Chapter 2: Literature Review and Hypotheses
2.7 Development of Hypotheses
2.7.6 Moderating Effect by Environmental Dynamism
In strategic management and organization theory literature, the external environment is viewed as a critical contingency factor (Child, 1972; Thompson, 1967).
According to future research on EO of Miller (2011), there have been numerous attempts to define context in terms of environmental uncertainty or dynamism (e.g., Becherer & Maurer, 1997), and organizational structure and process (Covin et al., 2006;
Green et al., 2008). Moreover, Rauch et al. (2009) review past studies, and suggest that environmental dynamism, a moderator, has been identified in most of EO research.
Although most studies propose and examine the influence of environmental dynamism on the EO-performance relationship (Covin & Slevin, 1989; Covin & Slevin, 1991;
Dess et al., 1997; Lumpkin & Dess, 1996; Wiklund & Shepherd, 2005; Zahra, 1993), several studies propose a concept of relationship between EO and internal resources that may be moderated by environmental dynamism (Hitt et al., 2011; Ireland et al., 2003;
Schumpeter, 1934). Therefore, how environmental dynamism moderate the relationship between EO and internal resources (such as resource attributes) has formed a gap in literature of EO. Following paragraphs argue the definition of environmental dynamism,
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the influence of environmental dynamism on the EO-performance relationship, and the moderating effect of environmental dynamism on the EO-resource attributes.
Environmental challenges often refer to the degree of dynamism of the environmental setting of a company (Lumpkin & Dess, 2001; Miller & Friesen, 1982).
Miller (1983) argues that environmental dynamism is associated with the unpredictability of customer tests, aggressive competitor actions, product/service shifts, and high rates of change in market and industry innovation. Miller (1990) further argues that firms with a higher degree of EO are more likely to pursue success when customers are able to be satisfied by obtaining a premium on innovation and unique services. According to the study of Porter and Kramer (2006), every firm operates within a competitive environment that can be derived from solving the issues of corporate social responsibility (CRS), and the external stakeholders are effort to let firms accountable for these issues. To respond competitive environment and to satisfy the rules of government and the sophistication of customer needs from external stakeholders, Porter and Kramer (2006) further integrate inside-out from value chain and outside-in practices from external competiveness, and each firm exploits resources (including management talent from human resource, expertise from knowledge resource, and relationships from organizational resource), thus gaining the greatest competitive benefits. Hamel (2000) suggests that the lifecycle of products and business models has been shortened in today’s competitive and dynamic environment, so that a firm with EO is encouraged to introduce novel products and services, which helps to
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minimise the threat resulting from environmental dynamism, thus sustaining the profitability of a firm.
Prior scholars have argued that environmental dynamism can influence the EO−firm performance relationship (Covin & Slevin, 1991; Lumpkin & Dess, 1996), and a great deal of existing literature suggests that environmental dynamism magnifies the link between EO and firm performance. For example, the empirical results gained by Li, Guo, Liu, and Li (2008) from a sample of 607 Chinese firms reveal an important finding, which is that technological turbulence significantly and positively moderates the relationship between EO and firm performance. Frese, Brantjes and Hoorn (2002) report that, in a dynamic and hostile environment, EO is positively related to firm growth. Similarly, in the empirical study by Miller (1988), the sample is composed of 89 firms from the province of Quebec, and he finds that innovative strategies in a dynamic environment are associated with higher performance. That is, firms facing higher environmental dynamism are more likely to make a profit from innovation (Kreiser & David, 2010; Miller, 1988), from making risky resource commitments (Kreiser & Davis, 2010), and from responding to the changes of competitors and customers (Lumpkin & Dess, 1996) than firms facing a relatively stable environment.
Although this study has argued that environmental dynamism would be an advantage for firms with EO, environmental dynamism could also be a disadvantage for firms (Dess et al., 1997; Wiklund & Shepherd, 2005). Firms may need the ability to control valuable and scarce resources in order to reduce the environmental dynamism
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they face (Jones, 2007). In other words, environmental dynamism acts to influence the relationship between EO and internal resources. To increase profits in a dynamic environment, firms often employ an EO to access valuable or rare tangible/intangible resource−capability combinations (Brown et al., 2001; Stevenson & Gumpert, 1985;
Sirmon, Hitt, & Ireland, 2007).
