Conclusion

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In their 2002 MIS Quarterly article, Webster and Watson (2002) stated, “the progress of information systems as a field is impeded because there are few published review articles” (p.13). This chapter contributes to the field by bringing together IOIS research and providing a starting point for work on emerging IOISs. This chapter summarizes significant independent variables, dependent variables, study focuses, research methods and theoretical approaches of 25 IOIS studies. (See Table 2.) We further analyzed significant independent variables found in IOIS research. (See Table 3.)

Chwelos et al.’s (2001) synthesis of EDI research and EDI adoption model test provide the hypothesis framing this research. Chwelos et al. hypothesized that constructs at organizational, technological, and inter-organizational levels facilitate IOIS adoption. This paper evaluates Chwelos et al.’s hypothesis by reviewing independent variables, from 25 empirical IOIS studies, found to significantly influence IOIS adoption and diffusion. This paper supports and extends Chwelos et al.’s hypothesis by applying it to an array of IOISs and to both adoption and diffusion.

In this review, significant independent variables fell into Chwelos et al.’s categories, however, a few variables fell into multiple categories (organizational and inter-organizational). As such, we extend Chwelos et al.’s hypothesis and propose that variables found to significantly influence IOIS adoption and diffusion also facilitate adoption and diffusion of emerging IOIS forms, such as varying forms of B2B electronic marketplaces.

Table 3 shows occurrences of independent variables influencing adoption and diffusion to be about equal. Fifty-five independent variable occurrences facilitate adoption, and 61 independent variable occurrences influence diffusion. Most variables with significant IOIS adoption and diffusion relationships are in the organizational category. The technological and inter-organizational categories have nearly equal occurrences of significant independent variables. External pressure, top management support, and relative advantage have been frequently proven to significantly influence IOIS adoption and diffusion.

The main limitation of this paper is the process by which we categorized the many significant independent variables in Table 3. We categorized the variables based on a comparison of Chwelos et al.’s category definitions to each variable’s definition from the studies. Enhancing this approach with Q-sort would have added more rigor to the categorization. Q-sort uses statistics to measure the areas of concurrence between experts.

Table 1 indicates that 59% of the reviewed work focuses on EDI. This is because EDI is more widespread and has been in existence longer than B2B EC, customer-oriented strategic systems and electronic markets. The field will benefit from further empirical investigations into the adoption and diffusion of the emerging types of IOISs. For example, Table 1 indicated one investigation of electronic market adoption and diffusion facilitators. This review provides a starting point for such investigations. This chapter guided a dissertation investigating electronic market adoption and diffusion facilitators (see Koch, 2003).

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