Interpreting strategic issues: Effects of differentiation strategies and resource configurations on corporate entrepreneurship

Abstract

Differentiation strategy represents the shared belief about the market and provides the lens through which executives filter external information. Based on the relevant information peculiar to the strategy and resource configurations in the firm, executives develop opportunity or threat interpretations and take responsive actions. Using the two-wave survey data from 294 CEOs in China during the 2008 macro crisis, we find that the configuration of differentiation, financial slack, and technological capabilities affects corporate entrepreneurship through opportunity interpretations.

Keywords

differentiation entrepreneurship opportunities threats

Introduction

As an economic crisis can bring fundamental, unpredictable changes in the environment, interpreting such environmental jolts as beneficial opportunities (Wan and Yiu, 2009) can drive firms to take entrepreneurial actions (Tan and See, 2004). Given that firms pursuing a differentiation strategy may promote top managers to perceive more opportunities in abrupt environmental changes, entrepreneurial actions may represent the path dependency nature of the firms’ dominant differentiation strategy. Yet, under what situations do firms adhere to or modify their differentiation strategies? Two research theoretical frameworks may provide distinctive but complementary perspectives.

The strategic issue diagnosis (SID) literature (e.g. Julian and Ofori-Dankwa, 2008; Thomas and McDaniel, 1990) highlights that current strategy defines issue interpretations and the resulting organizational actions. Firms often scan external conditions, interpret environmental changes as opportunities or threats, and adopt responses to deal with environmental fluctuations. A firm’s strategy, as a central part of the organizational paradigm (Dutton, 1992), represents the shared belief about the market and its competitive methods, incorporates past beliefs and organizational knowledge, and provides the lens through which top managers filter external information. Based on the relevant information peculiar to the strategy, top managers develop opportunity or threat interpretations (Hoffman and Ocasio, 2001), and take responsive actions. In this regard, existing differentiation strategy will influence issue interpretations and the resulting actions. However, later empirical studies have almost unequivocally focused on the impact of opportunity/threat interpretations but ignore how current strategy and organizational context influence interpretations.

Different from the SID literature, recent studies of entrepreneurial opportunities (Haynie et al., 2009; Kor et al., 2007) focus on the origin of opportunity heterogeneity. Built upon Penrose (1995) and the resource-based view, scholars contend that an opportunity is evaluated if it “is attractive in the context of the existing knowledge, skills, abilities, and resources of the venture” (Haynie et al., 2009: 338). They also stress that there is not a single predictor to recognize entrepreneurial opportunities, but it requires a combination of variables (Urban and Willard, 2017). These scholars stress entrepreneurs’ knowledge and existing resources as key determinants of opportunity evaluation. A firm’s differentiation strategy will thus affect opportunity evaluations in the firm.

The resource focus on opportunity heterogeneity thus complements the SID literature by underlining that resource endowments, in addition to differentiation strategies, influence to what extent firms maintain or adjust organizational responses to an economic crisis through their effects on opportunity interpretations. We reason that top managers embodying a differentiation strategy may be cognitively biased toward new opportunities and abrupt environmental changes may open up more space for new combinations. Such opportunity interpretations may drive the firms to exercise the opportunities through corporate entrepreneurship (CE) activities, such as strategic renewal and business venturing activities (Zahra, 1996).

We further argue that resource configurations will facilitate firms to interpret and manage ambiguous external events, as environmental jolts may demand firms to reconfigure, integrate, or evolve resources and capabilities to attain new sources of competitive advantage. Specifically, resource superiority as compared to competitors (i.e. technological capabilities) and resources’ common availability beyond present demand levels (i.e. financial slack) would be paramount when engaging in environment scanning, and that interpretation of strategic issues gleaned from scanning will influence CE activities. (The major relationships are summarized in Figure 1.)

Figure 1.

The proposed moderated mediation model.

Based on the context of the 2008 macro crisis and two waves of survey data, we find that differentiation strategies and resource configurations together influence CE activities as organizational responses to environmental jolts through opportunity interpretations. As suggested by the SID literature and the resource-based understanding of opportunity heterogeneity, organizational strategies provide the mental models that top managers use to filter information to interpret environmental changes, and the interpretation varies with the configurations of resources. Top managers interpret environmental issues from the perspective of the dominant strategies and resource configurations, and their behaviors on opportunity interpretations are subjective in nature, identical to individual entrepreneurs who evaluate opportunities from their personal background and knowledge.

Our study examines how the effects of strategy on opportunity interpretations vary with configurations of technological capabilities and financial slack, thereby reconciling the mixed results from the limited number of empirical studies on the connection between organizational strategies and strategic moves (e.g. Milliken, 1990; Thomas and McDaniel, 1990). Specifically, we find that differentiation strategies can have both positive and negative effects on opportunity interpretations. Although existing strategies function as the shared belief for top managers to filter and interpret environmental jolts, interpretations and responsive strategic moves may vary because of heterogeneous resource configurations.

Theoretical development

Interpretation of opportunities/threats

The SID literature examines how executives interpret the external forces and argues that top managers will take action based on the interpretation of threats and opportunities (Dutton and Jackson, 1987; Julian and Ofori-Dankwa, 2008). Scholars in the SID stream have conceptualized both the antecedents and outcomes of opportunity/threat interpretations. Regarding the antecedents of opportunity interpretations, Dutton (1992) proposes that the issue context, organizational context, and institutional context together favor the construction of opportunities. The issue context describes both the social setting and the personal attributes and networks of an issue sponsor; the organizational context includes the information processing capacity of an organization, an organization’s paradigm or theory of action (e.g. organizational strategy and assumptions about the environment), and characteristics of an organization’s current agenda; and the institutional context refers to the social, economic, and competitive environment in which an organization operates. However, only a very small number of empirical studies (e.g. Milliken, 1990; Thomas and McDaniel, 1990) following the SID literature test the determinants of opportunity and threat interpretations, while most tend to conceptualize the impact of interpretations on organizational moves.

Complementary to the SID literature, the resource-based understanding of opportunity heterogeneity (e.g. Haynie et al., 2009; Kor et al., 2007) stresses the entrepreneur’s personal knowledge and existing resource endowments in opportunity evaluations. There is a complex integration of heterogeneous factors that influence individuals who recognize these opportunities (Baron, 2006). Some of these differences include aspirations, intentions, abilities, experiences, and knowledge; these attributes provide a basis for appreciating and interpreting the external shocks as useful market disequilibriums that could translate to future innovative endeavors (Urban, 2014). In addition, these differences can separate entrepreneurs who can identify and exploit opportunities from the many who cannot. In other words, the ability to evaluate opportunities is not due to random variation, but springs from systematic processes (Urban, 2014). Some scholars (e.g. Kor et al., 2007) emphasize experiential knowledge in enacting new combinations, with the personal knowledge coming from team-, firm-, and industry-specific experience, while some others (e.g. Haynie et al., 2009) focus on existing resource competencies and resource attributes. Different from the SID literature, opportunity heterogeneity is attributed to heterogeneity in resources and the usage of resources. These resources are guided by complex organization processes and relevant experienced and motivated individuals which creates an array of interpreted opportunities.