Therefore, this study expects that the levels of changes of environmental dynamism may influence EO-resource attributes relationship. In the pilot case study, according to the views of top managers in YAGEO Company and GIGA-BYTE Technology Company, a firm with EO is encouraged to have insights into, and exploit the relative value and rareness of resource-capability combinations when it faces the unpredictability of customer tests, aggressive competitor actions, the differentiations of products from other firms, and product/service changes involved with environmental dynamism. This argument is also consistent with the view of Schumpeter. According to Schumpeter (1934), entrepreneurship facilitates unique resource-capability combinations in dynamic and high-risk environments in a manner that distinguishes one firm from another by reducing costs or differentiating their products and services.
With respect to the model of strategic entrepreneurship (Ireland et al., 2003), it involves simultaneously opportunity-seeking (i.e., entrepreneurship) and advantage-seeking (i.e., strategic management) behaviour and results in a superior firm performance. Alvarez and Busenitz (2001) argue that entrepreneurial opportunities exist primarily because different agents among firms have different views or beliefs about the
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heterogeneity of resources that others do not have when they decide which resources to input into their production.
With respect to the entrepreneurial mindset, it represents the integration of individual entrepreneurs, managers and employees in established firms that think and act entrepreneurially. The entrepreneurial mindset is usually involved in an entrepreneurial posture or entrepreneurial orientation (Covin & Slevin, 1991). Firms with an entrepreneurial mindset are able to search for entrepreneurial opportunities in uncertain business environments and then determine the necessary resources to successfully exploit them (Ireland et al., 2003; McGrath & MacMillan, 2000). That is, in high levels of environmental dynamism, a firm with EO is more likely to have an entrepreneurial mindset and alertness, and thus it has opportunities to recognize valuable/rare resources and capabilities.
Based on the dynamic capability approach, Teece et al. (1997) emphasize that a firm has the capability to integrate and configure internal resources with the requirement of environmental dynamism; thus, competitive advantage or economic rents can be achieved. According to the perspective of dynamic capability (Zahra et al., 2006), the firm with entrepreneurship enable it to grasp market opportunities, which influences the configuration and combination of resources and capabilities to respond to shifts in the business environment.
In addition, pilot case study (please see Appendix B) has formed propositions 5 and 6 and represents that a firm with EO of innovation, proactiveness, and risk-taking
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would influence the exploitation and cultivation of valuable and rare resources in stimulation of environmental dynamism.
In summary, it can be concluded from the above discussion and pilot case study that to match high levels of environmental dynamism, firms that require EO (or entrepreneurial posture) can promote the value and rareness of their internal resources and capabilities, and the following hypotheses can be formed:
Hypothesis 6a: Environmental dynamism moderates the relationship between entrepreneurial orientation and the exploitation of value of resource-capability combinations.
Hypothesis 6b: Environmental dynamism moderates the relationship between
entrepreneurial orientation and the exploitation of rareness of resource-capability
combinations.
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Chapter 3
Methodology
Chapter 1 provides the background and motivations of the relationship between EO and firm performance in terms of the views of organization’s internal and external environment. Chapter 2 reviews three block literature: entrepreneurship and entrepreneurial orientation, resource-based view, and environmental dynamism, which highlights the influence of EO, environmental dynamism, and resource attributes on firm performance. In this methodology, four sections are included. First, based on the literature review, the research framework is introduced. Second, sample and data used in this study will be conducted and demonstrated by several analytical methods. The next section describes the measurements of following variables: (1) independent variables (i.e., EO, value, rareness, and environmental dynamism), (2) dependent variable (firm performance), and (3) control variables (i.e., firm size, firm age, debt-to-market ratio, and industry affiliation). The final section of this chapter introduces several analytical methods.
