Diffusion of environmental business practices: A network approach

Journal of Purchasing & Supply Management 19 (2013) 264–275

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Diffusion of environmental business practices: A network approach$ Wendy L. Tate a,n, Lisa M. Ellram b, Ismail Gölgeci c a b c

Department of Marketing and Supply Chain Management, University of Tennessee, 315 Stokely Management Center, Knoxville, TN 37996, USA Supply Chain Management, Farmer School of Business, Department of Marketing, Miami University, Oxford, OH, USA Department of Marketing, University of Vaasa, Tervahovi, Wolffintie 34, 65200 Vaasa, Finland

art ic l e i nf o

a b s t r a c t

Article history: Received 27 March 2013 Received in revised form 10 August 2013 Accepted 12 August 2013 Available online 30 August 2013

The purpose of this research is to build a conceptual foundation that examines network effects on the diffusion of environmental business practices (EBP) among suppliers. This research extends a network perspective to adoption of an environmental business practice across a large network of suppliers. The context of EBP is used to better understand adoption of a complex business practice, with perceived costs that are often greater than the perceived benefit. Variation in the level of structural and relationship embeddedness affect network diffusion of environmental business practices differently. Increased levels of structural and relational embeddedness are proposed to be positively associated with diffusion of EBP. From a practical standpoint, firms that leverage embeddedness may facilitate higher diffusion and adoption of environmental business practices. This facilitation may lead network actors to engage in EBP, and leverage benefits that may stem from these practices. This research introduces the concept of embeddedness to the environmental supply chain literature. Practicing managers can use the findings in this research to better position themselves within a network to diffuse EBP. This research also helps managers understand how supply chain members that are weakly connected to the primary network are important for introducing new ideas and innovations. & 2013 Published by Elsevier Ltd.

Keywords: Supplier networks Social network theory Embeddedness Environmental business practices Diffusion

1. Introduction and research impetus Environmental sustainability issues have gained increasing attention from both private institutions and public policy makers (De Brito et al., 2008). Social concerns and public pressure dictate that manufacturers and service providers reduce the environmental footprint of their products and services (Mendleson and Polonsky, 1995; Dos Santos et al., 2012). Further, there is evidence that firms may gain a wide range of benefits such as reduced costs and enhanced competitiveness, when their suppliers adopt environmental business practices (EBP) (Lee and Klassen, 2008; Rao and Holt, 2005). The idea that environmental business practices enhances firm and supply chain performance is becoming widely accepted in the literature (e.g. Carter and Dresner, 2001; Handfield et al., 2005; Pil and Rothenberg, 2003). Environmental business practices refer to the set of activities employed to manage and advance a firm′s environmental responsibilities (Huppes and Ishikawa, 2005) and can include

☆ The authors would like to thank the participants in the first annual international symposium on supply chain sustainability held in Toronto, February 2013 for their insightful feedback and input. n Corresponding author. Tel.: þ 865 974 1648; fax: þ1 865 974 1932. E-mail addresses: [email protected] (W.L. Tate), [email protected] (L.M. Ellram), [email protected] (I. Gölgeci).

1478-4092/$ - see front matter & 2013 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.pursup.2013.08.001

any business activity that serves the goal of advancing environmental sustainability. To improve the research operationalization of the concept of EBP, Sarkis (1998) specifically defined environmentally conscious business practices (ECBP) as including (but not limited to) design for the environment (DfE), life cycle analysis (LCA), total quality environmental management (TQEM), green supply chain management (GSC), and ISO 14000 environmental management systems requirements. These categories are also defined rather broadly. For example, DfE includes design for recyclability, usability, remanufacturing, disassembly and disposal. Green Supply Chain management (GSC) links EBP to external partners, and includes inbound logistics and procurement, materials management, outbound logistics, packaging and reverse logistics that are designed to reduce waste and focus on environmentally friendly materials and transportation modes. It appears that the key factor distinguishing EBP from other practices is a focus on making changes that will somehow reduce environmental impact versus current practices. Clearly, many of these changes and programs have goals and impacts far beyond only improving the environment. It is increasingly clear that business processes that drive resource productivity are becoming just as important as those that drive economic productivity, raising the level of interest in EBP. Development and adoption of environmental business models and clean technologies are a means of improving resource productivity and

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therefore company performance (Bisson et al., 2010; Green et al., 2012). Managers are also increasingly aware that the environmental impact of supply chains is driven by the processing and movement of materials, goods and services across the various interconnections in the supply chain network, with significant environmental impacts generated outside of the focal firm (Faruk et al., 2001; Sarkis, 2012; Walmart, 2012). This complexity of interconnections and interdependencies among the organizations and actors in supply chain networks makes it difficult to measure, manage and understand the environmental footprint of products or services (Gimeno, 2004). Supply chain research has explored environmental sustainability for over a decade, but has generally not taken a holistic supply base perspective using the supplier network as the context (Carter and Jennings, 2002a; Capó-Vicedo et al., 2011; Linton et al., 2007). Research has focused primarily on internal operations and corporate social responsibility (CSR) reporting. Even most studies of supply management involvement in EBP focus on the role of supply management (Carter and Dresner, 2001; Walker et al., 2008), rather than the engagement of suppliers in EBP (Tate et al., 2012; Miemczyk et al., 2012), as supply management involvement is generally a prerequisite to supplier engagement. EBP support the organization′s adoption of environmentally sustainable operations and often contribute to improved resource productivity (Abbasi and Nilsson, 2012). Because of the extended and increasingly complex supplier network, the challenge is in diffusing these practices. The EBP should be diffused throughout the firm and the network to achieve the full potential impact. A more holistic integration of EBP creates network visibility and reduces costs, to help overcome the common perception that the costs of EBP outweigh the benefits. The network perspective provides an explanation of how ideas and practices are diffused in supplier networks (Autry and Griffis, 2008). “The extension of social network theory to supply chain management is natural in that supply chains represent the fundamental network structures of the social science of business,” (Autry and Griffis, 2008, p. 160). Networks1 that develop via the exchange of goods, services, and information between organizations may provide a natural avenue to understand and diffuse EBP (Borgatti and Li, 2009; Carter et al., 2007; Crespin-Mazet and Dontenwill, 2012). Network theory refocuses the attention from individual actors as the source of action, to understanding how the structure of networks engenders action (Burt, 1995; Parkhe et al., 2006). With the growing amount of research and practice involving EBP (Hoejmose and Adrien-Kirby, 2012; Tate et al., 2012; Walker et al., 2012), it seems clear that diffusion of EBP has gone beyond early adopters, and in some aspects is becoming mainstream. The investigation of EBP in relation to network theory has been scant. While the key function of networks is the flow or dissemination of information (Borgatti and Halgin, 2011), the way in which network involvement impacts the diffusion of EBP in supply networks is largely under-researched (Midgley et al., 1992; Bohlmann et al., 2010), leaving a gap in the literature regarding how EBP are diffused in networks. The efforts of European scholars in considering environmental sustainability in a network context using qualitative studies and literature reviews (Kourula et al., 2007; Varga et al., 2009) have not fully addressed this topic. Likewise, the dyadic unit of analyses (Golicic et al., 2003; Heide and Wathne, 2006; Miemczyk et al., 2012) and even the growing triadic unit of analyses (Choi and Wu, 2009a, 2009b) seen in the mainstream supply chain research do not embrace the complex involvement of