We follow the SID literature, especially the works of Dutton (1992) and Thomas and McDaniel (1990), to propose that organizational strategies, as a crucial component of organizational paradigm, influence interpretations and subsequently lead to organizational moves. Moreover, from the resource-based understanding of opportunity heterogeneity, a firm’s resource configurations are also crucial in opportunity interpretations.

Differentiation and opportunity/threat interpretations mediate the relationship between differentiation and corporate entrepreneurship

Organizational strategies represent a firm’s commitment to specific value orientations. Firms engage in specific strategies, such as low cost or differentiation, in order to serve their existing customers and gain future customers with similar interests. Low-cost leadership strategies adhere to formalization, efficiencies, and centralization, which attempt to create products and services at overall lower cost price points (Priem, 1994). These strategies thrive in commodity type industries where cost cutting and process efficiencies are paramount. Yet, low-cost leadership strategies may not be effective in uncertain and ambiguous changes. Volatile environmental changes often demand firms to incorporate innovative strategies to take advantage of the disequilibrium of strategies and the environment (Basardien et al., 2013). Differentiation emphasizes the importance of innovation of new product development and market responsiveness (Urban, 2010). Porter (1985) defined differentiation as creating products, services, and processes that are difficult to replicate, thus are uniquely designed and valued within the industry. Miller (1988) argues that within differentiation, there are two dimensions, namely product innovation and marketing. Marketing differentiation focuses on perception of the product (i.e. prestige). The intent of marketing differentiation is to insure that customers or potential customers perceive an element of prestige or respect with using a product. Yet with any business-level strategy, organizations must go beyond perception with an emphasis on innovation of products or services; thus, our focus will be on product differentiation when discussing differentiation.

Differentiation not only requires firms to constantly monitor the environment to ensure that their customers’ demands are in line with their business-level strategy, but also represents previous experience with which executive managers will rely heavily on when interpreting the external environment (Daft and Weick, 1984). Differentiation thus equips top managers with specific mental models and allows them to see their way through extensive flow of information.

A differentiation strategy may induce executives to perceive more opportunities and fewer threats when environmental jolts arise. As differentiation requires constant research for new product or service development, firms with a differentiation strategy may be able to strengthen their innovative product base and have a solid foundation for innovation. A differentiation strategy may also transform the operations of the organization with ingrained processes supporting new opportunity identifications. Firms with a differentiation strategy will thus become more opportunistic since they will have a culture of looking for new prospects (Urbano and Turró, 2013). On the other hand, firms will downplay the potential threats when pursuing differentiation since the core of this business-level strategy is about developing and improving processes and products for stakeholders that view these processes and products as unique and valuable.

However, a differentiation strategy may also prompt executives to perceive more threats and fewer opportunities when external environment abruptly changes. Although environmental jolts are associated with more market opportunities for firms to try new combinations (Bradley et al., 2011), potential ambiguity of environmental changes often appear to be incomprehensible and threatening (Amburgey and Miner, 1992). There is research which shows that managers can be more sensitive to threats than opportunities (Jackson and Dutton, 1988). Organizations may emphasize the importance of the avoidance of losses, and thus create systems that reward those who confront threats that are deemed to harm the organization. Thus, there is support for our arguments that environmental jolts create uncertainty which can lead to either opportunity or threat interpretations (Osiyevskyy et al., 2017).

We argue that differentiation will influence CE through opportunities and threats analysis. Opportunities and threats interpretation is the imagery of ongoing external activities, which allows differentiation to further CE activities. In other words, opportunities and threats interpretation provides external related ideas to the experiences and processes of differentiation that influence CE activities. Both opportunity and threat interpretations have been connected to various organizational actions, such as internal versus external responses and expansionary versus defensive moves (e.g. Chattopadhyay et al., 2001; Tan and See, 2004). As CE activities are closely associated with opportunity seeking and exploitation, CE activities are inherently related to both differentiation strategies and opportunity/threat interpretations.

While both differentiation and CE require firms to focus beyond their existing area of emphasis, we argue differentiation has specific parameters concerning the actions taken, while CE outcomes have a range of activities. Differentiation will focus on existing customers but also engage in activities that encourage new customers to become loyal buyers of existing products and services. This strategy will also devote resources in order to further expand the innovative emphasis of strategy due to changing markets (Pertusa-Ortega et al., 2009). In a similar vein, executives will cognitively consider actions based on their strategic initiatives while being influenced by opportunities and threats (Pérez-Nordtvedt et al., 2014). Thus, firms following a differentiated strategy innately scan the environment with the important resources and capabilities which may spill over to CE activities, and will gain a perspective of potential CE activities such as innovations or new business development.

Opportunity and threat interpretations can also lead to CE activities. CE activities cannot be created in a vacuum but through processes and activities that scan for and interpret opportunities and threats. Plambeck and Weber (2009) argue that executives will engage in strategic risk-taking when viewing both opportunities and threats, since each focus will provide executives a connection of existing CE activities with potential activities that were not necessarily strategies before the examination and interpretation of the environment. In fact, Plambeck and Weber (2009) found that European firms that were more open to both threats and opportunities regarding European Union enlargement issues were much more likely to vigorously respond to strategic issues relating to the EU enlargement. Another study found that both opportunity and threat interpretations were positively related to expand exploratory actions (Osiyevskyy and Dewald, 2015). Therefore, differentiation engages in both opportunity and threat interpretations, which in turn provides relevant and timely information that may be the catalyst for firms to pursue CE activities. Thus, we hypothesize:

H1: Opportunity interpretations mediate the relationship between differentiation and CE.

H2: Threat interpretations mediate the relationship between differentiation and CE.

Technological capabilities and financial slack as moderators of differentiation on opportunity and threat interpretations

As firms must manage and survive environmental jolts through exploiting their resources and quickly utilizing different responses (Kraatz and Zajac, 2001), we reason that resources and slack will provide a more complete picture in examining the complex relationship of differentiation and opportunity/threat interpretations. Studies have shown that business strategies respond differently to levels of technological capabilities (Martinez-Simarro et al., 2015). For strategic action to produce a competitive advantage, top management must understand the interaction between organizational resources and capabilities and the external environment (Cox, 2014). These resources and capabilities will allow firms to more effectively manage and interpret ambiguous external events (Barreto and Patient, 2013). Both quality and quantity of resources will matter for executives to assess the alignment between resources, environmental changes, and existing strategies to develop their opportunity/threat interpretations (Verbeke and Yuan, 2007). The quality of resources (capabilities hereafter) refers to the superiority of resources as compared with industry competitors regarding resource rarity, value, and inimitability, while the quantity of resources (slack hereafter) delineates the availability of resources beyond present demand. As capabilities and slack represent different dimensions of a firm’s resource base and the impact of differentiation on interpretations depends on the firm’s resource configurations, we expect a three-way interaction among differentiation strategies, capabilities, and slack.

Not all types of capabilities and slack will matter significantly for opportunity/threat interpretations. As differentiation strategies emphasize the development of new products and processes, successful implementation of differentiation demands strong technological capabilities to build and incorporate multiple technologies within the firm (Afuah, 2002). Exploitation of existing technological capabilities may spill over to the firm’s overall ability to increase innovation. For example, resources provided for technology development to promote incremental changes to a product may lead to other findings due to the nature of developing those technological capabilities.

