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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Theoretical Background
  5. Hypotheses Development
  6. Methods
  7. Discussion and Conclusion
  8. References

Based on institutional theory, this study investigates the moderating effects of different types of managerial networking (political networking, financial networking, and business networking) on the relationship between entrepreneurial orientation (EO) and new venture performance in China. The study finds that political networking has a negative moderating effect on the positive relationship between EO and new venture performance, financial networking has an inverse U-shaped impact, and business networking has a positive effect. The findings not only enrich our understanding of the impact of managerial networking on the performance implication of EO in new ventures, but also offer new ventures some guidance on how to use EO and different types of managerial networking to enhance performance in China's transition economy.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Theoretical Background
  5. Hypotheses Development
  6. Methods
  7. Discussion and Conclusion
  8. References

Although entrepreneurial orientation (EO) facilitates the pursuit of new opportunities to enhance performance, “adopting a strong EO is increasingly considered necessary but insufficient for wealth creation by new ventures” (Stam and Elfring 2008, p. 97). To realize its performance implication, EO requires large resource commitments (e.g., Covin and Slevin 1991; Su et al. 2011). However, due to the lack of resources, new ventures often fail to satisfy this resource requirement (Hitt et al. 2001; Li and Zhang 2007). As a result, access to resources plays an important role in whether new ventures can translate EO into higher performance (Wiklund and Shepherd 2005).

Managerial networking is a critical way to access resources for new ventures (e.g., Li and Zhang 2007; Luo 2003); thus, it moderates the relationship between EO and new venture performance (Simsek, Lubatkin, and Floyd 2003). Extant research indicates that different types of managerial networking function differently in new ventures (e.g., Huang 2008; Peng 2003; Peng and Zhou 2005). Thus, they may have different impacts on the performance implication of EO in new ventures. Consequently, how and in what manner different types of managerial networking affect the relationship between EO and new venture performance represents an important research issue (e.g., Stam and Elfring 2008; Walter, Auer, and Ritter 2006), yet few studies have investigated it, which is a serious research gap (Simsek, Lubatkin, and Floyd 2003).

The purpose of this paper, therefore, is to address this gap. Specifically, this study will employ a data set of Chinese new ventures to test the hypotheses. China's transition economy is used as the research context for three reasons. First, previous research on EO has been mainly limited to Western markets with relatively stable institutional environments; only a small part of these studies were conducted in transition economies (Su, Xie, and Li 2011; Zhou and Li 2007). As research horizons are now increasingly expanded to transition economies such as China, it is critical to know more about “what is going on there” if the field aspires to be globally relevant (Peng 2003). Second, the long tradition of using managerial networking makes China a good place to investigate managerial networking (Peng and Luo 2000). Finally, the failure rate of new ventures is exceptionally high in China. A recent report finds that the life expectancy of Chinese new ventures is fewer than three years, and more than 70 percent of them do not survive one year (Wang and Chen 2010). Thus, how to help Chinese new ventures gain success is a critical research question (Li and Zhang 2007).

It is noteworthy that the formal institutions that support free markets are still evolving in transition economies (Peng 2003; Puffer, McCarthy, and Boisot 2010). Institutional theory suggests that managerial networking serves as an informal institutional arrangement that substitutes for formal institutions in transition economies (Li, Poppo, and Zhou 2008; Xin and Pearce 1996) because it can fill in the institutional voids that result from an inadequate formal institutional infrastructure (Khanna and Palepu 1997; Luo 2003). Thus, institutional theory is insightful in exploring the value of managerial networking in transition economies, and it will be taken as the theoretical foundation of this study.

We will accomplish our objectives in four steps. First, we identify three important types of managerial networking—political networking, financial networking, and business networking. Then, we hypothesize their moderating effects on the relationship between EO and new venture performance by using institutional theory as the theoretical foundation and taking the characteristics of the Chinese institutional environment into consideration. Third, using the data on Chinese new ventures, we empirically test our hypotheses. Finally, we discuss our contributions, limitations, and future directions.

Several theoretical values distinguish this study. First, through investigating the moderating effects of different types of managerial networking on the relationship between EO and new venture performance, this study enriches our knowledge of how to transfer EO into higher performance in new ventures. Second, this study takes institutional theory as the theoretical foundation to examine the functions of different types of managerial networking, which improves our understanding of managerial networking during institutional transitions. Finally, how to help Chinese new ventures gain success is a critical research question (Li and Zhang 2007). This study contributes to this line of research by demonstrating the roles of EO and managerial networking.

Besides its theoretical value, this study also has strong practical implications. This study can guide Chinese new ventures to improve performance through the use of EO and managerial networking. Moreover, the findings have important implications for guiding Western firms in interacting with Chinese new ventures (Child and Tse 2001), and they can shed light on new ventures in other transition economies (Peng 2003). Overall, the importance of the research topic and context clearly suggests that this study is in a position to extend our theoretical understanding and to guide managerial implications as well.

Theoretical Background

  1. Top of page
  2. Abstract
  3. Introduction
  4. Theoretical Background
  5. Hypotheses Development
  6. Methods
  7. Discussion and Conclusion
  8. References

EO and New Venture Performance

EO, which refers to the “processes, practices, and decision-making activities that lead to new entry” (Lumpkin and Dess 1996, p. 136), consists of three dimensions: proactiveness, innovativeness, and risk-taking (Covin and Slevin 1991; Miller 1983). Proactiveness reflects the process of “seeking new opportunities which may or may not be related to the present line of operations, introduction of new products and brands ahead of competition, and strategically eliminating operations which are in the declining stages of life cycle” (Venkatraman 1989, p. 949). It aids finding opportunities in the market, quickly seizing those opportunities, and garnering a high profit (Wiklund and Shepherd 2005). Innovativeness refers to the tendency to “engage in and support new ideas, novelty, experimentation, and creative processes that may result in new products, services, or technological processes” (Lumpkin and Dess 1996, p. 142). It facilitates the use of new approaches to seize opportunities brought about by changes in external environment (Covin and Slevin 1989). Risk-taking implies a willingness to commit resources to projects with high failure rates and unknown outcomes (Wiklund and Shepherd 2005). It enables new ventures to conduct risk-taking behaviors in the interest of obtaining high returns (Lumpkin and Dess 1996), and it contributes to embarking on proactive and innovative initiatives to alter the competitive landscape of the market (Covin and Slevin 1991).

