Collaborative Green Innovation in Emerging Countries - A Social Capital Perspective [PDF]

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Collaborative green innovation in emerging countries: a social capital perspective Ping-Chuan Chen and Shiu-Wan Hung Department of Business Administration, National Central University, Jung-Li City, Taiwan Abstract



Collaborative green innovation



347 Received 11 June 2012 Revised 23 September 2012 15 December 2012 Accepted 7 March 2013



Purpose – The new paradigm for green innovation has already shifted to a collaborative model. This study aims to examine how environmental collaboration across organizational boundaries affects green innovation from the social capital perspective. Design/methodology/approach – This study used structural equation modeling method to analyze the innovation performance of 237 Taiwanese firms. Non-response bias was also assessed statistically and appropriate measures taken to minimise the impact of common method variance. Findings – The empirical results showed that: structural capital and cognitive capital have a positive influence on relational capital, relational capital plays a significant role in green management and in turn leads to greater innovation. To achieve effective green innovation, companies should leverage their social capital in order to produce additional competitive advantages through environmental collaboration. Originality/value – With the relative scarcity of resources and the increased pressures for environmental sustainability, there is an increasing interest in studying collaborative green innovation in emerging countries. Unlike many other empirical studies, this study makes an important contribution to the literature by examining how environmental collaboration in emerging countries affects green innovation from the social capital perspective in a detailed manner. Keywords Collaboration, New product development, Knowledge management, Environmental management, Capabilities Paper type Research paper



1. Introduction Under the trends of international green management, the competition in global industries has become more complex and uncertain. Most product and technology developments are moving towards a green-based structure. Such accounting for environmental impacts in business strategies has resulted in significant changes in the social system and competitive arena (Schiederig et al., 2012; Rao and Holt, 2005; Azzone et al., 1997; Welford, 1995). The new paradigm for green innovation has already shifted to a collaborative model (Dangelico and Pujari, 2010; Pujari, 2006). Due to the environmental collaboration’s need for more exchanges of resources, organizations should execute collaboration activities across organizational boundaries in order to acquire information, resources, and knowledge (Noci and Verganti, 1999). Therefore, how efficiently utilization of corporate innovative capacities from inter-organization activities can enhance green innovation is an important issue that organizations cannot afford to overlook. The impact of green management on innovation has recently received much attention (Zhu et al., 2011; Qi et al., 2010; Eiadat et al., 2008; Rehfeld et al., 2007;



International Journal of Operations & Production Management Vol. 34 No. 3, 2014 pp. 347-363 q Emerald Group Publishing Limited 0144-3577 DOI 10.1108/IJOPM-06-2012-0222



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Noci and Verganti, 1999; Porter and van der Linde, 1995). Companies have no choice but to implement strategies to reduce the environmental impacts of their products and services and take into account the operations of collaborators (Costantini and Mazzanti, 2012; Zhu et al., 2005; Biondi et al., 2002). The traditional view among managers concerning environmental issues is that the incorporation of environmental considerations into the improvements of operations has mainly sunk costs for companies. Strict environmental regulation raises an addition cost imposed on firms, which may reduce their competitiveness. Porter and van der Linde (1995) argued, however, that properly designed environmental standards can trigger innovation that may partially or fully offset the costs of complying with them. Ever since, various studies have examined this new concept of an environment-competitiveness relationship (Lanoie et al., 2008; Arimura et al., 2007; Popp, 2006; Brunnermeier and Cohen, 2003; Berman and Bui, 2001; Klassen, 2000). Although most studies have pointed out the trade off between environmental and industrial competitiveness, they have neglected to discuss the role of emerging countries and their impact on triggering green innovation on the global market. Given the limitation of country-specific resources, there is an increasing interest in studying collaborative green innovation in emerging countries. While companies in developed countries use innovations to command price premiums for green products and open up new market segments (Porter and van der Linde, 1995), the companies in emerging countries play important roles as major manufacturers in the international markets. As parts of supply chains, emerging countries have many opportunities, but they also face substantial environmental burdens, which may erode their global competitiveness. For example, Taiwan is a well-known electronic and information technology manufacturer. Taiwanese companies have produced many electronic products for multinational organizations and collaborated with developed countries in order to meet environmental requirements. The environmental improvements of operations, however, come at additional costs imposed on these companies. With the relative scarcity of resources and the increased pressures for environmental sustainability, how to build corporate capacities from environmental collaborations with developed countries becomes of primary concern to Taiwanese companies. Given the competitive environment faced by emerging industries, this study takes the Taiwan industry as an example to analyze how environmental collaboration with supply chain partners affects green innovation from the social capital perspective. Social capital refers to the set of social resources embedded in not only the relationships, but also interactions among the different actors and the processes derived from those relationships (Min et al., 2008; Nahapiet and Ghoshal, 1998). Companies can acquire information, resources, and knowledge (Ahuja, 2000) by combining direct or indirect interfirm network interactions with relationship development. In the context of green management, much valuable knowledge is socially embedded in the form of institutional practice. This may prevent required information from being transmitted between green partners (Tsoukas and Vladimirou, 2001; Cousins and Stanwix, 2001; Blackler, 1995). In this study, we argue that social capital may affect companies in exchanging green technological knowledge with their partners, and in turn boost an organization’s capacity for green innovation effectively. Organizations require complex green technology and knowledge from multinational organizations and developed countries by lessening the environmental burden of their products. Hence, they need to obtain external resources through environmental collaboration. These companies also



