when r&d spending is not enough: the critical role of culture when you really want to innovate

WHEN R&D SPENDING IS NOT

ENOUGH: THE CRITICAL ROLE

OF CULTURE WHEN YOU REALLY

WANT TO INNOVATE

S H E N G W A N G , R E B E C C A M . G U I D I C E , J U D I T H W. TA N S K Y, A N D Z H O N G - M I N G W A N G

Organizations invest substantial resources in research and development (R&D) to increase long-term performance. Despite these investments, con-textual contingencies can impact innovation. Our fi ndings show that Chinese manufacturers with cultures emphasizing innovation and teamwork more effectively use fi nancial resources in the innovation process. Findings also demonstrate that the impact of education on innovation is greater with low stability and high teamwork and innovation orientations. Results also indicate that a culture emphasizing outcomes and stability leads to lower levels of in-novation irrespective of fi nancial and human resources invested. Finally, we found a negative curvilinear interaction between R&D spending and outcome orientation on innovation. © 2010 Wiley Periodicals, Inc.

Keywords: organizational culture, innovation, China

It is widely recognized that by bringing together unique combinations of re-sources and creative tension to exploit opportunities, innovation and entrepre-neurship enable a firm to survive, grow,

profit, and achieve a competitive advantage in a dynamic environment (Drucker, 1985; Fiol, 1995; Ireland & Webb, 2007; Peng, 2001; Schumpeter, 1934; Zahra, Ireland, Gutierrez, & Hitt, 2000). Both the academic and practitioner literature have stressed the critical role that a culture for innovation can play in improving a firm’s capacity to inno-vate (e.g., Garnier, 2008; Lyons, Chatman, & Joyce, 2007; Tellis, Prabhu, & Chandy, 2009).

While our research centers on innova-tion, we make periodic reference to entrepre-neurship herein, because of the significant overlap that exists between the two (Lassen, Gertsen, & Riis, 2006). Conceptually, innova-tion is “a process that begins with a novel idea and concludes with market introduc-tion” (Freeman & Engel, 2007, p. 94), and entrepreneurship, or, more precisely, corpo-rate entrepreneurship is a proactive behavior used in firms to stimulate and utilize innova-tions (e.g., Kuratko, Ireland, Covin, & Horn-sby, 2005; Naman & Slevin, 1993).1 Scholars have often argued that innovation is a key activity, primary characteristic, and central theme of entrepreneurship (Covin & Miles,

Correspondence to: Sheng Wang, Department of Management, University of Nevada, Las Vegas, 4505 Maryland Parkway, Las Vegas, NV 89154, Phone: (702)895-5394, Fax: (702)895-4370, E-mail: [email protected].

Human Resource Management,Human Resource Management, July–August 2010, Vol. 49, No. 4, Pp. 767– 792

© 2010 Wiley Periodicals, Inc.

Published online in Wiley InterScience (www.interscience.wiley.com).

DOI: 10.1002/hrm.20365

768 HUMAN RESOURCE MANAGEMENT, JULY–AUGUST 2010

Human Resource Management DOI: 10.1002/hrm

1999; Kelley, Peters, & O’Connor, 2009; Lip-parini & Sobrero, 1994; Sharma & Chrisman, 1999; Stopford & Baden-Fuller, 1994; Teng, 2007; Zahra, Kuratko, & Jennings, 1999). For example, Ireland, Kuratko, and Morris (2006) noted that corporate entrepreneurship is “a process through which individuals in an es-tablished firm pursue entrepreneurial oppor-tunities to innovate” (pp. 10–11). Yang and Li (2008) likewise stated that “a fundamental characteristic of entrepreneurship is its focus on creation, including the creation of new ventures and organizations, and the discov-ery of new goods, services, raw materials, and organizing methods as well as organizational renewal and innovations within an existing organization” (p. 337).

Interestingly, in the midst of a global eco-nomic recession, Booze and Company’s Global Innovation 1000 report indicates that

more than two-thirds of firms studied maintained or increased their R&D spending in 2008. This translated into a 5.7% increase in R&D outlays, a figure just slightly lower than the 7.1% global five-year compound annual growth rate (CAGR) (Jaruzelski & Dehoff, 2009). Research has also indicated that stimulating innovation and enabling entrepreneurship are among the top ten challenges CEOs face despite the undeniable

importance of doing these things (Board, 2008). In a study that asked 800 executives across 20 countries what they believed to be the most significant barriers to innovation (IBM Global Business Services, 2006), an un-supportive culture was reported as a top bar-rier. As Rosabeth Moss Kanter (2000) sug-gested, it is important that executives learn to use their organization’s culture to mobilize and motivate members to be creative and in-novative when the goal is to create new prod-ucts, concepts, and services. This advice, combined with the aforementioned surveys, suggests that additional study is sorely needed to better understand the characteristics of in-novating firms, including features of their organizational culture (Damanpour & Sch-neider, 2006). Of particular importance is

understanding how different dimensions of organizational culture influence innovation. Unfortunately, relatively little empirical work has been conducted in this area (Hauser, Tellis, & Griffin, 2006; McLean, 2005).

Organizational culture refers to a set of shared assumptions, values, and beliefs held by organizational members (Schein, 2004; Svyantek & Bott, 2004). Studies of the rela-tionship between organizational culture and innovation have typically focused on a cul-ture of innovation, finding it to have a direct and positive relationship with innovation (Fitzgerald, Flood, O’Regan, & Ramamoorthy, 2008; Lau & Ngo, 2004; Smith, Collins, & Clark, 2005). Few have investigated other, more specific dimensions of organizational culture in relation to organizational innova-tion. Researchers have also argued that orga-nizational culture does not produce innova-tion per se (Covin & Slevin, 1991). Resources, both financial and human, are needed to make it happen. These resource investments that help foster innovation and lead to better long-term performance are also scarce re-sources. Unfortunately, existing research on resource investments tends either to examine their direct relationship with innovation without considering the organizational con-text or to control for their effects when inves-tigating other factors of interest. Our study addresses this gap by investigating organiza-tional culture and resource investment simul-taneously in an interactive fashion. Specifi-cally, we examine how different dimensions of organizational culture present conditions in which capital investments, including R&D spending and employee education level, may be more (or less) effective in fostering inno-vation. Given the significant resources in-vested in innovation and the resource con-straints found in most, if not all firms, our findings, obtained from a wide range of firms, are intended to provide a better under-standing of how financial and human capital is related to innovation.

The setting for our study, the industrial economic zones of Zhejiang province in China, constitutes an additional contribu-tion to the literature. Research to date has given only limited attention to whether the-

There has

been marked

improvement in

China’s innovation

capabilities in

recent years.

THE CRITICAL ROLE OF CULTURE WHEN YOU REALLY WANT TO INNOVATE 769


ories of innovation are applicable outside the Western societies in which they are fre-quently developed and tested. Hence, one must ask whether the conclusions drawn and prescriptions offered for an advanced econ-omy (e.g., the United States or Japan) are ap-propriate in a transitional economy such as China, a setting that differs significantly on a wide array of factors, including its political, economic, and social systems (Child, Yuan, & Tsai, 2007; Tan, 2001; Wang & Wang, 2008). Answering this question should be a priority for a number of reasons. For one, China has become one of the largest recipients of for-eign direct investments (Luo & Peng, 1999) and is considered by many multinational firms to be a favorable location in which to expand R&D operations (Altenburg, Schmitz, & Stamm, 2008; Dobson & Safarian, 2008; Zhang, Li, Hitt, & Cui, 2007). It is therefore essential that these firms understand whether and how practices from their home country might transfer abroad.

Second, the Organisation for Economic Co-Operation and Development (OECD), in collaboration with the Ministry of Science and Technology (MOST), has explicitly an-nounced its goal of making China an innova-tion-oriented nation by 2020 (OECD, 2008). To reach this goal, regulatory reforms and institutional changes have been initiated, including policies that (1) support innova-tion within private enterprises, (2) promote technology development zones and incuba-tion parks near major universities, (3) priori-tize education initiatives tailored toward sci-ence and technology, (4) encourage foreign direct investment, and (5) establish guide-lines and funding for venture capital invest-ments (e.g., Walcott, 2003; Wolff, 2007; Zhang, 2003). While there has been marked improvement in China’s innovation capabili-ties in recent years, those capabilities remain underdeveloped relative to prominent OECD countries, a fact that suggests Chinese firms will benefit from additional innovation re-search conducted directly in China.

Finally, researchers have emphasized the importance of innovation in the manufactur-ing sector in China (e.g., Jefferson, Bai, Guan, & Yu, 2006). As China transitions from being

a country dominated by manufacturers of goods (i.e., made in China), however, to one focused on product development and inno-vation (i.e., made by China), it finds itself facing severe resource and management chal-lenges (Peng & Heath, 1996; Xin & Pearce, 1996). Such challenges could readily make the difference between innovation success and innovation failure, especially for rela-tively smaller companies. We believe research such as that offered here may help alleviate some of the challenges found in China.

Theoretical Background and Hypotheses

Innovation and Organizational Culture

Innovation can be an informal, ad hoc pro-cess or a formal, structured process (Vermeu-len, 2005). Research has further recognized the importance of both intra- and extra-organizational links in cre-ating and implementing innova-tions and has further suggested that an iterative and integrated process helps reduce the chal-lenges associated with innovation (Vermeulen, 2005) and increases the speed and efficiency with which innovation activities are accomplished (Rothwell, 1994).

Described as “a cycle that goes through stages and requires drivers to conceive and carry ideas from the mind to the market place” (Verhaeghe & Kfir, 2002, p. 410), in-novation is an inherently collaborative, peo-ple-intensive effort emanating from an orga-nization’s learning initiatives, capabilities, and accomplishments (Brandt, 1985; Smith et al., 2005; Tsai & Ghoshal, 1998; Van de Ven, 1986). Although the number of stages identified varies across studies, each offers a logical progression that begins with generat-ing a new idea and concludes with success-fully diffusing or commercializing a new product, service, or process. Studies have often highlighted interactive and interdepen-dent activities occurring between these stages, such as design, testing, manufacturing, and channel relations (e.g., Khilji, Mroczkowski,

Chinese firms

will benefit from

additional innovation

research conducted

directly in China.



