmental hostility has a curvilinear moderating effect on the ICE–performance relationship.

Lee et al. (2001)

• EO • Technological capabilities • Social capital • Financial resources

• Firm performance

• External networks

• EO positively affects performance.

Lumpkin and Dess (2001)

• EO (proactiveness and competitive aggressiveness) • Environment • Stage of industry life cycle

• Firm performance

• Environmental dynamism • Environmental hostility • Stage of industry life cycle

• Proactiveness is positively related to performance. • Competitive aggressiveness is poorly related to performance. • Competitive aggressiveness is helpful in the mature stages of an industry. • EO’s dimensions vary independently.

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Table 1 Moderating variables of the EO–performance relationship.

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Moderator variable

Findings

Wiklund and Shepherd (2003)

• Knowledge-based resources • EO

• Firm performance

• EO

• EO enhances the positive relationship between knowledge-based resources and firm performance. • EO positively affects firm performance.

Dimitratos et al. (2004)

• EO

• International performance

• Domestic environment • Foreign environment

• There is a positive relationship between entrepreneurship and international performance that is positively moderated by the level of uncertainty in the domestic country.

Richard et al. (2004)

• Cultural diversity (race and gender)

• Firm performance

• EO

• Innovativeness positively and risk-taking negatively moderate the nonlinear relationship patterns between racial and gender heterogeneity and firm performance.

Wiklund and Shepherd (2005)

• EO

• Firm performance

• Environmental dynamism • Access to financial capital

• EO positively influences firm performance. • EO positively influences firm performance when companies face severe constraints like limited financial resources and a stable environment.

Covin et al. (2006)

• EO

• Firm performance

• Participation in strategic decision-making • Mode of strategy formation • Strategic learning from failure

• The EO–performance relationship is positive. • The EO–performance relationship is more positive when firms employ autocratic decision-making and exhibit an emergent strategy-formation process.

Lumpkin et al. (2006)

• EO

• Firm performance (revenue and employee growth)

• Firm age

• Age negatively moderates the relationship between risk-taking and performance. •Age positively moderates the relationship between competitive aggressiveness and proactiveness and between aggressiveness and performance.

Walter et al. (2006)

• Network capabilities • EO

• Firm performance

• Network capabilities • EO

• A spin-off’s EO fosters competitive advantages. • Network capabilities strengthen the relationship between EO and spin-off performance.

Moreno and Casillas (2008)

• Strategy • EO • Environmental dynamism • Environmental hostility

• Firm growth strategy

• Environmental dynamism • Environmental hostility • Expansion based on new products and technology • Availability of resources

• There is no significant relationship between EO and firm growth. • Greater EO favors the use of expansion strategies.

Runyan et al. (2008)

• EO • Small business orientation

• Firm performance

• Longevity

• EO and small business orientation are unique constructs. • EO is positively associated to the firm performance of only younger firms. • Longevity moderates the relationships of EO and of SBO to small business performance.

Stam and Elfring (2008)

• EO

• Firm performance

• Intra-industry social capital • Extra-industry social capital

• Bridging ties positively moderates the EO–performance relationship. • For firms with high levels of bridging ties, the EO–performance relationship is stronger when network centrality is high.

Richard et al. (2009)

• EO

• Firm performance

• CEO’s position tenure • CEO’s industry tenure

• EO positively affects firm performance. • CEO’s industry tenure positively and CEO’s position tenure negatively moderate this relationship.

De Clercq et al. (2010)

• EO

• Firm performance

• Internal social exchange processes

• EO is positively linked to firm performance. • The EO–performance link is stronger for higher levels of procedural justice, trust, and organizational commitment and when the organization’s social context comes closer to an “ideal.”

Chririco et al. (2011)

• EO • General involvement • Participative strategy

• Firm performance

• EO • General involvement • Participative strategy

• EO and participative strategy have positive effects on performance. • EO and generational involvement interact to affect performance negatively.

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Table 1 (Continued)

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Independent variables

Dependent variables

Moderator variable

Findings

Su et al. (2011)

• EO

• Firm performance

• Firm type (new venture vs. established firm)

• The EO–performance relationship has an inverse U shape in new ventures but is positive in established firms.

Chaston and Sadler-Smith (2012)

• Entrepreneurial cognition (intuition, rationality) •EO • Firm capability

• Firm capability • EO • Sales growth

• Market conditions

• In highly intense markets, firms with a low EO show the lowest growth, whereas firms with a high EO show the highest growth.

Kraus et al. (2012)

• EO

• SME business performance

• Market turbulence

• Only proactiveness has a direct impact on performance. • The interaction of innovativeness with turbulence is significantly positive. • The interaction of risk taking with turbulence is significantly negative.

Engelen et al. (2013a)

• EO

• Firm performance

• Transformational leadership behavior

• EO is positively associated with firm performance. • This relationship is positively moderated by four transformational behaviors, regardless of national setting. • The higher top management scores on all transformational leadership behaviors, the greater EO’s performance consequences.

Anderson and Eshima (2013)

• EO

• SME firm growth

• Firm age • Intangible resources

• The relationship between EO and firm growth is strongest among younger SMEs. • Higher levels of intangible resources relative to industry rivals positively strengthen the EO–performance relationship. • The relationship between EO and firm growth is strongest among younger SMEs that have higher levels of intangible resources than their peers.

Engelen et al. (2013b)

• EO

• Firm performance

• CEO narcissism

• EO is positively associated with firm performance. • This relationship is weakened when the CEO has narcissistic traits.

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Table 1 (Continued)

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most valuable for the EO–performance relationship in turbulent markets.

Absorptive capacity H2

Market turbulence

3. Hypotheses derivation

H1 Entrepreneurial orientation

Firm performance

Controls: Firm size, firm age, ownership, industry sector, respondent position, respondent tenure, market orientation.