1 The management literature uses the terms “social network”, “network”, “inter-organizational network”, and “business network” interchangeably. In this paper, the term “network” will be used to refer to all, as it covers both individual and institutional ties, unlike the individual connation of “social network” and institutional connation of “business network” and “inter-organizational network”.

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diverse network members. Walmart is an example of an organization that engages its suppliers in EBP. The belief is that by looking at the supply chain as a whole, it can find ways to make products more sustainable—from farm to shelf (Walmart, 2012). This supports the need for research that looks at the diffusion of EBP across the complex network of suppliers. Utilizing the lens of social network theory to discover structural and behavioral implications of networks on organizations’ EBP may help facilitate synergies among business partners in achieving superior environmental performance. It seems that an increasing number of buying firms would like to encourage members of their supplier network to learn and embrace EBP. Thus, some elements of network theory can be leveraged to predict the diffusion of EBP across the supplier network. The overarching purpose of this research is to understand how the structural and behavioral embeddedness of members of a supplier network affect the diffusion of EBP. The paper contributes to theory and practice by enhancing the understanding of the relationship between relational and structural embeddedness relative to the diffusion of EBP. The findings from this research may have application to diffusion of other business practices and different contexts, particularly in buyer–supplier relationships. This paper is organized as follows. First, the literature on network theory and environmental sustainability is briefly presented. This discussion is followed by an explanation of how the general tenets of network theory are used to develop theoretical propositions and closes with theoretical and managerial implications followed by future research.

2. Literature review A review of the key premises of network theory and embeddedness is introduced, and then the interplay with EBP is discussed. This discussion helps to establish the relationship between network theory, EBP and EBP′s diffusion across supplier networks. 2.1. Network theory The core concept of network theory is the “social network”. A social network consists of a finite set or sets of actors (nodes) – discrete individual, corporate, or collective social units – and the relation or relations among them (Barabási et al., 2002; Wasserman and Faust, 1994). “Any theoretically meaningful unit of analysis may be treated as actors: individuals, groups, organizations, communities, states, or countries” (Streeter and Gillespie, 1993, p. 221). The network′s boundaries need to be defined to clarify the network being explored. The term network, as used in this paper, refers to a set of organizational and individual connections, links, and ties that form a relationship structure (Herranz, 2004). A basic assumption in network analysis is that network actors influence each other through their network ties (Borgatti and Li, 2009). Many networks are characterized by two attributes: first, they are composed of “units and their interactions,” and second, these units are grouped together in “a hierarchical or nested structure” (Harary and Batell, 1981; Moliterno and Mahony, 2011). Thus, SNA examines network structure from the perspective of individual members; subgroups, such as organizations, to which these members belong; and the network, which represents relationships among the various subgroups (Streeter and Gillespie, 1993). These attributes may also be reflected in the business world, and in supply chains in particular (Choi et al., 2001). The application of social network theory has only recently expanded to supply chain disciplines (Autry and Griffis, 2008; Borgatti and Li, 2009; Carter et al., 2007; Crespin-Mazet and Dontenwill, 2012). However, the earlier works by the Industrial

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Marketing and Purchasing (IMP) group focused on supply chain management as a series of relationships among network actors. The IMP group focuses on the relationships in the supply network, and where the organization lies along the spectrum of trying to “control” versus “cope” within that network. (Harland, 1996; Harland and Knight, 2001; Harland et al., 2001; Lamming et al., 2000). The research from the IMP group tends to be more descriptive in nature, depicting networks in terms of actors, resources and activities (Hakansson, 1987). The IMP school of thought is contrasted to the network research in the areas of strategic management, and operations, which tend to be more prescriptive in nature (Harland and Knight, 2001; Harland et al., 2001; Lamming et al., 2000). The IMP groups’ focus on behavior rather than just linkages has influenced other supply chain network research by increasing the awareness and understanding of supply chain networks in terms of soft issues like relationships and behavior. In addition, this IMP school of thought has also raised the issue of the appropriate level of analysis from which to conduct network research, suggesting that multiple levels are preferred (Harland, 1996). The current research focuses on the linkages between organizations in a supply network. There are many participants both upstream and downstream in the network. The embeddedness of these participants is the key issue in this research to help understand the adoption of an EBP.

