Importance of social capital to student creativity within higher education in China

Thinking Skills and Creativity 12 (2014) 14–25

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Importance of social capital to student creativity within higher education in China Jibao Gu, Yanbing Zhang ∗ , Hefu Liu School of Management, University of Science and Technology of China, PR China

a r t i c l e

i n f o

Article history: Received 13 May 2013 Received in revised form 21 November 2013 Accepted 1 December 2013 Available online 14 December 2013 Keywords: Graduate students Socio-cultural Creativity Social capital

a b s t r a c t Drawing on socio-cultural theory, this paper investigates the effects of different sources of social capital on student creativity. A sample of 216 graduate students from a leading Chinese research university were surveyed regarding their social capital and creativity. Our results indicated that the peer, advisor, and expert social capital of graduate students can independently and interactively influence their creativity. Specifically, the three sources of social capital can positively affect creativity. In addition, peer and advisor social capital had a significant joint effect on creativity. However, peer and expert social capital had a negative interactive effect on creativity. The theoretical and practical implications of these findings are discussed in this paper. Crown Copyright © 2013 Published by Elsevier Ltd. All rights reserved.

1. Introduction Creativity is a popular topic among practitioners, and has entered discourse on higher education (Chan & Ngok, 2011; Reza & Reza, 2011; Yeh, Yeh, & Chen, 2012). Creativity is the ability to develop novel and potentially useful ideas (Shalley, Zhou, & Oldham, 2004; Zhou & George, 2001). It has been recognized as a beneficial factor for a society such as China, which continually requires innovation to survive and prosper (Chan & Ngok, 2011; Cropley & Cropley, 2009). Thus, studies on higher education indicate that “it is essential for students to cultivate creativity in an increasingly competitive contemporary society” (Davis, 2008, p. 223). Consequently, enhancing student creativity is currently regarded as the priority aim of higher education institutions (Reza & Reza, 2011) because they are responsible for educating, instructing, and generating knowledge (Celik, 2013). However, an increasing number of administrators and scholars have realized that the higher education system must do more to encourage the development of student creativity (Cropley & Cropley, 2009; Pil & Leana, 2009; Wu & Albanese, 2010). Such realization has prompted calls from numerous scholars for more research into ways to help boost student creativity in higher education contexts (Chan & Ngok, 2011; McWilliam, 2009). In the existing literature, scholars increasingly realize that socio-cultural origin is becoming critical for creativity development, especially student creativity (Amabile, 1996; Barron & Harrington, 1981; Eteläpelto & Lahti, 2008; Rojas-Drummond, Albarrán, & Littleton, 2008; Sternberg & Lubart, 1996). According to the socio-cultural theory, which emerged from the work of psychologist Lev Vygotsky, social interaction plays a fundamental role in individual development (Vygotsky, 1978b). This theory describes human learning as a social process (John-Steiner & Mahn, 1996; Sawyer, 2002). In this view, some scholars indicate that social interaction, which provides access to new knowledge and information (Tsai & Ghoshal, 1998), is essential

∗ Corresponding author at: School of Management, University of Science and Technology of China, No. 96, JinZhai Road, Baohe District, Hefei, Anhui 230026, PR China. E-mail addresses: [email protected] (J. Gu), [email protected] (Y. Zhang), [email protected] (H. Liu). 1871-1871/$ – see front matter. Crown Copyright © 2013 Published by Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tsc.2013.12.001