& Bernstein, 2006; Kotler, 1997; Tower, Seb-ora, Hartman, & Cornwall, 1993; Verhaeghe & Kfir, 2002; Vermeulen, 2005). To this we add the belief that progressing through these stages of innovation requires firms to provide an environment that facilitates collaboration among employees and the generation of new ideas, while it tolerates the inevitable uncer-tainty involved in this process.

Described as a valuable, rare, nonsubsti-tutable, and inimitable contextual variable (Barney, 1986), organizational culture is both varied and distinct across organizations (Schein, 2004). As a form of social control (O’Reilly & Chatman, 1996) and powerful frame of reference (Jassawalla & Sashittal, 2002), organizational culture can encourage (or discourage) a variety of behaviors and de-

cisions, including those related to innovation. In fact, it has been suggested that nearly all employ-ees are capable of entrepreneur-ship and innovation if the right cultural environment exists (e.g., Kanter, 1982; Lau & Ngo, 2004; van der Panne, van der Beers, & Kleinknecht, 2003). Uljin and Brown (2004) likewise argued that innovation success depends on cultural fit—“a key but routinely neglected source of failure” (p. 10). Thus, firms that consider in-novation a strategic priority should make cultivating and nur-

turing an innovation-inducing culture a pri-ority because lack of alignment reduces the likelihood of success (Hidalgo & Albors, 2008; Oden, 1997; Rule & Irwin, 1988).

Conceptually, firms with cultures of in-novation and entrepreneurship are those that appropriately use rewards and tolerate failure, and in which members share values such as openness to new ideas, creativity, change, continuous learning, autonomy, col-laboration, flexibility, and informal commu-nication (e.g., Amabile, 1988; Covin & Slevin, 1991; Dess, Lumpkin, & McGee, 1999; Dough-erty, 1999; Hurley & Hult, 1998; Oden, 1997). Empirically, Tellis et al. (2009) found corpo-rate culture to be a primary driver of radical innovation. A study by Chandler, Keller, and

Lyon (2000) revealed that a culture for inno-vation is one in which employees perceive that workloads are not excessive and in which management support and organiza-tional reward systems are consistent with a commitment to innovation. Similarly, Gud-mundson, Tower, and Hartman (2003) showed that innovation is positively im-pacted by the level of organizational support and the degree of worker empowerment. In terms of benefits, de Brentani and Klein-schmidt (2004) found that companies rated high on innovation culture and management commitment had greater new product devel-opment success than those with low ratings. Both Jassawalla and Sashittal (2002) and Kha-zanchi, Lewis, and Boyer (2007) found that an innovation culture assisted in overcoming the challenging and tenuous requirements for both control and flexibility—two compet-ing demands necessary for successful innova-tion (Dougherty, 1999).

In sum, what quickly becomes apparent from the preceding review is that an innova-tion-rich culture is an important, if not es-sential, ingredient in producing innovation. Drawing from this belief, we describe how organizational culture should moderate the relationship between R&D spending and in-novation and between R&D employee educa-tion and innovation.

R&D Spending

Conventional wisdom considers resource availability, particularly a commitment to and investment in R&D, as a key strategic input to innovation (e.g., Damanpour, 1991; Nohria & Gulati, 1996). Indeed, some studies have shown a positive relationship between R&D intensity or input and innovation (e.g., Ahuja & Katila, 2004; Hitt, Hoskisson, John-son, & Moesel, 1996; Katila & Ahuja, 2002). Other research, however, has reported no sig-nificant relationship between R&D intensity and innovation (e.g., Greve, 2003; Katila, 2002). These mixed results suggest a need to investigate potential moderators, such as the internal context in which resources are used.

In keeping with a contingency perspec-tive of innovation (e.g., Kor, 2006; Li & Atua-

A firm’s resources

do not exist in

isolation; their value

depends upon the

environment within

which they exist

(Katila & Shane,

2005).



hene-Gima, 2001; Lin, Lee, & Hung, 2006), we expect organizational culture to moderate the relationship between R&D expenditures and innovation performance. A firm’s re-sources do not exist in isolation; their value depends upon the environment within which they exist (Katila & Shane, 2005). Moreover, while providing resources may make innova-tion possible, doing so is not sufficient to maintain ongoing identification, develop-ment, and adoption of innovation. The nec-essary catalyst is the motivation to innovate (Amabile, 1988). In other words, innovation is rooted in the creative minds of humans, thereby raising the question of whether a social context exists that encourages creativ-ity and innovativeness (e.g., Amabile, Conti, Coon, Lazenby, & Herron, 1996; Chandler et al., 2000; Damanpour, 1991; Jassawalla & Sashittal, 2002; Lyons et al., 2007).

In their influential study of person-organization fit, O’Reilly, Chatman, and Caldwell (1991) identified seven dimensions of organizational culture that represent a wide range of values—innovation, stability, respect for people, outcome orientation, attention to detail, team orientation, and aggressiveness. Based on our review of the innovation litera-ture and its frequent reference to collabora-tion, risk taking, change, and uncertainty, we have chosen to concentrate on the four di-mensions that we believe are most relevant to our line of inquiry. Specifically, we consider three dimensions that we expect to facilitate innovation—team, innovation, and outcome orientations—and one that is expected to sub-stantially restrain innovation—stability.

Organizations have a basic constitution that motivates them to be innovative or not. Organizations with a strong team-oriented culture are those in which members work together, are concerned about one another, and collaborate to achieve goals (O’Reilly et al., 1991). R&D is an integrative and complex activity that requires non-routine, creative problem solving and is often best achieved by drawing upon the collective expertise and views of others (Jassawalla & Sashittal, 2002; Leonard & Sensiper, 1998). When a compa-ny’s culture emphasizes teamwork, financial investment in R&D is more likely to be used

effectively (and perhaps more efficiently) be-cause the personnel involved in the innova-tion process are likely to value interpersonal communication and collaboration and, as a consequence, better enable innovation. Therefore, we expect that team orientation will strengthen the R&D spending–innova-tion output relationship.

Cultures reputed to be innovation-ori-ented are those that value and promote such behaviors as risk taking, change, experimen-tation, innovativeness, tolerance of uncer-tainty, and opportunity exploitation (O’Reilly et al., 1991). Such values likely encourage the use of R&D spending on exploring and devel-oping ideas that are novel and risky, a prac-tice that subsequently increases the probabil-ity of turning those ideas into new products or services. Others have also characterized an innovation-oriented culture as being one in which a consistent, coherent, and compre-hensive presence of values and norms exists that promotes fresh thinking and swift exe-cution, one that is reinforced by incentives, socialization, role modeling, and venues for sharing information (Lyons et al., 2007). Hence, we expect that these norms and val-ues of innovation will interact with R&D re-source allocations to beneficially impact the number of new products and services firms introduce.

In outcome-oriented cultures, not only are performance assessments generally fo-cused on results, but organizational members are also characterized as being achievement-oriented (O’Reilly et al., 1991). Research has also found that individuals in such environ-ments typically set high performance expec-tations for themselves and their organiza-tions (O’Reilly et al., 1991). Building from this characterization, Price (2007) suggested that leaders of innovative organizations tend to have a clear picture of the result they wish to achieve and clearly articulate this vision such that members share the vision and are motivated to do more than just “get by.” Drawing from studies that have found that the psychological characteristic “achieve-ment-oriented” often encourages innovation (Shane, 1992) and that a culture of initiative often manifests itself in process innovative-



ness and firm goal achievement (Baer & Frese, 2003), we expect that outcome orienta-tion will increase the extent of innovations introduced as R&D spending intensifies.

Finally, grounded in the notion of change, innovation undoubtedly exposes firms to uncertainty. Indeed, it is argued that environ-mental uncertainty (e.g., economic, market, and technological) can reasonably be both a cause and a subsequent consequence of en-trepreneurial and innovative opportunities, actions, and outcomes (Freel, 2005). It there-fore seems likely that a culture of stability, in which norms of predictability and the status quo are valued (O’Reilly et al., 1991), restricts innovation even in situations in which a greater proportion of financial resources are devoted to R&D, because these firms are re-luctant to disrupt the status quo. Hence, in a cultural environment that values stability, it is likely that while there may be meaningful talk about innovation (and resource alloca-tion toward it), there may be little purposeful action, as such action runs counter to prefer-ence for consistency.

In summary, by virtue of a culture’s ability to guide and sustain members’ percep-tions of what is important, valued, and pos-sible within an organization, it is expected that three dimensions of culture (team, innovation, and outcome orientations) will strengthen the relationship between R&D spending and innovation performance while one dimension (stability orientation) will weaken this relationship. We thus propose our first hypothesis:

Hypothesis 1: Organizational culture moderates the relationship between R&D spending and innovation such that the positive impact of investment in R&D on innovation will be greater when (a) team orien-tation, (b) innovation orientation, and (c) outcome orientation are high rather than low, and when (d) stability orientation is low rather than high.

R&D Employees’ Education

Education is important in innovative and entrepreneurial organizations. Individuals with advanced education typically have a larger knowledge base, have a greater capac-

ity to use a variety of complex problem-solv-ing and decision-making methods, and are more likely to generate multiple solution al-ternatives and be more receptive to new ideas (e.g., Bantel & Jackson, 1989; Damanpour & Schneider, 2006; Huber, Sutcliffe, Miller, & Glick, 1993; Lee, Wong, & Chong, 2005). Smith et al. (2005) found a positive relation-ship between education and firms’ knowl-edge creation capabilities, thereby supporting the argument that education significantly influences cognitive reasoning skills. Hauser et al. (2006) concluded from their integrative review that studies have repeatedly demon-strated the importance of contextual and structural drivers of innovation capability, of which education is one meaningful driver. Many organizations have their own R&D units; therefore, the type of workers em-ployed in these units likely has an important influence on generating innovation.