2.2. Embeddedness Embeddedness is a central construct in network theory (Dacin et al., 1999; Gimeno, 2004; Moran, 2005). The definition and usage of embeddedness is subject to discussion and has evolved over time (Dacin et al., 1999). Granovetter (1985) explains embeddedness as an on-going contextualization of economic activity in social structures, pointing to the assumption that all economic behaviors are embedded in a social context. Embeddedness is central to the network and social capital theory (Autry and Griffis, 2008). The basic premise of embeddedness is that the structure of, and behaviors in, the network influences the actor behaviors and outcomes in the network (Anderson et al., 1994; Reagans and Mcevily, 2003), creating meaning in exchange relationships that differ from those stemming from traditional arms-length market relations (Borgatti and Foster, 2003; Uzzi, 1996). The opportunities and risks to which an actor is exposed also depend partly on the actors’ structural position in the network (Capaldo, 2007), and its relative power (Schneider and Wallenburg, 2012). Organizations increasingly seek to have closer relationships or connections with other organizations within the network in order to gain access to critical resources (Gulati and Gargiulo, 1999). However, it is the individuals within these organizations, acting on behalf of the organization, that diffuse the organizations’ overarching goals and strategies to its supplier network. As suggested by the IMP group and those who have extended that work, behavior and structure work together. The closer the ties between organizations, the increased inter-organizational embeddedness. Embeddedness has two key dimensions: structural embeddedness and relational embeddedness. Granovetter (1985, 2005) argues that both types of embeddedness are important: embeddedness of actors within the overall structural form of their socially constructed environment (structural embeddedness), and embeddedness associated with direct and indirect relationships, bonding actors that occupy similar social space (relational embeddedness). Gulati and Gargiulo (1999), contend that both embeddedness types have different effects on networks, and are relevant to supplier network analysis.

2.2.1. Structural embeddedness Structural embeddedness refers to the impersonal configuration of linkages between people or units (Nahapiet and Ghoshal, 1998). These include the presence or absence of network ties between actors, along with other structural features like cohesion, centrality and hierarchy (Moran, 2005). Nahapiet and Ghoshal (1998) suggest that structural embeddedness relates to the overall pattern of connections between actors, addressing the configuration of the network (Rowley et al., 2000). How the network is shaped and how ties are connected is extremely important to the network theory and is in itself a research stream (Borgatti and Foster, 2003). When examining structural embeddedness, another key concept is interconnectedness (cohesion), which refers to the ratio of the number of ties between actors to the number of actors in the network (Ahuja, 2000). Hence, some scholars refer to cohesion as “density” (Borgatti and Halgin, 2011). As the number of ties among a fixed number of actors increases, the network becomes increasingly interconnected, which also indirectly impacts tie strength among actors (Ahuja, 2000). 2.2.2. Relational embeddedness Another aspect of embeddedness is relational embeddedness. This is the second key dimension of embeddedness and is defined as “personal relationships people have developed with each other through a history of interactions” (Nahapiet and Ghoshal, 1998, p. 244) or the characteristics of the relationship in a social network (Rowley et al., 2000). In essence, relational embeddedness is a source of learning and social capital for organizations (Andersson et al., 2002). Relational embeddedness focuses on how information and resources are shared, collaboration, and ultimately how learning occurs within the network (Rowley et al., 2000). Relational embeddedness focuses on the softer issues and helps determine the type of knowledge that is transferred within the network: tacit or explicit (Dhanaraj et al., 2004). The focus on relational embeddedness here is on intensity or cohesiveness of relationships among the network actors (Gulati and Gargiulo, 1999). In terms of resource sharing, technological and financial resources are often common. However, relational embeddedness also considers emotional support, time, and managerial expertise (Uzzi and Lancaster, 2003). High levels of interaction between members of the network are indicative of strong social ties and increased trust among members (Dhanaraj et al., 2004). The more trust apparent in the social tie, the less likely that members of the network act opportunistically (Uzzi, 1997). This means that new ideas and innovation are more likely to be shared among members that have higher levels of relational embeddedness. The competitive advantage found in embedded relationships occurs when the partners invest in relation-specific assets, develop interfirm knowledge sharing routines, use effective governance mechanisms, and exploit complementary capabilities (Zacharia et al., 2009). Fig. 1 (adapted from Ahuja, 2000), illustrates two hypothetical networks. Circles with letters are actors (nodes), and lines connecting them are ties (links). Ties differ in their strength, referring to relational embeddedness. The thicker the lines representing the ties, the stronger the embeddedness due to increased tie strength and exchange intensity. Network A illustrates a highly dense network configuration, representing relatively high embeddedness. Network B illustrates low density and embeddedness, where the information has to go almost exclusively through actor N. 2.3. The level of analysis in networks Network theory “…views any system as a set of interrelated actors or nodes. The actors can represent entities at various levels of collectivity, such as persons, firms, countries and so on (Borgatti

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D I O T Fig. 1. Depiction of two hypothetical networks, adapted from Ahuja (2000).

and Li, 2009, p. 2). There are several different levels of analysis that can exist in network research: individual actor, organizational level, and supply chain or network level. The level of the individual actor assesses the activities and behaviors from the perspective of a single person. How does one actor′s behaviors and relationships affect those of other actors in the network, or how are other actors affected based on their position within the network? This type of research is often relevant for studying networks within an organization, or social networks of individuals. An example of this is Carter et al. (2007) study of how one individual with limited position power was able to develop a network to create important organizational change. The next level of the analysis is the organizational level, which explores the interaction among and between organizations (Contractor et al., 2006; Harland, 1996). This level of analysis is appropriate for examining broader supply chain issues and relationships among organizations, as in Koka et al. (2006) study of how interfirm networks evolve based on external environmental changes. These interfirm ties may be viewed from the lens of the firm as entities, for example firms that buy or sell to each other, have joint ventures or partnerships, or even technology transfers. Interfirm relationships can also be viewed via the relationships of individuals that know people at other organizations, whether formal, as in employees that work together on firms’ projects, or informal, as in neighbors, friends, or common social group membership (Borgatti and Li, 2009). Such research is sometimes conducted at the dyadic level of analysis, such as Ellram and Hendrick′s (1995) comparison of relationship perceptions between matched buyer–supplier partners. This research can also be conducted at the triadic level, as in Choi and Wu′s (2009b) examination of buyer–supplier–supplier relationships. Studies at the third level, or actual supply chain or supplier network level are very limited due to their complexity including issues related to defining the boundary of the network, and the often local-focus of network theories (Borgatti and Li, 2009; Galaskiewicz, 2011). Despite these difficulties, “…one way in which social network analysis can add value to the supply chain management literature is to remind researchers that social network ties among parties at the boundaries of organizations within the chain are important in building trust among actors that can facilitate information exchange, cooperation and coordination” (Galaskiewicz, 2011, p. 5). Looking at these relationships as “chains”, they can be viewed as the relationships between businesses, going beyond dyads and looking both upstream and downstream (Harland, 1996), as in the recent work of Mena et al. (2013). Extending the third level or perhaps creating a new level and building on the work of the IMP group, Harland (1996) and others