should increase access opportunities to exchange environment-related information through the interactive relationship with their partners. Previous studies have introduced the idea that social capital may contribute to a firm’s ability to create value in the form of innovations (Byosiere et al., 2010; Inkpen and Tsang, 2005; Lesser, 2000). No previous research, however, has explored social capital’s contribution to green management. In the context of green management, companies with an existing collaborative system are more adept at grasping customer’s environmental performance requirements (Simpson et al., 2007; Geffen and Rothenberg, 2000) and can rapidly obtain the required key resources. Furthermore, when partners join a common environmental project and share common interests, these established relations also may benefit the organizations. Through established relations, organizations could seek to solve new project-specific problems by sharing green technological knowledge more easily. Hence, building these valuable relational resources plays a significant role in the green management. In the following section, we discuss how social capital embedded in the environmental collaboration across organizational boundaries affects green innovation, and then we develop our hypothesis. In Section 3, we present our research methodology and results, including our data collection process, samples, and the variables in this study. Section 4 presents the empirical results obtained by using the structural equation modeling (SEM) method. We also present a further discussion of the results. In Section 5, we provide a conclusion and suggestions for future research. 2. Literature review and hypothesis development 2.1 Social capital theory Social capital refers to the set of social resources embedded in not only relationships, but also interactions among different actors and the processes derived from those relationships (Min et al., 2008; Nahapiet and Ghoshal, 1998). Social capital is the set of resources created through exchange. This type of resource is embedded in various relationships, including interpersonal and organizational networks (Bourdieu, 1986; Burt, 1992; Coleman, 1990; Nahapiet and Ghoshal, 1998). Social capital could facilitate the exchange/combination of resources in the social unit and also provide the rationale for the existence of the organization. Social capital, as it is commonly used in organization literature, refers to the quantity and quality of social relationships such as formal and informal social connections that exist in the social units. Social capital is understood in various disciplines as a fundamental factor in increasing the efficiency of information diffusion through minimizing redundancy, reducing transaction costs, and encouraging cooperative behavior thereby facilitating the development of new forms of innovative organization. Previous studies have explored at length the impact of social capital on organizational performance (Byosiere et al., 2010; Inkpen and Tsang, 2005; Lesser, 2000), but none thus far have explored social capital’s contribution to green management. In order to fill this research gap, this study investigates how social capital affects access to partners for exchanging green technological knowledge, and in turn boosts an organization’s capacity for green innovation. When implementing green management, organizations have to involve many environmental collaboration activities. Social capital could be an important channel for the exchange and integration of green knowledge. For example, when companies improve the recyclability