Theoretically, proactiveness, innovativeness, and risk-taking all facilitate the pursuit of new opportunities that enhance performance; thus, EO should have a significant performance implication in new ventures (Covin and Slevin 1989). However, “adopting a strong EO is increasingly considered necessary but insufficient for wealth creation by new ventures” (Stam and Elfring 2008, p. 97). The empirical findings regarding the extent to which EO is associated with improved performance are inconsistent as well. Although a large number of studies find a strong positive relationship between EO and performance, other studies report weak correlations (e.g., Lumpkin and Dess 2001; Walter, Auer, and Ritter 2006) or are unable to find a significant relationship (e.g., Covin, Slevin, and Schultz 1994; George, Wood, and Khan 2001; Li, Zhang, and Chan 2005; Stam and Elfring 2008). “Although differences in findings may be attributed to differences in research design or methodological idiosyncrasies, such differences apparently reflect the fact that EO may sometimes, but not always, contribute to improved performance” (Wiklund and Shepherd 2005, p. 73).

Scholars indicate that EO is resource-consuming (e.g., Covin and Slevin 1991; Su et al. 2011). Proactiveness, innovativeness, and risk-taking all “involve making large resource commitments to risky projects, untried technologies, new products or services to the market” (Tang et al. 2008, p. 222). Conversely, “resource constraints may be associated with internal control and attempts to conserve the limited resources at hand, stifling entrepreneurial initiatives” (Wiklund and Shepherd 2005, p. 73). Without considerable resources, the performance implication of EO will be impeded (Tang et al. 2008). Hence, only with sufficient resources can EO be translated into higher performance (Covin and Slevin 1991; Zahra 1991).

New ventures often lack resources (e.g., Hitt et al. 2001; Li and Zhang 2007); thus, a possible reason for the failure of new ventures to translate EO into higher performance is that they are not able to satisfy the resource requirement of EO. To pursue opportunities, new ventures often need to acquire external resources; therefore, the access to resources is critical to the performance implication of EO in new ventures (Wiklund and Shepherd 2005). Managerial networking plays an important role in accessing resources in new ventures (e.g., Li and Zhang 2007; Luo 2003); thus, it has an important impact on the relationship between EO and new venture performance. As a result, the role played by managerial networking in transferring EO into higher new venture performance represents an important research issue (e.g., Stam and Elfring 2008; Walter, Auer, and Ritter 2006).

Several scholars have investigated this issue, from different points of view. For example, Walter, Auer, and Ritter (2006) focus on the impact of network capability, and they find that network capability contributes to the performance implication of EO in university spin-offs. Stam and Elfring (2008) examine how the configuration of the industry network shapes the relationship between EO and new venture performance. They find that the combination of high network centrality and extensive bridging ties strengthen the linkage between EO and new venture performance, but centrality weakens this relationship in ventures with few bridging ties.

Although existing studies have enriched our knowledge of the impact of managerial networking on the relationship between EO and new venture performance, a serious research gap remains: How and in what manner do different types of managerial networking moderate the relationship between EO and new venture performance (Simsek, Lubatkin, and Floyd 2003)? Because different types of managerial networking function diversely in new ventures (e.g., Huang 2008; Peng 2003; Peng and Zhou 2005), it is important to investigate the roles played by them in the relationship between EO and new venture performance. This is because it aids providing a more comprehensive picture of how managerial networking affects the relationship between EO and new venture performance (Stam and Elfring 2008; Walter, Auer, and Ritter 2006).

Managerial Networking

Top managers play crucial roles in new ventures, and their actions are embedded in their social network of relationships (Granovetter 1985). As a result, managerial networking, which is defined as the extent to which managers cultivate relationships with executives in external entities (Li and Zhang 2007), affects an organization's competitive advantage and performance (e.g., Luo 2003; Peng and Luo 2000).

During institutional transitions, because the redistributive mechanism (the allocation of resources mainly by government agencies) and the market mechanism (the allocation of resources mainly by market forces) coexist, firms can acquire resources from both the government and financial institutions (Li and Zhang 2007; Luo 2003; Peng and Luo 2000). Thus, both political networking (cultivating relationships with government officials and agencies) and financial networking (cultivating relationships with financial institutions) are emphasized as important managerial networking. In addition, business networking (cultivating relationships with buyers, suppliers, and competitors) can facilitate interfirm resource exchanges; thus, it is also a critical component of managerial networking (see, e.g., Chen, Chen, and Xin 2004; Li, Poppo, and Zhou 2008; Luo 2003; Peng and Luo 2000). In summary, political networking, financial networking, and business networking are three important types of managerial networking.

Scholars have paid considerable attention to managerial networking (e.g., Acquaah 2007; Park and Luo 2001; Peng and Luo 2000). They find that managerial networking is particularly important in countries without a stable legal and regulatory environment that allows for impersonal business dealings (Redding 1990; Zucker 1986). Moreover, the values of managerial networking change diversely with institutional transitions (e.g., Huang 2008; Peng 2003; Peng and Zhou 2005). Thus, institutional theory is an insightful theory for investigating managerial networking in transition economies.

Institutional Theory and Managerial Networking

Institutions are commonly understood as the “rules of the game in a society” (North 1990, p. 3). A firm's strategy is shaped, at least in part, by the institutional framework (Peng 2003). Institutional theory on strategy has two core propositions: “managers and firms rationally purse their interests and make strategic choices within institutional constraints” and “while formal and informal institutions combine to govern firm behavior, in situations where formal constraints fail, informal constraints play a large role in reducing uncertainty and providing constancy to managers and firms” (Peng 2006, p. 117).

In transition economies, the formal institutions supporting free markets are still evolving (Peng 2003; Puffer, McCarthy, and Boisot 2010). A common feature permeating transition economies is that the factor markets are underdeveloped; thus, it is often difficult for firms to acquire resources in the market (Peng and Heath 1996). In addition, the lack of market-supporting institutions allows widespread opportunistic behaviors (Hoskisson et al. 2000). In such a context, through filling in the institutional voids resulting from an inadequate formal institutional infrastructure (Khanna and Palepu 1997; Luo 2003), managerial networking can reduce transaction costs and increase transaction values by facilitating the exchange of resources (Luo 2003). Thus, “the institutional voids force managers to rely on personal ties and connections to substitute for formal institutional support” (Li, Poppo, and Zhou 2008, p. 384).

Although managerial networking serves as an informal institutional arrangement that substitutes for formal institution in transition economies (Li, Poppo, and Zhou 2008; Xin and Pearce 1996), it is not always beneficial (Huang 2008; Peng 2003). The implication of managerial networking depends on the net return after adjusting for the cost (Luo 2003; Mizruchi and Galaskiewicz 1994). Extant research finds that the value of managerial networking is contingent on the institutional environment (Peng 2003; Peng and Zhou 2005). Thus, to probe deep into the roles of different types of managerial networking, the institutional characteristics of China's transition economy will be briefly discussed.