In the meantime, new products development often requires significant financial slack which is generic and can be readily redeployed within the firm (Voss et al., 2008). Financial resources are valuable, but they are generic and less rare as compared with technological capabilities. We propose that differentiation strategies, financial slack, and technological capabilities together influence opportunity/threat interpretations. Below, we discuss how the relationship between differentiation and opportunity/threat interpretations varies when the configurations between financial slack and technological capabilities change.

In the first scenario, a firm has limited financial slack but strong technological capabilities. Firms pursuing differentiation require the necessary technology to be aware of not only existing customers, but also innovative opportunities to complement and build upon the firm’s strategy. Technological capabilities provide the firm with tools to access and attract the necessary information that is critical for seeking opportunities (Liu and Wu, 2011). Technological capabilities can improve a firm’s strategy by providing a greater ability to respond to the rapidly changing markets (Pertusa-Ortega et al., 2009). Finally, technological capabilities are an ideal support to firms pursuing innovative strategies such as differentiation since competent scanning requires information about existing and future customers, changing market demands, and other relevant opportunities. Although the lacking of financial slack may constrain opportunity perceptions, technological capabilities can allow other non-technology-related resources or capabilities to capture value (Wales et al., 2013). We thus suggest that stronger technological capabilities tend to provide a powerful base for executives following a differentiation strategy to perceive more opportunities in an environmental jolt when financial slack is limited.

In the second scenario, a firm with significant amount of financial slack, a double-edged sword nature of financial slack may change the impact of a firm’s resource configurations. Financial slack may permit firms to pursue initiatives that otherwise may be avoided, such as opening new manufacturing plants or investing in new product development, thereby allowing the firms to perceive more opportunities. On the other hand, financial slack could give firms a false sense of security which may trigger complacency and inertia within resource-endowed firms.

When a firm commands high levels of slack but weak technological capabilities, executives following a differentiation strategy may find that the firm is not well equipped with the necessary technologies to develop new products to match emerging needs in an environmental jolt. In addition, the availability of financial slack may function as a buffer against environmental fluctuations and allow the firm to reduce the need for investment in risky projects (Bradley et al. 2011). The inability of the firm to meet new opportunities resulting from weak technological capabilities may enable executives following a differentiation strategy to view new customer needs irrelevant to them, while the potential complacency and security from the abundant financial slack may decrease executives’ motivation to actively search for new opportunities. These arguments suggest that when the firm has high levels of financial slack but weak technological capabilities, executives following a differentiation strategy perceive fewer opportunities in environmental jolts.

In contrast, when a firm has both abundant financial slack and strong technological capabilities, financial slack would provide the extra means while technological capabilities would provide the ability to allow firms following differentiation to vigorously and confidently scan the external environment to seek beyond these existing markets/customers or develop improved operations. Firms with complementary resources and capabilities will pursue more areas outside their product/services scope than will their existing competitors. Differentiation promotes uniqueness and outside thinking for new products and services. When firms have high financial slack and strong technological capabilities, the options become more focused on seeking new innovations since these resources and capabilities would supplement each other to develop a foundation necessary for firms wanting to seek opportunities. In this scenario, executives following a differentiation strategy perceive more opportunities in environmental jolts. Therefore, we hypothesize:

H3: There is a three-way interaction among differentiation, financial slack, and technological capabilities on opportunity interpretations. When financial slack is low, differentiation has an increasingly positive effect on opportunity interpretations while technological capabilities become stronger. When financial slack is abundant, the impact of differentiation on opportunity interpretations changes from a negative one for firms with weak technological capabilities to a positive one for firms with strong technological capabilities.

Opposite to opportunity interpretation, threat interpretation is the perception of a negative external environment which could include financial losses (Dutton and Jackson, 1987). Firms that engage in differentiation will be seeking innovative and unique opportunities that will further their strategy rather than worrying about potential losses brought on by threats. Technological capabilities provide important information and knowledge in an uncertain environment for firms following innovation differentiation to interpret the complex environment with more relative certainty, which will decrease threat interpretation. Thus, even if financial slack is low, stronger technological capabilities can influence a negative relationship between differentiation and threat interpretation.

On the other hand, abundant financial slack without technological capabilities provides differentiator firms with different abilities and options. Firms with financial slack may interpret the external environment events as losses and threats since they do not have the technological capabilities to effectively scan the potential gains. Thus, executives following a differentiator strategy may perceive more threats when the firms have abundant slack but weak technological capabilities. In contrast, firms with significant amount of slack and strong capabilities have the technological repertoire to develop new products for emerging demands; and abundant financial slack provides the additional means for further investment. In this scenario, a firm emphasizing a differentiation strategy may perceive fewer threats. Thus, we hypothesize:

H4: There is a three-way interaction among differentiation, financial slack, and technological capabilities on threat interpretations. When financial slack is low, differentiation has an increasingly negative effect on threat interpretations while technological capabilities become stronger. When financial slack is high, the impact of differentiation on threat interpretations changes from a positive one for firms with weak technological capabilities to a negative one for firms with strong technological capabilities.

Moderation effects of financial slack and technological capabilities on the mediating process between differentiation and CE through opportunity/threat interpretations

Following our previous propositions that differentiation strategies, financial slack, and technological capabilities together determine executives’ interpretations of environmental jolts, we argue that financial slack and technological capabilities will moderate the mediating process of opportunity/threat interpretation on differentiation and CE. Despite some studies that have found support in the opportunity/threat interpretations on CE activities, overall results show the association between opportunity/threat interpretations and CE activities to be mixed (e.g. Chattopadhyay et al., 2001; Thomas et al., 1993). Katila and Shane (2005) argue that a firm’s innovation is contingent on utilizing capabilities and understanding the external environment. Interpretation of the external environment provides the cognitive basis for implementing CE. Yet, the integration of capabilities within this cognitive enrichment creates necessary capital to engage in innovative activities. Thus, the overall integration of resources is necessary to have the ability to sense opportunities and threats and determine appropriate responses (Frank et al., 2017).

Stronger technological capabilities may give executives higher levels of confidence to meet new demands. Such firms not only tend to perceive more opportunities and less threats in environmental jolts, but also commit existing technological capabilities to pursue new business. Firms without much financial slack, differentiation strategies have a stronger positive impact on CE activities through opportunity/threat interpretations when the firms’ technological capabilities become stronger.

On the other hand, when a firm holds significant financial slack but weak technological capabilities, executives following a differentiation strategy may find that the firm is not well armed with the necessary technologies even if they see potential chances in an environmental jolt. In addition, abundant financial slack may indicate that the environment is still safe. Executives may perceive fewer opportunities (and more threats), and the interpretations will trigger fewer CE activities. In contrast, significant financial slack and strong technological capabilities provide both technological foundations and financial resources. Firms emphasizing differentiation strategies not only identify more opportunities (and fewer threats), but also have the necessary resources/capabilities to pursue them. We thus propose that in the case of abundant financial slack and strong technological capabilities, differentiation has a positive effect on CE activities through opportunity/threat interpretations.

H5: Financial slack and technological capabilities have a moderation effect on the mediating process between differentiation and CE through opportunity interpretations.

H6: Financial slack and technological capabilities have a moderation effect on the mediating process between differentiation and CE through threat interpretations.