(Lamming and Hampson, 1996; Lamming et al., 2000) describe supply networks as collections of supply chains, capturing more of the reality of the way that business is really conducted, and discerning among various types of networks, with the interest of operationalizing and conceptualizing the networks. Lamming et al. (2000) and Harland et al. (2001) took a unique approach to this problem of conducting a SC network level study by defining the unit of analysis as, “…the physical flow of a particular product within the total supply network, i.e. the upstream and downstream network.” (Lamming et al., 2000, p. 682) in order to explore strategic, structural and operational characteristics of a variety of supply chains. Thus, there are many different ways that the level of analysis issue can be broached in studying supply chains or supply networks. 2.4. Linking environmental business practices and diffusion Network theory augments previously studied theoretical lenses concerning diffusion of EBP, and provides an alternative lens for understanding diffusion. Networks represent an important way to diffuse ideas and practices among actors/nodes within a network (Granovetter, 1983). Linking EBP and diffusion using network theory helps researchers move beyond the dyadic and triadic perspectives more common in supply chain research to better understand the role of suppliers, customers, NGOs, governmental organizations and others in diffusing these practices. Collaboration in a supply chain network is one where independent but related firms share knowledge and skills so that the ultimate customer′s needs are met. Competitive advantage is obtained from the value created by a network of firms (Zacharia et al., 2009). EBP vary from strategic to operational initiatives (Handfield et al., 2005; Pagell et al., 2007). Driving forces behind EBP include government regulation, customer requests, and costs savings (Rugman and Verbeke, 1998). Tate et al. (2011) provide several examples of supplier environmental practices, such as recycling and remanufacturing, life cycle analysis, and environmental design, that are routinely presented in the public press. Sarkis (1998) adds design for the environment (DfE), total quality environmental management (TQEM), green supply chain management (GSC), and ISO14000 environmental management systems requirements to this list. Green purchasing (Min and Galle, 1997; Tate et al., 2012), closed-loop supply chain management (Savaskan et al., 2004), and collective resource utilization (Payne et al., 2011) are also commonly regarded as EBP that may engage suppliers. There is much research concerning the benefits of EBP, including empirical support that indicates EBP may facilitate improved firm performance (Carter et al., 2000; Zhu and Sarkis, 2004). Carter and Rogers (2008) argue that firms with a holistic approach

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to environmental SCM are likely to create capabilities that are difficult to imitate. Carter and Jennings (2002a, 2002b) found a link between socially responsible purchasing practices and increased relational commitment and trust between the buyer and the supplier. Firms can derive a competitive advantage from non-imitable environmental practices and by securing proprietary access to resources that are required for better environmental performance (Hart, 1995; Rugman and Verbeke, 1998). Overall, EBP supports organizations and supply networks in achieving longterm business survival while preserving society′s environmental welfare. Many companies, NGOs and government organizations are interested in how to encourage more widespread adoption of EBP for the benefit of adopting firms and society as a whole.2 Lamming and Hampson (1996) squarely identified the environment as a supply chain issue, where buyers need to influence their suppliers to source more sustainably. In exploring the diffusion of business practices across supplier networks, it appears that such practices may be spread across organizations through diffusion as long as they are perceived to be beneficial to all those involved (Grawe, 2009). Diffusion across institutions and individuals consists of knowledge, persuasion, decision, implementation, and confirmation steps, and thus, encompasses adoption (Rogers, 1995). For example, Roy et al. (2004) suggest that interaction between a firm and its connected network actors are key drivers of innovation, as networks are the domains that facilitate the flow of ideas and information (Borgatti and Halgin, 2011). Granovetter (1983, p. 214) argues that these same patterns followed by diffusion of innovation apply to “…diffusion of any ideas or information.” Like the diffusion of other business practices as a consequence of networks (Borgatti and Foster, 2003; Davis, 1991), EBP may diffuse across organizations through the interaction of supplier network actors. Diffusion can be bidirectional, following both upstream and downstream paths (Rogers, 1995). It may stem from both intentional, systematic efforts, such as explicit requirements of a leading actor and from spontaneous, unsystematic sharing of information (Haunschild, 1993). Early adoption of EBP was often driven by a champion (Carter et al., 2007; Drumwright, 1994), while today it appears to have reached the mainstream, and is being driven by strong leaders in the channel or supply chain like Walmart, P&G, and other organizations that want suppliers to follow EBP (Ellram and Golicic, 2013; Schneider and Wallenburg, 2012). The network can play a powerful role in diffusing EBP today, and engaging late adopters. Late adopters likely do not have a key strategy in place for implementation of EBP, but may have individuals without positional power that are passionate about environmental issues that will help to diffuse these practices within the organization (Tate et al., 2011). These individuals may have a tangential relationship to the overall network through both personal and professional organizations that helps them to understand the context and importance of EBP therefore influencing the introduction and adoption of EBP within their organization (Carter et al., 2007). Network actors often do not internalize or diffuse ideas and practices from groups with which they do not feel somehow associated (Granovetter, 1983). Amalgamation brings functionally interdependent nodes together in a common normative network, creating understanding and consistent norms (Galaskiewicz, 2011). For example, a research study of an industrial network in India shows that actors who have a high level of social embeddedness also have a

2 Well-known examples include the U.S. Government (clean air act, EPA), Walmart, the National Resource Defense Council, Carbon Disclosure Project, Nature Conservancy and countless others.