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3.1 Research Framework
Figure 3-1 illustrates the research framework of this study. This framework is anchored in theoretical contributions, extracted mainly from the resource-based view and entrepreneurship perspective. In this study, the main construct in the proposed model consists of EO, including innovation, proactiveness and risk-taking. Mediating constructs include the value and rareness of resource-capability combinations, and the moderating construct is environmental dynamism. The proposed conceptual linkage of these constructs is as follows: EO provides the starting point of this model and directly influences firm performance. The value and rareness of resource-capability combinations act as two critical positions and mediating roles in the relationship between EO and firm performance. Environmental dynamism acts as a moderating role in the associations between EO, value and rareness of resource-capability combinations, and firm performance. The association of all constructs is presented below.
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Figure 3-1 Theoretical Model of the Relationships among Entrepreneurial Orientation, Environmental Dynamism, Value, Rareness, and Firm Performance
3.2 Sample and Data
This cross-sectional study uses a sample from Taiwanese public firms for several reasons. First, Emerging economies are rapid-growth countries and economic liberalization is the primary engine of their growth. Taiwan represents an emerging market economy with relatively limited natural production factors, while its advanced factors, such as innovativeness and entrepreneurship, play an important role in its economic development (Wu et al., 2008). Oliver (1997) suggests that a firm can create and develop institutional environments to enhance the optimal use of resources. A firm with EO, comprising innovation, risk-taking, and competitive aggressiveness (Lumpkin & Dess, 1996; Miller, 1983), is the critical factor to manage its resources
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and capabilities in order to generate profits in an institutional environment of emerging economies (Luo, Sun, & Wang, 2011). Although prior scholars suggest that the relationship between EO and firm performance can be influenced by environmental factors, the study of this relationship in emerging economics is still lack. Only several studies examine the impact of EO on firm performance in emerging economics, such as Taiwan and China. For example, Lee and Sukoco (2007) investigate the effects of EO on organizational effectiveness in Taiwan, listed in the Top 1000 firms, and find a significant and positive association between EO and effectiveness. Based on the 607 firms in China, Li et al. (2008) identify the significantly positive impact EO on technology commercialization in turbulent technological environment.
In 2009, there have been 716 non-financial-sector TSE companies and 531 non-financial-sector OTC companies that provided complete data for analysis. Financial service firms were excluded from the research sample because their accounting practices were incompatible with those of other industries. Two methods were used for data collection. First, data on EO, value, rareness, environmental dynamism, and satisfication were obtained via a questionnaire survey, with top management as the respondents. The CEOs and top management of firms were initially contacted via telephone or personal visits to explain the purpose of this study. We sent a total of 1,247 questionnaires to the non-financial-sector TSE/OTC companies via post mail. A total of 247 questionnaires were returned, with a response rate of 20 percent. After eliminating some incomplete questionnaires, the final sample comprised 201 firms.
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Second, dependent variables (ROA and Tobin’s q) and some control variables were collected via a secondary database maintained by the Taiwan Economic Journal (TEJ), a leading credit analysis research agent and the most comprehensive business database in Taiwan, subscribed to by many international research agents such as Datastream, Dialog, Reuters, and Capital International.
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3.3 Measures
3.3.1 Independent Variables
EO. The independent variable in this study is EO. Three dimensions are used to measure EO, including innovation, proactiveness, and risk-taking. The three dimensions are measured by using nine questions developed by Miller (1983) and Covin and Slevin (1986, 1988, & 1989). Following these studies, a semantic differentials method is used in the questionnaire. This means that two opposing phrases are offered for each question, and respondents are asked to rank the indices on a seven-point Likert scale, ranging from 1 to 7. The higher the score, the stronger the EO is the firm. Reliability is estimated by using both coefficient alpha (Peter, 1979) and composite reliability (Fornell & Larcker, 1981). The Cronbach’s alpha values of the three dimensions are 0.800, 0.850, and 0.903 respectively, with an overall Cronbach’s alpha of 0.868. The test of reliability in our sample is consistent with past studies (Runyan, Droge, &
Swinney, 2008). The measure items of EO are shown in the Appendix A.