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and fundamental for creativity development (Gl˘aveanu, 2010). Rojas-Drummond et al. (2008), for example, posit that creativity development is “achieved through dialog and that education is enacted through the interactions between students and teachers reflecting the historical development, cultural values and social practices of the societies and communities in which educational institutions exist” (p. 178). Accordingly, social capital, which reflects important socio-cultural resources of the respective communities, has been proposed as the essential socio-cultural factor for creativity (Reagans & McEvily, 2003). Social capital refers to “the sum of the actual and potential resources embedded within, and derived from the network of relationships possessed by an individual or social unit” (Nahapiet & Ghoshal, 1998, p. 243). Scholars have argued that social capital helps people acquire, allocate, and utilize resources to develop personal competence (Nahapiet & Ghoshal, 1998). This premise indicates that establishing close relationships with key field professionals could help students achieve critical resources and expertise, which is important for fostering their creativity (Davies et al., 2013; Pascarella & Terenzini, 2005). However, few studies have empirically investigated the role of social capital, especially its sources, in fostering student creativity in higher education (McWilliam, 2009; Wei, 2012). This research is an effort to address the above mentioned shortcoming. We aim to investigate how various sources of social capital affect the development of student creativity in China according to socio-cultural theory. In China, research network of graduate students normally involves peers, advisors, and external experts, who are the key sources of social capital for graduate students (Bienkowska & Klofsten, 2012; Reza & Reza, 2011). Thus, we label the sources of graduate students’ social capital as (a) peer social capital; (b) advisor social capital; and (c) expert social capital, respectively. Peer social capital is developed based on connections with classmates or research team members, whereas advisor social capital reflects the nature of the relationship between students and their supervisor (Bienkowska & Klofsten, 2012). Expert social capital originates from student ties with experts who are outside of the organization (Hansen, 1999). Accordingly, we argue that the different sources of social capital play different roles, both independently and interactively, in affecting student creativity. The present study is distinct from previous research in several aspects. First, this study applied socio-cultural theory to examine how socio-cultural origins (namely, social capital sources) affect the development of the creativity of graduate students. The findings help extend the application of socio-cultural theory in general and social capital in particular in higher education. Second, this study facilitates a more detailed understanding of the influence of social capital on creativity because it examines the nuances of different sources of social capital and their effects on student creativity. The study investigates not only the independent effects of various sources of social capital but also their interactive influences on creativity. Finally, this study empirically examines how various sources of social capital would affect the development of student creativity in the emerging economy of China. Complementing prior research on social capital that was primarily conducted in mature economies, this work empirically assesses the role of social capital to explain the development of student creativity in China. 2. Theoretical background 2.1. Graduate student creativity in the higher education sector in China The creativity of graduate students reflects their ability to generate novel and potentially useful ideas concerning products, procedures, and processes (McWilliam, 2009; Zhou & George, 2001). For higher education today, especially in China, cultivating the creativity of graduate students is becoming the critical quality evaluation standard. The higher education sector in China is experiencing rapid expansion (Chan & Ngok, 2011) and has become the largest in the world (Zhou, 2009). The total enrollment in higher education has increased nearly fourfold in six years, from 3.6 million in 1998 to 14.2 million in 2004 (Zha, 2009). Graduate student enrollment has reached approximately 540,000 in 2010, which is 2.26 times that in 2001. These graduate students have significantly contributed to innovation and economic development in China. For instance, they have participated in more than 58% of scientific research projects in China (Zhou, 2010). A study reported that 70% of graduate students, advisors, and college administrators in China consider student creativity as a key measure of the quality of graduate education (Zhou, 2010). Nevertheless, through headlines such as “Chinese students lack creativity” and “Chinese people need to be more creative,” the Chinese media and academic journals continue to portray the Chinese as lacking in creativity or as needing to be more creative (Wu & Albanese, 2010), which implies that Chinese higher educational institutions must do more to promote the innovation and creativity of graduate students. In the existing literature, scholars indicate that socio-cultural factors can function as critical predictors of graduate student creativity (Westwood & Low, 2003). The literature contends that interaction between students as well as between students and faculty members functions as one of the key university experiences associated with student development, including enhancing creativity (Pascarella & Terenzini, 2005). In China, the government and higher education institutions have realized the importance of socio-cultural factors in creativity development and have substantially invested resources and effort in improving research cooperation to enhance graduate student creativity. For instance, the government has promoted the “Project of Innovation in Postgraduate Education” to help graduate students enhance their creativity through participation in research teams or the research innovation process (Ministry of Education, 2005). However, the effect of these projects is limited and difficult to investigate because of the lack of a specific theoretical direction. Although several studies have explored how socio-cultural factors influence creativity, they were primarily conducted in the context of mature market economies (Rudowicz, Tokarz, & Beauvale, 2009). Insights from these studies may not be directly applicable in the context of China because of different economic, cultural, and political contexts. Hence, scholars propose that understanding the