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of new products by choosing appropriate materials from their suppliers, they can obtain green knowledge and external resources through collaboration, accelerating enhancements to environment-related performance. This study emphasizes the idea that the stock of social capital can potentially build an interactive relationship with a company’s partners to enhance the sharing of green knowledge and also motivate partners to accelerate the reform of green management. In the context of green management, there is a complex interrelation between systemic changes in an organization’s R&D strategy and green innovation (Noci and Verganti, 1999). Organizations need to incorporate environmental considerations into their corporate strategies on product and process innovations. Hence, knowledge sharing and exchanges based on environmental requirements is a critical issue of green innovation. Under strict environmental regulations, organizations have to build their capacity for managing green knowledge. When organizations have greater social capital, it will improve their innovation performance through the process of sharing knowledge related to green management. In this study, we identify the interrelationship among the different types of social capital and examine the way in which social capital affects knowledge sharing and innovation performance related to green management. 2.2 The interrelationship among the three types of social capital This study adopts the classification of social capital proposed by Nahapiet and Ghoshal (1998) in terms of structural capital, relational capital, and cognitive capital. Structural capital refers to the overall pattern of relationships among social actors (Nahapiet and Ghoshal, 1998). Previous studies have shown that strong ties influence the level of knowledge exchange between actors (Renzl, 2008). Structural capital offers opportunities for exchanging green knowledge and resources through the structural environment mechanism. When organizations can easily obtain critical information with greater structural capital, they can rapidly understand the impact of environmental regulations on partners, and in turn improve environmental performance. Relational capital refers to the assets that are created and leveraged through relationships (Nahapiet and Ghoshal, 1998). Previous studies have indicated that greater supply chain relationships can assist companies in reducing production costs, increasing flexibility, and improving the efficiency of supply chain operation (Shi et al., 2012; Vachon and Klassen, 2006). Relational capital could possibly make partners become more willing to share knowledge and their resources. Interactive relationships based on trust and reciprocity can help inspire partners to take the initiative to exchange green knowledge. Cognitive capital refers to the resources providing shared representation, interpretations, and systems of meaning among parties (Nahapiet and Ghoshal, 1998). This kind of social capital endows partners with willingness and capacity for collective action, creating critical resources for organizations (Tsai and Ghoshal, 1998). Cognitive capital can assist partners in fully understanding each other’s considerations and enhancing green technology or knowledge combination to improve performance (Lee, 2008). Having a consistent consensus between partners contributes to achieving environmental goals that are beneficial to green knowledge exchange. Identifying the interrelationship among the three different dimensions of social capital is useful in deciding how to manage the collaborative relationships in green management. Previous studies have mentioned that relational capital evolves from the interaction between two parties (Gabarro, 1978). As members interact over time, their trust



relationships will become more concrete, and the actors become more likely to perceive each other as trustworthy. In the context of green management, companies must elicit, organize, and disseminate information and resources from their team members, customers, suppliers, and partners. The more sophisticated a company’s organizational capabilities, information management system, and managerial mechanisms regarding environmental management are, the more easily its partners can interact and exchange information and resources relating to green management with them. Thus, companies with greater structural capital have more opportunities to develop relational capital. Moreover, a trusting relationship is rooted in value congruence (Sitkin and Roth, 1993). When companies and their partners all work towards collective goals regarding green management, it encourages the development of a trusting relationship. Hence, the stock of cognitive capital with team members, customers, suppliers, and partners may contribute to the development of relational capital. In order to respond to strict environmental regulations and international environmental trends, organizations can build a higher level of relational capital through a stock of structural and cognitive capital. Therefore, we propose the following hypotheses: H1a. Structural capital is positively related to relational capital embedded in environmental collaborations. H1b. Cognitive capital is positively related to relational capital embedded in environmental collaborations. 2.3 The relationship among relational capital, knowledge sharing, and innovation Previous research has pointed out that higher levels of relational capital facilitate social exchange, communication, and cooperation among individuals, and also enhance teamwork performance (McAllister, 1995). In this study, we argue that relational capital may affect environmental collaboration. A firm’s developing inter-organizational environmental practices would involve trust, commitment, and joint goal setting among multiple supply chain members (Simpson et al., 2007). Rackaham and Ruff (1995) indicated that when two entities agree to integrate their operational modes and share common interests, it will constitute a partner relationship. Hence, existing relationships based on trust and reciprocity between suppliers help inspire partners to take the initiative to exchange knowledge. Greater relational capital with partners would facilitate the sharing of green knowledge as trusting relationships build. Therefore, we propose the following hypothesis: H2. Relational capital is positively related to knowledge sharing in environmental collaborations. Knowledge exchange aids companies in comprehending green knowledge and applying it into an organizational knowledge system (Grandori and Soda, 1995; Popper and Lipshitz, 1998). Through adequate exchange processes of green knowledge, it will assist R&D teams in identifying their requirements and facilitate the development of specific action plans for green innovation. Because green product development activities need more exchange of green knowledge, companies can enhance innovation performance through the sharing of knowledge regarding environmental requirements. Therefore, we propose the following hypothesis: H3. Knowledge sharing in environmental collaborations is positively related to innovation.