Human capital theory helps explain why education should be an important consider-ation in innovation research. This theory is based on the belief that individuals’ capacity to learn and create knowledge is (or should be) just as valuable to an organization as its other resources (Schultz, 1961). Investment in and effective use of human capital (i.e., individuals with higher levels of knowledge, skills, and experience) can increase produc-tivity and organizational performance (e.g., Fritz-Enz, 2000; Psacharopoulos, 1985; Romer, 1986). For example, Pelz and Andrews (1976) found that scientists with Ph.D.’s outper-formed those without Ph.D.’s in terms of quality and quantity of R&D outputs. Simi-larly, Lee et al. (2005) found that education had a positive impact on multiple R&D out-comes, including patents/copyrights, articles published, and product/process improve-ments. Finally, Dobson and Safarian’s (2008) empirical analysis suggested that the quality of an organization’s human capital is funda-mental to its learning and innovation accom-plishments.

Much like allocating financial resources, innovation-related skills and abilities that are acquired and developed through ad-vanced education are important, but not necessarily sufficient for innovation. The



necessary catalyst is the motivation to inno-vate (Amabile, 1988). Dimensions of organi-zational culture such as team, innovation, and outcome orientation likely strengthen the education-innovation output relation-ship in that these facets of culture can moti-vate individuals to interact, share their expertise and knowledge, and create innova-tions. In contrast, education level is less likely to be leveraged to generate innova-tions when the organizational culture em-phasizes preserving the status quo. Consistent with our previous hypothesis, therefore, we argue that the relationship between educa-tion and innovation will be stronger when a culture is compatible with entrepreneurial and innovative aspirations. That is, the ben-efits of advanced education levels on innova-tion will be greater when the organization’s culture is perceived as valuing teamwork and innovativeness and being outcome-oriented, but not when stability is a dominating value among organizational members. This leads to our second hypothesis:

Hypothesis 2: Organizational culture moderates the relationship between R&D employee educa-tion and innovation such that the benefi cial im-pact of higher levels of education will be greater when cultural values of (a) team orientation, (b) innovation orientation, and (c) outcome orienta-tion are high rather than low and when (d) sta-bility orientation is low rather than high.

Method

Sample and Data Collection

The data used to test our hypotheses were collected from private manufacturing firms located in the industrial economic zones in China’s Zhejiang province. According to the National Bureau of Statistics, Zhejiang is one of the fastest developing provinces in China, with both total GDP and GDP per capita ranked fourth among all provinces in 2006. Zhejiang is also well known for the govern-ment’s support of the domestic private sector of its economy (Huang, 2003), a sector that accounted for more than 70% of Zhejiang’s annual GDP in 2006.

We obtained a list of companies in these development zones from the Provincial Bu-reau of Small and Medium-Size Enterprises. A random sample of 600 companies was drawn from the list, and all were contacted by phone to ask them to participate in the study. To motivate them to participate, contacts were informed of the academic nature of this research and were assured that their responses would be confidential. Respondents were kept unidentified on written materials be-cause previous research has suggested that Chinese managers are more willing to pro-vide accurate information when they remain anonymous (Tan & Litschert, 1994). All ques-tionnaires were coded to facilitate matching the data from various respondents in each company. As an added incentive for partici-pating, we offered to provide participants with a summary of the study’s results.

Questionnaires were personally delivered to the companies that initially agreed to par-ticipate in the study. During this visit, in-structions were provided and any questions were answered. A second visit several days later provided an opportunity to let respon-dents ask additional questions about survey items and to collect the questionnaires that had not been completed during the first visit. Those companies that had not yet completed their questionnaires were reminded to do so and were asked to send them back by mail to the researchers using the self-addressed re-turn envelopes provided.

Within each company, data were collected from three distinct sources. First, one ques-tionnaire was directed to the CEO or general manager of the company, which asked ques-tions regarding firm age, industry, innovation performance, R&D expenses, and annual sales. A second, separate questionnaire was directed to the human resource (HR) manager to collect information on the education level of employees in the R&D unit and firm size. For companies that did not have an HR man-ager position, the questionnaire was directed to the senior manager who assumed duties related to HR functions. Research has sug-gested that HR managers are a credible source of company information (Sun, Aryee, & Law, 2007); therefore, we also asked them about



the firms’ average sales over the past three years to check reliability. The rationale for this was that the nature of these HR managers’ work involves hiring talent as well as plan-ning and monitoring HR practices. They therefore tend to equip themselves with com-pany information that can be provided to potential applicants and help make decisions concerning needed changes to their HR prac-tices. Comparing the CEO/general manager survey and the HR manager survey showed high consistency on the comparable parame-ters. Finally, ten copies of an organization culture questionnaire were provided to each company and distributed to their employees. Respondents in each company held jobs at various levels and in diverse functions such as manager, accountant, senior staff, quality controller, engineer, and R&D worker.

We received completed matching ques-tionnaires from 210 companies. Among those, the data from 52 companies were deemed not usable because of missing data. Thirty-two companies did not have an R&D unit, and 16 companies fell into both catego-ries. Sixty-eight companies were therefore excluded from analysis. The final sample size was 142 companies, resulting in a conserva-tive response rate of 23.7%. Among these companies, the average firm age was 12.23 years, with an average of 289 employees. Of these companies, 29% were in high-tech in-dustries (e.g., electronics and computers). The average company tenure of key infor-mants was 5.62 years. To assess non-response bias, we followed Armstrong and Overton (1977) in comparing early and late respon-dents in terms of firm age, size, and sales. The t-test results showed no significant differ-ences across groups, suggesting no important non-response bias. Appendix 1 presents de-tailed profiles of the firm sample across the high- versus low-tech industries.

Measures

The questionnaires were first developed in English, then translated into Chinese by bi-lingual management researchers using the conventional back-translation procedure (Brislin, 1980). All discrepancies identified in

the back-translation process were corrected. The translated version was then pilot tested in 15 companies not included in the final sample to ensure relevance to the Chinese context and to resolve ambiguity in the mea-surements. We also interviewed respondents to elicit feedback, a process that resulted in only minor changes prior to reaching the final version. Appendix 2 presents the ques-tions asked for each measure.

R&D Spending

Following prior research (Greve, 2003), R&D spending was operationalized the same way as R&D intensity, which is R&D expenses di-vided by sales. Recognizing that R&D pro-cesses take some time to result in innovation, we used an average of R&D expenses and sales over three consecutive years.

R&D Employee Education

The level of R&D employees’ education was measured by the percentage of R&D employ-ees whose highest level of education was a master’s or doctorate degree.

Organizational Culture

A modified version of O’Reilly et al.’s (1991) Organizational Culture Profile (OCP) was used to measure organizational culture. To make the OCP more manageable for respon-dents, a shorter 40-item version of this in-strument developed by Cable and Judge (1996) was used. Following a forced distribu-tion, respondents sorted the 40 items into nine categories (1 = very uncharacteristic of my organization to 9 = very characteristic of my organization).

Our pilot study suggested that it would be difficult to collect data using a Q-sort method from a large number of employees in any single company. As a result, we asked each participating company to send culture ques-tionnaires to a random group of ten employ-ees who were familiar with the company and who would have an accurate and compre-hensive understanding of their company’s culture.



In the original validation of the OCP conducted in the United States, 26 items represented seven culture dimensions (O’Reilly et al., 1991). Because our study relied on a Chinese version of the scale, we conducted an exploratory factor analysis to determine if the factor structure differed from that in U.S. samples. To obtain a more accurate picture of the culture dimensions in Chinese companies, we included re-sponses not only from the 142 companies in our final sample, but also the 127 other companies that had returned completed OCP surveys but had missing data on other variables or failed to return one of the other two questionnaires.

We conducted an exploratory factor anal-ysis of all 40 items with varimax rotation on a total of 1,436 responses. After removing items with significant cross-loadings and with low loadings, the final result revealed 19 items with loadings of greater than .40 on a single factor (cf. Gorsuch, 1983), representing six dimensions. These items explained 46.95% of the variance in our data.2 We were able to retain the labels O’Reilly et al. (1991) used with the only difference being that our study combined the original dimensions of respect for people and team orientation into one fac-tor. We did not find this result to be surpris-ing considering China’s highly collectivistic culture (Gelfand, Bhawuk, Nishii, & Bechtold, 2004; Hofstede, 1980). Internal consistency estimates of reliability cannot be computed for ipsative measures; therefore, these esti-mates cannot be provided for the subscales. Earlier research has demonstrated, however, high test-retest reliability (Chatman, 1991) and validity of the OCP (e.g., Judge & Cable, 1997; O’Reilly et al., 1991).

Tests of our hypotheses centered on four of the six culture dimensions identified. In-novation orientation was measured with two items that assessed the extent to which an organization values exploiting opportunities and taking risks. Stability orientation was measured with two items assessing the degree to which stability and security are valued. Outcome orientation was measured with four items that assessed the degree to which an organization values achievement, results, and

being less rule-oriented, or is constrained by many rules (reverse). Finally, team orienta-tion was measured with five items assessing the extent to which an organization empha-sizes confronting conflict directly (reverse), being people oriented, working long hours (reverse), having low informality, and offer-ing a clear guiding philosophy.

A total of 746 employees in the final sample of companies responded to the modi-fied OCP, with an average of 5.3 respondents per company. Their responses were used to test our hypotheses. All respondents had been with their companies for at least two years, with an average tenure of 4.9 years. Of those who revealed their job functions, about 32% held an R&D-related position.