China's Institutional Transitions

Since its economic reform, China has been reforming its institutions from a command economy to market economy, and fundamental changes in its institutional frameworks have occurred over the past three decades (Huang 2008; Peng 2003). “The most notable change in formal constraints has been the gradual dismantling of the central planning regimes, replaced by more market-based transactions to facilitate economic exchange” (Peng and Heath 1996, p. 502). As increasingly mature formal rules are being promulgated, China is located at the middle stage of institutional development (Li and Yang 2006; Peng and Zhou 2005). “In this phase, relational transacting begins to give way to a rules based mode of exchange while markets and institutions are still under development” (Walsh, Bhatt, and Bartunek 2009, p. 266).

Today, China presents three important institutional characteristics that strongly affect the values of managerial networking. First, the “dismantling of the central planning regimes” (Peng and Heath 1996, p. 502) has led the resources controlled or redistributed by the governments to diminish (Pistor, Raiser, and Gelfer 2000). “With the decrease of resource level that a government could control, the return for firms' strong ties with governments may gradually diminish” (Peng and Zhou 2005, p. 326). In addition, because more transparent rules are being introduced, “the need to interact with the government is reduced” (Peng 2003, p. 289). Thus, many Chinese firms, especially new ventures, which historically had linkages with the governments, are now distancing themselves from the bureaucrats (Peng 2000).

Second, China's financial market infrastructure is weaker than those of developed economies (Khanna and Palepu 2000). For example, the first official regulation on venture capital was announced on March 1, 2006, and ChiNext, which aims to provide solid support for the development of independently innovative firms and other growing ventures (http://www.szse.cn/main/en/ChiNext/aboutchinext/) was launched on October 30, 2009. Nowadays, China is still trying to build its multitier capital market system. Podolny (2001) suggests that through offering a fast mechanism to obtain private information, financial networking provides an advantage for obtaining resources and reducing the tendency to behave opportunistically. Thus, financial networking is critical to obtain resources from financial institutions under the context of a weak financial market infrastructure (Batjargal and Liu 2004).

Finally, Chinese “markets and institutions are still under development” (Walsh et al. 2009, p. 266). On the one hand, there are significant institutional voids resulting from an inadequate formal institutional infrastructure (Khanna and Palepu 1997; Luo 2003); on the other hand, the formal institutions supporting free markets are evolving (Peng 2003; Puffer, McCarthy, and Boisot 2010). Under such conditions, business networking is still critical because it aids reducing the transaction costs of the rules-based mode of exchange and the hazardous effect of market volatility (Luo 2003; Park and Luo 2001; Xin and Pearce 1996).

In summary, China's institutional transitions have significant influences on managerial networking (Peng 2003; Peng and Luo 2000), and they lead to different types of managerial networking that are diverse in their values (Huang 2008). Thus, the impacts of political networking, financial networking, and business networking on the relationship between EO and new venture performance will be discussed by taking China's institutional characteristics into consideration.

Hypotheses Development

  1. Top of page
  2. Abstract
  3. Introduction
  4. Theoretical Background
  5. Hypotheses Development
  6. Methods
  7. Discussion and Conclusion
  8. References

EO and New Venture Performance in China

Although “adopting a strong EO is increasingly considered necessary but insufficient for wealth creation by new ventures” (Stam and Elfring 2008, p. 97), we still argue that EO contributes to new venture performance in China for three reasons. First, China's institutional transitions have brought a large number of opportunities (Peng and Heath 1996). For example, private firms are allowed to enter most industrial sectors (a small part of industries concerned with national safety are still forbidden or restricted), and they can export their products directly (formerly, they needed to export their products through international trading companies). EO facilitates the pursuit of opportunities (Covin and Slevin 1991; Lumpkin and Dess 1996; Wiklund and Shepherd 2005); thus, it enhances new venture performance. Second, China's institutional transitions have led to great uncertainties in the market (Peng and Heath 1996). Firms with higher EO are good at monitoring environmental changes and adapting quickly to those changes (Keh, Nguyen, and Hwei 2007; Rauch et al. 2009; Venkatraman 1989). Thus, greater EO puts new ventures in a position to deal with such uncertainties more effectively and to enjoy high entrepreneurial profit (Wiklund and Shepherd 2005). Finally, prior research finds that EO enhances new venture performance and Chinese firm performance (e.g., Keh, Nguyen, and Hwei 2007; Su et al. 2011; Wiklund and Shepherd 2005). The meta-analysis by Rauch et al. (2009) also suggests new ventures benefit from pursuing a strong EO. Therefore,

  • H1: There is a positive relationship between EO and new venture performance in China.

The Moderating Effect of Political Networking

The resources controlled by the government directly affect the extent of firms' resource dependence on the government (Peng and Zhou 2005). With the reformation of economic systems, the resources controlled and redistributed by the Chinese government are gradually diminishing (Luo 2003; Peng 2003; Pistor, Raiser, and Gelfer 2000). The decrease in level of resources that the government controls makes the return from political networking diminish (Peng and Zhou 2005). In addition, the development of factor market and the introduction of transparent rules in China make “the need to interact with the governments reduced” (Peng 2003, p. 289). Therefore, China's institutional transitions have reduced the return of ties with the government (Huang 2008; Peng and Zhou 2005), and firms no longer rely on the government for dispatching needed resources (Luo 2003). In other words, China's institutional transitions have dramatically decreased the benefit of political networking. Nowadays, many Chinese firms, especially new ventures, which historically had linkages with government, are now distancing themselves, because they cannot acquire resources from the government (Peng 2000).

It is also noteworthy that the cost of establishing and maintaining a political network is still very high (Huang 2008; Luo 2003). Chen and Chen (2004) indicate that the development of a political network takes a long time. And during this process, firms need to spend considerable time, resources, and effort on cultivating connections with government officials and agencies (Chen and Chen 2004; Huang 2008; Li and Zhang 2007). In addition, firms need to devote substantial time, resources, and effort to maintain good relationships with government officials and agencies (Li and Zhang 2007). As a result, the low return and high cost of political networking makes it not cost-effective for new ventures (Huang 2008; Peng and Zhou 2005).

To achieve the goal of EO, new ventures need to acquire sufficient resources (Keh, Nguyen, and Hwei 2007; Su et al. 2011). Yet political networking not only cannot provide resources, but also spends the tiny resources held by new ventures. Thus, political networking damages the performance implication of EO in new ventures. In addition, firms with political relationships are often risk-averse and short-term-oriented (Peng, Tan, and Tong 2004; Tan and Tan 2005). However, risk-taking is a critical dimension of EO, and it assists firms in embarking on proactive and innovative initiatives (Wiklund and Shepherd 2005). Moreover, the values of proactive and innovative initiatives caused by EO are long-term (Wiklund 1999). As a result, the risk-averse and short-term orientation caused by political networking impedes the positive relationship between EO and new venture performance as well. Therefore,

  • H2: Political networking has a negative moderating effect on the relationship between EO and new venture performance, such that the relationship between EO and new venture performance will become less positive as political networking increases.