Methods

Data and sample

We used the strategic issue of the global economic crisis in mainland China during 2009 and 2010 to test our hypotheses. The late 2000s global economic crisis was a salient issue and represented an ill-structured and ambiguous situation. The abrupt slowdown of the major advanced economies brought a negative export shock to China (Woo and Zhang, 2011), while the aggressive monetary policy adopted by the Chinese government significantly boosted consumer and business confidence (McKissack and Xu, 2011). The meaning of the global economic crisis was vague and diverse interpretations have emerged.

We tested the hypotheses with two waves of survey data. The first wave asked the CEOs about their organizational strategy, perceptions of the environment, other independent and control variables, and the background information of the firm; the second wave focused on CE activities. We developed the two questionnaires in two stages, with all constructs measured by scales from previous research. We first developed English-language versions of the two questionnaires, and we applied the back translation method to avoid translation errors and ensure conceptual equivalence (Roy et al., 2001). We then tested the questionnaires with 113 EMBA students at two top research universities in Shanghai, and the pilot study led to minor wording changes to enhance the clarity.

We initially selected a random sample of 1000 firms from a list of Chinese firms located in the Yangtze Delta area provided by the Provincial Administration for Industry and Commerce. In the summer of 2009, we conducted the first wave of data collection, by sending three rounds of mail to the CEOs of the firms, and training interviewers to conduct structured interviews based on the questionnaire. We received valid responses from 346 CEOs. In summer 2010, we conducted the second wave of data collection for the same 346 CEOs using the same procedure applied in the first wave, and we received 294 usable questionnaires. Thus, the 294 CEOs who responded to both questionnaires are the final sample, representing an effective response rate of 29.4%. On average, these firms have an average age of 21.85 years; they hire 2441 employees, and 70% of them have 2000 employees or fewer; and they have annual sales between RMB 10 million and 30 million. On average, the CEOs are 40 years old and have worked in their firms for 10 years.

Measures

All measures come from existing literature, and all items related to CE, opportunity and threat interpretations, technological capabilities, financial and human resource (HR) slack, strategy variables, flexibility, environmental uncertainty, and past performance are based on 10-point likert-type scales.

Dependent variable

Corporate entrepreneurship

We use Ling et al. (2008) 16-item scale to measure the three dimensions of CE, including innovation, venturing, and strategic renewal. The scale is based on the 14-item scale developed by Zahra (1996) which has demonstrated significant correlation with objective indicators such as a firm’s research and development (R&D) spending and number of new products. We ask respondents to evaluate to what extent their firms have conducted these activities in the past year to deal with changes brought by the economic crisis. In the second survey, we stressed that these activities should be new actions to deal with environmental changes after the environmental jolt, as compared with CE activities before the jolt. We eliminate six items due to low loadings, and keep four items for innovation, and three items each for venturing and strategic renewal.¹ We aggregate the 10 items for an overall CE score.

Independent and control variables

Opportunity and threat interpretations

We measure the opportunity (three items) and threat (three items) interpretations of the 2000s global economic crisis with items adapted from Thomas et al. (1993). A subset of these items has been used in previous strategy/organization research to measure opportunity and threat interpretations to external environmental changes (e.g. Pérez-Nordtvedt et al., 2014).

Technological capabilities

We use the three items in Song et al. (2005) to measure technological capabilities. The three items are used to assess firms’ technology development capabilities, manufacturing processes, and new product development capabilities relative to those of their major competitors.

Financial slack and HR slack

Organizations need slack resources to take actions. We adapt the scale in Miller and Friesen (1982) to measure HR slack (two items), and the scale in Tan and Peng (2003) to measure financial slack (two items).

Organizational strategy

We include three types of generic strategies (i.e. differentiation, cost leadership, and marketing differentiation; Dess et al., 1997). Cost leadership (two items) and differentiation (two items) are based on measures in Durand and Coeurderoy (2001), and marketing differentiation (three items) is based on Miller (1988). Marketing differentiation is a refined measure of the two proposed differentiation measures. Marketing differentiation emphasizes advertising to create uniqueness through perception of concepts such as prestige or convenience, whereas differentiation emphasizes the uniqueness of the product or service itself.

Flexibility

As firms which emphasize the flexible use of resources may be more willing to change their strategies to adjust to environmental fluctuations (e.g. Zahra et al., 2008), we include flexibility as an important control variable, with five items from Zahra et al. (2008).²

Environmental uncertainty

Perceived environmental uncertainty is likely to affect organizational responses. We measure environmental uncertainty with two items from Marino et al. (2008).

Past performance

As past performance may influence organizational actions, we include past performance of firms in the past 2 years, with items adopted from Song et al. (2005).

Other control variables

Other control variables include jolt duration, firm age, firm size, firm ownership, industry, CEO company tenure, and CEO functional background. We measure jolt duration by asking CEOs how long they think the macro crisis will last (1 = very short; 10 = several years). We measure firm age as the logarithm of the number of years of operation by the firm, firm size as the logarithm of the number of employees, and industry as a dummy variable, where 1 = manufacturing and 0 = service. We measure firm ownership with two dummy variables. These two dummy variables represent state ownership and foreign ownership (international joint ventures and wholly owned joint ventures), with the other types as the base category. We measure CEO company tenure by the number of years CEOs have worked at the company and CEO functional background by a dummy variable, with 0 indicating backend and 1 for customer-end background.

Construct validity

To validate the measurement of our constructs in the context of privately owned firms in mainland China, we conduct a confirmatory factor analysis (CFA) with constructs including CE, opportunity and threat interpretations, technological capabilities, financial and HR slack, innovative differentiation, cost leadership, marketing differentiation, flexibility, environmental uncertainty, and past performance. The CFA achieves a good model fit with the data (χ²(713) = 1367.75, p < 0.001, CFI = 0.96, TLI = 0.95, RMSEA = 0.055, SRMR = 0.056). All factor loadings are highly significant. Overall, the measures demonstrate good convergent validity and reliability (Brown, 2006).

Analyses and results

Table 1 presents means, standard deviations, and correlations for the variables. The Kolmogorov–Smirnov tests support the univariate normality assumption. We apply hierarchical regression analyses to examine hypotheses 1–4, and we use the bootstrap method with an SPSS macro developed by Hayes (2018) to examine the moderated mediation models in hypotheses 5 and 6. We applied the bootstrapping method to generate confidence intervals (CIs) for the proposed moderated mediation processes (Hayes, 2013). Similar approaches have been adopted in earlier studies that used mediated moderation and moderated mediation models (e.g. Chang et al., 2012).

Table 1.

Descriptive statistics.