high level of shared norms related to handling product waste. This demonstrates correlation, but not causation (Ashton and Bain, 2012). While some research suggests that effective external influence on suppliers to adopt EBP is based mainly on some type of power (Schneider and Wallenburg, 2012). Network theory suggests that there are additional sources of influence. The understanding of diffusion of business practices extends beyond the view that network actors are inert entities that merely respond to inducements and constraints (power) arising from their network ties (Dhanaraj and Parkhe, 2006). Instead, it adopts the view that all actors in the network can play a significant and dynamic role in diffusion of such practices (Choi et al., 2001), hence the interest in network embeddedness. Regardless of whether the source of initiatives is the customer or the supplier (Ettlie and Rubenstein, 1981), practices may disseminate from many directions. Therefore, network theory provides a powerful lens to help explain the diffusion of EBP across network actors (Reagans and Mcevily, 2003) with different levels of power (Carter et al., 2007), and to study the interactions among a diverse web of actors. The following theoretical propositions draw on network and diffusion theory to advance the application of these theories to the diffusion of EBP across supplier networks, and to the late majority and the late adopters of EBP in particular. The EBP leaders were early adopters who tend to be self-motivated. The late majority represents the joiners and spectators who wait for others to make changes before they get on board. The late adopters (also referred to as laggards) would rather sit on the sidelines and do nothing, so often have to be strongly influenced to adapt to new circumstances and make changes (Rogers, 1995). Influence from strongly embedded social relationships may be one way get them to adopt EBP.

3. Theoretical propositions Fig. 2 illustrates the proposed framework combining two dimensions of embeddedness that impact the diffusion of EBP. The diffusion of EBP is lowest when both structural and relational embeddedness are low, highest when both embeddedness types are high, and in between when one type of embeddedness is high

Fig. 2. Theoretical framework for the role of embeddedness in diffusion of environmental business practices.

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Raw Material Supplier

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Fig. 3. A hypothetical network with low structural and low relational embeddedness.

and the other low. Theoretical and anecdotal support pertinent to specific propositions is provided below.

3.1. Low structural embeddedness—Low relational embeddedness Relational embeddedness is characterized by reciprocity, interaction, expert division of labor, trust and joint problem solving arrangements (Uzzi, 1997). Similarly, structural embeddedness requires a highly dense, well-connected network configuration that is conducive to the fast and fluid flow of information and ideas (Tichy et al., 1979). Networks vary in their levels of structural and relational embeddedness. Some networks consist of weak, non-existent, or even negative relationships (Labianca and Brass, 2006; Mattsson, 2003). Actors in these networks are either extremely loosely tied, not tied at all (Granovetter, 1983), or lack a sufficient level of exchange to interact and generate new ideas. The lack of connection among network actors can stem from an information bottleneck arising from constraints in information processing capabilities, or can result from a network that is very small and isolated from other networks (Newman and Watts, 1999). Fig. 3 depicts such a network. In the brewing industry there are a number of small craft-beer breweries. These smaller organizations often face high volatility in raw material prices. The Craft Beer Brewers Group Purchasing Organization was formed to provide a networking service that has a sole purpose of allowing parties to leverage volume and decrease prices by consolidating orders together on materials and products such as hops, yeast, malt, bottles, caps and crates (Brewers Consortium, 2013). This is an example of a network with low relational and low structural embeddedness. The same contention may be valid for EBP. EBP that originate at a node in networks with low relational and structural embeddedness may fail to diffuse due to lack of network connections, or lack of interactions between existing nodes. Firms who only rarely do business together would not develop either structural or relational embeddedness, because they lack the need and opportunity to do so. For example, a retailer like Walmart may have a supplier that it conducts business with once a year at Christmas, but Walmart still wants to utilize only suppliers that are SmartWay certified.3 Rather than help a one-time supplier gain SmartWay certification (EBP diffusion), Walmart will likely only consider suppliers who are already certified. It is simply not worth the time and effort for either party to invest in EBP diffusion/adoption for a once-a-year transaction. Hence, the exchange of ideas and knowledge about EBP in networks characterized by low relational and structural embeddedness may virtually be absent due to low overall 3 SmartWay is a voluntary public–private partnership that is part of the U.S. Environmental Protection Agency that certifies carriers and shipper for using environmentally sound transportation practices.

interconnectedness. In these types of situations, managers need to focus less on the relational aspects of the process and more on ensuring successful operational outcomes. Over time, success may lead to greater commitment, productivity and a more effective working relationship (Zacharia et al., 2009). Poor operational outcomes lead to conflict and poor relationships. Proposition 1a. When both structural embeddedness and relational embeddedness of supplier networks are low, limited to no diffusion of environmental business practices is expected, as there is very limited to no exchange of knowledge on EBP. Proposition 1b. When both structural embeddedness and relational embeddedness of supplier networks are low, an organization that wants to pursue EBP is likely to seek out companies that already have such practices in place. 3.2. High structural embeddedness—High relational embeddedness Networks with high relational and high structural embeddedness are identified by strong and consistent relationships supported by intense and well-configured network structure, as can be seen in Fig. 4. An example of such networks exist within hightech electronics industry in Silicon Valley (EICC, 2008). In general, Silicon Valley is identified with strong connections, high level of collaboration, and rapid information flow between actors. These networks consist of a voluntary group of focal firms with common and proximate suppliers with very tight relationships. This high relational and structural embeddedness leads to formulation and implementation of within-industry EBP standards. Participants in the Electronics Industry feel obligated to comply and implement EBP. Interaction in such networks is intense, and because there are many connections per actor there are few bottlenecks. Consequently, ideas generated in such a network may be diffused very quickly across to the whole network. Being highly embedded within the network generates a number of benefits to the actors involved. Embeddedness can facilitate diffusion of EBP through inter-organizational learning and knowledge transfer (Grewal et al., 2006), increased visibility and information processing speed (Uzzi, 1997), customer responsiveness (Bernardes, 2010), and relationship specific investments (Capaldo, 2007). There are a number of companies requiring the adoption of EBP in order to be competitive for contract selection. Organizations like Walmart and P&G are mandating that their suppliers comply with EBP, and then measuring those suppliers on established environmental metrics. Embeddedness can have a particularly relevant positive impact on practices that are viewed as essential to a supplier network. Increasingly, EBP is seen as such a business practice. Network density, or cohesiveness is defined as the ratio of the number of ties between actors to the number of actors in the

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Fig. 5. A hypothetical network with high structural and low relational embeddedness.