The Moderating Effect of Financial Networking

Compared with developed economies, the financial market infrastructure is weaker in China (Khanna and Palepu 2000). Because of the high risks of new ventures, information asymmetries between new ventures and financial institutions, and the weak financial market infrastructure (Batjargal and Liu 2004; Su, Xie, and Li 2009), it is often difficult for Chinese new ventures to acquire funds from financial institutions. Podolny (2001) suggests that by offering a fast mechanism to obtain private information, financial networking provides an advantage for obtaining resources from others and reducing the tendency to behave opportunistically. Financial networking enables the transfer of information that reduces financial institutions' doubts about new ventures and instills greater confidence (Shane and Cable 2002). Thus, new ventures with strong financial networking are more likely to obtain resources from financial institutions. Batjargal and Liu (2004) present empirical evidence that financial networking has a significant impact on the investment decisions of financial institutions in China.

Nevertheless, there is an upper limit to the funds new ventures can acquire from financial institutions for several reasons. First, Chinese commercial banks face rigorous regulations on lending to new ventures, which makes them unwilling to loan to new ventures (Cooper and Yin 2006). Second, the high failure rate of new ventures makes it impossible for commercial banks to provide a large number of loans to new ventures, because commercial banks cannot prosper with very high-risk loans and they need to ensure the safety of their loans with reasonable returns (Batjargal and Liu 2004; Shane and Cable 2002). Finally, as venture capital and ChiNext are just now emerging in China, they are not able to provide adequate funds to new ventures either (Liao and Sohmen 2001). As a result, the total funds available to Chinese new ventures from financial institutions are finite.

However, building and maintaining a financial network requires substantial time and resources, and its costs increase dramatically (Adler and Kwon 2002). When cultivating relationships with financial institutions, an executive needs to spend substantial time and resources. And the time and resources spent on financial networking increase at an accelerating rate, since financial networking becomes more and more complicated as the network gains strength and expands (Gulati, Nohria, and Zaheer 2000; Perry-Smith and Shalley 2003). Thus, the costs of financial networking increase dramatically (Adler and Kwon 2002). As a result, the limited funds new ventures can acquire and the dramatically increased cost of financial networking lead to an inverse U-shaped relationship between financial networking and the net resource new ventures can acquire from financial institutions.

EO involves making large resource commitments (Keh, Nguyen, and Hwei 2007; Li, Zhang, and Chan 2005). Thus, we argue that the moderating effect of financial networking on the relationship between EO and new venture performance is inverse U-shaped. When new ventures are lacking a financial network, it is difficult for them to acquire resources from financial institutions. Such resource constraints stifle entrepreneurial initiatives (Wiklund and Shepherd 2005) and impede the performance implication of EO (Tang et al. 2008). Hence, the positive relationship between EO and new venture performance is restricted when the financial networking is at a low level.

With the strengthening of financial networking, new ventures can acquire more resources from financial institutions to meet the resource commitments of EO (Batjargal and Liu 2004; Shane and Cable 2002), which can enhance the relationship between EO and new venture performance. Thus, the relationship between EO and new venture performance will be increasingly positive as financial networking increases.

However, the inverse U-shaped relationship between financial networking and the resources new ventures can acquire from financial institutions indicates that there is an optimal level of financial networking. If financial networking passes this level, its net value decreases. The decrease in the net value of financial networking reduces the resources it can provide to satisfy the requirement of EO; thus, the positive relationship between EO and new venture performance will diminish as financial networking passes the optimal level.

In other words, new ventures with medium-level financial networking can acquire more resources to satisfy the requirement of EO than those with low- and high-level financial networking. Because resources are crucial to the performance implication of EO (see, e.g., Covin and Slevin 1991; Su et al. 2011), the positive relationship between EO and new venture performance will be the strongest when financial networking is at the medium level. Therefore,

  • H3: Financial networking has an inverse U-shaped moderating effect on the relationship between EO and new venture performance, such that the relationship between EO and new venture performance will be the strongest when financial networking is at the medium level.

The Moderating Effect of Business Networking

Existing studies have provided ample evidence that business networking aids acquiring resources, valuable information, and knowledge (e.g., Acquaah 2007; Peng and Luo 2000). Ties with customers and suppliers facilitate the creation, acquisition, and exploitation of knowledge (Li, Poppo, and Zhou 2008; Luo 2003). Furthermore, close contacts with suppliers is helpful in acquiring quality materials, superior services, and timely and reliable delivery (Peng and Luo 2000). Ties with buyers create customer loyalty, sales volume, and reliable payment (Park and Luo 2001). Good relations with competitors facilitate information and resource sharing (Acquaah 2007) and implicit collusion to deal with environmental uncertainties (Chen, Chen, and Xin 2004). Thus, business networking is helpful for new ventures to benefit from sharing not only operational resources but also organizational resources (Luo 2003).

In China's transition economy, the “markets and institutions are still under development” (Walsh et al. 2009, p. 266). There are significant institutional voids resulting from an inadequate formal institutional infrastructure (Khanna and Palepu 1997; Luo 2003), and the formal institutions supporting free markets are evolving (Peng 2003; Puffer, McCarthy, and Boisot 2010). Such faulty institutional conditions create an uncertain and risky business environment (Li and Zhang 2007). Thus, business networking becomes important for new ventures because it can reduce the hazardous effect of market volatility (Peng and Luo 2000). In addition, by reducing transaction costs, business networking helps new ventures save resources (Luo 2003). Thus, as new ventures continue their interactions with other firms, there exists a deliberate and unintended accumulation of resources (Park and Luo 2001).

Furthermore, the cost of business networking is much less than its benefit for three reasons. First, new ventures can cultivate business networking through regular business and cooperation with buyers, suppliers, and competitors rather than spending special resources and time on it (Luo 2003). Second, new ventures often interact with buyers, suppliers, and competitors; thus, a designed effort to maintain business networking is unnecessary (Acquaah 2007). Finally, China has a long tradition of utilizing business networking, and the evolution of such a tradition has dramatically reduced its cost (Li, Poppo, and Zhou 2008; Peng and Luo 2000). Overall, the significant benefit and the low cost of business networking enable new ventures to acquire more resources (Luo 2003; Park and Luo 2001).

