A review of the predictors, linkages, and biases in IT innovation adoption research
We present a review and analysis of the rich body of research on the adoption and diffusion of IT-based innovations by individuals and organizations. Our review analyzes 48 empirical studies on individual and 51 studies on organizational IT adoption published between 1992 and 2003. In total, the sample contains 135 independent variables, eight dependent variables, and 505 relationships between independent and dependent variables. Furthermore, our sample includes both quantitative and qualitative studies. We were able to include qualitative studies because of a unique coding scheme, which can easily be replicated in other reviews. We use this sample to assess predictors, linkages, and biases in individual and organizational IT adoption research. The best predictors of individual IT adoption include Perceived Usefulness, Top Management Support, Computer Experience, Behavioral Intention, and User Support. The best predictors of IT adoption by organizations were Top Management Support, External Pressure, Professionalism of the IS Unit, and External Information Sources. At the level of independent variables, Top Management Support stands as the main linkage between individual and organizational IT adoption. But at an aggregate level, two collections of independent variables were good predictors of both individual and organizational IT adoption. These were innovation characteristics and organizational characteristics. Thus, we can consistently say that generic characteristics of the innovation and characteristics of the organization are strong predictors of IT adoption by both individuals and organizations. Based on an assessment of the predictors, linkages, and known biases, we prescribe 10 areas for further exploration.
Dead Or Alive? The Development, Trajectory And Future Of Technology Adoption Research
Research on individual-level technology adoption is one of the most mature streams of information systems (IS) research. In this paper, we compare the progress in the area of technology adoption with two widely-researched streams in psychology and organizational behavior: theory of planned behavior and job satisfaction. In addition to gauging the progress in technology adoption research, this allows us to identify some fruitful areas for future research. Based on our comparison, we conclude that there has been excellent progress in technology adoption research. However, as a next step, we call for research focused on interventions, contingencies, and alternative theoretical perspectives (to the largely social psychologybased technology adoption research. Also, we believe it would be important to use the comparisons discussed here as a basis to develop a framework-driven set of future research directions to guide further work in this area.
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