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effects of special sociopolitical factors, such as social capital, on graduate student creativity in China is critical and necessary (Eteläpelto & Lahti, 2008; Pluut & Curs¸eu, 2013; Wu & Albanese, 2010). 2.2. Socio-cultural theory and social capital Vygotsky’s socio-cultural theory has been widely cited by educators and scholars to explore and understand individual development (John-Steiner & Mahn, 1996; Matusov, 1998). This theory proposes that learning is embedded in interpersonal connections and the socio-cultural context in which people interact with shared experiences (Rogoff, 1998). According to Vygotsky, giving students access to new ideas and concepts, which operate above their current knowledge level, is especially important for them to form new ideas (Vygotsky, 1978a). Accordingly, scholars posit that creativity is achieved through dialog and that education is enacted through the interactions between students and teachers that represent educational institutions (Fischer, Giaccardi, Eden, Sugimoto, & Ye, 2005). Prior research further suggests that social network-related factors, (such as advisor support, development feedback, social interactions, team learning, cooperation, and research team characteristics), might contribute to the creativity of an individual (Maulana, Opdenakker, den Brok, & Bosker, 2011; Zhou and George. 2001). In this view, scholars propose that higher education institutions such as universities should help students develop creativity by providing a supportive or resourceful environment in the special socio-cultural context. Interacting with network members, such as peers, advisors, and experts, allows a student to obtain valuable information regarding opportunities, which is important for developing innovative ideas (Tsai & Ghoshal, 1998; Yeh et al., 2012). In the existing literature, scholars have proposed social capital as the representative socio-cultural factor based on sociocultural theory. Coleman (1988) argued that social capital reflects a set of socio-cultural resources inherent in a social network, which includes both interpersonal relationships and the resources embedded within, and accessed through, social relationships. In this view, social capital has been widely applied in research on performance, innovation, creativity, knowledge sharing, value creation, and career satisfaction (Chow & Chan, 2008; Pil & Leana, 2009; Tsai & Ghoshal, 1998). The literature postulates that social capital enables individuals to obtain information, resources, and opportunities by activating their social networks (Chow & Chan, 2008; Davies et al., 2013). In addition, high-quality social networks enable individuals to receive psychosocial and work-related support from coworkers (Nahapiet & Ghoshal, 1998). In the context of creativity, organization and management scholars have proposed factors related to social capital, such as a central position in the network, a broader source of knowledge, and trust, as critical factors for creativity (Hansen, 1999; Reagans & McEvily, 2003; Tsai, 2001). Subramaniam and Youndt (2005) indicated that social capital is essential for innovation. Similarly, education researchers have increasingly directed their attention to addressing the role of social capital in the development of students’ creativity. Eggens, van der Werf, and Bosker (2008) suggested that the academic attainment of students might be affected by the quality and quantity of their personal networks and social support. Furthermore, Bienkowska and Klofsten (2012) argued that Ph.D. students might improve their academic entrepreneurship if they build social networks. Although these scholars have recognized the role of social capital in creativity, others have called for more empirical studies to better specify and establish the relationships between key antecedents and the outcomes of social capital in the context of higher education, especially in emerging economies (McWilliam, 2009). The existing literature has identified advisors, peers, and external experts as the primary sources of social capital for graduate students. For example, Heath (2002) contended that a graduate student could develop creativity through a good connection with his or her advisor, who is a critical source of expertise, support, and encouragement. Such a relationship enables advisor to frequently and freely share ideas with his or her student. Brooks and Ammons (2003) suggested that by engaging in discussions with peers such as friends, classmates, and team-mates, a graduate student could exchange and assimilate new ideas, which is important for creativity. Furthermore, in the current state of higher education, graduate students are increasingly engaged in external collaborations (Bienkowska & Klofsten, 2012). Under this condition, external experts who are outside the university become important members of the social networks of graduate students (SalminenKarlsson & Wallgren, 2008). In this study, we propose that these three sources of social capital could differentially affect the creativity of graduate students by providing different types of advice, knowledge, and resources. The overarching rationale for our framework is that these different sources of social capital (peer, advisor, and expert) exert varying influences on graduate student creativity. Thus, documenting the independent and interactive effects of these sources of social capital on student creativity in the context of an emerging economy, such as China, would constitute an important contribution to the literature. 3. Conceptual framework and hypotheses development Based on the socio-cultural theory, this study aims to investigate how three sources of social capital, namely, peer, advisor, and external expert social capital, independently and interactively influence the creativity of Chinese graduate students. The following sections present the detailed hypotheses related to these relationships. 3.1. Social capital sources and creativity 3.1.1. Peer social capital and creativity Peer social capital originates from the good relationships of students with peers such as friends, classmates, and teammates. Graduate students normally have a large group of peers who have a variety of knowledge and skills. Eggens et al.

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(2008) suggested that developing a close and stable relationship with these peers would help students obtain information and knowledge or receive help and advice from a broader network of colleagues. Furthermore, high peer social capital indicates a high level of trust and obligation between students and their peers. Trust has been defined as “the extent to which a person is confident in, and willing to act on the basis of, the words, actions and decisions of another” (McAllister, 1995, p. 25). In this view, Moran (2005) revealed that trust enables peoples to acquire and exchange knowledge. It also encourages them to freely challenge each other’s ideas without having to worry about committing mistakes. In this view, Aquino and Serva (2005) argued that the obligations of students to their peers demonstrate their high work motivation, which is conducive to the formation of creative thinking. In addition, students and their peers typically confront the same situations or engage in similar research. Chow and Chan (2008) noted that students and their peers share goals. Thus, they could have better mutual understanding, share knowledge and experiences, and provide emotional support for each other, which might increase the intrinsic motivation of students to be more creative. Specifically, shared goals could promote greater cooperation and reduce potential conflicts and misunderstandings with peers, which accelerate the process of knowledge and skill acquisition. With shared goals, students and peers encourage each other to address common challenges and focus on achieving the desired goals of producing significant intellectual contributions, which enables them to complete a degree successfully. Hypothesis 1a.

The peer social capital of graduate students is positively related to their creativity.