We argue that business networking has a positive moderating effect on the relationship between EO and new venture performance. The performance implication of EO depends on the extent to which its resource requirement is met (Covin and Slevin 1991; Su et al. 2011). By leading to a deliberate and unintended accumulation of resources (Park and Luo 2001), business networking helps new ventures meet the resource requirement of EO and supports its performance implication (Keh, Nguyen, and Hwei 2007). In addition, business networking aids in monitoring market changes and identifying emerging technologies and demands, which present opportunities for entrepreneurial activities (Christensen 1997). Moreover, as an informal institutional arrangement, business networking becomes an effective substitute for formal contracts in transition economies to facilitate interfirm collaboration, which helps translate EO into higher performance (Adler and Kwon 2002; Li, Poppo, and Zhou 2008). Therefore,

  • H4: Business networking has a positive moderating effect on the relationship between EO and new venture performance, such that the relationship between EO and new venture performance will become more positive as business networking increases.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Theoretical Background
  5. Hypotheses Development
  6. Methods
  7. Discussion and Conclusion
  8. References

Sample and Data Collection

We initiated this research with in-depth interviews of five Chinese new ventures in order to enrich our understanding of EO and managerial networking. To test the hypotheses, we used the questionnaire survey method. We developed a questionnaire following previous studies and modified it through consulting with the executives of the interviewed ventures. A pilot test was conducted with 10 firms (not including those five interviewed ventures). The responses of the pilot test were excluded from the final study. The questionnaire was revised using the feedback from the pilot study. The questionnaire was first prepared in English and then translated into Chinese. The Chinese version was subsequently back-translated into English by a third party to ensure accuracy (Chen, Chun, and Sego 1998). Two translations indicate no substantial differences in the meaning of the scales.

To perform the data collection task more effectively, we collected data with three partners at three universities located in Beijing, Shandong, and Henan. We gathered our data in three phases. First, our partners provided us the directories of firms in the manufacturing sector. The directories included as many firms as possible. In previous research, firms that were eight years old or younger were considered new ventures (Li and Zhang 2007; McDougall et al. 1994); thus, a sampling strategy was employed to identify prospective firms based on this criterion. We randomly selected 300 new ventures from the directories. Then, we gave them a brief outline of our study and requested their participation in the project. To encourage participation, we promised to provide a customized report if they participated.

Finally, the direct interview method was adopted to obtain responses. The direct interview method permits us to clarify respondents' queries on the spot, to avoid a situation in which a busy executive or senior manager delegated the task of completing the survey to his/her secretary, and to ensure that most of the responses collected were complete and usable for data analysis. Based on the number of firms that agreed to participate in our survey, we assigned one or two interviewers to each geographical area. All of the interviewers were Ph.D. students and faculty in Chinese universities, and some of them had taken part in an interview survey before. All the interviewers received about one week's training before embarking on the interview process. The training covered the background information, the objectives of the survey, interviewing techniques, and, most importantly, the exact meaning of each question in the questionnaire. This procedure helped to ensure the correct interpretation of questions in the survey instrument.

A special effort was made to contact the executive or senior manager in each firm who was directly in charge. Once they agreed to an interview, our interviewers would go to the firm to conduct the interview. At the beginning of each session, the interviewer showed the interviewee a letter that explained the intent of the survey and stated our promise to keep the responses confidential. Then, they requested top managers to complete the survey. Most of the surveys were completed by CEOs; the others were done by another top manager who had full information.

We started the survey in November 2006 and had obtained 101 new ventures by March 2007. After omitting samples with missing data, we finally got 84 firms for an effective response rate of 28 percent. The profile of the respondents can be seen in Table 1. The responses were from the municipality of Beijing and from Shaanxi, Henan, Shandong, and Hebei provinces. These provinces cover the eastern, western, and central areas of China. By drawing samples from a diverse geographical base, we minimize the possible bias caused by characteristics specific to a particular area. New ventures in the manufacturing industry account for a large part of new ventures in China; thus, the manufacturing industry is suitable for research on new ventures. We focused on it to eliminate the differences between industries.

Table 1. Profile of Responding New Ventures and Respondents
  1. a

    S.D., standard deviation.

Respondents'Number of Years in the Company, Mean (S.D.)a5.15 (1.18)
Number of Employees (percent) 
≤30070.2
301–60014.3
601–1,00010.7
1,001–2,0003.6
>2,0001.2
Sales (million RMB) (percent) 
≤1023.8
10–5027.4
50–10019.0
100–20010.7
>20015.5
Unreported3.6
Type of Ownership (percent) 
State-Owned Enterprises3.6
Private Companies34.5
Collective Enterprises10.7
Limited Companies38.1
Joint Ventures8.3
Others (e.g., Village Firms)4.8

One issue commonly raised concerning survey methodology is nonresponse bias. Following previous research (e.g., Li, Liu, and Liu 2011; Villena, Revilla, and Choi 2010), the likelihood of nonresponse bias was tested by splitting the total sample into two equal parts based on the time we got the response (Armstrong and Overton 1977). A comparison of the two groups revealed no significant difference in firm size (t = 0.12, p = .90), age (t = −0.73, p = .47), EO (t = 0.24, p = .81), performance (t = 0.43, p = .67), political networking (t = −0.45, p = .65), financial networking (t = 0.28, p = .78), or business networking (t = −0.42, p = .67). Moreover, there were no significant differences for key factors such as size, age, and performance between our 84 usable firms and the 17 deleted firms. The comparison between responding and nonresponding firms in terms of age was insignificant as well. These results collectively support the assumption that respondents were not different from nonrespondents.

Variables and Measures

Where possible, standard and validated instruments from the literature are used or adapted. In the absence of any existing scale, new items are created based on the literature and refined by our pilot test. Questionnaire items, unless stated otherwise, are measured using a seven-point scale in which “1” represented “strongly disagree” and “7” represented “strongly agree.”

Entrepreneurial Orientation

Based on previous studies (e.g., Covin and Slevin 1989; Keh, Nguyen, and Hwei 2007; Miller 1983), EO is measured by nine items: (1) “In my company, there exists a very strong emphasis on R&D, technological leadership, and innovations”; (2) “The changes in product lines (types/number of products) for my company have usually been dramatic”; (3) “When it comes to problem solving, we value creative new solutions more than the solutions of conventional wisdom”; (4) “Top managers here encourage the development of innovative marketing strategies, knowing well that some will fail”; (5) “I have a strong preference for high-risk projects (with chances of very high return)”; (6) “I believe that, owing to the nature of the environment, bold, wide-ranging acts are necessary to achieve the firm's objectives”; (7) “My company is typically the first to initiate actions to competitors, for which the competitors then respond”; (8) “Very often, my firm is the first company to introduce new products/services, techniques, technologies, etc.”; and (9) “We firmly believe that a change in market creates a positive opportunity for us.”