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3. Methodology and measurement 3.1 Data collection and samples The data collection in this study was conducted by distributing the survey instrument in the form of questionnaires to firms in Taiwan. The samples were randomly selected from Taiwanese manufacturing companies, which are listed in the 2010 survey of the top 1,000 enterprises by the Common Wealth Magazine. These selected samples have the end-product manufacturing, and all their clients are enterprise customers. Several steps were taken to ensure data validity and reliability by refining and rigorously pre-testing the questionnaire. Experts who have green management experiences in the manufacturing industry were interviewed to further validate whether the survey questionnaire satisfied practical developments in the first pretest stage. The questionnaire was then pre-tested by ten managers in the manufacturing industry. Survey packages were sent out to each company that had worked on a specific environmental collaboration with foreign partners. Prior to mailing the questionnaire out, we called each company to explain the objectives of our research confirm the names and job titles of the respondents. The respondents were asked to return the completed questionnaires. Questionnaires were then mailed to the respondents, who are executives and managers of manufacturing, R&D, or environmental protection departments of these manufacturing companies that have contact experiences with their suppliers or enterprise customers. To improve the valid survey response rate, we further reminded the respondents again after one month. The survey was conducted for about four months. A total of 390 questionnaires were distributed. After excluding incomplete questionnaires, there were 237 valid questionnaires, and the effective response rate was 60.8 percent. Table I lists the characteristics of the sample. The sampling population consisted of 20.7 percent in the semiconductor industry, 21.9 percent in electronics, 16.5 percent in manufacturing, 12.7 percent in information technology, 13.9 percent in communication, 8.4 percent in energy, and 5.2 percent in other industries. Among the respondents in these selected samples, there were 167 males (70.5 percent) and 70 females (29.5 percent). The age raged from 21 to 60 years old. 60.3 percent were over 30 years old. 54.4 percent of the respondents have more than six years of working experience and most of them were senior mangers. To detect any potential non-response bias, Armstrong and Overton (1977) and Kanuk and Berenson (1975) recommend assuring that the last quartile or second wave of respondents’ responses is similar to that of non-respondents. We divided selected samples into two groups (one consists of 34 samples that were returned within two weeks, and the other is 26 samples which returned within one month). There are no significant differences in the two groups’ perceptions of the implementation level of the various items presented in the questionnaire. The results thus suggested that non-response bias was not a problem in this study. 3.2 Measurements of variables The research questions devised were based on previous literature. To ensure consistent interpretation of the questionnaire, the meaning of green partners in the context of the environmental collaborations, including green supply chain members or collaborators for the environmental improvement activities, was illustrated in the preface of the questionnaire. The questions used for measuring each variable are listed in Table II. The constructs utilized in this study are measured with the seven-point Likert scale,



Characteristics Gender Male Female Age 21-30 years 31-40 years 41-50 years 51-60 years Tenure 2 years or less 3-5 years 6-10 years 11-15 years 16-20 years 21 years or above Industry type Semiconductor Electronics Manufacturing Information technology Communication Energy Other



n ¼ 237



%



167 70



70.5 29.5



94 118 22 3



39.7 49.8 9.3 1.2



35 73 66 48 9 6



14.8 30.8 27.9 20.3 3.8 2.4



49 52 39 30 33 20 14



20.7 21.9 16.5 12.7 13.9 8.4 5.2



from 1 to 7 rating, from strong disagreement to strong agreement. Following the definition of social capital provided by Nahapiet and Ghoshal (1998), this study classifies the social capital constructs into relational capital, structural capital, and cognitive capital. The relational capital was assessed by a scale proposed by Morgan and Hunt (1994), McAllister (1995) and Tsai and Ghoshal (1998), including four items relating to trust and commitment between the focal firm and its green partners. The structural capital was evaluated using a three-item scale developed by Smith et al. (1994) and Tsai and Ghoshal (1998), which is comprised of social relationships, network interaction, and communication frequency with green partners in the environmental collaboration. The cognitive capital was assessed using a scale proposed by Tsai and Ghoshal (1998) and Chiu et al. (1999), including three items relating to shared vision, shared values, and shared language. Knowledge sharing was adapted from four items by Bock et al. (2005), including the sharing of work reports, official documents, experience, and know-how with partners frequently in the environmental collaboration. Innovation performance was evaluated by a scale by Lovelace et al. (2001), comprised of four items to evaluate innovativeness and three items to evaluate constraint adherence relating to green management. 3.3 Methodology After data collection, we used the SEM method for data analysis. In the SEM method, we can examine the mutual relationships simultaneously among a set of posited constructs, which are measured by the observed variables. It includes the analysis of two models: the structural model and the measurement model.