3.1.2. Advisor social capital and creativity Advisor social capital enables graduate students to formulate a good work model with clear planning and feedback (McWilliam, 2009), which is critical for fostering their creativity. Specifically, an advisor who has extensive research experience could help students identify research directions and solve research problems (Maulana et al., 2011). For instance, Pascarella and Terenzini (2005) suggested that advisors can use their position, reputation, and networks to provide assistance, such as research funding and laboratory support, to graduate students. In an empirical investigation of 355 Ph.D. candidates at the University of Queensland, Heath (2002) indicated that when advisors gave more instructions to their students, the students would gain more benefits. According to scholars, building a coherent network connection with their advisors enables students to obtain more tutorial guidance and professional advice (Whitelock, Faulkner, & Miell, 2008). The literature argued that when students trust their advisors, they share ideas with the latter without any hesitation, which could ensure efficient exchange of information and knowledge (Tschannen-Moran, 2001). According to Hughes, Luo, Kwok, and Loyd (2008), trust can make students confident in the knowledge bases, suggestions, and authority of advisors. Thus, students follow the suggestions of their advisors actively, which maximizes the use of the latter’s expertise and stimulates original thinking skills. Several scholars likewise argued that a sense of obligation may boost the creativity of students by serving as role models in the development and implementation of innovations (Perry-Smith & Shalley, 2003; Tierney & Farmer, 2002). Advisors could help clarify future challenges, point out opportunities through innovation, and motivate students by envisioning an attractive future (Amabile, 1996). The shared language and goals between students and advisors provide the kinds of cognitive social capital that enable them to easily communicate with and understand each other (Heath, 2002). Shared language can help students use professional language to effectively exchange knowledge and ideas with the advisor and avoid potential misunderstandings (Eteläpelto & Lahti, 2008). For instance, Leana and Pil (2006) indicated that shared goals increase student achievement. Shared goals also help students generate awareness of self-reinforcement, promote original thinking, and create practical results (Kim & Sax, 2009; Pil & Leana, 2009). Hypothesis 1b.

The advisor social capital of graduate students is positively related to their creativity.

3.1.3. Expert social capital and creativity External experts who come from different organizations are useful sources of new knowledge (Salminen-Karlsson & Wallgren, 2008). Reilly (2008) suggested that external experts normally have diverse knowledge in their areas, which can help students overcome their lack of knowledge in such areas. Connecting with these experts allows students to gain access to extra information, expertise, and ideas, which are not easily available from their internal network of peers and advisors (Protivnak & Foss, 2009). Through formal or informal interactions, experts could contribute new and diverse knowledge to students, which could help them improve their existing knowledge structures and thinking modes (Pyhältö, Vekkaila, & Keskinen, 2012). Subsequently, such improvements help them develop existing ideas or generate new ones. Trust between students and experts boosts the confidence of students in their abilities, which enables them to assimilate and apply new knowledge that they obtained from experts and enhances their innovation and creativity (Bidault & Castello, 2009). Specifically, such trust makes students more inclined to interact with trusted external experts (Eggens et al., 2008), which further enables them to be more willing to communicate their ideas and opinions with experts. Hansen, Mors, and Løvås (2005) argued that interactions with experts further improve students’ depth and breadth of knowledge, which enables them to communicate more effectively with experts in a specific research. Thus, expert social capital enriches the expertise of students, enhances their creative thinking, and motivates them to boost their creativity. Hypothesis 1c.

The expert social capital of graduate students is positively related to their creativity.

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3.2. Interactive effects between different sources of social capital on creativity Although each source of social capital independently improves creativity, the existing literature indicates that these sources may also interdependently operate to some degree (Eggens et al., 2008). For instance, McWilliam (2009) suggested that different sources of social capital allow an individual to achieve varying and complementary resources and knowledge, which might enhance a student’s innovation through shared and complementary resources and knowledge. Thus, we argue that when different sources of social capital exist, these sources would generally operate interactively, such that when all three sources of social capital are high/low, we would expect to see the highest/lowest creativity. 3.2.1. Interactive effects between peer and advisor social capital We propose that peer and advisor social capital would have positive interactive effects on creativity. Specifically, peer social capital is epitomized in how the exchange of ideas among peers with diverse knowledge backgrounds is facilitated (Pluut & Curs¸eu, 2013). Frequent exchanges would help students generate new ideas (Cummings, 2004), that is, peer social capital might enhance the capacity of students to explore new ideas and ask interesting research questions. In contrast, Hansen et al. (2005) suggested that advisor social capital allows students to obtain the kind of advice and help that enables them to more efficiently and effectively address any problems or challenges encountered during the research process, that is, advisor social capital might enhance the ability of students to exploit and utilize knowledge as well as refine available ideas related to the research at hand. Davies et al. (2013) argued that advice and assistance enable students to set appropriate and realistic research goals, analyze problems, and develop ideas effectively. Thus, students who have a high level of advisor social capital could easily discuss with their advisors the ideas that they obtained from their peers and then receive professional advice that would help them efficiently and effectively conduct creative research. Conversely, similar to a student with high advisor social capital, the student with high peer social capital might be in a better position to discuss ideas with and obtain new opinions from peers. Thus, the combined effect of high peer and advisor social capital would be expected to boost the research creativity of students. Hypothesis 2a. The peer and advisor social capital of graduate students may interactively influence their creativity, such that a higher peer social capital results in a stronger influence of advisor social capital on their creativity. 3.2.2. Interactive effects between peer and expert social capital We expect that peer social capital could augment the role of expert social capital in increasing knowledge exchange, thereby strengthening the influence of expert social capital on creativity. The literature has indicated that through external network connections, people are able to gain access to new information, expertise, and ideas that are unavailable in their existing organization (Perry-Smith & Shalley, 2003). Communicating with experts could help students strengthen the richness of shared knowledge, whereas communicating with peers may help them extend the reach of knowledge. In particular, experts could help students gain professional knowledge, which would extend the existing knowledge structures of students, thereby facilitating the development of existing ideas or the generation of new ones (Bienkowska & Klofsten, 2012; Pascarella & Terenzini, 2005). Cummings (2004) argued that students with expert social capital are more likely to encounter unique and new knowledge that has not been previously shared within the group. Most expertise knowledge is tacit and highly embedded (Wei, Zheng, & Zhang 2011). Thus, assimilating and applying such knowledge would considerably challenge students. Under this condition, high peer social capital would enable students to easily discuss the shared expertise knowledge with their peers. The discussion would help students understand unique knowledge via different perspectives (Ford & Randolph, 1992) and apply such knowledge to effectively improve their creative projects. Thus, the students with both high expert and peer social capital would be exposed to novel ideas and perspectives that might contribute to their own creative ideas. Hypothesis 2b. The peer and expert social capital of graduate students may interactively influence their creativity, such that a higher peer social capital results in a stronger influence of expert social capital on their creativity. 3.2.3. Interactive effects between advisor and expert social capital Generally, students with both advisor and expert social capital could simultaneously acquire specialized knowledge and advice within and outside an organization. In China, most external experts are collaborators of advisors. The advisors provide students with the opportunity to exchange ideas and knowledge with external experts. This arrangement indicates that when students have high advisor social capital, they could easily apply expert social capital with the help of their advisors. Hansen et al. (2005) suggested that advisors could provide students with basic knowledge and resources to develop ideas. Reilly (2008) noted that an expert would provide additional “raw materials,” such as different perspectives and additional research opportunities, to develop and refine ideas. When students have high advisor social capital, they could combine these resources and obtain help from advisors to translate these resources into actual creativity (Salminen-Karlsson & Wallgren, 2008). Such attributes further facilitate the role of expert social capital in promoting student creativity. Moreover, research involves a high degree of difficulty and challenge. Students with high advisor social capital would have a strong incentive to overcome difficulties to complete research tasks. This premise implies that students would be more likely to use expert social capital to overcome their knowledge limitations and expand their scope for creative and critical thinking. Thus, we expect that advisor and expert social capital will jointly boost student creativity.