Political Networking

Three items are adapted from Li and Zhang (2007) to measure political networking.1 The scale indicates the extent to which the new ventures' senior management over the past three years has (1) spent much effort on cultivating connections with officials of government and its agencies; (2) maintained good relationships with officials of government and its agencies; and (3) devoted substantial resources to maintain good relationships with officials of government and its agencies.

Financial Networking

Following the measurement of political networking, financial networking is measured by the extent to which the new ventures' senior management over the past three years has (1) spent much effort on cultivating connections with financial institutions; (2) maintained good relationships with financial institutions; and (3) devoted substantial resources to maintain good relationships with financial institutions.

Business Networking

Consulting Peng and Luo (2000), business networking is measured by the extent to which the new ventures' senior management over the past three years has spent much effort on cultivating connections with (1) buyers; (2) suppliers; and (3) competitors.

New Venture Performance

Measuring new venture performance has been a challenging task for scholars. In this study, self-reported performance measures are used for three reasons. First, objective financial data are not publicly available for new ventures, because new ventures hold their objective financial data as confidential and they are reluctant to divulge this confidential information (Li, Zhang, and Chan 2005). Under such circumstances, subjective performance measures can yield more complete information (Covin and Slevin 1989). Second, it has been indicated that managerial self-reporting has a strong correlation with internally objective performance measures (Dess and Robinson 1984). New venture studies have provided substantial evidence supporting the reliability and validity of self-reported performance measures (Li and Atuahene-Gima 2001). Finally, subjective performance measurements have been widely used in new venture research (e.g., Li and Zhang 2007; Li, Zhang, and Chan 2005; Wiklund and Shepherd 2005). In this study, we use three measures to assess new venture performance. The respondent was asked to rate his/her new venture's performance relative to its principal competitors over the last two years on (1) market share growth; (2) net profit; and (3) return on sales.

Control Variables

Firm size has long been emphasized as an important factor affecting performance. Thus, we adopt firm size as a control variable. Firm size refers to the number of full-time employees measured by a five-point scale (1 = less than 300; 5 = more than 2,000) (Su, Xie, and Li 2011). Firm age is used as the second control variable. In addition, there are significant differences in performance between independent new ventures and new ventures affiliated with other firms (Shrader and Simon 1997). As a result, the third control variable is whether the new venture is affiliated with other firms (1 = affiliated, 0 = not affiliated). Environmental turbulence is critical to new venture performance. Jaworski and Kohli (1993) suggest that environmental turbulence is made up of market turbulence, technological turbulence, and competitive intensity; thus, they are taken as the last three control variables. Consulting Jaworski and Kohli (1993) and Su et al. (2011), market turbulence, technological turbulence, and competitive intensity are measured respectively by (1) “Our demand fluctuates drastically from week to week”; (2) “Our industry is characterized by rapid technology changes”; and (3) “The competition we face is cut-throat.”

Reliability and Validity

We took several steps to ensure data reliability and validity. Composite reliability is estimated by Cronbach's alpha. Typically, reliability coefficients of 0.70 or higher are considered adequate (Cronbach 1971). Nunnally (1978) further states that permissible alpha values can be slightly low (> 0.60) for newer scales or in new contexts. As can be seen from Table 2, the Cronbach's alpha for each construct is 0.617 or higher, exceeding the 0.60 benchmark.

Table 2. Standard Estimates and Alpha Coefficients
ItemsStandardized Loadingt-Value
  1. Model Fit Index: χ2 = 344.42; p = 0.000; χ2/df = 1.92; goodness-of-fit index = 0.91; comparative fit index = 0.92; normed fit index=0.91; root mean square error of approximation = 0.08.

Entrepreneurial orientation (α = 0.867)  
1. In my company, there exists a very strong emphasis on R&D, technological leadership, and innovations.0.808.47
2. The changes in product lines (types/number of products) for my company have usually been dramatic.0.636.05
3. When it comes to problem solving, we value creative new solutions more than the solutions of conventional wisdom.0.717.17
4. Top managers here encourage the development of innovative marketing strategies, knowing well that some will fail.0.818.59
5. I have a strong preference for high-risk projects (with chances of very high return).0.605.70
6. Owing to the nature of the environment, bold, wide-ranging acts are necessary to achieve the firm's objectives.0.575.37
7. My company is typically the first to initiate actions to competitors, for which the competitors then respond.0.615.83
8. Very often, my firm is the first company to introduce new products/services, techniques, technologies, etc.0.707.02
9. We firmly believe that a change in market creates a positive opportunity for us.0.474.29
Political networking (α = 0.662)  
1. Spent much effort on cultivating connections with officials of governments and their agencies.0.645.63
2. Maintained good relationships with officials of governments and their agencies.0.645.69
3. Devoted substantial resources to maintain good relationships with officials of governments and their agencies.0.635.55
Financial networking (α = 0.718)  
1. Spent much effort on cultivating connections with financial institutions.0.787.41
2. Maintained good relationships with financial institutions.0.666.04
3. Devoted substantial resources to maintain good relationships with financial institutions.0.625.59
Business networking (α = 0.617)  
1. Spent much effort on cultivating connections with buyers.0.615.33
2. Spent much effort on cultivating connections with suppliers.0.605.00
3. Spent much effort on cultivating connections with competitors.0.615.31
New venture performance (α = 0.888)  
1. Market share growth.0.778.06
2. Net profit.0.9110.15
3. Return on sales.0.899.79

Discriminant validity is assessed by chi-square difference tests (Bagozzi 1980). We conducted a chi-square difference test for all of the multi-item constructs in pairs to see if they were distinct from one another. The process involved collapsing each pair of constructs into a single model and comparing its fit with that of a two-construct model (Anderson and Gerbing 1988). The results of ten pairwise tests indicate that in each case the difference in chi-square value is significant (the smallest one is 9.49 with p = .002 from the pairwise test of financial networking and political networking), providing evidence of discriminant validity.

We assessed convergent validity of the multi-item constructs following the procedures recommended by Anderson and Gerbing (1988). First, we ran an exploratory factor analysis for each set of constructs and attained the theoretically expected factor solutions. Second, we conducted a confirmatory factor analysis (CFA) (Zhang and Li 2010). Results of the CFA indicate that the measurement model fits the data well (χ2 = 344.42; p = .000; χ2/df = 1.92; goodness-of-fit index [GFI] = 0.91; comparative fit index [CFI] = 0.92; normed fit index [NFI] = 0.91; root mean square error of approximation [RMSEA] = 0.08), all of which confirm the unidimensionality of each construct in the model. Convergent validity is observed when the path coefficients from the latent constructs to their corresponding manifest indicators are statistically significant (t > 2.0) (Anderson and Gerbing 1988). As can be seen from Table 2, all t-values are significant, which indicates that our multi-item constructs have good convergent validity. In addition, given the sample size restrictions, we divided the constructs into two submodels of theoretically related groups (Bentler and Chou 1987; Li, Zhang, and Chan 2005): EO and new venture performance (χ2 = 137.36; p = .000; χ2/df = 2.59; GFI = 0.90; CFI = 0.91; NFI = 0.90; RMSEA = 0.08) and financial networking, political networking, and business networking (χ2 = 64.91; p = .000; χ2/df = 2.70; GFI = 0.92; CFI = 0.93; NFI = 0.91; RMSEA = 0.07). All items loaded on their respective constructs, and each loading was large and significant at the 0.01 level. These results further indicate convergent and discriminant validity of the scales.

