The purpose of this research is to examine the possibility of distinguishing between adopters and nonadopters when conceptualizing the drivers of the decision to adopt technologically based innovations. A second research objective is to examine factorial validity through the assessment of the explanatory power of the investigated conceptualization. In the pursuit of these objectives, the theory of bounded rationality represents the underlying theoretical framework, and Internet banking (IB) represents the nomological framework, in which two alternative conceptualizations, one for IB adopters and a second for nonadopters, are considered. “Intention to adopt” and “adoption” are the criterion variables, respectively.To meet the objectives of the study, two different populations are examined: adopters of IB and nonadopters. The former was used to examine the hypothesized framework for predictive validity against actual adoption; the latter was used to examine the predictive validity regarding intention to adopt. To collect data from IB adopters, the four leading banks, which account for approximately 73% of adopters, agreed to place a link to a Web-based questionnaire at the log-in page of their IB system inviting customers to participate in the study. Through this process, 858 useable questionnaires were produced. To reach the nonadopters population, a convenience sample of executive M.B.A. students from two leading Greek universities was employed. Respondents from this sample were screened to ensure that they had never used IB. This process yielded 418 useable questionnaires from the nonadopters population.A major finding from this investigation is that the decision to adopt improves the understanding of adopters regarding the benefits delivered by an innovation. Consequently, they hold a precise, less ambiguous perception of how specific innovation attributes translate into benefits. Hence, when recalling the decision process through which they adopted an innovation, adopters relate specific innovation attributes, including specific benefits received. This situation is displayed in the ability of a direct, first-order model to capture the relationships between specific innovation attributes and the adoption decision. In contrast, nonadopters, having no direct experience with the innovation, lack this familiarity. They require a significantly greater amount of information in order to associate innovation attributes with potential benefits. The intangibility of technologically based service innovation further increases a nonadopter’s need for information. However, this increased need for information renders nonadopters subject to cognitive strain, which causes them to aggregate innovation attributes into more abstract constructs. That aggregation was displayed in the ability of a second-order model to capture the relationships between specific innovation attributes and the nonadopters’ intention to adopt the innovation in the future. In both occasions though, the instrumental drivers of adoption represent the most powerful explicators of the adoption decision. From a practitioner’s perspective, this study shows that managers can structure the content of their communication to facilitate the rise of societal drivers, but they should avoid relying on such elements to quicken the pace of the adoption rate. Rather, at the core of communication campaigns, practitioners should place brief and clear claims demonstrating the instrumental arguments in favor of the adoption decision