	Mean	SD	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19
1. CE	4.69	1.50	1.00
2. Opportunity	5.63	1.83	0.33**	1.00
3. Threat	4.00	1.62	0.01	−0.42**	1.00
4. Financial slack	5.39	1.86	0.19**	0.27**	−0.19**	1.00
5. HR slack	5.00	1.98	0.07	0.11	0.02	0.27**	1.00
6. Technological capabilities	6.13	1.95	0.47**	0.26**	−0.12*	0.31**	0.19**	1.00
7. Cost leadership	5.32	1.68	0.10	0.04	−0.03	0.04	0.07	0.21**	1.00
8. Marketing differentiation	6.13	1.61	0.33**	0.19**	−0.02	0.14*	0.10	0.32**	0.28**	1.00
9. Differentiation	5.29	2.14	0.26**	0.22**	−0.11	0.18**	0.18**	0.37**	0.15*	0.27**	1.00
10. Environmental uncertainty	7.40	2.72	0.18**	0.09	−0.11	0.04	0.00	0.30**	0.13*	0.17**	0.27**	1.00
11. Flexibility	6.20	1.64	0.38**	0.35**	−0.13*	0.24**	0.120*	0.41**	0.06	0.30**	0.23**	0.09	1.00
12. Past performance	5.39	2.38	0.16**	0.22**	−0.11	0.19**	0.21**	0.35**	0.17**	0.12*	0.23**	0.12*	0.17**	1.00
13. Jolt duration	5.17	1.95	0.16**	0.08	0.18**	0.07	0.01	0.15**	0.02	0.09	0.02	0.00	0.16**	0.06	1.00
14. Industry (dummy)	0.53	0.50	0.04	−0.01	0.11	−0.01	−0.02	−0.07	−0.16**	0.06	−0.08	−0.09	0.02	−0.03	0.08	1.00
15. State ownership (dummy)	0.29	0.45	0.01	−0.12*	0.10	−0.05	0.17**	0.01	−0.03	−0.02	−0.01	−0.05	−0.07	0.11	−0.03	0.15*	1.00
16. Foreign ownership (dummy)	0.09	0.28	0.01	−0.03	−0.01	−0.02	0.00	0.05	0.12*	0.11	−0.01	0.03	−0.13*	−0.01	−0.08	−0.17**	−0.20**	1.00
17. Firm age	21.85	22.50	−0.04	−0.11	0.00	−0.02	0.11	0.06	0.16**	0.06	0.09	0.08	−0.17**	0.11	−0.07	0.03	0.22**	0.09	1.00
18. Firm size	2441.00	4594.29	0.05	−0.10	0.10	−0.04	0.13*	0.06	0.08	0.04	0.05	0.09	−0.12*	0.09	0.07	−0.04	0.26**	0.13*	0.24**	1.00
19. Company tenure	10.35	6.54	0.08	−0.03	0.08	0.07	0.19**	0.12*	0.09	0.13*	0.09	0.11	0.01	0.11	0.02	0.10	0.20**	−0.12*	0.45**	0.20**	1.00
20. Functional background	0.45	0.50	0.09	0.06	0.01	0.09	0.04	−0.02	0.07	0.05	0.01	−0.14*	0.09	−0.01	−0.11	−0.04	−0.09	0.08	−0.05	−0.15*	−0.09

Note: CE: corporate entrepreneurship; SD: standard deviation; HR: human resource.

*p < 0.05; **p < 0.01.

Hypotheses 1 and 2 propose mediation effects between differentiation and CE through opportunity/threat interpretations. In models 1 and 4, differentiation has nonsignificant effects on opportunity and threat interpretations. Therefore, hypotheses 1 and 2 are not supported.

Hypothesis 3 proposes a three-way interaction effect among differentiation, financial slack, and technological capabilities on opportunity interpretations. Model 3 in Table 2 shows that the three-way interaction effect is significant (p = 0.02), and the three-way interaction contributes an additional 1% increase in R² than the model without the three-way interaction (model 2).

Table 2.

Regression results.

	Model 1		Model 2		Model 3		Model 4		Model 5		Model 6		Model 7
	DV: Opportunity						DV: Threat						DV: CE
	β	p	β	p	β	p	β	p	β	p	β	p	β	p	LLCI	ULCI
Differentiation	0.06	0.22	0.10	0.05	0.08	0.09	−0.02	0.70	−0.04	0.36	−0.03	0.47	0.03	0.43	−0.05	0.10
Financial slack	0.14*	0.02	0.11*	0.04	0.07	0.20	−0.16***	0.00	−0.14**	0.01	−0.11*	0.04	−0.02	0.59	−0.11	0.06
Technological capabilities	0.03	0.61	0.05	0.38	0.03	0.59	−0.01	0.81	−0.03	0.61	−0.03	0.43	0.29***	0.00	0.20	0.38
HR slack	0.02	0.66	0.00	0.94	−0.02	0.72	0.06	0.25	0.07	0.13	0.09	0.07	−0.07	0.08	−0.15	0.01
Cost leadership	−0.03	0.59	0.03	0.61	0.03	0.64	0.01	0.88	−0.04	0.48	−0.04	0.50	−0.02	0.70	−0.11	0.07
Marketing differentiation	0.08	0.23	0.06	0.38	0.05	0.46	0.02	0.78	0.04	0.55	0.04	0.49	0.09	0.07	−0.01	0.19
Environmental uncertainty	0.01	0.77	−0.01	0.89	0.00	0.93	−0.04	0.29	−0.03	0.46	−0.04	0.30	0.03	0.38	−0.03	0.08
Flexibility	0.24***	0.00	0.24***	0.00	0.25***	0.00	−0.11	0.09	−0.11	0.08	−0.12	0.06	0.12*	0.02	0.02	0.23
Past performance	0.11	0.02	0.08	0.08	0.08	0.05	−0.05	0.21	−0.03	0.45	−0.04	0.38	−0.03	0.39	−0.10	0.04
Jolt duration	0.00	0.92	0.00	1.00	0.01	0.82	0.17***	0.00	0.17***	0.00	0.16***	0.00	0.03	0.46	−0.05	0.11
Industry	0.02	0.91	−0.04	0.83	−0.07	0.57	0.25	0.20	0.30	0.11	0.31	0.09	0.15	0.35	−0.16	0.45
State ownership	−0.42	0.09	−0.40	0.09	−0.45	0.05	0.21	0.35	0.19	0.38	0.23	0.30	0.13	0.47	−0.23	0.49
Foreign ownership	−0.17	0.66	−0.25	0.49	−0.22	0.54	0.07	0.84	0.13	0.70	0.10	0.75	0.11	0.69	−0.43	0.65
Firm age	−0.21	0.45	−0.23	0.39	−0.26	0.32	−0.33	0.21	−0.32	0.20	−0.30	0.24	−0.21	0.32	−0.61	0.20
Firm size	−0.02	0.88	0.03	0.82	0.05	0.70	0.16	0.25	0.12	0.37	0.11	0.43	0.13	0.25	−0.09	0.35
CEO company tenure	−0.01	0.51	−0.02	0.31	−0.01	0.47	0.03	0.13	0.03	0.07	0.03	0.11	0.01	0.49	−0.02	0.04
CEO functional background	0.06	0.77	0.11	0.55	0.12	0.54	0.18	0.34	0.14	0.45	0.14	0.45	0.24	0.11	−0.06	0.53
Opportunity													0.19***	0.00	0.08	0.28
Threat													0.14**	0.01	0.04	0.25
Differentiation × financial slack			−0.05*	0.05	−0.06*	0.02			0.03	0.20	0.04	0.12	0.15	0.48	−0.03	0.06
Differentiation × technological capabilities			0.10***	0.00	0.10***	0.00			−0.08***	0.00	−0.07***	0.00	−0.01	0.71	−0.04	0.03
Financial slack × technological capabilities			0.10***	0.00	0.10***	0.00			−0.07**	0.01	−0.07**	0.00	0.00	0.84	−0.04	0.05
Differentiation × financial slack × technological capabilities					0.02*	0.03					−0.02	0.11	0.01	0.14	−0.01	0.03
R ²	0.21***		0.31***		0.32***		0.14***		0.21***		0.21***		0.40***
F	4.29		6.17		6.17		2.58		3.62		3.59		7.69
R² increase due to three-way interaction					0.01*						0.00
F change	4.29		13.51		4.68		2.58		8.34		2.54

Note: N = 294. Unstandardized coefficients are reported. CE: corporate entrepreneurship; HR: human resource; LLCI: lower limit confidence interval; ULCI: upper limit confidence interval.