It has been argued that interrater agree-ment is necessary to aggregate individual rat-ings of organizational culture to the firm level (James, 1982). To this end, we first ex-amined within-group interrater agreement as indicated by rwg (James, Demaree, & Wolf, 1993). The median rwg for stability, outcome, innovation, and team orientation for our final sample were .86, .84, .76, and .86, re-spectively, exceeding the recommended min-imum value of .70 (George & Bettenhausen, 1990). This suggested reasonable levels of agreement. We also examined ICC(1) and ICC(2) as recommended by Bliese (2000). ICC(1) indicates the percentage of variance due to company level variability. It has also been interpreted as indicating the extent to which individuals from the same company responded similarly. ICC(2) is an estimate of the reliability of the group mean scores (Bliese, 2000; James, 1982). Our results showed that ICC(1) values for stability, out-come, innovation, and team orientation were .22, .24, .25, and .22, respectively, and the ICC(2) values for the four dimensions were .59, .61, .63, and .60, respectively. Research-ers have suggested ICC(1) values close to .20 and ICC(2) values of .60 or higher are desir-able (Bliese, 2000; Glick, 1985). Overall, our results suggest acceptable levels of agreement for aggregation.

In addition, we conducted semi-struc-tured follow-up interviews with two manag-ers from each of 20 companies (one from or



familiar with the R&D unit and another se-nior manager), of whom 35% were from high-tech industries. We asked them to rate the extent to which their companies empha-sized teamwork and stability and tolerated risk taking. Their responses showed strong consistency with aggregated employee rat-ings (Pearson coefficients ranged from .68 to .83), also lending credence to the reliability of our aggregated data.

Innovation Performance

Consistent with Smith et al. (2005) and other research that showed counts to be a robust measure of innovation (Damanpour, 1991), innovation performance was measured by the number of new products and services a company had introduced in the past three years. This period is comparable to other studies on innovation in transitional econo-mies of Asia, in which project durations and payback periods are typically shorter than those found in advanced economies (He & Wong, 2004; Li & Atuahene-Gima, 2001). We selected this measure of innovation over pat-ent data because intellectual property rights protection is often neglected in China and firms do not always apply for patents (Zhao & Yang, 2008).

Control Variables

Based on prior research (Damanpour, 1991; Smith et al., 2005), we controlled for several variables that might influence R&D invest-ments and innovation. Firm size was mea-sured by the log-transformation of the num-ber of employees in the company. Firm age was measured by the number of years since the company was founded. Last, a dummy variable indicated whether a company was high-tech (e.g., electronics, computer equip-ment) or not (e.g., industrial machinery) (Chandler et al., 2000).

Statistical Analysis Strategy

Negative binomial regression was used for data analysis for two reasons. First, innova-tion, operationalized as the number of new

products and services introduced, was a count variable and had non-negative integer values. Thus, the Poisson regression model is recom-mended for estimation (Cohen, Cohen, West, & Aiken, 2003). Second, our count variable was overdispersed (i.e., the variance of inno-vation performance exceeded the mean). A likelihood ratio test of the overdispersion pa-rameter (�) also provided evidence of overdis-persion in our data (p[variance > mean] <.05). The negative binomial model, a generalized form of the Poisson model, adjusts for over-dispersion (Cohen et al., 2003). We also mean-centered variables prior to creating the product terms in order to reduce multicol-linearity (Cohen et al., 2003).

Results

Table I displays the descriptive statistics and correlations among all variables in the study. Table II shows the results of negative bino-mial regression analyses of innovation. Model 1 includes control variables only. In Model 2 the main predictors, including R&D spending, R&D employee education, and the four dimensions of organizational culture, were included in the equation in addition to the control variables. Models 3 and 4 incorporate the interaction terms to test the moderation effects involving R&D spending and R&D employee education, respectively.

Hypotheses 1a–d predicted a moderating role of team, innovation, outcome, and sta-bility orientation on the relationship between R&D spending and innovation, respectively. As shown in Model 3 of Table II, consistent with our prediction, team orientation (b = 7.76, p < .01) and innovation orientation (b = 6.68, p < .01) strengthened the R&D spending–innovation relationship, providing support for Hypotheses 1a and 1b. The inter-action terms of R&D spending by outcome orientation (b = 3.08, ns) and R&D spending by stability orientation (b = .66, ns) were not significant. Thus, Hypotheses 1c and 1d were not supported.

Hypotheses 2a–d predicted a moderat-ing role of team, innovation, outcome, and stability orientation on the relationship be-



TA

BL

E

I

Corr

elat

ions

and

Des

crip

tive

Stat

istic

sa

Vari

ab

les

Mean

s.d

. 1

23

45

67

89

1. F

irm

siz

eb5.

32.9

7

2. F

irm

ag

e12

.24

9.68

.30*

* 3

. Hig

h-t

ech

.29

.45

�.4

3**

�.1

5 4

. R&

D s

pen

din

g.0

7.1

0�

.49*

*�

.25*

*.3

8**

5. R

&D

em

plo

yee

edu

cati

on

9.20

15.2

9�

.10

�.1

7*.1

1.0

7

6. T

eam

ori

enta

tio

n6.

50.8

0.0

6.0

4�

.01

�.0

3�

.07

7. S

tab

ility

ori

enta

tio

n5.

19.7

2�

.00

.02

�.0

8�

.15

�.0

9�

.05

8. O

utco

me

orie

ntat

ion

4.71

.62

.18*

�.0

5.0

2�

.02

.07

�.1

9*�

.27*

* 9

. In

nov

atio

n

ori

enta

tio

n4.

97.8

7.0

7.0

1�

.13

�.0

3�

.07

�.1

3.0

6�

.08

10. I

nn

ovat

ion

22.0

452

.19

.23*

*.0

1.0

2.0

4.0

8.0

5�

.12

.00

.11

a n =

142

; tw

o-t

aile

d t

ests

.bLo

gari

thm

.*p

< .0

5; *

*p <

.01



tween R&D employee education and inno-vation, respectively. Consistent with our prediction, results shown in Model 4 of Table II indicate that team orientation (b = .02, p < .05) and innovation orientation (b = .03, p < .01) strengthened the R&D em-ployee education–innovation relationship while stability orientation weakened this relationship (b = �.02, p < .05). These re-sults provide support for Hypotheses 2a, 2b, and 2d. The interaction between outcome orientation and R&D employee education

was not significant (b = .00, ns). Thus, Hy-pothesis 2c was not supported.

Figures 1–5 illustrate the significant mod-eration effects. Because a negative binomial model is nonlinear, we calculated multiple points to plot the graphs. The patterns of these graphs are consistent with our predic-tions.

To better understand the unexpected non-significant findings concerning the moderating role of outcome orientation with the significant negative main effect,

T A B L E I I Results of Negative Binomial Regression Analyses for Innovationa

Variables Model 1 Model 2 Model 3 Model 4

Control variables

Firm sizeb 0.70** (0.09) 0.77** (0.10) 0.55** (0.11) 0.66** (0.10)

Firm age �0.01 (0.01) �0.01 (0.01) �0.00 (0.01) �0.00 (0.01)

High�tech 0.53** (0.19) 0.23 (0.19) 0.06 (0.19) 0.19 (0.19)

Predictors

R&D spending 2.88** (1.06) 2.86** (1.10) 1.97* (0.98)

R&D employees educa-tion (edu)

0.00 (0.01) 0.00 (0.01) 0.01 (0.01)

Team orientation �0.07 (0.10) 0.09 (0.11) �0.04 (0.10)

Stability orientation �0.25* (0.12) �0.22 (0.11) �0.27* (0.11)

Outcome orientation �0.26* (0.13) �0.08 (0.14) �0.14 (0.13)

Innovation orientation 0.06 (0.09) 0.12 (0.09) 0.12 (0.08)

Interaction terms

R&D spending*team 7.76** (2.62)

R&D spending*stability 0.66 (0.94)

R&D spending*outcome 3.08 (2.30)

R&D spending*innovation 6.68** (1.77)

Edu*team 0.02* (0.01)

Edu*stability �0.02* (0.01)

Edu*outcome 0.00 (0.08)

Edu*innovation 0.03** (0.01)

Constant �.80 (.48) 1.29 (1.39) �0.01 (1.40) 0.81 (1.32)

LR �2 54.29** 72.44** 90.47** 93.20**

Log-likelihood �556.77 �547.70 �538.68 �537.32

Likelihood ratio test 18.14** 18.04** 20.76**a Standard errors are in parentheses.b Logarithm.*p < .05; **p < .01.



we conducted an additional set of analyses. To examine the possibility of a curvilinear effect, we created a squared term of out-come orientation and interaction terms of squared outcome orientation by R&D spend-ing and squared outcome orientation by education level. The quadratic related terms were included after controlling for the con-

trol variables and the main and one-way interaction effects. The results of negative binomial regression showed that outcome orientation did not have a simple quadratic relationship with innovation in either the R&D spending model (b = �.15, ns) or the education level model (b = �.01, ns). The quadratic outcome orientation did have a

FIGURE 1. The positive moderating effect of team orientation on the relationship between R&D spending and innovation

FIGURE 2. The positive moderating effect of innovation orientation on the relationship between R&D spending and innovation

FIGURE 3. The positive moderating effect of team orientation on the relationship between R&D employee education and innovation



moderating effect on the R&D spending–innovation relationship (b = �8.20, p < .01), but it did not have a similar effect on the education level–innovation relationship (b = �.01, ns).3 Figure 6 depicts the signifi-cant moderation effect.

Discussion

Given that innovation and entrepreneurship top many of today’s corporate agendas, it is important to recognize the critical role orga-nizational culture plays in achieving these goals (e.g., Brazeal, 1993; Hornsby, Kuratko, & Zahra, 2002; Kanter, 1985). Our study con-tributes to the literature by demonstrating empirically how organizational culture can influence the effects of resources, specifically R&D spending and employee education level, on innovation in the underinvestigated, emerging market of China. As O’Reilly et al. (1991) suggested, organizational culture

shapes attitudes, behaviors, and how re-sources are used. Our findings indicate that the extent to which culture reflects and pro-motes stability, outcome orientation, team-work, and innovation can facilitate or hinder (depending upon the dimension) innovation in different ways. The findings also lend sup-port to executives’ reported belief that corpo-rate culture can be a significant barrier to (or facilitator of) innovation (IBM Global Business Services, 2006).