Fig. 1. Conceptual framework and hypotheses.

are the enabling mechanism for entrepreneurial firms to exploit the opportunities they discover and act accordingly. An ongoing discussion in the dynamic capability research stream is the question concerning which organizational skills are actually dynamic capabilities (Eisenhardt and Martin, 2000). One concept various researchers agree in a dynamic capability is ACAP (George and Zahra, 2002; Jansen et al., 2005) so we use ACAP as a moderating factor to extend the current research perspective regarding the EO–performance relationship. ACAP is defined as “an ability to recognize the value of new information, assimilate it, and apply it to commercial ends” (Cohen and Levinthal, 1990; p. 128), based upon related knowledge in the firm. ACAP is a prime example of a dynamic capability since it is embedded in a firm’s routines, and it combines the firm’s capabilities in such a way that they build on each other to influence “the firm’s ability to create and deploy the knowledge necessary to build other organizational capabilities (e.g., marketing, distribution, and production)” (Zahra and George, 2002; p. 188). ACAP is generally understood as a process of steps that are closely related and that build one aggregate construct. While the number of steps that underlie ACAP is subject to debate (Lane et al., 2006), the steps from Zahra and George (2002)—acquisition, assimilation, transformation, and exploitation—are among the most prominent and comprehensive in that they cover all activities identified in other ACAP process definitions. Acquisition refers to a firm’s ability to identify and obtain knowledge from external sources (e.g., trade fairs, suppliers, competitors) (Todorova and Durisin, 2007). Assimilation describes the firm’s ability to develop processes and routines useful in analyzing, interpreting, and understanding externally acquired knowledge (Szulanski, 1996). Transformation focuses on the development and refinement of routines that facilitate the combination of existing knowledge with acquired and assimilated knowledge for future use (Zahra and George, 2002). Finally, exploitation is the use of knowledge for commercial ends (Cohen and Levinthal, 1990). A central tenet of the ACAP construct is that it encompasses an outward-looking component that deals with the identification and generation of useful external knowledge and information and an inward-looking component that deals with how this knowledge is analyzed, combined with existing knowledge, and implemented in new products, new technological approaches, or new organizational capabilities (Cohen and Levinthal, 1990; Escribano et al., 2009). Guided by the “strategic fit” paradigm, our research model, depicted in Fig. 1, links EO with firm performance and integrates ACAP as a moderator of this relationship. To facilitate a nuanced understanding of this relationship, we also consider the degree to which this moderation depends on the turbulence of the market in which the firm operates. Theoretical arguments in the strategic management literature suggest that dynamic capabilities play a particularly important role in turbulent environments since these environments require the firm to adapt constantly to new conditions (Eisenhardt and Martin, 2000), suggesting that ACAP may be

Guided by the “strategic fit” paradigm and the understanding of the EO and the ACAP construct as explained in the previous section, we now develop theoretical arguments concerning why the success of entrepreneurial firms increases as the firm’s ACAP increases. In so doing, we consider the outward- and inward-looking components of ACAP and relate these perspectives to the theoretical rationales for why EO leads to increased performance. Entrepreneurial firms are typically more successful than nonentrepreneurial firms since entrepreneurial firms are able to pursue high-quality opportunities in the marketplace (Lumpkin and Dess, 1996). A high degree of ACAP in entrepreneurial firms can give these firms constant access to new knowledge and information about opportunities via various formal and informal channels (e.g., customers, university cooperations; Rothaermel and Alexandre, 2009), increasing the number and the quality of opportunities entrepreneurial firms can pursue. Anderson and Eshima (2013) argue that an entrepreneurial firm’s success increases with its number of opportunities since a higher number of opportunities increases the chance of high-quality opportunities with significant potential. Further, information about new opportunities can be evaluated by firms with ACAP on the basis of their extensive existing knowledge base (Cohen and Levinthal, 1990; Cassiman and Veugelers, 2006) such that ACAP ensures that the newly acquired information is correctly interpreted and the “right” conclusions about these opportunities are drawn (Zahra and George, 2002). While these aspects of ACAP ensure that a high number of highquality opportunities are available and that they are correctly evaluated, the extensive knowledge base and the ability to interpret and evaluate new information about emerging opportunities enable a firm to select and pursue opportunities efficiently at comparatively low cost. In a similar vein, extant research reports that radical innovations tend to be much more successful when firms can build upon prior related knowledge than when they cannot. Sorescu et al. (2003) add that firms with large asset and knowledge bases see lower costs in developing and introducing such radical innovations. However, when entrepreneurial firms do not have ACAP, they are likely to have fewer opportunities and to evaluate them inappropriately since the abilities and the knowledge base from prior experience are missing, all inhibiting the EO–performance relationship. Further, the cost of implementing innovative activities is likely to be higher when no prior experience or knowledge is available, inhibiting the EO–performance relationship. Successful entrepreneurial firms engage in risky activities (Lumpkin and Dess, 2001), and since EO is a firm-wide phenomenon, entrepreneurial activities are typically implemented by a large number, if not all, employees, so the effective implementation of EO depends on their willingness to engage in such activities (Wales et al., 2011). Non-managerial employees in entrepreneurial firms often resist engaging in these risky endeavors (Monsen and Boss, 2009), so a high degree of firm-level ACAP ensures that all employees, managerial and non-managerial, involved in implementing entrepreneurial activities have the knowledge required to determine the risk rationally and to acquire and interpret existing and new information and knowledge to minimize—or at least handle—risk (Jansen et al., 2005). Further, firms with a high degree of ACAP tend to have more access to and engage more strongly in alliances than other firms do (Lane et al., 2001; Rothaermel and Alexandre, 2009). When pursuing risky endeavors in uncertain environments, alliances allow firms to share risk and profit from the