Resource-Capability Combination. These are the mediated variables of this study and are operationalized as two dimensions of resource attributes: value and rareness. The dimensions of value and rareness are measured by using the scales developed by Newbert (2008). Again, a seven-point Likert scale is used.
Value. The value of resource-capability combination is operationalized as an attribute in which the value of a resource (or a capability) can be enhanced when it is combined
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with a capability (or a resource) to reduce costs and exploit market opportunities (Newbert, 2008). It is measured using four questions, each with five items developed by Newbert (2008), including financial, human, intellectual, organizational, and physical resources/capabilities. An averaged score of the questions is then calculated to indicate the overall value of a firm’s resource-capability combination. The higher the score of a firm, the higher is the value of its resource-capability combination.3 This construct has an overall Cronbach’s α of 0.887. The measure items of value are shown in the Appendix A.
Rareness. The rareness of resource-capability combination is operationalized as a firm’s exploitation of a common resource (or capability) with a unique capability (or resource) or a firm’s exploitation of unique resource-capability combinations, in order to reduce costs, utilize market opportunities, or withstand competitive threats. Following Newbert (2008), this construct is measured using three questions, each with five items—financial, human, intellectual, organizational and physical resources/capabilities. Similarly, the averaged score of the questions is then calculated to indicate the overall rareness of a firm’s resource-capability combination. The higher the score of a firm, the higher is the rareness of its resource-capability combination.4 This construct has an overall Cronbach’s α of 0.925. The measure items of rareness are shown in the Appendix A.
Environmental dynamism. Environmental dynamism is a moderating variable in this
3 The respondents are asked to rank the extent to which they agree on a seven-point Likert scale, ranging from extremely disagree (=1) to extremely agree (=7).
4 Ibid, footnote 2.
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study. It is measured by using five questions, including extreme changes in marketing practices, a rapid rate of obsolescence in fashion goods/semi-conductors, the unpredictability of competitors, unpredictable demand and tastes of customers, and the modes of production/service change. The scales of environmental dynamism developed by Miller and Friesen (1982), and a semantic differential method is used in the questionnaire. Each question offers two opposite phrases. The overall Cronbach’s α is 0.81. The measure items of environmental dynamism are shown in the Appendix A.
3.3.2 Dependent Variables
Firm performance. Firm performance is the dependent variable in this study. Consistent with prior studies, this study uses two categories to measure firm performance:
subjective and objective measures, according to the recommendation of Weinzimmer, Nystrom, & Freeman (1998).
First, subjective measures are divided into competitive advantage and satisfaction, representing long-term performance. Following Newbert (2008), competitive advantage is based on the respondents’ answers to three questions, including cost reduction, opportunity exploration, and the defense of competitive threats. Each question includes five items to indicate different types of resource-capability combinations, i.e. financial, human, intellectual, organizational, and physical resources/capabilities.5 It has an overall Cronbach’s α of 0.903. The measure items of competitive advantage are shown in the Appendix A. In term of satisfaction, it is used in strategic management literature
5 Ibid, footnote 2.
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and organization literature (Murphy et al., 1996; Venkatraman & Ramanujam, 1986).
Following the studies of Beal and Yasai-Ardekani (2000), Newbert (2008), and Venkatraman and Ramanujam (1986), satisfaction consists of five indicators: sales growth rate, return of assets, rate of profits, customer satisfaction, and brand image.6 The overall Cronbach’s α is 0.844. The measure items of satisfaction are shown in the Appendix A.