Consistent with prior research that has shown the impact of individual dimensions of culture on important organizational pro-cesses and outcomes (e.g., Jassawalla & Sashittal, 2002; Smith et al., 2005), our study found that team and innovation orienta-tions strengthened the effects of both R&D spending and R&D employee education level on innovation performance. These results also support Boulding and Staelin’s (1995) contention that a firm’s ability to

FIGURE 4. The negative moderating effect of stability on the relationship between R&D employee education and innovation

FIGURE 5. The positive moderating effect of innovation orientation on the relationship between R&D employee education and innovation



leverage its R&D investments hinges on both ability and motivation. A high team-oriented culture emphasizes collaboration and cooperation and helps manage conflict among employees and across units. These are attributes that together can improve the organization’s ability to be more efficient and effective in using its R&D resources. A team-oriented culture can also motivate R&D employees to be more actively engaged in sharing and combining knowledge, thereby enabling the integration, synthesis, and use of the knowledge and skills that come with higher levels of education. Our findings also support the argument that there is still meaningful variation across firms within a collectivistic society (Kirk-man, Lowe, & Gibson, 2006); therefore, one should not assume the existence of a high level of team orientation in all companies in China. As our results indicate, firms high in team orientation were able to better use financial and human capital investments to produce innovations than those low in team orientation.

In an innovation-oriented culture, in which seizing opportunities is emphasized and risk taking accepted, R&D employees tend to be more open and receptive to new and unusual ideas. As such, they are more likely to use fully the knowledge and skills that come with an advanced education. Our findings also suggest that firms high in

this orientation should advocate spending R&D resources in areas that have the opportunity to develop into new products and services, even though their successful introduction to the market may be uncertain.

Contrary to our prediction, the culture dimension of outcome orientation did not have a moderating effect, but instead showed a negative main effect on innova-tion. One possible explanation for this finding is that while it is important to strive for achievement and successful out-comes, it may be that high outcome-oriented cultures hinder the effective use of R&D investments. As noted, the innovation process inevitably involves uncertainty. Thus, it may be that a heavy emphasis on innovation outcomes (rather than innova-tive behavior) causes individuals to fixate on the personal risk associated with failure. Consistent with research on individual cre-ativity, this fixation could subsequently have an adverse effect on the type of cre-ativity needed for radical innovation (Mehr & Shaver, 1996; Mumford, 2000). That is, rather than pursuing more unpredictable innovation-related activities, employees may react by choosing tasks with which they are more familiar and in which they have a higher probability of succeeding. The high uncertainty avoidance associated with the Chinese culture (Sully de Luque &

FIGURE 6. The moderating effect of quadratic outcome orientation on the relationship between R&D spending and innovation (i.e., R&D spending–innovation relationship is strongest when outcome orientation is at the medium level)



Javidan, 2004) may also have exacerbated this negative effect.

Interestingly, our post hoc analysis re-vealed a nonlinear effect, such that up to a point, increasing emphasis on outcomes is increasingly beneficial for innovation (i.e., strengthening the R&D spending–innova-tion relationship). After that point, addi-tional emphasis has an increasingly negative impact on innovation output. Hence, it could be that even when financial invest-ments are made to facilitate R&D, beyond a certain threshold, emphasizing outcomes results in employees’ being more conserva-tive in experimenting and developing ideas into new products and services for fear of possible failure. This effect would then re-duce the number of innovations the com-pany subsequently offers.

The culture dimension of stability showed different results between R&D spending and R&D employee education. Stability did not have a moderating effect on the R&D spending–innovation relation-ship but instead had a negative main effect. This suggests that while increasing R&D spending results in higher levels of innova-tion, there can be opposing forces, such as a strong cultural value for stability, which concurrently stifle the innovation process. Employees are less likely to engage in uncer-tain activities such as innovation in an en-vironment that values stability. In this con-text, resources may be allocated to activities that are more familiar to limit disruption to the status quo. Indeed, correlations in Table I show that companies with a culture of sta-bility tended to invest less financially in innovation. Consistent with our expecta-tions, results indicate that a culture of sta-bility weakens the relationship between ed-ucation level and innovation. Even when R&D employees with higher levels of educa-tion have been hired to leverage their knowledge and skills for innovation, a cul-ture of stability apparently signals them to shy away from the uncertainty and complexity inherent in innovation and instead to engage in relatively routine tasks. Consequently, this tendency likely prevents employees from effectively sharing

and combining knowledge to pursue innovation activities that carry a degree of uncertainty and stimulate change within the organization.

Finally, it is worth noting that education level did not have a significant main effect on innovation in our study. While the relation-ship was positive, as suggested by the es-poused “more is better” belief (Marvel & Lumpkin, 2007), this insignificant main effect is contrary to what has been found in other studies. It is typically thought that employees who are more educated are catalysts for in-novation or otherwise marry the needed in-gredients for innovation. Yet, it appears from our results that without the right culture, the practice of hiring employees with advanced education does not ensure the expected re-sult. Further, the study’s cultural context may explain our non-significant finding. As de-scribed, China has placed a strategic priority on improving educational opportunities as a means to becoming an innovation-oriented nation (Wolff, 2007). The country is, how-ever, still in transition in terms of increasing the level of education found within organiza-tions (Li, Hu, & Chi, 2007). Thus, if increased education indeed enhances an organization’s talent and innovation capabilities, then it may be that the direct relationship between R&D workers’ education level and innovation will emerge once the benefits from China’s investments in education accrue. It is also possible, had we been able to divide our data according to incremental versus radical inno-vation, that we might have found, similar to Marvel and Lumpkin (2007), that formal edu-cation was directly related to creating radical innovations, but not so in developing incre-mental innovations.

Implications

Our study’s findings suggest that increasing financial input is only one aspect of facilitat-ing innovation in Chinese firms; social con-text should also be considered. This finding has significant implications for firms that pursue innovation, particularly small and medium-sized Chinese firms constrained by financial resources. Rather than worrying



about how to increase financial inputs, these firms might do well to shift their focus to building a culture that helps maximize re-sources currently available. Creating the right culture for innovation will also give the firm a competitive advantage that is difficult for competitors to imitate given its intangible nature (Barney & Wright, 1998).

Firms that wish to develop and intro-duce new products and services need to ad-vocate novel thinking and teamwork, de-emphasize the value of stability, and avoid placing excessive emphasis on outcomes. An emphasis on collaboration and tolerance for uncertainty and the unfamiliar are nec-essary for corporate entrepreneurship and innovation to flourish. Managers play a cru-cial role in communicating the importance of these values in their firms. For example, they can encourage employees to experi-ment with innovative ideas by altering the organizational structure to be more flexible and less resistant to change and facilitate knowledge exchange and combination (cf. Hornsby et al., 2002). Recognizing employee efforts and encouraging people to think “outside the box” to get results—without the fear of being penalized if an idea ulti-mately fails—can also be helpful in foster-ing a culture of innovation and discourag-ing a norm of stability. We caution that in an uncertainty-avoiding society such as China (Sully de Luque & Javidan, 2004), it may be more difficult to engage individuals in championing the role of innovation. It will be important, therefore, for top man-agement to empower middle- and lower-level managers to become innovation cham-pions. In addition, to the extent that firms can facilitate culture building or organiza-tional change through staffing and career development systems, it will likely be easier for them to build and sustain a culture for innovation.

Finally, while cultures of innovation are known to value risk taking (Jassawalla & Sashittal, 2002), our findings suggest that a culture that has too much of an outcome orientation may result in a limited number of innovations. An outcome orientation may therefore be a more effective cultural

norm when complemented with the assur-ance that the firm also values and rewards contributions made in earlier stages of the innovation process. This combined focus on both innovation outcomes and innova-tive behavior could perhaps ease some of the personal risks (real or perceived) that employees associate with organizational in-novation. It is also important that managers clearly communicate to employees how their performance will be evaluated and whether or how innovation failure would be factored into this evaluation. To this end, practitioners should consider developing an incentive system that refrains from penal-izing employees solely for failures, as doing so will help foster a culture of corporate en-trepreneurship and innovation. By reward-ing innovative ideas and behaviors, firms may also reduce the likelihood of their cul-ture’s being perceived as highly outcome oriented.

Limitations and Future Research

There are several limitations of this study. First, R&D spending and innovation data were collected from the same sources; thus, common method bias is a possible concern. The objective nature of this data and the focus of the study on the interaction effects, however, render it less vulnerable to bias (Ko-tabe, Martin, & Domoto, 2003; Organ, Podsa-koff, & MacKenzie, 2006).

Second, our study chose to focus on only one attribute of a firm’s human resources, the education level of R&D employees, be-cause innovation involves new ideas, those that emanate from knowledge and expertise (Mumford, 2000). One means through which innovation-beneficial knowledge and exper-tise develops is education (Zhao, 2008). While education levels are directly linked to the knowledge stock members of a firm share and use for innovation, other human re-source attributes and group dynamics might also influence innovation processes. For ex-ample, a high level of minority dissent can be functional to team innovation as it helps stimulate diverse thinking (De Dreu & West, 2001). The personality each employee brings



into a unit may also influence the effective-ness of interpersonal interactions and how ideas develop (Neuman, Wagner, & Chris-tiansen, 1999). Along this line, it might be interesting for future research to examine how organizational culture influences the dynamics of the human resource utilization process. In China’s quest to reach its innova-tion-powerhouse goal, it may also be useful to explore in detail how Chinese firms’ HR practices influence creating and sustaining an innovation culture in transitional mar-kets.

Third, in the study, we examined innova-tion using a three-year time frame. While we believe this performance time frame is appro-priate and logical for our study, future re-searchers might do well to examine how or-ganizational culture influences innovation over a longer period.

Fourth, because of the difficulty in man-aging the Q-sort method, we were not able to collect culture data from a large number of employees in each company. We do not believe, however, that this limitation de-tracts from the value of our study or its find-ings. As mentioned, we collected organiza-tional culture data from employees at different levels and functions at each com-pany; the interrater agreement indicators suggested acceptable agreement; and the re-sponses from interviews with management were consistent with employee ratings. Still, we encourage future researchers to collect data from as many respondents as logisti-cally possible when assessing organizational culture.