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knowledge and expertise of alliance partners in other areas, such as unfamiliar markets (Simonin, 1999). If employees do not have this knowledge and the ability to interpret and act upon it when implementing risky endeavors, they may overestimate the risk and refrain from pursuing these activities, inhibiting the performance potential of EO (Barringer and Bluedorn, 1999). Further, entrepreneurial firms outperform non-entrepreneurial firms because entrepreneurial firms can realize first-mover advantages, that is, create a monopoly-like situation with high returns for a specific period of time before the competition catches up (Lumpkin and Dess, 2001). First movers typically operate in uncertain environments where there is no data from prior experiences (Kerin et al., 1992). The risk inherent in this situation can be mitigated by ACAP since the outward-looking component supports the rapid generation of insights on the new environment from diverse sources. The inward-looking components ensure that the first insights gained from a first-mover market entry are correctly interpreted based on an extensive knowledge base that might even contain information on similar market entries in related environments that can be adapted and applied (Cohen and Levinthal, 1990; Escribano et al., 2009). The full performance potential of first-mover activities can also be strengthened by ACAP’s contribution to rapid, flexible reactions before a market window closes or the opportunity loses attractiveness (Rothaermel and Alexandre, 2009). A firm with a high degree of ACAP has strong communication and cooperation routines among its employees (Zahra and Hayton, 2008), which allows the entry of a new innovative product to the marketplace to be faster and more flexible than is possible when there are conflicts and communication barriers within the firm (De Clercq et al., 2010). Further, a strong level of communication and knowledge dissemination in the firm can help to add and combine diverse views (e.g., from different functional backgrounds) on an opportunity, which might add value to the opportunity (Kearney et al., 2009). Entrepreneurial first-movers that lack ACAP might need longer to collect experiences and might not be able to interpret these data appropriately, which would delay these firms’ ability to correct market-entry activities (e.g., in terms of choosing markets or product properties), opening the chance to later entrants and reducing the performance potential of entrepreneurial activities. Entrepreneurial firms also achieve superior performance because they can target premium segments ahead of the competition with their innovative products and reap above-average returns in these segments (Lumpkin and Dess, 1996). ACAP can support these activities by acquiring external information about market segments to determine which are the most promising premium segments and how they can best be addressed, such as in terms of marketing mix (Zahra and George, 2002). Further, premium segments are typically demanding customers who want “state-ofthe-art” products. Entrepreneurial firms with strong ACAP typically have the ability to leverage their network contacts (e.g., Tsai, 2001) in order to learn the newest trends in terms of these products or their underlying technologies, to understand this new information, and to integrate it into the product, increasing the performance potential of EO in these premium segments. If a firm with a high degree of EO does not have ACAP, it may not identify the most promising segment or not be able to react to current trends in the industry, limiting the performance potential of a given degree of EO (Covin et al., 2006). Finally, firms with a high degree of EO are typically good at conducting trial-and-error and experimentation processes. Covin et al. (2006) state that the ability to engage in such processes in the inherently uncertain environments of entrepreneurial firms is a major condition for converting any degree of EO into improved firm performance. A high degree of ACAP ensures that entrepreneurial firms recognize early when an innovative product brought proactively to the marketplace does not meet customer requirements, making a

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prompt correction possible (Liao et al., 2003). ACAP also enables the firm to interpret and assimilate information about a threatening failure of an innovative product rapidly in order to integrate these new insights into the product and make the necessary corrections (e.g., in terms of the product’s properties, target markets, or marketing activities), increasing EO’s performance contribution (Cohen and Levinthal, 1990). This notion is line with learning literature, which states that learning is more effective when there is base of prior knowledge and experience from prior learning efforts (Anderson et al., 1984). ACAP may even allow the firm to build new firm-level resources or capabilities as a response to these corrections (Zahra and George, 2002). Finally, firms with a strong degree of ACAP learn from failures and trial-and-error processes so the firm’s knowledge base is stronger for the next trial-anderror process. This suggestion is in line with McGrath’s (1995) observation that successful entrepreneurial processes are often accompanied by disappointments and errors that, when the right learning effects are derived, can strengthen future entrepreneurial activities. Entrepreneurial firms with no ACAP might overlook necessary corrections or, if they do recognize problems, might not be able to interpret them correctly or act on them in a timely manner, inhibiting EO’s positive performance potential. Overall, we conclude that the ability to acquire new knowledge and information and to react to this information, all based on prior information and knowledge in the firm, facilitate the successful conversion of EO into improved firm performance. Therefore, we state: Hypothesis 1. ACAP positively moderates the relationship between EO and firm performance. Next, we examine a boundary condition of ACAP’s role on the EO–performance relationship by investigating how market turbulence impacts this relationship (Govindarajan, 1988). Market turbulence refers to “the rate of change in the composition of customers and their preferences” (Jaworski and Kohli, 1993; p. 57). In markets with low turbulence, changes in customers and their preferences happen slowly, while firms that operate in turbulent markets must frequently improve their offerings and innovate in order to respond to customers’ rapidly changing preferences (Jaworski and Kohli, 1993; Slater and Narver, 1994). The literature on dynamic capabilities conceptually argues that those capabilities are likely to be even more valuable in dynamic market environments than in other environments because dynamic capabilities allow the firm to deal with the turbulence and uncertainty in these environments by reconfiguring existing resource bases to fit the new circumstances (Teece et al., 1997; Zahra et al., 2006). Based on these insights, we develop arguments concerning how market turbulence is related to ACAP’s moderation on the EO–performance relationship. In deriving H1, we argued that ACAP is important in leveraging EO’s full potential since ACAP helps to identify opportunities and to clarify and interpret them internally. This ability appears to be even more important when market turbulence is strong than when it is weak. In turbulent environments, customer behavior and competitor actions change constantly, which implies that opportunities also emerge regularly, such as when the customers’ shopping preferences, to which entrepreneurial firms must react, change (Helfat et al., 2007). Further, in turbulent environments, the value of opportunities is less obvious at first sight such that experience, prior knowledge, and internal interpretation capabilities are necessary if the high-potential opportunities are to be selected and pursued rather than less attractive opportunities (Shane, 2000). Turbulent environments also require that opportunities are acted upon quickly since the competition is likely to react and customers are likely to change their preferences again. Based on prior knowledge and experience, ACAP ensures that the entrepreneurial firm