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Hypothesis 2c. The advisor and expert social capital of graduate students may interactively influence their creativity, such that a higher expert social capital results in a stronger influence of advisor social capital on their creativity.

4. Method 4.1. Participants We conducted a field study among graduate students from a leading research university in China to test our hypotheses. Samples were selected from master and Ph.D. students majoring in physics, chemistry, and biology. In China, scholars have argued that graduate students from these fields have similar academic backgrounds and are reasonably heterogeneous because they have unique individual traits and different creativity levels (Gu, Lin, Vogel, & Tian, 2011). With the assistance of the graduate manager from the Academic Affairs Office of the university, 260 students were randomly selected to participate in a questionnaire survey. Questionnaires were then delivered to the students. The cover letter introduced the aim of the survey and provided instructions for completing the survey. Respondents were assured that participation was voluntary and that the data collected would be kept confidential and used for academic research only. We received usable survey responses from 243 students, which indicates a response rate of 93%. Of the 243 returned questionnaires, 27 incomplete or unusable questionnaires were eliminated, which resulted in 216 useful questionnaires for data analysis. Of the remaining samples of respondents, 70.8% were male, and 84.7% were between 23 and 28 years old. Ph.D. students accounted for 60.6% of the total number of respondents.

4.2. Instruments We initially developed an English questionnaire based on previously validated measures. All items were measured by using a five-point Likert scale with anchors ranging from “strongly agree” to “strongly disagree.” All respondents were native speakers of Mandarin Chinese; thus, we translated the questionnaire into Chinese based on the translation committee approach. Specifically, the original English questionnaire was translated into Chinese through a committee that included two scholars. These scholars, who are from the area of higher education and innovation, are fluent in English and have published papers in international academic journals. We asked them to help us independently translate the English measures, and then discussed their translation item by item to achieve a consensus. We also invited three scholars and three graduate students to review the translated questionnaire, thus ensuring the face and content validity. The questionnaire was revised based on their comments. Finally, we selected 10 graduate students from potential respondents to participate in the pilot test. To ascertain that the respondents understood the constructs and accurately interpreted the questions, we spent at least one hour with each respondent to discuss every item. Based on their feedback, we reworded several questions to provide greater clarity and enhance comprehension. Finally, the questionnaire was back-translated by two independent translators to ensure equivalence of measure and meaning (Brislin, 1970).

