In today's increasingly competitive global marketplace, companies create value and ensure survival based on their ability to manage the complex web of suppliers and customers comprising their value chain. At the heart of this process is the accurate, timely, and complete disclosure of information between value chain partners to enables the types of coordinated action mandated by exchange partners (Handfield and Nichols, 1999). This coordinated action is facilitated by inter-organizational systems (IOS) such as EDI (electronic data interchange), ERP (enterprise resource planning), and VMI (vendor managed inventory), which act as electronic information conduits between partners. IOS

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Journal of Business & Industrial Marketing 20/4/5 (2005) 200-210

e Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603873]

systems commonly include hardware, software, network facilities, procedures and rules, data/databases, and knowledge exchange between two or more firms (Barrett and Konsynski, 1982). As such, IOS are complex, involving substantive changes in the operation of individual firms, with requisite adoption extending to encompass other networked firms.

Unfortunately, IOS are a two edged sword and most of the advantages of these systems are also its major drawbacks. Specifically, sharing between organizational units decreases flexibility in the network by increasing idiosyncratic investment and increases firm vulnerability to potentially unethical behaviors of both partners and outsiders who might effectively breach system security (Emmelhainz, 1990). Add to this the tangible and intangible costs of adoption, including acquisition costs and short-term productivity declines, and it is easy to see why adoption of such systems is problematic (Emmelhainz, 1990; Iacovou et al., 1995). Now add to these difficulties by imagining the inter-organizational effort needed to encourage adoption by networked firms and the potential power struggle between them and you get some idea of the difficulties encountered.

Extant research on organizational adoption suggests that organizational adoption is more complex and this complexity increases as the number of firms affected increases (e.g. Tornatzky and Fleischer, 1990; Wang and Tsai, 2002; Srinivasan et al., 2002). The very nature of inter-organizational adoption adds an additional layer of

Journal of Business & Industrial Marketing 20/4/5 (2005) 200-210

e Emerald Group Publishing Limited [ISSN 0885-8624] [DOI 10.1108/08858620510603873]

Angela Hausman, Wesley J. Johnston and Adesegun Oyedele complexity to the organizational process, since adoption in this context (termed cooperative adoption) is often initiated by a major value chain partner (the focal firm) who encourages other networked firms (the recipient firms) to adopt an IOS system to facilitate the exchange and flow of transaction information (Barber, 1991; Hausman and Stock, 2003). In networks, we might more accurately model this as focal firms, recognizing that several firms may band together to encourage adoption among a group of recipient firms. Effective cooperative innovation adoption requires recipient firms implement the system without creating conflict that might damage the relationship between recipients and focal firms.

Network theory argues that each firm is embedded within multiple overlapping networks, such that changes in one network impact their functionality and relationship with firms in other networks to which they are members. This web of relationships is analogous to an ecosystem, in that changes tend to ripple through the system affecting the appropriateness of individual strategic decisions. Additionally, in a focal firm-initiated adoption, the recipient firms may perceive some level of pressure as the focal firm uses its leverage to influence their adoption (Pitts, 1991) or members lobby for alternate strategies. Since networks are self-organizing systems, where cooperation occurs through the successful negotiation of numerous local internal and external relationships, individual firms have the ability to either acquiesce to the demands of the focal firm or reject those demands (Ritter et al., 2004). Recipient firms who are "coerced" into cooperation by stronger partners may not be totally committed to the implementation of the system and their lack of commitment can hinder networked firms from realizing the system's full benefit. Moreover, use of leverage by the focal firm (or other network firms) might negatively impact the relationship between one or more recipient firms; a danger that might outweigh the benefits of IOS adoption.

The dominant paradigm in the diffusion/adoption literature involves the role of information exchange in driving the process, including the bass model (Mahajan et al., 1990) and Rogers's (1995) treatment of adoption. These models presume awareness of an innovation is a major limiting factor in its adoption and extensive research has investigated factors that promote the flow of this awareness to non-adopters, as well as adopter traits and product features that promote adoption. Certainly, awareness of the innovation and its relative advantages contribute significantly to our understanding of the adoption decision by the focal firm, but do not go far enough in explaining how the innovation moves from the focal firm to those recipient firms whose adoption is needed. Less research has fully developed the role of inter-organizational and social forces between actors involved in the adoption process, although this aspect is alluded to in the Bass model through the interpersonal communication construct. Maute and Locander (1994) contend that adoption is better understood by looking at these social forces.

Prior research associated social aspects of adoption has been fragmented, focusing on evaluating a relatively small number of variables that potentially impact the adoption of specific IOS, while ignoring the breadth of forces acting on this adoption. In addition, while existing models define intrafirm variables affecting the decision, dyadic and network factors impacting adoption of these systems have been largely

ignored. Finally, existing models tend to be static and fail to model the sustained use of the innovation (implementation) and the ultimate effect of the process on the network. To fill this void, a multi-level model of adoption is needed, incorporating empirically tested financial, economic, and interpersonal variables that may influence the decision to adopt and implementation of an innovation (simply referred to as adoption) proposed by a focal firm. This paper develops a model to facilitate understanding of the first level of this model, the network level.

There are two major advantages to the model developed in this paper over existing ones. First, the model is more holistic, proposing relationships between a very broad number of potential influential variables acting at the network interface.. Second, the model proposes relationships affecting the adoption process within the network, recognizing the effect of these variables on multiple firms and how that effect might be different in the network context than within an individual firm. In developing this framework, we integrate work on inter-organizational adoption (cf. Tornatzky and Fleischer, 1990; Hausman and Stock, 2003; Wang and Tsai, 2002; Srinivasan et al., 2002), with insights from other types of adoption and innovation literature, especially those alluding to the social nature of adoption like, Maute and Locander (1994) and Rogers (1995). These perspectives are combined with other adoption research (both in organizational and consumer adoption) and empirical evidence from the inter-organizational adaptation and relationship literatures (cf. Anderson and Weitz, 1992; Anderson et al., 1994; Heide and John, 1990; Venkatesh et al., 1995; Wilson, 1995).

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