Fig. 4. A hypothetical network with high structural and high relational embeddedness. University

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network (Ahuja, 2000). Density facilitates relational embeddedness and plays a direct and positive role in diffusion (Nijssen and Frambach, 2000). Information and knowledge tend to be disseminated more quickly and effortlessly in highly cohesive (dense) networks, due to their higher number of communication links per actor (Ahuja, 2000). A major retailer like Walmart may have very dense and numerous connections with a key supplier like Procter & Gamble, and with some of the key suppliers that are engaged in getting the right products to Walmart, such as logistics service providers and suppliers of recyclable packing materials that Walmart returns via a reverse logistics process. These suppliers will share practices and information in order to increase their own effectiveness, as well as the effectiveness of the supplier network. Thus, theoretical and anecdotal findings support the contention that relational and structural embeddedness work in tandem to facilitate smooth and rapid diffusion of EBP. Proposition 2a. When both structural embeddedness and relational embeddedness of supplier networks are high, the highest level and reach of diffusion of environmental business practices is expected, versus networks with lower embeddedness. Proposition 2b. When both structural embeddedness and relational embeddedness of supplier networks are high, companies are willing to specifically invest in programs to enhance the diffusion of environmental business practices in their existing networks. 3.3. Low–high combinations of structural embeddedness and relational embeddedness Coupling similar levels of relational and structural embeddedness provides diffusion outcomes at both ends of a continuum. When a high level of one type of embeddedness is coupled with a low level of the other type of embeddedness, the outcomes are expected to lie somewhere along the continuum. While relational embeddedness and structural embeddedness are often complementary (Moran, 2005), there are cases where networks with high structural embeddedness may be low in relational embeddedness and vice versa. As in Fig. 5, networks identified with weak or non-existent relationships but with high density where the relationships exist can be labeled as networks with low relational and high structural embeddedness. In such networks, the structure is dense but the existing ties are very loosely connected. For example, some large companies such as Walmart may have an online contract and/or

University Trade Association

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Fig. 6. A hypothetical network with low structural and high relational embeddedness.

pre-approval for purchasing from specific catalogues for supply orders. In such systems, individuals within the firms do not need to talk personally to each other to conduct an exchange. The catalogue company may have mainly very distant relationships with most of its suppliers, because it buys very standard, easily specified and easily substituted items. The supplier may have been selected based on enhancing EBP, such as consolidation of orders to improve the shipping and packaging footprint, or availability of green/recycled office supplies. All transactions can be conducted online. The system is structurally embedded but since there is no personal interaction, relational embeddedness is low. If EBP is an important aspect of the supplier′s performance, the main aspects of EBP were likely in place when the supplier was selected. Thus, while such networks may perform better in terms of diffusion of EBP than the ones with low structural and low relational embeddedness, such networks have only mechanistic support, but no relational support to reinforce, strengthen and continually improve EBP practices. Whereas communication of ideas and knowledge is a major facilitator to diffuse practices (Rogers, 1995), it is met only to a moderate extent in such networks. Proposition 3. When structural embeddedness is high and relational embeddedness of the supplier network is low, diffusion of environmental business practices is expected to be moderate, in between that of a network with low structural and low relational embeddedness, and that of a network with high relational and high structural embeddedness. Conversely, when networks have strong relationships and high exchange intensity but low tie density with a weakly configured network structure, they can be labeled as networks with high relational and low structural embeddedness, as can be seen in Fig. 6. Network theory asserts that factors such as network learning, resource sharing, and collaborative actions may provide plausible explanation for external influences (Beckman and Haunschild, 2002). High

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relational embeddedness provides a venue for such influences, though the lack of structural embeddedness may impair its effectiveness. By its very nature, the boundary spanning role of supply chain members can be important in diffusing information and practices (Galaskiewicz, 2011). An example of networks with low structural and high relational embeddedness could be among the members of trade associations such as Council of Supply Chain Management Professionals (CSCMP) and Institute for Supply Management (ISM). For example, supply chain professionals that work at a large retailer may join these organizations and become part of ISM′s sustainability forum. If an individual becomes committed to implementing EBP and learning new approaches to EBP through her ISM membership, she may view the membership as a way to advance her career and move the firm forward in implementing EBP. She may become actively involved in ISM committees, developing strong relational ties and relational embeddedness with this trade organization, and bring those ties to her employer in her job capacity. However, the relationship with that trade organization is not structurally embedded within the member′s firm, as in this example membership is not an organizational mandate, and only a small number of employees in a specific function are members of these organizations (Tate et al., 2011). Thus, the unit of analysis is still at the organization level (subgroup), but it clearly derives from the individual actor′s relationship with ISM. Taking this to the next node, the trade association may be strongly affiliated with a particular University in terms of accessing University faculty′s EBP knowledge for its members. However, the employees of the focal firm may not have a relationship with that University, so EBP information coming into the firm from that University is filtered through the trade association, and may be strongly influenced by the University. These linkages can continue for multiple levels, as illustrated in Fig. 6. The reason that these relationally embedded connections may be impactful is that people often join such trade organizations with the specific goal, such as gaining EBP knowledge. They purposefully try to bring new ideas into their employer organization and may act as champions for a specific initiative they learn about and believe in. This is potentially more influential in driving change than structural embeddedness without the associated “commitment” that can be derived from relational embeddedness. Therefore, despite the lack of structure to support it, the commitment level stemming from high relational embeddedness may facilitate moderate levels of diffusion of EBP. The concept is illustrated in prior research by the notion of a project champion (Carter et al., 2007; Drumwright, 1994). Soft and informal roles such as organizational transformation, innovation and opinion leadership, and membership opportunities in the network (Defee et al., 2009; Sparrowe and Liden, 2005) demonstrate increased relational embeddedness. If partners value their relationships with other network actors and are highly relationally embedded, network theory and common wisdom suggests that they may act more collaboratively and receptively on demands and ideas put forth by these actors within the limits of the network structure. Proposition 4. When structural embeddedness is low and relational embeddedness of the supplier network is high, diffusion of environmental business practices is expected to be moderate, but higher than supplier networks with high structural and low relational embeddedness due to the presence of a project champion. 3.4. The complementary role of weak external ties The discussion of the different combinations of relational and structural embeddedness brings up another important idea related to diffusion of EBP: the role of weak external ties. Where network actors