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quickly understands and commercializes promising opportunities (Zahra and George, 2002). When the market is less turbulent, only a few opportunities are present and the environment’s complexity is reduced such that entrepreneurial firms face few difficulties in selecting opportunities, making ACAP a less critical capability (Zahra et al., 2006). Similar arguments apply to how ACAP might strengthen EO’s first-mover advantages. In turbulent markets, a first-mover advantage can be endangered easily by competitor moves such that entrepreneurial firms realize the full performance potential of EO only when ACAP enables these firms to commercialize new products early, maximizing the time before the second entrant follows (Slater and Narver, 1994). When competitors’ lethargy in changing strategy in stable markets reduces the danger of second entrants, the entrepreneurial firm’s need for ACAP is reduced. We also argued that ACAP supports entrepreneurial firms in finding the most promising premium segments, which might be especially difficult to spot in turbulent markets, where customer behaviors and preferences change regularly and quickly (Haleblian and Finikelstein, 1993). When there is little market turbulence (or none at all), even entrepreneurial firms that have no ACAP can find these premium segments, either because the segments have not changed over time and are well-known or because the market situation is not complex and the identification and evaluation of premium segments is easy. Finally, ACAP is expected to facilitate the trial-and-error experimentation processes that are part of any entrepreneurial activity (Covin et al., 2006). Turbulent markets in particular may require these processes since market conditions are difficult to evaluate and change often, which requires that efficient trial-and-error processes are undertaken regularly. Without ACAP, entrepreneurial firms are likely to have problems in turbulent markets since they have difficulty evaluating their steps in the marketplace (i.e., the trial) and understanding whether these steps are successful (i.e., the error) (Rerup and Feldman, 2011). In turbulent markets interpretation and correction processes that take too long can be fatal, but customers in non-turbulent environments tend to be less demanding, which requires the firm to make fewer corrections (Jaworski and Kohli, 1993). Overall, we conclude that the facilitating role of ACAP on the EO–performance relationship derived in H1 are consistent with the nature of turbulent markets, while non-turbulent markets impose less challenging and complex conditions on entrepreneurial firms such that they can be successful with less ACAP. Therefore, we state: Hypothesis 2. The moderation of ACAP on the relationship between EO and performance is stronger when market turbulence is high than when it is low. 4. Method 4.1. Data collection technique and sample composition We generated primary data by conducting an online survey of 804 SMEs in Germany randomly chosen from the database of the German Chamber of Commerce, in which membership is mandatory in Germany. SMEs are suitable for our study since they have fewer constraints in making decisions than large companies have because of SMEs’ fewer intervening levels of managers or intervening boards of external directors (Ling et al., 2008). In addition, Germany is a suitable environment in which to examine our model because empirical research shows that EO is positively associated with firm performance in the German context (e.g., Walter et al., 2006). The survey was fielded over a period of three months. We identified CEOs and members of their top management teams (TMT) as

suitable key informants concerning a firm’s knowledge processes and organizational aspects since they have a good overview of the entire organization (Kumar et al., 1993). Following Dilman (2000), we sent a member of the TMT of each firm an email with a survey invitation and a letter that explained the background and purpose of our research. We took several measures to increase the response rate, offering participants the opportunity to answer the survey using an offline questionnaire and to return it by regular mail, facsimile, or email; offering respondents a report of our findings, including descriptive statistics and an anonymous comparison of the participating companies; and sending two successive personalized reminder emails to all potential participants who had not submitted their questionnaires. In the end, we received results from 219 of the 804 firms that we invited to complete the survey (27% response rate). The industry distribution of our responding firms reflects the overall industry distribution in Germany in general. In an effort to enrich the primary data with objective data on the surveyed firms’ performance, we retrieved secondary financial performance data for 34 companies by leveraging Hoover’s database and scanning individual company websites. This validity check showed a positive and significant correlation between the aggregated performance index and the secondary financial performance data (r = .36, p < .05). Both correlations from these triangulation analyses are in Cohen’s (1988) “acceptable range.” We follow the US size standard for SMEs, which defines SMEs as companies with 500 or fewer employees. In accordance with that definition, we excluded 23 firms that reported having more than 500 employees, resulting in 196 firms used for our hypothesis testing. In this sample, 60 percent of the questionnaires were answered by the CEO, 14 percent by board members, 6 percent by managers who report directly to the executive board, 14 percent by those who hold another management position, and 2 percent by those who hold a non-management position (Table 2). 4.2. Tests for potential biases We tested for a potential non-response bias by dividing the answers for our main constructs (performance, EO, ACAP, and market turbulence) into groups of early and late respondents and then testing the means of early and late respondents, following Armstrong and Overton (1977). Since we found no significant statistical differences, we are confident that non-response bias is not a problem in our sample. Chandler and Hanks (1993) find that self-reports from top management team members of small firms are reliable and valid. However, since our study relies on a single key informant, we included an item to validate the respondents’ reliability by asking them to indicate how knowledgeable they felt in answering the questionnaire using a 7-point Likert scale ranging from 1 (very low) to 7 (very high). A mean score of 5.6 points shows that our respondents generally felt knowledgeable in answering the questions. Less than four percent of all respondents rated their knowledge below 4. Taken together, the results mitigate concerns regarding informant bias in our sample. In order to account for a potential common method bias, we followed Podsakoff et al. (2003) in including several procedural remedies. We included only well-established item sets and reduced the impact of contextual cues in our questionnaire by using controls and unrelated questions as separators between questions for dependent and independent variables (Fulmer et al., 2008). We also assured the respondents that answers are neither right nor wrong and allowed anonymous participation in our survey. Further, we applied the marker variable test (Lindell and Whitney, 2001) using the variable which captures the degree to which the respondent felt knowledgeable in answering the

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A. Engelen et al. / Research Policy xxx (2014) xxx–xxx Table 2 Sample composition. Firm employees Number of full-time equivalents

Percentage (%)

Cumulative percentage (%)

<10 10–50 51–100 101–250 251–500 Missing values

5.1 39.8 19.9 20.4 5.6 9.2

5.1 44.9 64.8 85.2 90.8 100

Firm age Years since foundation

Percentage (%)

Cumulative percentage (%)

<5 5–10 11–15 16–20 21–50 >50 Missing values

.5 7.7 8.7 9.7 39.8 30.6 3.1

.5 8.2 16.8 26.5 66.3 96.9 100

Industry sector

Percentage (%)

Cumulative percentage (%)

Construction Manufacturing Wholesale Service Retail Other

7.7 37.8 7.1 32.1 3.6 11.7

7.7 45.4 52.6 84.7 88.3 100

Respondents’ positions

Percentage (%)

Cumulative percentage (%)

CEO Board members (except CEO) Direct report to the board Other management position Other Missing values