Common Method Bias

We examined the possibility of common method bias via Harman's one-factor test (Podsakoff and Organ 1986). Significant common method bias would result in one general factor accounting for the majority of covariance in the variables. We took all the items (EO, new venture performance, political networking, financial networking, business networking, market turbulence, technological turbulence, and competitive intensity) into Harman's one-factor test. We extracted eight distinct factors that accounted for 70.8 percent of the total variance, with the first factor explaining 29.4 percent. No general factor is apparent; thus, common method bias is unlikely to be a threat to this study. In addition, following the latent variable approach suggested by Podsakoff, MacKenzie, and Lee (2003, p. 894), we further tested the potential of common method bias through controlling the effects of an unmeasured latent methods factor. We allowed the items to load on both their theoretical constructs and a latent common methods bias factor. Then, we examined the significance of the structural parameters. We found that all significant relationships held after controlling for the latent common methods bias factor; thus, common method bias is not an issue in this study (Zhang and Li 2010).

Analysis and Results

The descriptive statistics in Table 3 show basic information on each factor and correlations among these factors. Following previous studies, we test our hypotheses by regression analysis. We mean-centered all the variables to minimize the threat of multicollinearity in the equation where we include interaction terms (Aiken and West 1991). All values of the variance inflation factor are well below the cutoff of 10 recommended by Neter, Wasserman, and Kutner (1985). The significance of the change in R2 is examined by F-test (Atuahene-Gima and Li 2006), both of which are significant.

Table 3. Descriptive Statistics and Correlation Matrix
Factor1234567891011
  1. *p < .05.

  2. **p < .01.

 1. Firm Size1          
 2. Firm Age0.1721         
 3. Whether Affiliated with Others−0.431**−0.0211        
 4. Market Turbulence0.181−0.1470.1761       
 5. Technological Turbulence0.000−0.101−0.1900.1471      
 6. Competitive Intensity0.045−0.0390.1210.308**0.0541     
 7. Entrepreneurial Orientation−0.137−0.094−0.2130.241*0.543**0.1151    
 8. Political Networking0.036−0.168−0.0630.1260.1850.2040.326**1   
 9. Financial Networking0.113−0.118−0.0020.288**0.300**0.1180.406**0.595**1  
10. Business Networking0.092−0.1200.0380.0070.1040.1610.2110.278*0.2121 
11. New Venture Performance0.0480.122−0.1890.1980.360**0.0270.411**0.355**0.276**0.276**1
Mean1.515.180.174.685.055.745.125.304.796.205.47
Standard Deviation0.912.420.381.951.491.070.970.810.950.610.99

Table 4 reports the results of the three-step regression analysis. In step one, we entered the control variables into the model. In the second step, we entered EO and managerial networking into Model 2. Our results indicate the relationship between EO and new venture performance is positive (β = 0.314, p < .001), which supports H1. In step three, we entered the interaction items into the model. Our results indicate that political networking has a negative moderating effect on the relationship between EO and new venture performance (β = −0.277, p < .001); thus H2 is supported. We also find the moderating effect of financial networking is inverse U-shaped (β = −0.514, p < .001), which supports H3. H4 suggests that the moderating effect of business networking is positive, which is supported by our results as well (β = 0.243, p < .01). In summary, all four of our hypotheses are supported by our regression results.

Table 4. Results of Regression Analysis
FactorModel 1Model 2Model 3
  1. *p < .05.

  2. **p < .01.

  3. ***p < .001.

  4. ****p < 0.1.

Firm Size−0.106−0.033−0.002
Firm Age0.242**0.175*0.147****
Whether Affiliated with Other Firms−0.0930.0290.007
Market Turbulence0.168****0.216**0.201**
Technological Turbulence0.475***0.369***0.456***
Competitive Intensity−0.170****−0.277***−0.394***
Entrepreneurial Orientation (EO) 0.314***0.634***
Political Networking (PN) 0.209*0.262***
Business Networking (BN) 0.330***0.234***
Financial Networking (FN) −0.298***−0.306***
FN × FN 0.1000.103
EO × PN  −0.277***
EO × BN  0.243**
EO × FN  0.580***
EO × FN × FN  −0.514***
R20.3460.6090.737
Adjusted R20.2470.4210.480
F-value3.470**3.231**2.869***
R2 change0.2630.128
F-test for R2 change9.686***8.274***
Degrees of freedom of the F-test for R2 change5/724/68

To facilitate interpretation, we plotted the moderating effects of political networking, financial networking, and business networking in Figures 1, 2, and 3 respectively. Figure 1 indicates that the relationship between EO and new venture performance becomes less positive as political networking increases. Thus, political networking has a negative impact on the relationship between EO and new venture performance. As shown in Figure 2, the positive relationship between EO and new venture performance is the strongest when financial networking is at medium level. Thus, financial networking has an inverse U-shaped moderating effect. Figure 3 shows that the positive relationship between EO and new venture performance is stronger when business networking is at high level. Thus, the moderating effect of business networking is positive.

figure

Figure 1. Moderating Effect of Political Networking (PN)

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figure

Figure 2. Moderating Effect of Financial Networking (FN)

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Figure 3. Moderating Effect of Business Networking (BN)

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Discussion and Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Theoretical Background
  5. Hypotheses Development
  6. Methods
  7. Discussion and Conclusion
  8. References

Based on institutional theory, this study examined the moderating effects of different types of managerial networking on the relationship between EO and new venture performance in China. We find that EO contributes to new venture performance and that the moderating effect of political networking is negative and that of financial networking is inverse U-shaped, but that of business networking is positive.