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lack relationships with actors outside of the network, a structural hole is said to exist. Such tight and closed networks cannot bring in ideas from outside the social network (Granovetter, 1983). There is support in the literature that strong ties need to be augmented by external weaker ties in order to leverage possible other opportunities in the network (Granovetter, 1983; Uzzi, 1997). Likewise, Burt (1995) posits that firms should cultivate weak ties with other actors who are different than their network members, to fill structural holes and reduce their insularity. In particular, if highly embedded networks are complemented with diverse actor characteristics, diffusion of new EBP can be successfully sustained over time, drawing on knowledge of those outside the tightly coupled network. The leverage of nongovernmental organizations (NGOs) may illustrate this contention. NGOs play an increasingly significant role in the decision-making process of for-profit firms, especially in terms of social and environmental issues (Gemmill and Bamidele-Izu, 2002). An example from business practice is ExxonMobil′s collaboration with NGO′s from all around the world for its corporate citizenship activities concerning environmental sustainability (Exxon Mobil, 2009). Exxon learns about possible ideas from its arms-length relationships with NGOs that it donates to, and those supported by its employees. The benefit is mutual; as firms gain low cost access to alternative critical resources to leverage EBP, NGOs attain the benefits and changes that they seek. Once such practice penetrates ExxonMobil′s extensive network, it is highly possible that other actors this embedded network would adopt it. Inclusion of weak external ties to the network does not need to be limited to NGOs and similar institutions. For example, Apple Inc.′s network is known for its hybrid nature. Through adopting high relational and structural embeddedness with some of its network members, the firm intentionally keeps some suppliers “out of the circle” and at arms-length reach. These suppliers function as weak external ties and bring in radical ideas whenever it is needed (Satariano and Burrows, 2011). This network structure and operational excellence are what drive Apple′s success in the market. Based on network theory and research, it appears that EBP diffusion is more likely if the industry networks have high yet diverse relational structural embeddedness, and include some actors that adopted EBP. Cohesive and highly embedded networks may drive fast and smooth diffusion of EBP that have already penetrated into parts of the network. However, ensuring some weaker external ties and structural diversity is essential to sustain the inflow of such practices. Proposition 5. For firms to enjoy the maximum benefit of diffusion of EBP into their supplier network, firms need to maintain some weak external ties to bring in external innovation and new ideas. Thus, individual members and their relationships with weaker ties, those considered outside the network can play an essential role in bringing in new ideas and innovations (Granovetter, 1983). Highly embedded networks allow for diffusion of EBP, however there may also be much cohesiveness to overcome to develop new and innovative ideas. Therefore, these loosely linked network ties help to overcome this barrier to diffusion.

4. Discussion Networks have a greater environmental impact on most product′s environmental footprint than do the operations of the end manufacturer itself (Faruk et al., 2001; Walmart, 2012). Effectively managing a network is also a source of competitive advantage for organizations (Zacharia et al., 2009). While the importance and

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complexity associated with managing supplier networks effectively for EBP was recognized about two decades ago (Lamming and Hampson (1996), very little progress has been made in understanding how to improve supplier participation in EBP. Hence, understanding the network factors that influence firms to adopt EBP can make an important contribution to effective diffusion of the initiative throughout the desired nodes of the supplier network. This research utilized network theory to explain diffusion of EBP. Seven testable theoretical propositions were developed that highlight the impact of networks and network utilization on diffusion of environmental business practices. The key premise of these propositions is that structural and relational embeddedness interact with each other when influencing diffusion of EBP across the supply chain. One dimension of embeddedness cannot be considered independently from the other dimension when predicting the diffusion speed, range, and efficiency. Also, the level of collaboration, knowledge and resource sharing is key to determining the diffusion speed. 4.1. Theoretical implications As pointed out by other researchers, most network research in supply chains has focused on dyads or triads (Borgatti and Li, 2009; Galaskiewicz, 2011). The true medium of business exchange is wide and diverse networks rather than isolated dyads or triads interacting. A key function of networks is the flow or distribution of information (Borgatti and Halgin, 2011), much of which occurs naturally as part of a business exchange. Thus, network theory applied to supplier networks can have powerful explanatory power (Lamming et al., 2000; Harland and Knight, 2001). Once the important role of networks is more widely recognized, researchers can further advance network theory by developing a specific network topic, conducting empirical research, and suggesting possible approaches for firms to use in spreading EBP in their network. Proposition 2b for example presents an exciting opportunity for empirical testing. As stated, when both structural embeddedness and relational embeddedness of supplier networks are high, companies are willing to specifically invest in programs to enhance the

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diffusion of environmental business practices in their existing networks. Understanding the influence of embeddedness on an organizations ability to diffuse EBP or any other innovation could have potential benefits. Zacharia et al. (2009) propose that networks are a source of competitive advantage. Effective levels of collaboration and the ability to integrate supply chain partners into the network may facilitate network adoption. Suppliers that already feel engaged in a relationship are the best candidates for effective engagement in EBP, assuming that the products or services they provide are important contributors to the organization′s environment supply chain footprint. Structural embeddedness helps answer the question of how networks influence diffusion; while relational embeddedness helps answer the question of why networks influence diffusion. Organizational embeddedness helps explain both when and why suppliers are more likely to cooperate in EBP initiatives. Expanding on the application of extant theory, this paper examines impact of networks on the implementation of EBP from a wide and inclusive perspective. Further, this study′s contribution stems from its exclusive approach to explain EBP. The study moves beyond broadly discussing diffusion and management of ideas in networks to examine specific impacts of embeddedness on diffusion of EBP. As EBP have moved from innovative to mainstream, networks may play an increasingly important role in both late majority and laggard adoption of EBP. The relationship between embeddedness and diffusion of EBP may have some peculiarities that are discussed briefly below in managerial implication and future research. Propositions 1–4 addressed both how and why structural and relational embeddedness in networks influence the diffusion of EBP, while Proposition 5 specifically considers the contribution of importance of weak ties to diffusion of EBP. Future empirical testing that compared and contrasted the high–low combinations of embeddedness (Propositions 3 and 4) would be interesting and provide theoretical development. Is one type of embeddedness more effective in influencing certain behaviors than the other? If you can strengthen either the relational or structural embeddedness, which would be more effective? Fig. 7 combines Figs. 3–6

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Fig. 7. Supply chain network.