60.2 14.3 6.1 14.3 2.0 3.1

60.2 74.5 80.6 94.9 96.9 100

questionnaire (“respondent reliability”), which is not theoretically linked to any of the other constructs as a theoretically unrelated marker variable. Specifically, we adjusted the correlations among the main constructs in our model using the marker variable and found only little change between the pairwise correlations of the main constructs and the partial correlations that included the marker variable. 4.3. Measures The questionnaire used established scales to measure our constructs. We translated these scales, written originally in English, into German following Brislin’s (1980) forward and backward translation approach to ensure consistency with the original measures and avoid mistranslations. We also assessed the equivalence of the constructs and precision in the language in terms of the German culture by running a pretest of all translated items with a group of German researchers, after which we implemented minor changes in wording. We analyzed the internal consistency reliability of our main constructs using Cronbach’s alpha, which ranged from .66 to .88. The composite reliability (CR) of our main constructs ranged from .81 to .92, and the average variance extracted (AVE) ranged from .50 to .73. A full list of all constructs and corresponding items with Cronbach’s alpha and CR values is provided in the Appendix. Entrepreneurial orientation. We measured EO using a nine-item forced-choice scale developed by Covin and Slevin (1989) based on Miller’s (1983) conceptualization of the three dimensions of

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innovativeness, proactiveness, and risk-taking. We measured EO as a unidimensional and reflective construct (George and Marino, 2011; Rauch et al., 2009). We eliminated one item of the EO scale because of low factor loadings in order to ensure measurement reliability, as shown in the Appendix. Absorptive capacity. We measured ACAP using Jansen et al.’s (2005) scale, which draws on the four ACAP dimensions defined by Zahra and George (2002). We aggregated the four dimensions of acquisition, assimilation, transformation, and exploitation to a composite score for each firm. All twenty-one items were measured on a 7-point scale that ranged from “strongly disagree” to “strongly agree.” We eliminated two items of the ACAP scale because of low factor loadings in order to ensure measurement reliability. We estimated one composite score for ACAP since the four dimensions showed high positive correlations (ranging from .56 to .74), suggesting a one-factor structure. Extant literature has often measured ACAP through proxies like the firm’s R&D intensity (e.g., Cohen and Levinthal, 1990; Drejer and Vinding, 2007; Tsai, 2009). The use of a perception-based ACAP measurement has several advantages over these proxies. In particular, the insight that ACAP is considered a process of related steps (Zahra and George, 2002) makes it questionable whether any single proxy can fully capture ACAP’s complexity. Moreover, investment in R&D is only one origin of ACAP; other important sources, such as employee skills and organizational memory, contribute significantly to a firm’s overall ACAP but are largely neglected by proxies (Flatten et al., 2011). Based on these concerns, Lane et al. (2006) call for an empirical exploration of ACAP in a non-R&D context using metrics that capture every dimension and indicate that the use of proxies leads to treating ACAP as a static resource and not as a process or capability. Applying the perceptual measurement of Jansen et al. (2005) enables us to capture ACAP’s effects as a dynamic capability empirically, which is in line with our theoretical arguments. Firm performance. We used a primary and secondary data approach to measure performance. In the primary data approach, we measured the aggregated performance index that asks respondents to use a 7-point Likert scale (Vorhies and Morgan, 2005) to compare themselves to their competitors. We also asked the respondents for financial indicators (current profitability) and non-financial indicators (customer satisfaction and market effectiveness) and operationalized the aggregated performance index as the mean of these dimensions. Market turbulence. We measured market turbulence based on Jaworski and Kohli’s (1993) six items using a 7-point Likert scale. We eliminated one item because of a low factor loading (Hulland, 1999). Controls. We included seven control variables in our analysis in order to control the effects of environmental and organizational influences: firm size, operationalized as the logarithmically transformed number of employees; firm age, calculated as the number of years since the firm’s foundation; firm ownership, operationalized as a dummy variable for whether the firm is publicly traded or not; industry, operationalized as a dummy variable for the construction, manufacturing, wholesale, service, and retail industries, and a reference category of other industries (agriculture, mining, transportation, finance, insurance, real estate, and public administration); respondent’s position, operationalized as a dummy variable for whether the respondent is the firm’s CEO or not; respondent’s experience, calculated as the number of years the respondent has worked for the company; and the firm’s market orientation, generated by aggregating the four dimensions of a firm’s ability to analyze the market and manage market information, an indicator from Vorhies and Morgan’s (2005) marketing capability scale. Incorporating this last control, market orientation, is important since research shows that EO and market orientation

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Table 3 Descriptive statistics and construct intercorrelations (square root of AVE in the diagonal).

1 2 3 4 5 6 7 8

Construct

Mean

SD

1

2

3

4

5

6

7

Performance EO ACAP Market turbulence Firm size Firm age Market orientation Respondent tenure

5.00 4.24 5.05 4.15 3.93 44.62 4.09 16.52

.74 1.13 .91 1.14 1.06 36.00 1.01 9.72

.77 .38 .53 .12 .09 −.10 .39 .02

.84 .48 .37 .07 −.14 .35 .04

.86 .26 .02 −.11 .43 .02

.71 −.08 −.14 .07 .05

.31 .06 .10

−.00 .27

.82 −.04

Note: SD, standard deviation.

interact in impacting firm performance (Atuahene-Gima and Ko, 2001; Bhuian et al., 2005; Li et al., 2008). 5. Results In order to test our measures for discriminant validity we have calculated the square roots of AVEs for all multi-item constructs (Table 3). The results show that, for all constructs, each correlation of one construct with another is smaller than the square roots of its AVE, indicating discriminant validity for our measures (Fornell and Larcker, 1981), so our measured concepts differ significantly from each other (Bagozzi and Phillips, 1982). Discriminant validity applies particularly to our core constructs of EO (square root of AVE: .84) and ACAP (square root of AVE: .86), which correlate at .48. We also conducted a factor analysis and found that all items and dimensions load on their respective constructs. The three EO dimensions’ loadings on one factor range from .80 to .84, while the four ACAP dimensions’ loadings on one factor range from .84 to .91. We used stepwise regression analysis to test our hypotheses. We calculated the variance inflation factors (VIF) for all regressions in our model to test for multicollinearity. All VIF values were

below 4.5—lower than the threshold of 10—indicating no concerns regarding multicollinearity (Aiken and West, 1991). We used meancentered variables for all controls and independent variables in order to remedy potential multicollinearity issues. See Table 4 for the results of all regressions from models 1–4. Model 1 shows the results for the regression that contains only control variables. Model 2 adds EO as the independent variable and reveals a significant and positive relationship between EO and performance (ˇ = .17, p < .01), results that are in line with prior research and with conceptual arguments on the EO–performance relationship (Rauch et al., 2009). The explanatory power of the model increases when 2 = .05, p < .01). EO is introduced (Radj H1 predicted that ACAP moderates the EO–performance relationship. Model 3 tests the hypothesis by adding the interaction terms between ACAP and EO, calculated by multiplying the meancentered ACAP and EO scores for each firm. The results show that ACAP positively moderates the EO–performance relationship (ˇ = .08, p < .10). We also conducted a simple slope test, following Aiken and West (1991), and found that the relationship between EO and firm performance is positive when ACAP is high (b = .17, t = 2.29, p < .05), whereas there is no significant effect of EO on firm