*p < 0.05; **p < 0.01; ***p < 0.001.

To help interpret this effect, we followed Aiken and West (1991) and ran simple slope tests (see Table 3) based on model 3. When financial slack is low, the simple slopes of the regression curve have a nonsignificant value for firms with weak technological capabilities (CI, lower bound = −0.02, upper bound = 0.06), and a significantly positive value for firms with strong technological capabilities (CI, lower bound = 0.01, upper bound = 0.12). When financial slack is high, the simple slopes of the regression curve have a significantly negative value for firms with weak technological capabilities (CI, lower bound = −0.13, upper bound = −0.02), and a significantly positive value for firms with strong technological capabilities (CI, lower bound = 0.02, upper bound = 0.10). Figure 2 demonstrates that when financial slack is low, differentiation has an increasingly positive effect on opportunity interpretations while technological capabilities become stronger. When financial slack is high, the impact of differentiation on opportunity interpretations changes from negative for firms with weak technological capabilities to positive for firms with strong technological capabilities. Thus, hypothesis 3 is supported.

Table 3.

Simple slope analyses for the association between differentiation and CE through opportunity at values of financial slack and technological capabilities.

Financial slack	Technological capabilities	Effect	LLCI	ULCI
Low	Low	0.02	−0.02	0.06
Low	High	0.03	0.01	0.12
High	Low	−0.06	−0.13	−0.02
High	High	0.02	0.02	0.10

Note: CE: corporate entrepreneurship; LLCI: lower limit confidence interval; ULCI: upper limit confidence interval.

Figure 2.

Three-way interaction among differentiation, financial slack, and technological capabilities on opportunity interpretations.

Hypothesis 4 proposes a three-way interaction effect among differentiation, financial slack, and technological capabilities on threat interpretations. Model 6 in Table 2 shows that the three-way interaction effect is nonsignificant (p = 0.11, lower bound CI = −0.04, upper bound CI = 0). Thus, hypothesis 4 is not supported.

Hypotheses 5 and 6 propose moderated mediation models between differentiation strategies and CE through opportunity and threat interpretation. We follow Hayes (2018) to examine moderated mediation. Hayes (2018) introduces “the concepts of partial moderated mediation, conditional moderated mediation, and moderated moderated mediation, along with corresponding indices used to test whether and to what extent an indirect effect is moderated in a model with two moderators. The indices of partial and conditional moderated mediation quantify the linear relationship between a moderator and an indirect effect when a second moderator is held constant (partial moderated mediation) or at a given value of the second moderator (conditional moderated mediation)” (Hayes, 2018: 5–6). The bootstrapping result based on 5000 bootstrap samples shows that for opportunity interpretations, the 95% CIs are between 0 and 0.0098. Because zero is not contained in the CIs, hypothesis 5 is supported. As shown in Table 4, when financial slack is low, differentiation has an increasingly positive effect on CE through opportunity interpretations while technological capabilities become stronger. When financial slack is high, the impact of differentiation on CE through opportunity interpretations changes from negative for firms with weak technological capabilities to positive for firms with strong technological capabilities.

Table 4.

Moderated mediation between differentiation and CE through opportunity interpretation.

Financial slack	Technological capabilities	Effect	LLCI	ULCI
Low	Low	0.01	−0.02	0.05
Low	High	0.05	0.02	0.12
High	Low	−0.06	−0.12	−0.02
High	High	0.04	0.01	0.09

Note: CE: corporate entrepreneurship; LLCI: lower limit confidence interval; ULCI: upper limit confidence interval.

As the three-way interaction among differentiation, financial slack, and technological capabilities on threat interpretations proposed in hypothesis 4 is not supported, hypothesis 6 is not supported.

We conduct a few supplementary analyses both as robustness tests and to explore potential determinants on threat interpretations. First, model 6 in Table 2 includes the nonsignificant three-way interaction among differentiation, financial slack, and technological capabilities on CE. We remove the three-way and all related two-way interactions, and the results still support hypothesis 5. Second, as executives may be more sensitive to threats, we examine the two-way interactions between differentiation and financial slack and between differentiation and technological capabilities on both threat interpretations and CE activities through threat. We find the significant interaction between differentiation and technological capabilities, and the mediating effect between differentiation and CE through threat interpretations is also significant. Specifically, we find that differentiation has an increasingly negative effect on CE through threat interpretations when technological capabilities become stronger. Finally, we explore the interaction effects between HR slack and other types of resources (e.g. financial slack, technological capabilities), which are nonsignificant.

Discussion

We find a three-way interaction with a differentiation strategy and technological capabilities and financial slack and its effect on opportunity interpretation. Technology capabilities provide the catalyst within the combination of strategy and resources to promote opportunistic framing. Financial slack can also be an important resource, but not in isolation. Our mediation model is confirmed when examining opportunity interpretation which provides insight into the effect reconfiguration of resources can have on CE, but there was less support for the threat interpretation side of the model.

Some interesting specific findings include the nonsignificant interaction effects between differentiation strategies and resource configurations on threat interpretations, and the nonsignificant mediating process between differentiation and CE through threat interpretation, though the two-way interaction between differentiation and technological capabilities is significant. One possible explanation for the finding is that threat interpretations are more driven by direct and external influence on the firm, especially on assets instrumental to the firms’ long-term survival. The significantly negative mediating effect between differentiation and CE through threat interpretations when firms hold strong technological capabilities may fit the perspective of threat rigidity (Staw et al., 1981).

Theoretical implications

Our findings illustrate the importance of examining business-level strategies and resource configurations in strategic issue interpretations and CE activities as responses to environmental jolts. Our findings suggest the importance of examining resources and external conditions when engaging in CE activities. Some researchers argue that studies that just focus on strategies and organizational outcomes provide models that are too simplistic (Mishina et al., 2004). The business-level strategy is the driving force of the firm, yet resource configurations are also important to provide the necessary tools to become that driving force. Although scholars (e.g. Dutton, 1992; Thomas and McDaniel, 1990) have proposed that current strategies should influence strategic actions with environmental changes through interpretations, this mediating process has been rarely examined in its full format. Our study is among the first to study the mediating role of interpretations between strategies and organizational responses to environmental jolts, based on the unique context of 2008 macro crisis. Our findings not only support the earlier theoretical proposition in Dutton (1992) that organizational paradigm, including strategy, is a crucial determinant of interpretations, but also extend earlier research by underlining the complementarity of differentiation strategy, technological capabilities, and financial slack.