Second, objective measures for performance include return on assets (ROA) and Tobin’s q (TQ), representing short-term performance (Beal & Yasai-Ardekani, 2000;
Fitzsimmons, Douglas, Antoncic, & Hisrich, 2005; Luke, Verreynne, & Kearins, 2007;
Venkatraman, & Ramanujam, 1986). The averaged annual rate of profit after taxes but before interest on total assets (ROA) between 2007 and 2009 is appropriate to estimate the effectiveness of the business operations (Combs & Ketchen, 1999) due to the high debt-equity ratio and imperfect capital markets in developing economics (Chang & Choi, 1988). Moreover, Tobin’s q has been widely used to examine the source of unequal profitability (Lindenberg and Ross 1981). The stock market of firm performance is Tobin’s q, the ratio of the firm’s market value to the replacement costs of its assets between 2007 and 2009. Following Khanna and Palepu (2000), Miller and Breton-Miller (2011), and Villalonga and Amit (2006), a proxy variable for Tobin’s q is defined as: (market value of equity plus book value of preferred stock plus book value of debt)/(book value of assets). ROA and Tobin’s q were collected via a secondary
6 The respondents are asked to rank the extent to which they agree on a seven-point Likert scale, ranging from not satisfactory at all (=1) to extremely satisfatory (=7).
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database maintained by the TEJ.
3.3.3 Control Variables
Control variables. Several variables that might influence the competitive advantage of firms are controlled in the regression models, including firm size, firm age, debt-to-market ratio (DEMKT), environmental dynamism, and industry affiliation.
Firm size reflects the economies and diseconomies of scale and may form barriers to entry (Bain, 1968) and is operationalized as the natural logarithm of the three-year average of total employees. Firm age is controlled because prior studies suggest that the established organizations are more bureaucratic, and this factor influences their competitive advantages (Hannan & Freeman, 1989). A firm’s age is measured as the company’s age since its establishment. DEMKT is controlled because a firm with a low debt-to-market ratio is more likely to create a competitive advantage (Chatterjee &
Wernerfelt, 1991; Palepu, 1986). Industrial environments are controlled by using industry affiliation (Khandwalla, 1976; Lumpkin & Dess, 2001, Miller & Friesen, 1982). Possible performance differences resulting from industrial affiliation are also controlled. Based on the industry classification of TSE, 17 dummy variables are used to classify the sample firms into 18 industries.7 Table 3.1 summarizes the number and percentage of firms based on their industrial categories.
7 According to the TSE database, these industries include cements, food and beverage, plastics, textile, electric machinery, electrical wire and cable, chemicals and biotechnology, glass and ceramic, paper, iron and steel, rubbers, information and electronics, building and construction, shipping and transportation, tourism, wholesale and retail trading, electricity, and other miscellaneous industries.
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TABLE 3.1 Number and Percent of Public Firms by TSE Industry Code
TEJ
23 Information and electronics 729 88 0.12 43.78%
25 Building and construction 53 20 0.38 9.96%
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3.4 Analytical Methods
This study uses several analytical methods to test all hypotheses. First, in subsections 4.2, 4.3, 4.4, and 4.5, the structural equation modeling (SEM) technique is conducted to test the proposed model.8 The data are analyzed by using the LISREL 8.54 software, and the maximum likelihood estimation (MLE) method is used to estimate the factor structure of the proposed model. A standard two-step process is followed, in which CFA is firstly performed to assess the measurement model, and the structural model is then constructed when the measurement model is upheld (Anderson
& Gerbing, 1988). The model fit is assessed by using χ2/df, goodness-of-fit index (GFI), comparative fit index (CFI), normal fit index (NFI), and root mean square error of approximation (RMSEA). The threshold for χ2/df should be less than 3.0, or less than 2.0 in a more restrictive sense (Premkumar & King, 1994). Values of GFI, CFI and NFI should be over 0.90, while the value of RMSEA should be less than 1.0. In order to confirm the validity of the measurement model, both the convergent and discriminant
& Gerbing, 1988). The model fit is assessed by using χ2/df, goodness-of-fit index (GFI), comparative fit index (CFI), normal fit index (NFI), and root mean square error of approximation (RMSEA). The threshold for χ2/df should be less than 3.0, or less than 2.0 in a more restrictive sense (Premkumar & King, 1994). Values of GFI, CFI and NFI should be over 0.90, while the value of RMSEA should be less than 1.0. In order to confirm the validity of the measurement model, both the convergent and discriminant