Table 4 Results of hierarchical regressions with firm performance as dependent variable. Variables

Model 1

Model 2

Model 3

Model 4

Controls Firm size (in employees) Firm age Ownership (publicly traded) Industry dummy (Construction) Industry dummy (Manufacturing) Industry dummy (Wholesale) Industry dummy (Service) Industry dummy (Retail) Respondent position Respondent tenure Market orientation

.08 −.00* .21 .06 .31 .20 .27 .20 .08 .00 .31**

.06 −.00† .19 .08 .28 .15 .27 .32 .04 .00 .24**

.04 −.00 .17 .22 .34† .20 .30 .43 −.03 .00 .13*

.04 −.00 .25 .19 .19 −.08 .19 .39 .01 −.00 .11†

Main effects Entrepreneurial orientation (EO) Absorptive capacity (ACAP) Market turbulence (MT)

.17**

Interaction effects H1: EO × ACAP EO × MT MT × ACAP H2: EO × ACAP × MT F R-Square Adjusted R-square Change in adjusted R-square Mean VIF

3.89** .26 .19 1.77

4.63** .31 .25 .05** , a 1.74

.10† .28** .01

.06 .25** −.00

.08†

.12 .05 −.14† .10*

5.27** .40 .33 .08** , b 1.74

4.66** .43 .34 .09* , b 2.02

Standardized coefficients are reported. a Compared to Model 1. b Compared to Model 2. * p < .05. ** p < .01. † p < .10.

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Fig. 2. Interaction of EO, ACAP, and market turbulence on firm performance.

performance when ACAP is low (b = .03, t = .40, p > .10). The results of the simple slope test support our regression results and confirm hypothesis H1, that EO is associated with firm performance when ACAP is high. Model 4 tests H2, which predicted that market turbulence moderates the moderation of ACAP on the EO–performance relationship. For the three-way interaction term, we multiplied the mean-centered EO, ACAP, and market turbulence scores for each firm, revealing that the three-way interaction is significant (ˇ = .10, p < .05) and suggesting that the moderation of ACAP on the EO–performance relationship is generally affected by a turbulent market environment (Dawson and Richter, 2006). In order to determine the direction of this moderation, we plotted the slopes for the four relevant cases (combining high/low ACAP and high/low market turbulence) (Fig. 2) and examined the resulting plots by conducting a slope difference test, following Dawson and Richter (2006). Findings indicate that there are significant differences between the slopes of “high ACAP/high market turbulence” and “low ACAP/high market turbulence” (p < .05). We find no significant differences for non-turbulent markets (p > .10), supporting the notion that ACAP is important to the EO–performance relationship in turbulent markets but not in more stable settings. As for the direction of ACAP’s moderation of the EO–performance relationship in turbulent markets, the simple slope test we conducted reveals that, in turbulent markets, the relationship between EO and firm performance is significantly positive when ACAP is high (b = .34, t = 2.84, p < .01), whereas there is no significant relationship between EO and firm performance when ACAP is low (b = −.10, t = −.63, p > .10). Overall, these findings from the three-way interaction analysis support H2, that EO is related to firm performance only when both ACAP and market turbulence are high. 6. Discussion and practical implications Guided by the “strategic fit” paradigm from strategic management literature, the present study develops theoretical arguments concerning how dynamic capabilities like ACAP facilitate the EO–performance relationship. It also introduces the degree of market turbulence in order to clarify the boundary conditions of ACAP’s role in terms of the EO–performance relationship. Empirical findings indicate that ACAP facilitates the association between EO and firm performance, especially in turbulent markets, thereby addressing Covin and Lumpkin’s (2011) call for research on the value of dynamic capabilities in the context of EO research. These findings contribute to the EO literature and the dynamic capabilities literature. The study’s contribution to the EO literature is the empirical validation of the theoretical argument that a firm’s EO–performance relationship is moderated by the dynamic capability of ACAP. In line with our theoretical arguments, ACAP moderates the EO

performance relationship, particularly in turbulent markets. Findings indicate that, when ACAP is low or when ACAP is high in environments characterized by low levels of uncertainty environment, there is no positive correlation between EO and firm performance. It follows that the EO–performance relationship is complex and not one that is positive in all situations. The inward and outward-looking components of ACAP improve an entrepreneurial firm’s ability to find and implement opportunities with strong risk using trial-and-error processes in turbulent markets. Thus, the present study introduces an important new theoretical lens (dynamic capabilities) and moderator (ACAP) to the list of moderators that extant research on the EO–performance research (Table 1) has already examined. Our findings are generally consistent with research calls and other studies that consider resources and capabilities important in leveraging the EO–performance relationship (e.g., Covin and Lumpkin, 2011). While extant research has started to investigate “ordinary” static resources and capabilities (e.g., financial resources) as drivers of the EO–performance relationship, we conclude that dynamic capabilities are relevant for entrepreneurial firms in turbulent market environments. While these conclusions are drawn from comparing the extant studies’ results with our own results, future research could conduct an integrative study to determine when “ordinary” resources and capabilities are important or even sufficient for driving the EO–performance relationship and when more complex dynamic capabilities like ACAP, which allows the firm to reconfigure “ordinary” resources, are necessary. More generally, our research also shows that limiting the examination of the EO–performance relationship to a single moderator (ACAP, in our case) may not capture the complexity of the relationship (Wiklund and Shepherd, 2005). Had we focused only on the moderation of ACAP, we would have concluded that there is a marginal significance with which ACAP positively moderates the EO–performance relationship. However, integrating market turbulence in a three-way interaction led to more nuanced findings. The analysis of individual moderators that has thus far dominated this literature stream may be too simplistic and may hide more nuanced relationships. Extant literature agrees that implementing an entrepreneurial strategic posture effectively can be a complex task (Covin and Slevin, 1991) since these firms face many uncertainties. We conclude that this complex relationship can be captured more accurately by considering more than one moderator at a time and finding sets of moderators that are associated with the EO–performance relationship simultaneously (Short et al., 2008). This study also contributes to the literature on dynamic capabilities. Barreto’s (2010) review of the dynamic capability literature concludes that dynamic capabilities like ACAP should be placed into a nomological net in order to develop this literature stream so the dynamic capability view can evolve into its own theory. Barreto (2010) suggests the need to determine how (and whether) dynamic