Our study revisits the conventional beliefs that lacking a significant performance gap often prevents executives from taking actions (Gilbert, 2006). Our findings suggest that opportunity interpretations can lead to actions, given specific resource configurations at the firm. Thus, understanding internal resources and how they relate to external knowledge is an important basis of innovation activities (Howell and Shea, 2001). Moreover, unlike most current studies (e.g. Chattopadhyay et al., 2001) which take interpretations as exogenous and investigate how interpretations interact with resources or strategies to influence strategic moves, we view interpretations as endogenous and find that executives interpret environmental changes based on current strategies and existing resource repertoires.

This study also raises doubts about a common assumption in the strategy and entrepreneurship literature that entrepreneurs pursue opportunities regardless the availability of resources. The bundling of resources can be firm-specific and thus create a competitive advantage. Our article, together with empirical studies on opportunity heterogeneity (e.g. Haynie et al., 2009), suggests that the assumption is unrealistic for both entrepreneurs and top managers. They see opportunities and develop opportunity interpretations while taking resource endowments into consideration, so firms are bounded by what they are in the sense of strategies, resources, identity, and so on.

This study has practical implications for governments. During major environmental jolts such as the 2008 macro crisis and as a general policy in some cases, many national governments chose to give low-interest loans to domestic firms to encourage them to conduct more R&D and pursue CE activities to develop new businesses. Our results demonstrate that this policy is only functional for firms with a combination of specific strategies and resource configurations, while the policy can be counterproductive for firms with weak technological capabilities. A practical implication for the firm would be the importance of top management stressing the importance of framing the external environment within an opportunistic perspective in order to take of advantage of complementary resources and their effects on CE.

Limitations and future research

In general, our models predict opportunity-related models better than threat-related models. This may suggest that opportunity and threat interpretations may have very different mechanisms, and future research may need to further explore how threat interpretations are construed and what their consequences are.

Future research could also include the decision-making processes involved in determining the perceptions of threats and opportunities. Trustworthy characteristics such as competence or cognitive diversity may affect how executives view threats and opportunities. For example, a cognitively diverse team may view external events more as opportunities than threats, while a more trusting executive team may have more confidence in seeking opportunities.

A potential threat to research quality is sample selection bias. We compared responding and non-responding firms in both waves, and the t-tests demonstrated no significant differences in firm size and age. Another comparison between the 346-firm sample and the 294-firm sample based on t-tests on the environmental interpretations showed no significant difference between the two groups on interpretations. Second, it is likely that some non-responding firms failed during two waves of surveys. The nonsignificance of the firm age control variable in our regression analyses suggests that a survivor bias is unlikely to have biased our results. Finally, complex data relationships such as the expected interaction effects suggest that common method bias should not have led to the significant findings of interaction effects, as quadratic and interaction effects can be severely deflated through common method variance and would be more difficult to detect if common method bias existed (Siemsen et al., 2010). Respondents would normally not be capable of guessing the interaction hypothesis (e.g. Buyl et al., 2011). We also measured the antecedents and dependent variables in two waves with a 1-year time lapse. Although this method would not totally eliminate the potential common method bias, the timing of the surveys will minimize the potential concern.

In conclusion, the discussions and findings provide insight into strategic management literature. We underscore the importance of business-level strategies contributing indirectly to entrepreneurial activities. As well, certain resources and capabilities can be important moderators that influence CE. Scanning for opportunities and threats allows firms to choose what opportunities and threats to focus on when determining CE activities. Thus, with the appropriate business-level strategy, resources, and capabilities, firms can pursue CE based on the environmental landscape.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

References

Afuah

(2002) Mapping technological capabilities into product markets and competitive advantage: the case of cholesterol drugs. Strategic Management Journal 23: 171–179.

Aiken

West

(1991) Multiple Regression: Testing and Interpreting Interactions. Newbury Park, CA: Sage.

Amburgey

Miner

(1992) Strategic momentum: the effects of repetitive, positional, and contextual momentum on merger activity. Strategic Management Journal 13: 335–348.

Baron

(2006) Opportunity recognition as pattern recognition: how entrepreneurs “connect the dots” to identify new business opportunities. Academy of Management Perspectives 20(1): 104–119.

Barreto

Patient

(2013) Toward a theory of intraorganizational attention based on desirability and feasibility factors. Strategic Management Journal 34: 687–703.

Basardien

Friedrich

Parker

(2013) The relationship between planning strategies and entrepreneurial success for start-up entrepreneurs in the Western Cape: a psychological approach to entrepreneurship. The International Journal of Entrepreneurship and Innovation 14(4): 281–288.

Bradley

Shepherd

Wiklund

(2011) The importance of slack for new organizations facing “tough” environments. Journal of Management Studies 48(5): 1071–1097.

Brown

(2006) Confirmatory Factor Analysis for Applied Research. New York: Guilford Publications.

Buyl

Boone

Hendriks

, et al. (2011) Top management team functional diversity and firm performance: the moderating role of CEO characteristics. Journal of Management Studies 48: 151–177.

10.

Chang

Gong

Peng

(2012) Expatriate knowledge transfer, subsidiary absorptive capacity, and subsidiary performance. Academy of Management Journal 55: 927–948.

11.

Chattopadhyay

Glick

Huber

(2001) Organizational actions in response to threats and opportunities. Academy of Management Journal 44: 937–955.

12.

Cox

(2014) Fundamental entrepreneurial planning processes: resources assessment and opportunities evaluation. The International Journal of Entrepreneurship and Innovation 15(2): 79–88.

13.

Daft

Weick

(1984) Toward a model of organizations as interpretation systems. Academy of Management Review 9: 284–295.

14.

Dess

Lumpkin

Covin

(1997) Entrepreneurial strategy making and firm performance: tests of contingency and configurational models. Strategic Management Journal 18(9): 677–695.

15.

Durand

Coeurderoy

(2001) Age, order of entry, strategic orientation, and organizational performance. Journal of Business Venturing 16: 471–494.

16.

Dutton

(1992) The making of organizational opportunities: an interpretive pathway to organizational change. Research in Organizational Behavior 15: 195–226.

17.

Dutton

Jackson

(1987) Categorizing strategic issues: links to organizational action. Academy of Management Review 12: 76–90.

18.

Frank

Guttel

Kessler

(2017) Environmental dynamism, hostility, and dynamic capabilities in medium-sized enterprises. The International Journal of Entrepreneurship and Innovation 18(3): 185–194.

19.

Gilbert

(2006) Change in the presence of residual fit: can competing frames coexist? Organization Science 17: 150–167.

20.

Hayes

(2013) Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York: Guilford Press.

21.

Hayes

(2018) Partial, conditional, and moderated moderated mediation: quantification, inference, and interpretation. Communication Monographs 85(1): 4–40.

22.

Haynie

Shepherd

McMullen

(2009) An opportunity for me? The role of resources in opportunity evaluation decisions. Journal of Management Studies 46: 337–361.

23.

Heavey

Simsek

Roche

, et al. (2009) Decision comprehensiveness and corporate entrepreneurship: the moderating role of managerial uncertainty preferences and environmental dynamism. Journal of Management Studies 46: 1289–1314.

24.