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Table I. Characteristics of the sample



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Constructs



Measurement item



Reference



Relational capital (RC)



RC1: whether green partners deal with each other honestly and open-heartedly in environmental collaboration RC2: whether green partners pay attention to the confidentiality of green concepts given by each other in environmental collaboration RC3: whether green partners abide by their mutual commitment in environmental collaboration RC4: whether the cooperative relationships with green partners in environmental collaboration are stable SC1: my company maintains close social relationships with green partners in environmental collaboration SC2: my company spends a lot of time interacting with green partners in environmental collaboration SC3: my company has frequent communication with green partners in environmental collaboration CC1: whether green partners have the same views on green concepts in environmental collaboration CC2: whether green partners have the same values regarding green concepts in environmental collaboration CC3: whether green partners use the same professional language to communicate with each other regarding green concepts in environmental collaboration KS1: the sharing of work reports with green partners frequently in environmental collaboration KS2: the sharing of official documents with green partners frequently in environmental collaboration KS3: the sharing of experiences with green partners frequently in environmental collaboration KS4: the sharing of know-how with green partners frequently in a more effective way in environmental collaboration P1: the innovativeness of the company’s green product compared with other companies’ innovativeness P2: the number of green innovations or new ideas introduced by the company compared with other companies P3: overall green management performance compared with other companies P4: adaptability to changes compared with other companies related to green management P5: progress compared with initial expectations related to green management P6: adherence to schedules related to green management P7: adherence to budgets related to green management



Morgan and Hunt (1994) McAllister (1995)



354



Structural capital (SC)



Cognitive capital (CC)



Knowledge sharing (KS)



Innovation performance (P)



Table II. Questions for measuring each variable



Tsai and Ghoshal (1998) Smith et al. (1994) Tsai and Ghoshal (1998) Tsai and Ghoshal (1998) Brashear et al. (2003) Chiu et al. (2006) Bock et al. (2005)



Lovelace et al. (2001)



The structural model specifies the relationship among the posited constructs. The equation of the structural model is presented below:



h ¼ B h þ Gj þ 6



ð1Þ



The measurement model specifies the relationships between the observed variables and their underlying constructs, which are allowed to inter-correlate with



other constructs. The equation of the measurement model is presented below as equations (2-1) and (2-2): y ¼ Ly h þ 1



ð2-1Þ



x ¼ Lx j þ d



ð2-2Þ



In this study, a two-step SEM process proposed by Anderson and Gerbing (1998) was employed to test our hypotheses with AMOS 16.0. First, employing the confirmatory factor analysis (CFA), we evaluated the scale validity of the measured constructs from the measurement model. After measurement model testing, we used the structural model testing to examine the hypotheses.



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4. Results and discussions 4.1 Measurement model testing The reliability of the constructs was measured by the composite reliability indicator. Reliability can reflect the internal consistency of the indicators measuring a given factor. As shown in Table III, all constructs exceeded 0.9, satisfying the general requirement of reliability. To test the convergent validity, all factor loadings for indicators measuring the same construct are statistically significant. The results of Table III show that all indicators effectively measure their corresponding construct and support convergent validity (Anderson and Gerbing, 1998). In this study, the average variance extracted (AVE) for each construct exceeds 0.50, suggesting that the hypothesized items capture more variance in the underlying construct than any attributable to measurement error. In all, the above results of Table III show that instruments used for measuring all indicators of the construct in this study reached a statistically adequate level. In addition, we also tested the discriminant validity. An assessment of discriminant validity among the constructs support the model fit. Table III summarizes the assessment results of the measurement model. 4.2 Structural model testing Following the first step of measurement model testing, the second step is to analyze the structural model. The overall fit of the structural model reaches an acceptable level (x2 ¼ 68.49, df ¼ 28, x2/df ¼ 2.446, GFI ¼ 0.95, AGFI ¼ 0.90, CFI ¼ 0.99, NFI ¼ 0.97, RFI ¼ 0.96, IFI ¼ 0.98, TLI ¼ 0.97, RMR ¼ 0.05, RMSEA ¼ 0.07). The fit indices Construct