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capabilities are associated with firm performance and to understand the boundary conditions of dynamic capabilities. The latter is also important for the ACAP construct, as Lane et al. (2006) state. In terms of the performance relationship, our findings—not hypothesized but shown by our regression analysis in Table 4—show that ACAP, as a major dynamic capability, is associated with firm performance, supporting the notion that firms with dynamic capabilities outperform those that lack them. The performance relationship is even marginally stronger when combined with the strategic posture of EO, indicating that dynamic capabilities interact with the firm’s strategy and confirming that the notion of the “strategic fit” paradigm from strategic management, which has largely been empirically tested with “ordinary” resources and capabilities (e.g., Song et al., 2007), holds in the context of dynamic capabilities. In terms of the boundary conditions, we learn that the dynamic capability of ACAP facilitates the EO–performance relationship in turbulent markets but that it has no additional benefit for entrepreneurial firms in non-turbulent markets. Thus, the market turbulence constitutes a boundary condition for ACAP as a dynamic capability, as only when there is a specific degree of market turbulence does ACAP have substantial value in EO’s conversion into superior performance. This condition may occur because these environments present an urgent need to acquire new knowledge and information upon which entrepreneurial firms should act by constantly, rapidly, and flexibly reconfiguring their resource bases. In non-turbulent environments, entrepreneurial firms do not need these dynamic capabilities. As Drnevich and Kriauciunas (2011) state, building and managing dynamic capabilities is a resourceintensive endeavor that, as our research finds, does not pay off for entrepreneurial firms in non-turbulent conditions. Interpreted from a practitioner’s point of view, the results of this study show that capabilities can help firms to implement a strategic orientation strengthening their relationship with performance. More specifically, the dynamic capability to acquire, assimilate, transfer, and exploit new external knowledge enables a firm to implement an entrepreneurially oriented strategic approach more effectively and efficiently than it could if it had no such capability. This insight is particularly important for entrepreneurially oriented firms that operate in turbulent markets, which are commonly characterized by regularly changing customer needs or quick technological developments. The performance of entrepreneurially oriented firms increases significantly when they have the ability to generate, process, and use new external knowledge.

7. Limitations and future research opportunities The present study has several limitations that offer avenues for future research. First, we use survey data and build on a perception-based construct from Jansen et al. (2005) to measure ACAP, as justified in the measurement section. However, future studies could examine alternative ACAP measures based on objective data from secondary research, such as R&D expenditures or attitude toward patenting, in order to determine the role of ACAP in the EO–performance relationship. Future studies might validate our findings with objective data using R&D surveys like the Community Innovation Survey (CIS), which focuses on manufacturing and service companies with more than ten full-time employees and provides data about indicators of innovative output and information about a firms’ tendency to patent (e.g., Brouwer and Kleinknecht, 1999; Lhuillery and Pfister, 2009). Especially for larger companies, which are obligated to release their financial statements, future studies could combine the CIS results with insights on EO from letters to the shareholders by means of computer-aided text analysis (Short et al., 2010) or by using the newly developed EO proxies from Miller and Le Breton-Miller (2011).

Second, our cross-sectional sample precludes our excluding the possibility of a causal bias. Especially because our study focuses on firm performance, a major avenue for future research should be the exclusion of a potential endogeneity bias in this relationship (Hamilton and Nickerson, 2003). From a methodical point of view, future studies could deal with this problem by using longitudinal data, such as the CIS micro panel dataset, which would enable them to, for example, apply vector autoregression (VAR) to analyze the Granger causality (Colombo and Garrone, 1996) among ACAP, EO, and firm performance or to use fixed effects modeling (David et al., 2000). Although we derived our hypotheses based on theory, and we are convinced of the validity of the causalities derived, additional research on cross-sectional data that explores the relationship between EO and ACAP can be instrumental in eliminating causal concerns and can provide support for our understanding that the relationship between strategy and firm performance is moderated by firm-level capabilities and not that strategy moderates the relationship between firm-level capabilities and firm performance. Third, the present empirical study was conducted in the empirical context of small and medium-sized firms in Germany so, following Bamberger (2008), the findings must be evaluated in the context of this highly developed society. Future studies might examine the EO, ACAP, and market turbulence interaction in less developed countries, where firms typically have fewer resources in order to determine how the findings discussed here change. We also focus on small and medium-sized firms, as the majority of firms fall into this category in most countries. However, since larger companies have more resources, they can develop ACAP more easily, perhaps strengthening the EO–performance relationship. On the other hand, one could argue that the effects of ACAP are stronger in smaller firms since these firms are more flexible and can assimilate and transform knowledge more easily. These are questions that future research could attempt to answer. Fourth, we limited our examination to dynamic capabilities, arguing that they are particularly important—possibly even more important than “ordinary” static resources and capabilities—to EO’s association with improved performance. Future research could develop an integrated model with both static and dynamic resources and capabilities in order to compare their importance and establish their interrelationship. In terms of the latter, it would be useful to determine how dynamic capability can reconfigure the existing “ordinary” resource base to render it suitable to drive the EO–performance relationship. Zahra et al. (2006) note that the research on the interaction of “ordinary” and dynamic capabilities is still in its infancy. Finally, we are aware that data from one survey that measure both an independent variable and a dependent variable might introduce a common method bias, although we took several measures to reduce the risk and our tests for common method bias reveal no threats in this regard.