Hoffman

Ocasio

(2001) Not all events are attended equally: toward a middle-range theory of industry attention to external events. Organization Science 12: 414–434.

25.

Howell

Shea

(2001) Individual differences, environmental scanning, innovation framing, and champion behavior: key predictors of project performance. Journal of Product Management 18: 15–27.

26.

Jackson

Dutton

(1988) Discerning threats and opportunities. Administrative Science Quarterly 33: 370–387.

27.

Julian

Ofori-Dankwa

(2008) Toward an integrative cartography of two strategic issue diagnosis frameworks. Strategic Management Journal 29: 93–114.

28.

Katila

Shane

(2005) When does lack of resources make new firms innovative? Academy of Management Journal 48: 814–829.

29.

Kor

Mahoney

Michael

(2007) Resources, capabilities and entrepreneurial perceptions. Journal of Management Studies 44: 1187–1212.

30.

Kraatz

Zajac

(2001) How organizational resources affect strategic change and performance in turbulent environments: theory and evidence. Organization Science 12: 632–657.

31.

Ling

Simsek

Lubatkin

, et al. (2008) Transformational leadership’s role in promoting corporate entrepreneurship: examining the CEO-TMT performance. Academy of Management Journal 51: 557–576.

32.

Liu

(2011) Technology embeddedness, innovation differentiation strategies and firm performance: evidence from Chinese manufacturing firms. Innovation 13: 20–35.

33.

McKissack

(2011) Chinese macroeconomic management through the crisis and beyond. Asian-Pacific Economic Literature 25: 43–55.

34.

Marino

Lohrke

Hill

, et al. (2008) Environmental shocks and SME alliance formation intentions in an emerging economy: evidence from the Asian financial crisis in Indonesia. Entrepreneurship Theory and Practice 32: 157–183.

35.

Martinez-Simarro

Devece

Llopis-Albert

(2015) How information systems strategy moderates the relationship between business strategy and performance. Journal of Business Research 68: 1592–1594.

36.

Miller

(1988) Relating Porter’s business strategies to environment and structure: analysis and performance implications. Academy of Management Journal 31: 280–308.

37.

Miller

Friesen

(1982) Innovation in conservative and entrepreneurial firms: two models of strategic momentum. Strategic Management Journal 3: 1–25.

38.

Milliken

(1990) Perceiving and interpreting environmental change: an examination of college administrators’ interpretation of changing demographics. Academy of Management Journal 33: 42–63.

39.

Mishina

Pollock

Porac

(2004) Are more resources always better for growth? Resource stickiness in market and product expansion. Strategic Management Journal 25: 1179–1197.

40.

Osiyevskyy

Dewald

(2015) Explorative versus exploitative business model change: the cognitive antecedents of firm-level responses to disruptive innovation. Strategic Entrepreneurship Journal 9(1): 58–78.

41.

Osiyevskyy

Tao

Jiang

, et al. (2017) Opportunity is in the eye of the beholder: behavioral drivers of alliance portfolio adaption to performance and environmental jolts. The International Journal of Entrepreneurship and Innovation 18(2): 115–127.

42.

Penrose

(1995) The Theory of the Growth of the Firm. Oxford: Oxford University Press.

43.

Pérez-Nordtvedt

Khavul

Harrison

, et al. (2014) Adaptation to temporal shocks: influences of strategic interpretation and spatial distance. Journal of Management Studies 51: 869–897.

44.

Pertusa-Ortega

Molina-Azorín

Claver-Cortés

(2009) Competitive strategies and firm performance: a comparative analysis of pure, hybrid and “stuck-in-the-middle” strategies in Spanish firms. British Journal of Management 20: 508–523.

45.

Plambeck

Weber

(2009) CEO ambivalence and responses to strategic issues. Organization Science 20: 993–1010.

46.

Porter

(1985) Competitive Advantage. New York: The Free Press.

47.

Priem

(1994) Executive judgment, organizational congruence, and firm performance. Organization Science 5(3): 421–437.

48.

Roy

Walters

Luk

(2001) Chinese puzzles and paradoxes: conducting business research in China. Journal of Business Research 52: 203–210.

49.

Siemsen

Roth

Oliveira

(2010) Common method bias in regression models with linear, quadratic, and interaction effects. Organizational Research Methods 13: 456–476.

50.

Song

Droge

Hanvanich

, et al. (2005) Marketing and technology resource complementarity: an analysis of their interaction effect in two environmental contexts. Strategic Management Journal 26: 259–276.

51.

Staw

Sandelands

Dutton

(1981) Threat-rigidity effects in organizational behavior: a multilevel analysis. Administrative Science Quarterly 26: 501–524.

52.

Tan

See

(2004) Strategic reorientation and responses to the Asian financial crisis: the case of the manufacturing industry in Singapore. Asia Pacific Journal of Management 21: 189–211.

53.

Tan

Peng

(2003) Organizational slack and firm performance during economic transitions: two studies from an emerging economy. Strategic Management Journal 24: 1249–1263.

54.

Thomas

Clark

Gioia

(1993) Strategic sensemaking and organizational performance: linkages among scanning, interpretation, action, and outcomes. Academy of Management Journal 36: 239–270.

55.

Thomas

McDaniel

(1990) Interpreting strategic issues: effects of strategy and the information-processing structure of top management teams. Academy of Management Journal 33: 286–306.

56.

Urban

(2010) Competitive strategies and links with environmental dynamism and hostility: a developing country study in technology enterprises. The International Journal of Entrepreneurship and Innovation 11(1): 69–77.

57.

Urban

(2014) The importance of attributes in entrepreneurial opportunity evaluations: an emerging market study. Managerial and Decision Economics 35(8): 523–539.

58.

Urban

Willard

(2017) The antecedents of opportunity recognition in international firms: an empirical study in South Africa. The International Journal of Entrepreneurship and Innovation 18(3): 175–184.

59.

Urbano

Turró

(2013) Conditioning factors for corporate entrepreneurship: an in(ex)ternal approach. International Entrepreneurship and Management Journal 9: 379–396.

60.

Verbeke

Yuan

(2007) Entrepreneurship in multinational enterprises: a Penrosean perspective. Management International Review 47: 241–258.

61.

Voss

Sirdeshmukh

Voss

(2008) The effects of slack resources and environmental threat on product exploration and exploitation. Academy of Management Journal 51: 147–164.

62.

Wales

Patel

Parida

, et al. (2013) Nonlinear effects of entrepreneurial orientation on small firm performance: the moderating role of resource orchestration capabilities. Strategic Entrepreneurship Journal 7: 93–121.

63.

Wan

Yiu

(2009) From crisis to opportunity: environmental jolt, corporate acquisitions, and firm performance. Strategic Management Journal 30: 791–801.

64.

Woo

Zhang

(2011) Combating the global financial crisis with aggressive expansionary monetary policy: same medicine, different outcomes in China, the UK and USA. The World Economy 34: 667–686.

65.

Zahra

(1996) Governance, ownership, and corporate entrepreneurship: the moderating impact of industry technological opportunities. Academy of Management Journal 39: 1713–1735.

66.

Zahra

Hayton

Neubaum

, et al. (2008) Culture of family commitment and strategic flexibility: the moderating effect of stewardship. Entrepreneurship Theory and Practice 32: 1035–1054.