Contributions

Several theoretical contributions emerge in this study. First, our findings contribute to the literature on EO. Existing studies indicate that managerial networking has significant impact on the performance implication of EO, and they have investigated the moderations of network capability (Walter, Auer, and Ritter 2006) and the structure of business networking (Stam and Elfring 2008). Due to different types of managerial networking functioning diversely (e.g., Huang 2008; Peng 2003; Peng and Zhou 2005), it is important to investigate the roles played by different types of managerial networking (Simsek, Lubatkin, and Floyd 2003). By examining the moderating effects of political networking, financial networking, and business networking on the relationship between EO and new venture performance, this study provides a more comprehensive picture of how and in what manner managerial networking affects the performance implication of EO among new ventures. In addition, a better understanding of the conditions under which EO can enhance performance requires identifying some contingent variables (Lumpkin and Dess 1996). Through investigating the moderating effects of different types of managerial networking, this study enhances our understanding of the relationship between EO and new venture performance as well.

Second, the study uses institutional theory as the theoretical foundation and takes the characteristics of the Chinese institutional environment into consideration to investigate the moderating effects of different types of managerial networking on the linkage between EO and new venture performance. All hypotheses on the moderating effects of managerial networking are supported. Thus, our findings suggest that institutional theory is a powerful tool for investigating the function of managerial networking in transition economies, and the characteristics of the institutional environment have a strong impact on the value of managerial networking, which offers a good threshold to probe deep into the values of managerial networking in transitional economies.

Finally, this paper contributes to the research on new ventures as well. The failure rate of new ventures is exceptionally high in China; thus, how to help Chinese new ventures gain success is a critical research question (Li and Zhang 2007). Most existing research on new ventures takes place in developed economies with relatively stable institutional environments; little attention has been paid to new ventures in transition economies experiencing significant institutional transitions (Li and Zhang 2007). Because China's institutional transitions have fundamentally and comprehensively changed the rules of the game, research on Chinese new ventures must take institutional factors into consideration. By using institutional theory as the theoretical foundation and considering the characteristics of the Chinese institutional environment, we find that EO significantly contributes to new venture performance, political networking has a negative moderating effect on the relationship between EO and new venture performance, financial networking has an inverse U-shaped impact, and business networking has a positive one. Thus, our study contributes to this line of research by demonstrating how Chinese ventures can utilize EO and managerial networking to improve their performance.

Managerial Implications

Besides theoretical contributions, our findings also have strong practical implications. First, our findings demonstrate that EO is beneficial for new ventures in enhancing performance in China. Consequently, Chinese new ventures should emphasize EO as a critical strategic element of their strategies to advance performance. Second, new ventures should have a clear understanding of different types of managerial networking in China. Our findings suggest that to effectively realize the performance implication of EO, Chinese new ventures should emphasize strong business networking, medium-level financial networking, and weak political networking.

Our findings also have practical implications for Western firms that have to compete and/or collaborate with Chinese ventures (Child and Tse 2001). When choosing a new venture as a partner, the new venture with strong EO and appropriate managerial networking is the best choice. In addition, Western firms often believe that managerial networking has a significant value in China. From our results, they should reconsider the values of different types of managerial networking. Moreover, the Chinese experience may shed light on the evolution of other transition economies (Peng 2000). Firms, especially new ventures, should make a good use of their EO and managerial networking to enhance performance.

Limitations

This study has several limitations. First, the findings should be viewed cautiously when generalized to other contexts because institutional characteristics are different in different economies. For example, the resources controlled by the government directly affect the extent of firms' resource dependence on the government (Peng and Zhou 2005). Thus, the moderating effect of political networking may not be negative in an economy where the government still redistributes resources.

Second, although we tried our best to get more data, we ended up with 84 samples. Despite this sample being sufficient for our statistical analysis, it undercuts the persuasiveness of our results. Thus, our model needs to be replicated by a survey with more samples.

Third, the performance measures could be improved. Previous research suggests that capturing the multidimensionality of new venture performance requires the use of multiple measures (Wiklund and Shepherd 2005). Although our measurements consulted previous research, we only take three measures—market share growth, net profit, and return on sales. Aggregated performance with more measures is a more powerful way to evaluate new venture performance (Stam and Elfring 2008). Thus, future research should take more measures to capture the multidimensionality of new venture performance.

Finally, although we find little trace of common method bias, we cannot completely rule out its potential influence. Podsakoff, MacKenzie, and Lee (2003) recommend that both procedural methods, such as collecting the measures of variables from different sources, and statistical techniques, such as the latent variable approach, should be used to reduce the potential of common method bias. Future research should integrate both procedural methods and statistical techniques to overcome this problem.

Future Directions

There are also some suggestions for future research. First, a better understanding of the conditions under which EO enhances performance requires identifying some contingent variables (Lumpkin and Dess 1996). North (1990) indicates that institutions have significant impact on entrepreneurship. Thus, institutions may significantly affect the performance implication of EO. This study investigates the moderation of managerial networking, which serves as an informal institutional arrangement in transition economies (Li, Poppo, and Zhou 2008; Xin and Pearce 1996). Yet there is minimal research on the impacts of formal institutions on the relationship between EO and performance. As a result, how formal institutions moderate the relationship between EO and performance is an important issue in future research.

Second, our results indicate that institutional theory is a powerful lens to investigate managerial networking in transition economies. Thus, further research on managerial networking in transition economies can take institutional theory as the theoretical foundation. In addition, institutional characteristics can influence the value of managerial networking; thus, they should be taken into consideration in future research on managerial networking. Moreover, institutional theory identifies three categories of institutional forces: the regulative pillar, cognitive pillar, and normative pillar. This study only regards managerial networking as an informal institutional arrangement, yet it does not expound on what dimensions are at play. Future research should explore more fully the details of the regulative pillar, cognitive pillar, and normative pillar, and examine how they work separately and jointly.

Third, besides the direct impact on performance, managerial networking also functions distinctly in other domains, such as moderating the relationship between EO and new venture performance. Thus, future research should go beyond its direct performance implication to provide a more comprehensive picture of managerial networking. For example, few studies have evaluated the impacts of managerial networking on new product development and its commercialization.

Finally, although this study finds that EO and managerial networking have significant influences on new venture performance, the roles played by EO and managerial networking in the process of setting up a new venture are still unclear, needing our further attention. In addition, how to help new ventures in transition economies enhance performance is a critical question. Given that existing research conducted in developed economies has improved our understanding of this issue, future research must take institutional factors into consideration because institutional transitions have changed the rules of the game. As a result, future research should pay more attention to institutional settings in order to enrich our knowledge of how to enhance new venture performance in the context of transition economies.

Footnotes
  1. 1

    Li and Zhang (2007) measure political networking by four items. The fourth is “spend a lot of money on building relations with the top officials in government.” However, most managers are very sensitive to this question. Our pilot test further indicated this item is not suitable for Chinese firms, because most managers refused to answer this item. Thus, this item was deleted in our survey.

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  1. Top of page
  2. Abstract
  3. Introduction
  4. Theoretical Background
  5. Hypotheses Development
  6. Methods
  7. Discussion and Conclusion
  8. References
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