Fifth, as indicated, we did not measure incremental and radical innovation separately in this study. Future research is needed that measures innovation in a more fine-grained way to help us better understand how organi-zational characteristics might differentially affect distinct types of innovation.

Finally, it is important to recognize that the population sampled in our study came from one fast-developing province in China, a province characterized by great support and pressure for market-based innovation (Dob-son & Safarian, 2008; Wang & Wang, 2008). Although this sample pool provides the

strength of controlling for differences in regu-lations and policies across provinces, it may also limit the findings’ generalizability. Con-sistent with the claim that innovative compa-nies across industries and geographic culture have common characteristics, qualities, and behaviors that differentiate them from less innovative companies (Zien & Buckler, 1997), our findings are important for firms (regard-less of age, size, and location) that value cor-porate entrepreneurship and innovation yet find themselves with limited resources to in-vest in innovation endeavors. Nevertheless, we realize that future research is needed to determine whether our findings can be repli-cated in other parts of China or in other countries. It is our hope that the issues raised and the findings revealed in this study will encourage others to pursue research along these and similar lines.

Acknowledgments

This research was supported by a grant of NSF of China (grant No. 70732001) to Zhong-Ming Wang. We thank Steven Phelan for his research assistance. We would also like to thank Editor-in-Chief Theresa Welbourne and the anonymous reviewers for their guidance during the review process. An earlier version of this research was presented at the 2009 annual conference of the Academy of Management in Chicago.

Notes

1. We acknowledge that some researchers consider

entrepreneurship solely as starting a new business

venture (e.g., Michael & Pearce, 2009; Tang & Ko-

veos, 2004; Woolley & Rottner, 2008). This narrow

conceptualization is not adopted here. As used in

our paper, entrepreneurship applies to new or more

mature firms as well as small, medium-, or large-

sized firms that seek to survive and prosper (John-

son, 2001).

2. A factor analysis involving responses from the final

sample only (n = 746) showed a factor structure that

was consistent with that of the larger sample, with six

factors accounting for 46.85% of variance in the data.

3. The results of the additional analyses are available

upon request.



SHENG WANG is an assistant professor in the College of Business at the University of Nevada, Las Vegas. She received her Ph.D. from Ohio State University. Her research interests include employee development (mentoring relationships in particular), knowl-edge management, human resources issues in small and entrepreneurial fi rms, and cross-cultural issues. Her work has been published in the Journal of Applied Psychology, Journal of Management, Journal of Vocational Behavior, and Research in Personnel and Human Resource Management, among others.

REBECCA M. GUIDICE is an assistant professor of management in the College of Business at the University of Nevada, Las Vegas. She earned her Ph.D. from Washington State Uni-versity. Her current research interests include issues related to corporate governance, en-trepreneurship, accountability, and competitive bluffi ng. She has published in many peer-reviewed journals including the Journal of Management and Journal of Business Ethics.

JUDITH W. TANSKY is a senior lecturer in labor and human resources and Director of the Honors Contract Program in the Max M. Fisher College of Business. She received her Ph.D. in labor and human resources from Ohio State University. She is associate edi-tor for Human Resource Management and has published in various journals including Human Resource Management, Entrepreneurship Theory and Practice, Journal of Small Business Management, Labor Law Journal, Employee Rights and Responsibilities Jour-nal, Psychological Reports, and Canadian Journal of Administrative Sciences. She has co-authored various book chapters and co-edited a book, Human Resource Strategies for the High Growth Entrepreneurial Firm. Judy has received grants from the Kauffman Foundation for research and an invitational conference on “Managing People in Small and Entrepreneurial Firms: What Are the Human Resource Issues?” Judy’s primary areas of research, teaching, and consulting are compensation, employee development, and human resources in small and entrepreneurial fi rms.

ZHONG-MING WANG is a professor of HRM, organizational behavior, and entrepreneur-ship at Zhejiang University. He received his master’s degree in applied psychology in Sweden and Ph.D. in industrial psychology at Hangzhou University, a joint program with Gothenburg University. Dr. Wang is the director of the Global Entrepreneurship Research Center and the Center for HR & Strategic Development at Zhejiang University. His research areas include leadership assessment and selection, organizational change and learning, women’s entrepreneurship, family business HR, and global HR strategies. He serves as the president of the Industrial Psychology Division of the Chinese Psychological Society. He is the editor-in-chief for the Journal of Chinese Human Resource Management and also serves on editorial boards of international journals.

References

Ahuja, G., & Katila, R. (2004). Where do resources come from? The role of idiosyncratic situations. Strategic Management Journal, 25(8/9), 887–907.

Altenburg, T., Schmitz, H., & Stamm, A. (2008). Breakthrough? China‘s and India‘s transition from production to innovation. World Development, 36(2), 325–344.

Amabile, T. M. (1988). A model of creativity and inno-vation in organizations. Research in Organizational Behavior, 10, 123–167.

Amabile, T. M., Conti, R., Coon, H., Lazenby, J., & Her-ron, M. (1996). Assessing the work environment for creativity. Academy of Management Journal, 39(5), 1154–1184.

Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Mar-keting Research, 14(3), 396–402.

Baer, M., & Frese, M. (2003). Innovation is not enough: Climates for initiative and psychological safety, process innovations, and fi rm performance. Journal of Organizational Behavior, 24(1), 45–68.



Bantel, K. A., & Jackson, S. W. (1989). Top management and innovation in banking: Does the composition of the top management team make a difference? Strategic Management Journal, 10(S1), 107–124.

Barney, J. B. (1986). Organizational culture: Can it be a source of sustained competitive advantage? Acad-emy of Management Review, 11(3), 656–665.

Barney, J. B., & Wright, P. M. (1998). On becoming a strategic partner: The role of human resources in gaining competitive advantage. Human Resource Management, 37(1), 31–46.

Bliese, P. D. (2000). Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis. In K. K. Klein & S. J. Kozlowski (Eds.), Multilevel theory, research, and methods in organizations: Foundations, extensions, and new directions, (pp. 349–381). San Francisco: Jossey-Bass.

Board, C. (2008). CEOs’ top 10 challenges overall. HRMagazine, 53(1), 10.

Boulding, W., & Staelin, R. (1995). Identifying general-izable effects of strategic actions on fi rm perform-ance: The case of demand-side returns to R&D spending. Marketing Science, 14(3), G222–G236.

Brandt, S. C. (1985). Entrepreneuring in established companies. Homewood, IL: Dow Jones/Irwin.

Brazeal, D. V. (1993). Organizing for internally de-veloped corporate ventures. Journal of Business Venturing, 8(1), 75–90.

Brislin, R. W. (1980). Translation and content analysis of oral and written material. In H. C. Triandis & J. W. Berry (Eds.), Handbook of cross-cultural psychol-ogy (Vol. 2, pp. 349–444). Boston: Allyn & Bacon.

Cable, D. M., & Judge, T. A. (1996). Person-organization fi t, job choice decisions, and organizational entry. Organizational Behavior and Human Decision Proc-esses, 67(3), 294–311.

Chandler, G. N., Keller, C., & Lyon, D. W. (2000). Unraveling the determinants and consequences of an innovation-supportive organizational culture. Entrepreneurship: Theory & Practice, 25(1), 59–76.

Chatman, J. A. (1991). Matching people and organiza-tions: Selection and socialization in public account-ing fi rms. Administrative Science Quarterly, 36(3), 459–484.

Child, J., Yuan, L., & Tsai, T. (2007). Institutional entre-preneurship in building an environmental protec-tion system for the People‘s Republic of China. Organization Studies, 28(7), 1013–1034.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis

for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.

Covin, J. G., & Miles, M. P. (1999). Corporate entrepre-neurship and the pursuit of competitive advantage. Entrepreneurship: Theory & Practice, 23(3), 47–63.

Covin, J. G., & Slevin, D. P. (1991). A conceptual model of entrepreneurship as fi rm behavior. Entrepre-neurship: Theory & Practice, 16(1), 7–25.

Damanpour, F. (1991). Organizational innovation: A meta-analysis of effects of determinants and moderators. Academy of Management Journal, 34(3), 555–590.

Damanpour, F., & Schneider, M. (2006). Phases of the adoption of innovation in organizations: Effects of environment, organization and top managers. British Journal of Management, 17(3), 215–236.

de Brentani, U., & Kleinschmidt, E. J. (2004). Corpo-rate culture and commitment: Impact on perform-ance of international new product development programs. Journal of Product Innovation Manage-ment, 21(5), 309–333.

De Dreu, C. K. W., & West, M. A. (2001). Minority dissent and team innovation: The importance of participation in decision making. Journal of Applied Psychology, 86(6), 1191–1201.

Dess, G. G., Lumpkin, G. T., & McGee, J. E. (1999). Link-ing corporate entrepreneurship to strategy, struc-ture, and process: Suggested research directions. Entrepreneurship: Theory & Practice, 23(3), 85–102.

Dobson, W., & Safarian, A. E. (2008). The transition from imitation to innovation: An enquiry into China‘s evolving institutions and fi rm capabilities. Journal of Asian Economics, 19(4), 301–311.

Dougherty, D. (1999). Organizing for innovation. In S. R. Clegg, C. Hardy, & W. R. Nord (Eds.), Manag-ing organizations: Current issues (pp. 174–189). Thousand Oaks, CA: Sage.

Drucker, P. (1985). Innovation and entrepreneurship. New York: Harper & Row.

Fiol, C. M. (1995). Thought worlds colliding: The role of contradiction in corporate innovation processes. Entrepreneurship: Theory & Practice, 19(3), 71–90.

Fitzgerald, C. A., Flood, P. C., O‘Regan, P., & Ramamoor-thy, N. (2008). Governance structures and innova-tion in the Irish software industry. Journal of High Technology Management Research, 19(1), 36–44.

Freel, M. S. (2005). Perceived environmental uncer-tainty and innovation in small fi rms. Small Busi-ness Economics, 25(1), 49–64.

Freeman, J., & Engel, J. S. (2007). Models of innova-tion: Startups and mature corporations. California Management Review, 50(1), 94–119.