4.2.1. Independent variables We selected peer social capital, advisor social capital, and expert social capital as independent variables in our model. We operationalized social capital as a second-order construct, which includes the dimensions of structural, relational, and cognitive capital, as most social capital studies suggest (Chiu, Hsu, & Wang, 2006; Tsai & Ghoshal, 1998). In the current study, three sources of social capital were separately measured based on the three dimensions. We defined structural capital as the overall pattern of network structures that an individual can reach (Nahapiet & Ghoshal, 1998). We then adopted Chiu et al.’s (2006) four-item scale of network connection to measure structural capital. Sample items for peer social capital include “I maintain close social relationships with peers” and “I know some peers on a personal level.” Relational capital describes the nature of a relationship in aspects such as trust and obligations (Nahapiet & Ghoshal, 1998). We adopted Chow and Chan’s (2008) three-item scale to measure trust. Sample items for advisor social capital include “I can always trust my advisor to lend me a hand if I need it” and “I can always rely on my advisor to make my job easier.” Obligation was measured based on Aquino and Serva’s (2005) two-item scale, which includes “I felt obligated to go beyond the project’s expectations because that is what I did” and “I felt obligated to work harder whenever my advisor exceeded expectations.” Cognitive capital is created when members of a network develop a shared meaning and understanding, such as shared language and goals (Nahapiet & Ghoshal, 1998). We adopted Chiu et al.’s (2006) three-item scale to measure shared language. Sample items for expert social capital include “Experts and I use common terms or jargon” and “Experts and I use understandable narrative forms to post messages.” Shared goal was measured by using Chow and Chan’s (2008) three-item scale. Sample items include “Experts and I always share the same ambitions and vision at work” and “Experts and I are always enthusiastic about pursing collective goals and missions.” As Table 1 shows, principal component analysis clearly indicates that all the scales are reliable; peer, advisor, and expert social capital have a Cronbach’s alpha of 0.889, 0.916, and 0.970, respectively.

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Table 1 Measurement of constructs. Constructs

Dimensions

Items

Cronbach’s alpha

Loading standard

Composite reliability

AVE

Peer social capital (Cronbach’s alpha = 0.889; composite reliability = 0.847; AVE = 0.581)

Peer network Peer trust Peer obligation Peer-shared goal Advisor network Advisor trust Advisor obligation Advisor-shared language Advisor-shared goal Expert network Expert trust Expert obligation Expert-shared language Expert-shared goal

4 3 2 3 4 3 2 3 3 4 3 2 3 3 13

0.854 0.738 0.601 0.826 0.888 0.799 0.701 0.722 0.811 0.954 0.940 0.931 0.930 0.929 0.922

0.768–0.875 0.736–0.863 0.802–0.889 0.806–0.896 0.851–0.883 0.818–0.876 0.964–0.970 0.663–0.875 0.794–0.889 0.929–0.950 0.937–0.952 0.946–0.970 0.923–0.950 0.924–0.945 0.582–0.785

0.901 0.852 0.835 0.897 0.922 0.881 0.967 0.835 0.888 0.967 0.960, 0.967 0.955 0.955 0.933

0.695 0.658 0.717 0.744 0.748 0.711 0.935 0.631 0.725 0.879 0.889 0.935 0.876 0.876 0.517

Advisor social capital; Cronbach’s alpha = 0.916; composite reliability = 0.868; AVE = 0.575)

Expert social capital; Cronbach’s alpha = 0.970; composite reliability = 0.913; AVE = 0.679)

Creativity Table 2 Means, standard deviations, and correlations.a Variable

Mean

s.d.

1

2

3

4

1.Creativity 2.Peer social capital 3.Advisor social capital 4.Expert social capital

3.84 3.90 3.82 3.09

0.51 0.52 0.55 0.85

0.719 0.51** 0.52** 0.44**

0.762 0.68** 0.46**

0.758 0.53**

0.824

a **

N = 216, variables 1, 2, 3,and 4 were measured on five-point scales. The diagonal elements are the square roots of AVEs. p < 0.01.

4.2.2. Dependent variable The dependent variable, creativity, was measured by using a 13-item scale adapted from Zhou and George (2001). Among the sample items are “Comes up with new and practical ideas to improve performance” and “Comes up with creative solutions to problems.” This scale has high reliability, with Cronbach’s alpha of 0.922. 5. Data analysis and results 5.1. Common method bias, reliability, and validity All data were perceptual and collected from a single source at the same time. Thus, we realized that common method bias might threaten the validity of our research. To test this possible bias, we used the Harman’s one-factor test on the questionnaire measurement items (Podsakoff & Organ, 1986). The principal component factor analysis yielded nine factors with eigenvalues greater than 1.0 and accounted for 68.68% of the variance. Meanwhile, the first factor of these nine factors did not account for the majority of the variance (only 19.10%). All these results indicated that common method bias was unlikely to be a serious concern in our study. To ensure the validity of our measurement, we examined the reliability and validity of all constructs. Specifically, we tested the reliability of the measurement by using composite reliability and the value of Cronbach’s alpha. The values of the composite reliability presented in Table 1 range from 0.835 to 0.967, which are all greater than 0.70; the values of Cronbach’s alpha range from 0.601 to 0.954, which are all greater than 0.60 (Fornell & Larcker, 1981). We then tested the convergent validity and discriminant validity of the measures. We assessed convergent validity based on item loading and average variance extracted (AVE). As shown in Table 1, the loadings varied from 0.582 to 0.970 at a significance level of 0.001. The AVE scores for constructs ranged from 0.517 to 0.935, which were above the recommended benchmark of 0.500 (Fornell & Larcker, 1981). The results indicated that all measurement items had an adequately high convergent validity. We assessed the discriminant validity by comparing correlations among constructs and the square roots of AVEs. As Table 2 shows, the square roots of AVEs for each construct were greater than the correlations between constructs, which confirmed the discriminant validity. 5.2. Regression analysis Table 3 presents the results of a hierarchical regression analysis. We mean-centered the independent variables to minimize the effects of multicollinearity. As Model 3 indicates, peer social capital (ˇ = 0.211, p < 0.05), advisor social capital (ˇ = 0.310, p < 0.01), and expert social capital (ˇ = 0.174, p < 0.05) are all significantly related to creativity, thereby providing support for Hypotheses 1a, 1b, and 1c. We further followed the approach adopted by Chin, Marcolin, and Newsted (2003) and

