Future research

Obviously, one of the most pressing issues is empirical testing of proposed relationships. Toward that end, we are planning a two-step approach, the first qualitative and the second

quantitative. The use of grounded theory to further develop the model while simultaneously testing the model appears appropriate (Glaser and Strauss, 1967). By using multiple informants representing firms both within the network and across networks this methodology achieves both improved specificity and generalizability.

The first step is designed to capture intricacy in the proposed relationships, specifically potential mediator/ moderator relationships between proposed variables and cooperative adoption. For example, the perceived benefit of the innovation may be influenced by the extent of the prospective adopter's involvement in the network. For example, a supplier or recipient firm with strong social ties with a focal firm may perceive the benefit of an innovation recommended by the focal firm as very high, due the high level of trust that may have been cultivated over a long period of time. Moreover, as suggested earlier, trust and communication may be related in some way, yet is not modeled in order to ensure the parsimony of the model. There may be additional interrelationships among modeled variables that have not been elucidated in extant literature. Further, qualitative data collection is designed to capture context factors affecting these relationships.

The final rationale for including qualitative data is to ensure modeling of all major factors impacting cooperative adoption. External variables acting on the network may affect cooperative adoption are one example that appears salient. Specifically, the response of customers and suppliers outside the focal network may impact the decision. There are also other variables mentioned in this discussion that have not been specifically modeled, such as social capital. Thus, despite efforts to develop a holistic model, the result is suboptimal. Quantitative data collection will further test proposed relationships, quantify the impact of proposed factors on cooperative adoption, and tease out additional contextual factors.

Another pressing need is to develop an understanding of the specific factors affecting implementation and continued use of the innovation. It is possible these are some of the same factors involved in the adoption process, but there may be additional factors that become critical at this stage in the process or the relative importance of proposed factors might shift during the implementation stage. Given the criticality of implementation for sustained benefit from the innovation, an understanding of these factors is important.

This study has, as promised, developed one level of the multilevel model for understanding cooperative adoption in networked organizations. Another level is at the inter-organizational level, where some firms may be promoting adoption while other firms lobby for other innovative solutions or the status quo. The question of how these political and social dynamics affect the cooperative process is unclear. Certainly, some of the same factors function in the inter-organizational interface, but how these affect and are affected by network level forces requires further development.

The next level in this multilevel model is the organizational level and several studies attempt to model influential variables at this stage (cf. Gatignon and Robertson, 1989; Frambach and Schillewaert, 2002). These models have not been empirically tested and there may be additional variables acting within the organization affecting implementation, which is not well incorporated into these models. The final level, the individual level appears to have received the most

Angela Hausman, Wesley J. Johnston and Adesegun Oyedele conceptual development and empirical testing of the model components. Thus, testing at this level is not deemed necessary.

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