8. Conclusion This paper contributes to both EO and dynamic capabilities research. It outlines theoretically that ACAP, a dynamic capability, helps a firm deploy its EO in order to improve its performance, especially if the firm operates in a turbulent market. In so doing, the study shows that the choice of strategy and a firm’s capabilities should be consistent. The theoretically derived research model, which links EO, ACAP, market turbulence, and firm performance, was empirically validated by means of an empirical study of 196 small and medium-sized firms.

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Cronbach’s alpha

Composite reliability

Average variance extracted

Performance Vorhies and Morgan (2005)

Customer satisfaction Please evaluate the performance of your business over the past year relative to your major competitors (1 = “Strongly disagree” . . . 7 = “Strongly agree”): Overall customer satisfaction Delivering value to your customers Delivering what your customers want Retaining valued customers

.66

.81

.59

.79

.88

.70

Market effectiveness Please evaluate the performance of your business over the past year relative to your major competitors (1 = “Strongly disagree” . . . 7 = “Strongly agree”): Market share growth relative to competitors Growth in sales revenue Acquiring new customers Increasing sales to existing customers Current profitability Please evaluate the performance of your business over the past year relative to your major competitors (1 = “Strongly disagree” . . . 7 = “Strongly agree”): Business profitability Return on investment (ROI) Return on sales (ROS) Reaching financial goals Entrepreneurial orientation Covin and Slevin (1989)

Innovativeness In general, the top managers of my firm favor . . . A strong emphasis on the marketing of tried-and-true products and services (1) How many new lines of products or services has your firm marketed in the past five years (or since its establishment)? No new lines of products or services (1) Changes in product or service lines have been mostly of a minor nature (1)

Proactiveness In dealing with its competitors, my firm . . . Typically responds to actions which competitors initiate (1)

Is very seldom the first business to introduce new products/services, administrative techniques, operation technologies, etc. (1)

Risk-taking In general, the top managers of my firm have . . . A strong proclivity for low-risk project (with normal and certain rates of return) (1)

...

A strong emphasis on R&D, technological leadership, and innovations (7)

...

Very many new lines of products or services (7) Changes in product or service lines have usually been quite dramatic (7)

...

...

...

...

Typically initiates actions to which competitors then respond to (7) Is very often the first business to introduce new products/services, administrative techniques, operating technologies, etc. (7)

13

A strong proclivity for high-risk projects (with chances of very high return) (7)

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Appendix A. Measurement scales

In general, top managers of my firm believe that . . . Owning to the nature of environment, it is best to explore it gradually via cautious, incremental behavior (1)

When confronted with decision-making situations involving uncertainty, my firm . . . Typically adopts a cautious, “wait-and-see” posture in order to minimize the probability of making costly decisions (1)

Assimilation We are slow to recognize shifts in our market (e.g., competition, regulation, demography). (R) New opportunities to serve our clients are quickly understood. We quickly analyze and interpret changing market demands. Transformation Our unit regularly considers the consequences of changing market demands in terms of new products and services. Employees record and store newly acquired knowledge for future reference. Our unit quickly recognizes the usefulness of new external knowledge to existing knowledge. Employees hardly share practical experiences. (R) We laboriously grasp the opportunities for our unit from new external knowledge. (R) Our unit periodically meets to discuss consequences of market trends and new product development. Exploitation It is clearly known how activities within our unit should be performed. Our unit has a clear division of roles and responsibilities. We constantly consider how to better exploit knowledge. Our unit has difficulty implementing new products and services. (R) Employees have a common language regarding our products and services.

...

Typically adopts a bold, aggressive posture in order to maximize the probability of exploiting potential opportunities (7)

Average variance extracted

.87

.92

.73

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(1 = “Strongly disagree” . . . 7 = “Strongly agree”) Acquisition Our unit has frequent interactions with corporate headquarters to acquire new knowledge. Employees of our unit regularly visit other branches. We collect industry information through informal means (e.g., lunch with industry friends, talks with trade partners). Other divisions of our company are hardly visited. (R) Our unit periodically organizes special meetings with customers or third parties to acquire new knowledge.

Owning to the nature of the environment, bold, wide-ranging acts are necessary to achieve the firm’s objectives (7)

Composite reliability

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Absorptive capacity Jansen et al. (2005)

...

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Construct (based on or adapted from)

Average variance extracted

Market turbulence Jaworski and Kohli (1993)

(1 = “Strongly disagree” . . . 7 = “Strongly agree”) In our kind of business, customers’ product preferences change quite a bit over time Our customers tend to look for new products all the time Sometimes our customers are very price-sensitive, but on other occasions, price is relatively unimportant We are witnessing demand for our products and services from customers who never bought them before New customers tend to have product-related needs that are different from those of our existing customers

.75

.83

.50

Return on sales

Over the last three years, what was the average annual return on sales of your business?

n/a

n/a

n/a

Firm size

How many employees in terms of full-time equivalents (FTE) does your firm have? Please enter the number of employees:

n/a

n/a

n/a

Industry

In which industry is your firm operating? Please select the most appropriate industry sector

n/a

n/a

n/a

Ownership

Is your firm publicly traded?

n/a

n/a

n/a

Respondent position

Which position do you hold in the company?

Firm age

2012-firm founding

n/a

n/a

n/a

Market orientation Vorhies and Morgan (2005)

Ability to gather information about customers and competitors compared to most important competitor Ability to use market research skills to develop effective marketing programs compared to most important competitor Ability to track customer wants and needs compared to most important competitor Ability to make full use of marketing research information compared to most important competitor Ability to analyze our market information compared to most important competitor

.88

.91

.68

Respondent tenure

Please state the number of years that you have already worked for this company

n/a

n/a

n/a

Perceived bargaining power

Please select, to which of the following statements you would rather agree: Our company has strong bargaining power vis-à-vis its customers Our customers have much bargaining power Our customers are stronger than our suppliers

n/a

n/a

n/a

Note: (R) indicates that an item was reverse-coded and re-coded before use in any calculations.

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Please cite this article in press as: Engelen, A., et al., Entrepreneurial orientation in turbulent environments: The moderating role of absorptive capacity. Res. Policy (2014), http://dx.doi.org/10.1016/j.respol.2014.03.002