Fritz-Enz, J. (2000). The ROI human capital: Measur-ing the economic value of employee performance. New York: American Management Association.

Garnier, J.-P. (2008). Rebuilding the R&D engine in big pharma. Harvard Business Review, 86(5), 68–76.

Gelfand, M. J., Bhawuk, D. P. S., Nishii, L. H., & Bech-told, D. J. (2004). Individualism and collectivism. In R. J. House, P. J. Hanges, M. Javidan, P. W. Dorf-man, & V. Gupta (Eds.), Culture, leadership, and organizations: The GLOBE study of 62 societies (pp. 437–512). Thousand Oaks, CA: Sage.

George, J. M., & Bettenhausen, K. (1990). Understand-ing prosocial behavior, sales performance, and turnover: A group-level analysis in a service con-text. Journal of Applied Psychology, 75(6), 698–709.

Glick, W. H. (1985). Conceptualizing and measuring organizational and psychological climate: Pitfalls in multilevel research. Academy of Management Review, 10(3), 601–616.

Gorsuch, R. L. (1983). Factor analysis. Hillsdale, NJ: Lawrence Erlbaum Associates.

Greve, H. R. (2003). A behavioral theory of R&D expen-ditures and innovations: Evidence from shipbuilding. Academy of Management Journal, 46(6), 685–702.

Gudmundson, D., Tower, C. B., & Hartman, E. A. (2003). Innovation in small businesses: Culture and ownership structure do matter. Journal of Develop-mental Entrepreneurship, 8(1), 1–17.

Hauser, J., Tellis, G. J., & Griffi n, A. (2006). Research on innovation and new products: A review and agenda for marketing science. Marketing Science, 25(6), 687–717.

He, Z.-L., & Wong, P.-K. (2004). Exploration vs. ex-ploitation: An empirical test of the ambidexterity hypothesis. Organization Science: A Journal of the Institute of Management Sciences, 15(4), 481–494.

Hidalgo, A., & Albors, J. (2008). Innovation manage-ment techniques and tools: A review from theory and practice. R&D Management, 38(2), 113–127.

Hitt, M. A., Hoskisson, R. E., Johnson, R. A., & Moesel, D. D. (1996). The market for corporate control and fi rm innovation. Academy of Management Journal, 39(5), 1084–1119.

Hofstede, G. (1980). Culture’s consequences: Interna-tional differences in work-related values. Beverly Hills, CA: Sage.

Hornsby, J. S., Kuratko, D. F., & Zahra, S. A. (2002). Middle managers’ perception of the internal envi-ronment for corporate entrepreneurship: Assessing a measurement scale. Journal of Business Ventur-ing, 17(3), 253–273.

Huang, Y. (2003). Selling China: Foreign investment during the reform era. New York: Cambridge Uni-versity Press.

Huber, G. P., Sutcliffe, K. M., Miller, C. C., & Glick, W. M. (1993). Understanding and predicting organiza-tional change. In G. P. Huber & W. H. Glick (Eds.), Organizational change and redesign (pp. 215–265). New York: Oxford University Press.

Hurley, R. F., & Hult, G. T. M. (1998). Innovation, mar-ket orientation, and organizational learning: An integration and empirical examination. Journal of Marketing, 62(3), 42–54.

IBM Global Business Services. (2006). Expanding the innovation horizon: The global CEO study 2006. Re-trieved January 16, 2010, from http://www-935.ibm.com/services/au/bcs/html/bcs_ceostudy2006.html

Ireland, R. D., Kuratko, D. F., & Morris, M. H. (2006). A health audit for corporate entrepreneurship: Innovation at all levels: Part I. Journal of Business Strategy, 27(2), 10–17.

Ireland, R. D., & Webb, J. (2007). A cross-disciplinary exploration of entrepreneurship research. Journal of Management, 33(6), 891–927.

James, L. R. (1982). Aggregation bias in estimates of perceptual agreement. Journal of Applied Psychol-ogy, 67(2), 219–229.

James, L. R., Demaree, R. G., & Wolf, G. (1993). rwg: An assessment of within-group interrater agreement. Journal of Applied Psychology, 78(2), 306–309.

Jaruzelski, B., & Dehoff, K. (2009). Profi ts down, spending steady: The global innovation 1000. Strat-egy & Business, 57, 1–14.

Jassawalla, A. R., & Sashittal, H. C. (2002). Cultures that support product-innovation processes. Acad-emy of Management Executive, 16(3), 42–54.

Jefferson, G. H., Bai, H., Guan, X., & Yu, X. (2006). R&D performance in Chinese industry. Economics of In-novation & New Technology, 15(4/5), 345–366.

Johnson, D. (2001). What is innovation and entrepre-neurship? Lessons for larger organisations. Indus-trial & Commercial Training, 33(4), 135–140.

Judge, T. A., & Cable, D. M. (1997). Applicant personal-ity, organizational culture, and organization attrac-tion. Personnel Psychology, 50(2), 359–394.

Kanter, R. M. (1982). The middle manager as innovator. Harvard Business Review, 60(4), 95–106.

Kanter, R. M. (1985). Supporting innovation and venture development in established companies. Journal of Business Venturing, 1(1), 47–60.

Kanter, R. M. (2000). A culture of innovation. Executive Excellence, 17(8), 10–11.



Katila, R. (2002). New product search over time: Past ideas in their prime? Academy of Management Journal, 45(5), 995–1010.

Katila, R., & Ahuja, G. (2002). Something old, some-thing new: A longitudinal study of search behavior and new product introduction. Academy of Man-agement Journal, 45(6), 1183–1194.

Katila, R., & Shane, S. (2005). When does lack of resources make new fi rms innovative? Academy of Management Journal, 48(5), 814–829.

Kelley, D., Peters, L., & O’Connor, G. (2009). Intra-organizational networking for innovation-based corporate entrepreneurship. Journal of Business Venturing, 24(3), 221–235.

Khazanchi, S., Lewis, M. W., & Boyer, K. K. (2007). In-novation-supportive culture: The impact of organi-zational values on process innovation. Journal of Operations Management, 25(4), 871–884.

Khilji, S. E., Mroczkowski, T., & Bernstein, B. (2006). From invention to innovation: Toward developing an integrated innovation model for biotech fi rms. Journal of Product Innovation Management, 23(6), 528–540.

Kirkman, B. L., Lowe, K. B., & Gibson, C. B. (2006). A quarter century of culture’s consequences: A review of empirical research incorporating Hofstede’s cultural values framework. Journal of International Business Studies, 37(3), 285.

Kor, Y. Y. (2006). Direct and interaction effects of top management team and board compositions on R&D investment strategy. Strategic Management Journal, 27(11), 1081–1099.

Kotabe, M., Martin, X., & Domoto, H. (2003). Gaining from vertical partnerships: Knowledge transfer, relationship duration, and supplier performance improvement in the U.S. and Japanese automotive industries, Strategic Management Journal, 24(4), 293–316.

Kotler, P. (1997). Marketing management: Analysis, planning, implementation and control (8th ed.). Up-per Saddle River, NJ: Prentice Hall.

Kuratko, D. F., Ireland, R. D., Covin, J. G., & Hornsby, J. S. (2005). A model of middle-level managers’ entrepreneurial behavior. Entrepreneurship: Theory & Practice, 29(6), 699–716.

Lassen, A. H., Gertsen, F., & Riis, J. O. (2006). The nexus of corporate entrepreneurship and radical in-novation. Corporate Entrepreneurship and Radical Innovation, 15(4), 359–372.

Lau, C.-M., & Ngo, H.-Y. (2004). The HR system, organi-zational culture, and product innovation. Interna-tional Business Review, 13(6), 685–703.

Lee, S.-H., Wong, P.-K., & Chong, C.-L. (2005). Human and social capital explanations for R&D outcomes. IEEE Transactions on Engineering Management, 52(1), 59–68.

Leonard, D., & Sensiper, S. (1998). The role of tacit knowledge in group innovation. California Manage-ment Review, 40(3), 112–132.

Li, H., & Atuahene-Gima, K. (2001). Product innovation strategy and the performance of new technology ventures in China. Academy of Management Jour-nal, 44(6), 1123–1134.

Li, K., Hu, Y., & Chi, J. (2007). Major sources of produc-tion improvement and innovation growth in Chinese enterprises. Pacifi c Economic Review, 12(5), 683–710.

Lin, B.-W., Lee, Y., & Hung, S.-C. (2006). R&D intensity and commercialization orientation effects on fi nan-cial performance. Journal of Business Research, 59(6), 679–685.

Lipparini, A., & Sobrero, M. (1994). The glue and the pieces: Entrepreneurship and innovation in small-fi rm networks. Journal of Business Venturing, 9(2), 125–140.

Luo, Y., & Peng, M. W. (1999). Learning to compete in a transition economy: Experience, environment, and performance. Journal of International Business Studies, 30(2), 269–295.

Lyons, R. K., Chatman, J. A., & Joyce, C. K. (2007). Innovation in services: Corporate culture and in-vestment banking. California Management Review, 50(1), 174–191.

Marvel, M. R., & Lumpkin, G. T. (2007). Technology entrepreneurs’ human capital and its effects on innovation radicalness. Entrepreneurship: Theory & Practice, 31(6), 807–828.

McLean, L. D. (2005). Organizational culture’s infl u-ence on creativity and innovation: A review of the literature and implications for human resource development. Advances in Developing Human Resources, 7(2), 226–246.

Mehr, D. G., & Shaver, P. R. (1996). Goal structures in creating motivation. Journal of Creative Behavior, 30(2), 77–104.

Michael, S., & Pearce, J., II. (2009). The need for in-novation as a rationale for government involve-ment in entrepreneurship. Entrepreneurship and Regional Development, 21(3), 285–302.

Mumford, M. D. (2000). Managing creative people: Strategies and tactics for innovation. Human Resource Management Review, 10(3), 313–351.

Naman, J. L., & Slevin, D. P. (1993). Entrepreneurship and the concept of fi t: A model and empirical tests. Strategic Management Journal, 14(2), 137–153.