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to illustrate how these various types of networks can be linked into a single supplier network. A weak tie is added to the logistics service provider in the highly structurally and relationally embedded network, to show how such a weak tie may penetrate an organization. 4.2. Managerial implications The propositions developed here put forward that effective management of interfaces between network members fosters the diffusion of EBP. The spatial diffusion of EBP and other innovative business practices is facilitated by rapid, accurate transmission of knowledge and the ability to interact frequently and efficiently among different actors (Frenkel and Shefer, 1996). A firm that truly recognizes and utilizes the power of both relational and structural embeddedness will sustain a competitive advantage over those that operate as if in isolation. From a managerial standpoint, firms should be very attentive to the network structure in which they operate. It may not be possible to purposefully configure the network alone, but reflecting upon different network configurations and contributing to change in the network configuration may facilitate diffusion of EBP for all actors involved. Firms that optimize the level of density and relational embeddedness among actors may be able to effectively foster EBP among their supplier network. Including NGOs (Schneider and Wallenburg, 2012) and professional organizations in the network and collaborating with them to foster EBP may also be a valuable approach to enhancing the diversity of ideas and the number of ideas within the common frame of interest. Diffusing EBP through cultivating weak ties requires a conscious commitment to network building and design. Walmart′s founding of the sustainability consortium is an example of the conscious creation of a network to diffuse EBP (Walmart, 2009; Cheeseman, 2010). Though this example may be strongly mediated by Walmart′s high level of power over its suppliers who have been invited to join the consortium, it demonstrates the recognition of the potential of network membership to influence firm behavior. From an operating level, analysis of the focal firm′s network is an imperative initial step. As suggested by Lamming et al. (2000) and Harland et al. (2001), the network should be configured to consider the firm′s level of influence as well as whether the supply chain is very dynamic or routine in nature. In support of the firm′s strategy, buyers should consider how their suppliers are connected to their firm, other suppliers, and competitors in the network, and reflect upon the strength and pattern of these connections. Because operating level supply chain employees are often boundary spanners (Perrone et al., 2003), and contribute significantly to the organization′s relational capital with other supplier network members (Cousins et al., 2006), support of operating level employees is imperative for the development of social capital that facilitates adoption of EBP. Trying to affect the nature of the embeddedness may alter the level of organizational influence possible. Finally, it should be noted that even though the propositions suggest a direct link between embeddedness levels and diffusion of EBP, the path to diffusion of EBP from network embeddedness may not be direct or immediate. First, perceived advantages of EBP may be a key moderator in diffusion and adoption of EBP. Many new practices have uncertain outcomes (Kline and Rosenberg, 1986; Levine, 1980). Moreover, while this belief is changing, many firms are reluctant to adopt EBP due to a conventional perception that it creates more cost than benefit (Larson and Greenwood, 2004). Being motivated to adopt something may not always lead to the actual adoption. Depending on other mediating or moderating variables such as financial feasibility, pressure, experience, power, or other factors pertinent to TCE and institutional theory as discussed in Tate et al. (2011), the adoption process may be positively or negatively

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affected. Furthermore, since such adoption may require significant financial or human resource investments in new practices (Lee and Klassen, 2008), adoption of EBP may be hindered even if the network is configured to facilitate diffusion and is supported by behavioral network drivers. Therefore, managers need to have a broader view when analyzing the effects of their supplier network and setting expectations concerning the adoption. Uncovering other drivers or obstacles to EBP implementation would at least facilitate having more realistic and accurate expectations.

5. Future research A clear next step for future research is to test the proposed model or to individually test some of the hypotheses such as the combination of high and low embeddedness. The propositions formulated were developed so that they can be transformed into testable research hypotheses. Since the model examines networks, the authors suggest an in-depth study involving investigation of embeddedness levels of several networks and the impact of embeddedness on the diffusion of EBP. Secondary data may also be a reliable and complementary source when conducting empirical research on networks (Ahuja, 2000; Autry and Golicic, 2010). If accessible, longitudinal and statistical data concerning firm connections, network structure including density and relational embeddedness of business interactions may be analyzed in relation to diffusion of different EBP in the network over time. Understanding of the spread of common practices such as environmental certification may also be gathered from secondary data sources. Divergent research directions pertinent to the model are also possible. The premises of network theory are not limited to relational and structural embeddedness. Other factors such as network range (Reagans and Mcevily, 2003), network complexity and adaptivity (Pathak et al., 2007), social cognition (Borgatti and Foster, 2003) and capabilities for change management and network leadership may provide interesting venues to understand their impact on diffusion of EBP. Investigating various types of interdependence in addition to embeddedness may also be fruitful. Perceived interdependence of actors and the expectation that the exchange generates benefits for the actors involved are two key drivers of embedded networks (Gulati and Gargiulo, 1999). Conventional channel literature argues that power based on the suppliers’ dependence leads them to adopt their customers’ requirements more readily (Hunt and Nevin, 1974). However, other literature builds a case for more amicable and collaborative construct of interdependence, which leads network members to become more open to network influences, as a driving motive for suppliers’ response to the requirements of their customers (Holm et al., 1999; Mahapatra et al., 2010). Therefore, examining the impact of interdependence in the networks on the diffusion of EBP may reveal interesting results. Such research may also shed some light on the questions of how power diffuses and how various types of influence are diffused across networks. References Abbasi, M., Nilsson, F., 2012. Themes and challenges in making supply chains environmentally sustainable. Supply Chain Management: An International Journal 17 (5), 517–530. Ahuja, G., 2000. Collaboration networks, structural holes, and innovation: a longitudinal study. Administrative Science Quarterly 45 (3), 425–455. Anderson, J., Håkansson, H., Johanson, J., 1994. Dyadic business relationships within a business network context. Journal of Marketing 58 (4), 1–15. Andersson, U., Forsgren, M., Holm, U., 2002. The strategic impact of external networks: subsidiary performance and competence development in the multinational corporation. Strategic Management Journal 23 (11), 979–996.

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