Indicators



Relational capital



RC1 RC2 RC3 RC4 SC1 SC2 SC3 CC1 CC2 CC3



Structural capital Cognitive capital



Standardized loading



R2



CR



AVE



0.91 0.98 0.87 0.86 0.81 0.96 0.81 0.94 0.93 0.90



0.83 0.96 0.76 0.74 0.65 0.92 0.66 0.88 0.86 0.81



0.95



0.82



0.90



0.74



0.95



0.85



Table III. Standardized loadings and reliabilities for measurement model



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showed reasonable fit values with no substantive differences. Therefore, the path diagram for the research model was an adequate representation of the entire set of causal relationships. Figure 1 shows the estimated path coefficients and their significance in the structural model. The results in Figure 1 support H1a (path coefficient ¼ 0.37, p , 0.005), which implies that the greater structural capital the focal firm has with their partners, the greater relational capital is embedded in the green network. Thus, if the companies increase access opportunities to the structural supply system through environmental collaborations, it would create an interactive platform for social capital transactions. As actors interact over time, relational capital develops (Nahapiet and Ghoshal, 1998). All actors have an incentive to develop a greater network of green partners, as not only are they called upon to share their own knowledge or experience, but also stand to benefit from others’ expertise (Simpson et al., 2007). According to the opinions of the industry experts interviewed in the pretest stage, only when green partners are willing to provide proprietary information and business operations based on the trusting relationship, can the levels of environmental commitment increase, and in turn lead to a greater likelihood of improving environmental performance. For example, Taiwan Semiconductor Manufacturing Company (TSMC), which provides largest integrated circuit technology and manufacturing services in the world, endeavor to promote environmental collaboration criteria on new objectives, including environmental management systems (EMS) complying with ISO 14000 standards and certification to ISO 14000, to help his partners determine effective solutions to environmental problems. They also organize supply chain management forum every year to build interactive relationship with their partners. Hence, building better structural capital within supply chain network would help companies open more channels of communication and gain additional opportunities to manage supply relationship effectively. Consistent with H1b, the empirical results of this study showed that cognitive capital has a positive and significant effect upon relational capital, with a path



The Development of Social Capital



Structural Capital



Figure 1. Parameter estimates for the structural model



The Creation of Green Innovation



0.37*** Relational Capital



Cognitive Capital



The Exchange of Green Knowledge



0.27***



Knowledge Sharing



0.20*



Innovation Performance



0.42***



Notes: Significant at: *p < 0.05, **p < 0.01 and ***p < 0.005; x2 = 68.49, df = 28, x2 /df = 2.446, GFI = 0.95, AGFI = 0.90, CFI = 0.99, NFI = 0.97, RMR = 0.05, RMSEA = 0.07



coefficient of 0.42 ( p , 0.005). This result can be explained by the fact that when actors share common goals for green management, they can avoid possible misunderstandings in their interactions and have more opportunities to exchange their knowledge freely. Furthermore, they will also tend to commit themselves more to their relationships when they have a higher level of cognitive capital. Greater cognitive capital provides intrinsic motivation for the actors involved in the green network (Wei et al., 2010). Because shared values enable one member to understand other member’s goals better, such harmony of purpose contributes to cultivate trust among members (Sahay, 2003). For example, the incorporation of environmental considerations into the supply chain often requires long-term allocation of resources, and whether the selected partners can commit to a continual investment of resources is crucial to their survival. These findings are consistent with the experts’ experience. One of the industry experts, who is in charge of risk management, labor safety and environmental health affair in TSMC, suggested that companies should avoid complex environmental initiatives with their partners when they do not have environmentally conscious practices to implement them. Inter-organizational collaboration appropriate for green supply chain needs to be developed by a proactive corporate environmental stance. It provides the foundation to align the organizations’ goal of social responsibility and further communicate supply chain members’ commitment to such goals. Hence, integrating commonly recognized goals for green management would help partners be more aware of the customer’s environmental concerns and value system and enhance positive customer-supplier relationship. Consistent with H2 and H3, the empirical results indicate that relational capital is an important antecedent of knowledge sharing, with a path coefficient of 0.27 ( p , 0.005), and in turn, knowledge sharing leads to greater innovation performance, with a path coefficient of 0.20 ( p , 0.05). This result is in accordance with previous studies finding that social relationships provide a motivational source of social capital (Alder and Kwon, 2002). This can be explained by the fact that greater relational capital will motivate partners to share their knowledge, because they will not be afraid of being taken advantage of. When organizations have more interactive green relationships with their partners, they will have more opportunities to leverage relational capital in order to facilitate inter-organizational activities (Dyer, 1997). Furthermore, if companies do not have much control over their suppliers, working to build trust within the relationship also can cause greater performance gains for both partners involved in the exchange (Handfield and Bechtel, 2002). For example, companies which are serious about their improving environmental performance should work towards building greater levels of trust with key-input partners and exploring opportunities for knowledge sharing on a regular basis. Greater levels of relational capital would be helpful in improving inter-organizational activities and enhancing greater green performance within an organization (Buysse and Verbeke, 2003; Bowen et al., 2001). These finding are supported by preliminary discussion with industry experts who have green management experiences in the manufacturing industry. One response in particularly illustrated the relationship perspective of those interviewed: companies need to make efforts on relationship-specific investment with green partners. These kinds of investment on relationship management would not only increase partners’ strategic environmental collaboration, but also provide the minimum assurance of risk management. Hence, to achieve effective knowledge sharing, the relevant parties should