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Table 3 Results of regression analyses with social capital on creativity.a Predictor Step1 Gender Age Educational level Major Step2 Peer social capital Advisor social capital Expert social capital Step3 Advisor social capital * Peer social capital Expert social capital * Peer social capital Expert social capital * Advisor social capital R2 R2 F F a * ** ***

Model 1

Model 2

Model 3

VIF

−0.174* −0.015 −0.029 0.380

−0.097 0.069 0.067 0.029

−0.101 0.076 0.052 0.016

1.081 1.807 1.678 1.058

0.239** 0.266** 0.168*

0.211* 0.310*** 0.174* 0.206** −0.175* 0.114

0.012 0.032 1.631 1.631

0.327 0.318 15.067*** 31.967***

2.439 2.631 1.556 1.652 2.115 2.067

0.361 0.042 12.448*** 4.469*

N = 216. Standardized regression coefficients are shown. p < 0.05. p < 0.01. p < 0.001.

Fig. 1. Hypothesized peer social capital and advisor social capital interaction plot.

Pavlou and Dimoka (2006) to test the factors that are more important to creativity. The path coefficients were compared by using Chin’s (2003) equation, which is an adaptation of the traditional t-test for comparing regression coefficients between samples. The results indicated that advisor social capital has the strongest impact on creativity compared with peer social capital (t = 3.360) and expert social capital (t = 12.930). The impact of peer social capital on creativity is stronger than that of expert social capital (t = 9.562). Table 3 further shows that the interaction term between peer and advisor social capital has a significant, positive relationship with creativity (ˇ = 0.206, p < 0.01), which supports Hypothesis 2a. However, the results show that the interactive effect of peer and expert social capital on creativity is negative and significant (ˇ = −0.175, p < 0.05), which is contrary to Hypothesis 2b. The joint effect of advisor and expert social capital on creativity is not significant, which did not support Hypothesis 2c. Figs. 1 and 2 illustrate the plot of the interaction effect. Table 4 summarizes the results on the hypotheses and shows whether the hypotheses were supported. 6. Discussion The findings of this study strongly support the premise that different sources of social capital could independently and interactively influence the creativity of graduate students. We found that social capital positively influenced the creativity of graduate students. Thus, social capital from peers, advisors, and experts seemed to help graduate students by enabling them to accumulate knowledge and information as well as by triggering original ideas and creative thinking, which consequently augments the incremental creativity of graduate students. We also compared the relative importance of the three sources of social capital for creativity. The findings provide a deeper understanding of the role of each source of social capital with respect to the creativity of graduate students.

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Fig. 2. Hypothesized peer social capital and expert social capital interaction plot.

Table 4 Results of hypothesis testing.

H1a H1b H1c H2a

H2b

H2c

Hypothesis

Results

The peer social capital of graduate students is positively related to their creativity The advisor social capital of graduate students is positively related to their creativity The expert social capital of graduate students is positively related to their creativity The peer and advisor social capital of graduate students may interactively influence their creativity, such that a higher peer social capital results in a stronger influence of advisor social capital on their creativity The peer and expert social capital of graduate students may interactively influence their creativity, such that a higher peer social capital results in a stronger influence of expert social capital on their creativity The advisor and expert social capital of graduate students may interactively influence their creativity, such that a higher expert social capital results in a stronger influence of advisor social capital on their creativity

Supported (ˇ = 0.211, p < 0.05) Supported (ˇ = 0.310, p < 0.01) Supported (ˇ = 0.174, p < 0.05) Supported (ˇ = 0.206, p < 0.01)

Not supported (ˇ = −0.175, p < 0.05)

Not supported (ˇ = 0.114, n.s.)