Neuman, G. A., Wagner, S. H., & Christiansen, N. D. (1999). The relationship between work-team person-ality composition and the job performance of teams. Group & Organization Management, 24(1), 28–45.

Nohria, N., & Gulati, R. (1996). Is slack good or bad for innovation? Academy of Management Journal, 39(5), 1245–1264.

Oden, H. W. (1997). Managing corporate culture, innovation, and intrapreneurship. Westport, CT: Quorum Books.

OECD. OECD reviews of innovation policy: China. (2008). Paris: Author. Retrieved January 16, 2010, from www.oecd.org

O’Reilly, C. A., Chatman, J., & Caldwell, D. F. (1991). People and organizational culture: A profi le com-parison approach to assessing person-organiza-tion fi t. Academy of Management Journal, 34(3), 487–516.

O’Reilly, C. A., & Chatman, J. A. (1996). Culture as so-cial control: Corporations, cults, and commitment. Research in Organizational Behavior, 18, 157–200.

Organ, D. W., Podsakoff, P. M., & MacKenzie, S. B. (2006). Organizational citizenship behavior. Thou-sand Oaks, CA: Sage.

Pelz, D. C., & Andrews, F. M. (1976). Scientists in organizations: Productive climates for research and development. Ann Arbor, MI: Institute for Social Research.

Peng, M. W. (2001). How entrepreneurs create wealth in transition economies. Academy of Management Executive, 15(1), 95–108.

Peng, M. W., & Heath, P. S. (1996). The growth of the fi rm in planned economies in transition: Institu-tions, organizations, and strategic choice. Academy of Management Review, 21(2), 492–528.

Price, R. M. (2007). Infusing innovation into corporate culture. Organizational Dynamics, 36(3), 320–328.

Psacharopoulos, G. (1985). Returns to education: A fur-ther international update and implications. Journal of Human Resources, 20(4), 583–604.

Romer, P. M. (1986). Increasing returns and long run growth. Journal of Political Economy, 94(5), 1002–1037.

Rothwell, R. (1994). Towards the fi fth-generation in-novation process. International Marketing Review, 11(1), 7–31.

Rule, E. G., & Irwin, D. W. (1988). Fostering intrapre-neurship: The new competitive edge. Journal of Business Strategy, 9(3), 44–47.

Schein, E. H. (2004). Organizational culture and leader-ship. San Francisco: Jossey-Bass.

Schultz, T. W. (1961). Investment in human capital. American Economic Review, 51(5), 1035–1039.

Schumpeter, J. A. (1934). The theory of economic development. Cambridge, MA: Harvard University Press.

Shane, S. (1992). Why do some societies invent more than others? Journal of Business Venturing, 7(1), 29–75.

Sharma, P., & Chrisman, J. J. (1999). Toward a recon-ciliation of the defi nitional issues in the fi eld of cor-porate entrepreneurship. Entrepreneurship: Theory & Practice, 23(3), 11–27.

Smith, K. G., Collins, C. J., & Clark, K. D. (2005). Exist-ing knowledge, knowledge creation capability, and the rate of new product introduction in high-tech-nology fi rms. Academy of Management Journal, 48(2), 346–357.

Stopford, J. M., & Baden-Fuller, C. W. F. (1994). Creat-ing corporate entrepreneurship. Strategic Manage-ment Journal, 15(7), 521–536.

Sully de Luque, M., & Javidan, M. (2004). Uncertainty avoidance. In R. J. House, P. J. Hanges, M. Javidan, P. W. Dorfman, & V. Gupta (Eds.), Culture, leader-ship, and organizations: The GLOBE study of 62 societies. Thousand Oaks, CA: Sage.

Sun, L.-Y., Aryee, S., & Law, K. S. (2007). High-per-formance human resource practices, citizenship behavior, and organizational performance: A relational perspective. Academy of Management Journal, 50(3), 558–577.

Svyantek, D. J., & Bott, J. P. (2004). Organizational culture and organizational climate measures: An integrative review. In J. C. Thomas (Ed.), Compre-hensive handbook of psychological assessment: Industrial and organizational assessment (Vol. 4, pp. 507–524). Hoboken, NJ: Wiley.

Tan, J. J. (2001). Innovation and risk-taking in a tran-sitional economy: A comparative study of Chinese managers and entrepreneurs. Journal of Business Venturing, 16(4), 359–376.

Tan, J. J., & Litschert, R. J. (1994). Environment-strat-egy relationship and its performance implications: An empirical study of the Chinese electronics in-dustry. Strategic Management Journal, 15(1), 1–20.

Tang, L., & Koveos, P. E. (2004). Venture entrepreneur-ship, innovation entrepreneurship, and economic growth. Journal of Developmental Entrepreneur-ship, 9(2), 161–171.

Tellis, G. J., Prabhu, J. C., & Chandy, R. K. (2009). Radi-cal innovation across nations: The preeminence of corporate culture. Journal of Marketing, 73(1), 3–23.



Teng, B.-S. (2007). Corporate entrepreneurship activi-ties through strategic alliances: A resource-based approach toward competitive advantage. Journal of Management Studies, 44(1), 119–142.

Tower, C. B., Sebora, T. C., Hartman, E. A., & Cornwall, J. R. (1993). Measurement of organizational innova-tion: A process approach. Journal of Business and Entrepreneurship, 5(2), 23–26.

Tsai, W., & Ghoshal, S. (1998). Social capital and value creation: The role of intrafi rm networks. Academy of Management Journal, 41(4), 464–476.

Ulijin, J., & Brown, T. E. (2004). Innovation, entre-preneurship and culture: A matter of interaction between technology, progress and economic growth? An introduction. In T. E. Brown & J. Ulijin (Eds.), Innovation, entrepreneurship and culture: The interaction between technology, progress and economic growth (pp. 1–38). Northampton, MA: Edward Elgar.

Van de Ven, A. H. (1986). Central problems in manage-ment of innovation. Management Science, 32(5), 590–607.

van der Panne, G., van der Beers, C., & Kleinknecht, A. (2003). Success and failure of innovation: A lit-erature review. International Journal of Innovation Management, 7(3), 309–338.

Verhaeghe, A., & Kfi r, R. (2002). Managing innovation in a knowledge intensive technology organisation (KITO). R&D Management, 32(5), 409–417.

Vermeulen, P. A. M. (2005). Uncovering barriers to complex incremental product innovation in small and medium-sized fi nancial services fi rms. Journal of Small Business Management, 43(4), 432–452.

Walcott, S. (2003). Chinese science and technology industrial parks. Burlington, VT: Ashgate.

Wang, Z.-M., & Wang, S. (2008). Modeling regional HRM strategies in China: An entrepreneurship per-spective. International Journal of Human Resource Management, 19(5), 945–963.

Wolff, A. W. (2007). China’s drive toward innovation. Issues in Science and Technology, 23(3), 54–62.

Woolley, J., & Rottner, R. (2008). Innovation policy and nanotechnology entrepreneurship. Entrepreneur-ship Theory and Practice, 32(5), 791–811.

Xin, K. K., & Pearce, J. L. (1996). Guanxi: Connections as substitutes for formal institutional support. Acad-emy of Management Journal, 39(6), 1641–1658.

Yang, J. Y., & Li, J. (2008). The development of en-trepreneurship in China. Asia Pacifi c Journal of Management, 25(2), 335–339.

Zahra, S. A., Ireland, R. D., Gutierrez, I., & Hitt, M. A. (2000). Privatization and entrepreneurial transforma-tion: Emerging issues and a future research agenda. Academy of Management Review, 25(3), 509–524.

Zahra, S. A., Kuratko, D. F., & Jennings, D. F. (1999). Guest editorial: Entrepreneurship and the acquisi-tion of dynamic organizational capabilities. Entre-preneurship: Theory & Practice, 23(3), 5–10.

Zhang, J. (2003). The development of high-tech en-terprises in China’s universities. Wuhan, China: Huanzhong Science and Technology University Press.

Zhang, Y., Li, H., Hitt, M. A., & Cui, G. (2007). R&D intensity and international joint venture perform-ance in an emerging market: Moderating effects of market focus and ownership structure. Journal of International Business Studies, 38(6), 944–960.

Zhao, S. (2008). Application of human capital theory in China in the context of the knowledge economy. International Journal of Human Resource Manage-ment, 19(5), 802–817.

Zhao, Z., & Yang, H. (2008). Management practices in high-tech environments and enterprises in the People’s Republic of China. Chinese Economy, 41(3), 17–33.

Zien, K. A., & Buckler, S. A. (1997). Dreams to market: Crafting a culture of innovation. Journal of Product Innovation Management, 14(4), 274–287.



A P P E N D I X 1 Major Characteristics of the Study Sample1

High Tech Low Tech Overall

% of sample 29% 71% 100%Average innovations 23.41 (76.87) 21.47 (38.41) 22.04 (52.19)Average sales2 51.5M (79.3M) 210M (419M) 164M (364M)Average R&D spending .12 (.16) .04 (.05) .07 (.10)Average education level 11.71(15.95) 8.17(14.97) 9.20(15.29)1 Standard deviation in parentheses.2 In Renminbi (RMB).



A P P E N D I X 2 Survey Items

CEO or General Manager Survey:

Innovation performance:

How many new products has the company introduced in the past three years? How many new services has the company introduced in the past three years?

Sales: Please indicate the annual sales in your company in: 2003 2004 2005

R&D expenses: What is the average R&D expense in your company over the past three years?

Firm age: Please indicate the year when your company was founded

Industries: Please indicate the primary industry of your company:

HR Survey:

R&D employee education: Please indicate the composition of education among the employees in the R&D unit in

your company: % doctorate % master’s % bachelor’s % some college % high school % other

Firm Size: Please indicate the number of employees in your company

Sales: What are the average annual sales of your company over the past three years?

Employee Survey:

Organizational Culture: Please sort the 40 values into the following categories ranging from “the most characteristic

of this organization” to “the least characteristic of this organization.” Each value can only appear once.

when r&d spending is not enough: the critical role of culture when you really want to innovate

Documents