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establish and reinforce collaborative relationships regarding green innovation, geared towards achieving greater competitive advantages. 5. Conclusion and limitations The results of this study indicated that social capital facilitates knowledge sharing regarding green management, and in turn leads to greater green innovation. The three kinds of social capital had significant effects, directly or indirectly, on knowledge sharing regarding green management. The social capital approach can be considered as strategies for companies, which leads to a new paradigm for green innovation and/or business operations. Companies have to consider environmental issues as a major source of strategic change, due to growing social and regulatory concerns for the environment. Particularly in emerging countries, the appropriate development of green concepts and practices may indeed aid these countries by lessening the environmental burden of the manufactured products, while even potentially improving their economic positioning. However, the development process of green management for developing countries is complex and dynamic, because their industries must face global competition. Hence, companies should leverage their social capital in order to produce additional competitive advantages through environmental collaboration with developed countries. This study also offers a frame of reference for those who wish to facilitate knowledge sharing and innovation in green management. Organizations need to pay more attention to the issues of environmental management and sustainable development. However, many companies with damages for failing to comply with the international environmental protection regulations have few resources to deploy in this regard. If organizations are able to manage and leverage their social capital effectively, they can open more channels of communication and gain additional opportunities to exchange green information and resources. For example, when partners were willing to make environmental commitments in the form of capacity and equipment, higher levels of trust were developed. In addition, when companies do not have a large degree of control over partners, working with them to improve levels of trust may be helpful in improving inter-organizational learning, and in turn trigger greater green innovation. The benefits from investment in social capital building have some upper limits. For example, technology investment may make it possible to stretch the limitation of networks for green innovation. Although it takes time and money to build social capital, more interactions with green partners could provide the unplanned opportunities for the accidental coming together of ideas that may lead to the development of green innovation within organizations. In addition, relationship stability and durability are key network features associated with high levels of norms of cooperation (Nahapiet and Ghoshal, 1998). Thus, building a stable network relationship may serve to reduce some transaction costs of environmental collaborations with partners. Therefore, it is suggested that managers consider the investment of social capital as one of the green strategies for companies, which are influential in the development of new green intellectual capital. To achieve effective green innovation, companies should leverage their social capital in order to produce additional competitive advantages through environmental collaboration. However, there are some limitations in this study, due to its empirical data and methods. First, this study did not measure how social capital and knowledge sharing



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from Yuan-Ze University of Taiwan. His research interest focuses on leveraging advanced technology for economic improvement and industrial development based on his practice experience.es on leveraging advanced technology for economic improvement and industrial development based on his practice experience. Shiu-Wan Hung is currently the Professor at the Department of Business Administration of National Central University, Taiwan. She received her PhD from the Institute of Business and Management of National Chiao Tung University, Taiwan. Before this, Dr Hung earned her MS from the University of Wisconsin-Madison in the USA and completed her BS from the National Chengchi University of Taiwan. Her researches mainly focus on the areas of technology management, knowledge management and performance management. Dr Hung has had articles published in the Information & Management, Scientometrics, Technovation, Computers & Operations Research, European Journal of Operational Research and other journals. Shiu-Wan Hung is the corresponding author and can be contacted at: [email protected]



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