The interactive term of peer and advisor social capital could significantly impact creativity. Advisor social capital strengthened the positive effects of peer social capital on student creativity. Graduate students with high peer and advisor social capital generally tend to have greater creativity. The interaction of peer and expert social capital negatively influences creativity, which is contrary to our expectations. This result is intriguing because it suggests that the high peer social capital of graduate students would adversely affect the relationship between expert social capital and creativity. Fig. 2 illustrates that the expert social capital of graduate students could significantly impact their creativity only when they have low peer social capital. The large power distance that characterizes Chinese culture may explain this finding. Chinese cultural exerts enormous pressure on most graduate students when they communicate with external experts; thus, these students view such communication as a challenge (Rudowicz et al., 2009; Ryan, Kang, Mitchell, & Erickson, 2009). Under this condition, these students would more likely communicate with their peers rather than with experts. Convenience may be another reason. Expert social capital typically stems from experts who come from other organizations. Most graduate students find communicating with experts difficult, especially through face-to-face discussions. Long-distance communication normally involves high cost and time requirements (Cummings & Teng, 2003), whereas communicating with peers is easier and more convenient. Graduate students would be more inclined to engage in discussions with peers when they have high peer social capital, which may limit the role of expert social capital in developing their creativity. Graduate students would attempt to seek any other source of knowledge to improve their creativity when they have low peer social capital. Expert social capital would then become the critical source that can help them develop creativity, even if they have to deal with cultural and communication challenges. This situation would highlight the role of expert social capital in developing creativity. 7. Theoretical and practical implications This study has several implications that not only enhance and refine the conceptualizations of the social capital–creativity link, but also offer useful and specific guidelines for management practices. First, the study identifies specific socio-cultural origins, that is, the sources of social capital for the creativity of graduate students in China. This implication extends existing socio-cultural theory and social capital literature. Categorizing social capital into peer, advisor, and expert social capital allows our study to contribute to a more systematic and integrative knowledge compared with previous research, which

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focused on the generic concept of social capital. This study extends the current understanding of social capital in the context of higher education in China and responds to the call for further exploration of the various roles of different sources of social capital, which generate behavioral outcomes such as creativity (Woolcock & Narayan, 2000). Furthermore, although the current study provides only a snapshot of social capital in China, its findings extend the understanding of the role of social capital in different social, political, and economic contexts. Second, our study offers strong evidence that the interaction between the different sources of social capital is worth investigating. Our findings support the interactive effects of peer, advisor, and expert social capital on creativity. A limited number of studies have provided insights into how the different sources of social capital affect personal ability. This study demonstrates the different impacts of peer social capital on the relationship between advisor and expert social capital and creativity. For instance, peer social capital strengthens the effects of advisor social capital but weakens the influences of expert social capital on creativity. This study also suggests to policymakers and practitioners that the complicated relationship between the social capital of graduate students and creativity should be examined more carefully. The study indicates that the creativity of graduate students could be enhanced by their social capital sources, especially in China. This finding implies that policymakers, including government officials and university administrators, should develop efficient and targeted policies to help graduate students develop their social capital. For instance, policymakers could establish a number of rules and mechanisms to ensure that graduate students can frequently and efficiently communicate with their supervisors. Policymakers could also provide support for research workshops, seminars, and conferences as well as encourage students to attend and actively participate in these fora. Our findings identify the interaction between the different sources of social capital and suggest that advisors should realize that aside from the supervisor, other members of the social network of graduate students are important for their creativity. The supervisor should encourage graduate students to communicate with their peers effectively and extensively. Graduate students should likewise be cautious in combining peer and expert social capital to improve their creativity; our study indicates that such a combination may negatively affect the development of their creativity.

8. Limitations and directions for future research This study has several limitations that could be addressed in future research. First, we collected data by using a single source at the same time, which may cause common method bias (Podsakoff & Organ, 1986) and the lack of data triangulation. Although our test has indicated that common method bias was not a serious problem in this study, we still recommend the use of a longitudinal design in future research to reduce the common method bias (Podsakoff & Organ, 1986). Furthermore, we recommend that future researchers use multiple sources of data for measuring social capital and creativity. Multiple data sources not only help limit common method bias, but also address the lack of data triangulation. For instance, social capital could be measured from both sides of a relationship, such as that of the advisor and graduate students. Investigating the advisor helps provide a more holistic sense of identity, and having students personally share their interpretations and opinions would be better. Second, our findings may be limited by our singular dependence on the survey. The use of multiple methods in future research is one way to address this limitation and avoid inappropriate conclusions. We suggest the combination of a survey and a case study in future research. A face-to-face interview with students and advisors can enable researchers to obtain more detailed and real-life information about social capital and creativity. Furthermore, future researchers could combine the subjective data that was collected through a survey with objective data. They can also collect information about publications and patents to present the creativity of graduate students. Finally, the demographics of the samples, such as major, gender, and age, may limit the generalizability of our findings. This study only selected graduate students from a limited range of majors as samples. Specifically, to avoid any confusion due to differences in majors, we purposely chose to examine graduate students majoring in the “hard” sciences, namely, physics, chemistry, and biology. Although these choices may help enhance the internal validity of this study within the context of these science disciplines, such choices limit the external validity and generalizability of this study across a broader range of disciplines or fields. Thus, scholars should be cautious in applying the findings to graduate students who major in other programs or belong in other fields. Meanwhile, among the respondents, most are male and are within the age range of 23–28 years. This choice may limit the generalizability of our findings across the broader population. To enhance the robustness and generalizability of findings, future research should be conducted over a longer period of time and use samples from more majors, universities, and countries as well as informants with more diverse backgrounds, genders, and ages.

Acknowledgements The work were supported by the National Natural Science Foundation of China (71371177), Anhui Provincial Natural Science Foundation (1308085MG110) and MOE (Ministry of Education in China) Project of Humanities and Social Sciences (13YJA880020). The authors thank Rupert Wegerif, Anna Craft and two anonymous reviewers for their constructive comments on this paper. We also would like to thank Augustine Lado for his helpful comments on early drafts of this paper.

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