Knowledge that Transforms

An important management question today is whether the anticipated economic benefits of Information Technology (IT) are being realized. In this paper, we consider this problem to be measurement related, and propose and test a new process-oriented methodology for ex post measurement to audit IT impacts on a strategic business unit (SBU) or profit center's performance. The IT impacts on a given SBU are measured relative to a group of SBUs in the industry. The methodology involves a two-stage analysis of intermediate and higher level output variables that also accounts for industry and economy wide exogenous variables for tracing and measuring IT contributions. The data for testing the proposed model were obtained from SBUs in the manufacturing sector. Our results show significant positive impacts of IT at the intermediate level. The theoretical contribution of the study is a methodology that attempts to circumvent some of the measurement problems in this domain. It also provides a practical management tool to address the question of why (or why not) certain IT impacts occur. Additionally, through its process orientation, the suggested approach highlights key variables that may require managerial attention and subsequent action.

While computer training is widely recognized as an essential contributor to the productive use of computers in organizations, very little research has focused on identifying the processes through which training operates, and the relative effectiveness of different methods for such training. This research examined the training process, and compared a behavior modeling training program, based on Social Cognitive Theory (Bandura [Bandura, A. 1977. Self-efficacy: Toward a unifying theory of behavioral change. Psych. Rev. 84(2) 191–215; Bandura, A. 1978. Reflections on self-efficacy. Adv. Behavioral Res. Therapy 1 237–269; Bandura, A. 1982. Self-efficacy mechanism in human agency. Amer. Psychologist 372 122–147; Bandura, A. 1986. Social Foundations of Thought and Action. Prentice-Hall, Englewood Cliffs, NJ.]), to a more traditional, lecture-based program. According to Social Cognitive Theory, watching others performing a behavior, in this case interacting with a computer system, influences the observers' perceptions of their own ability to perform the behavior, or self-efficacy, and the expected outcomes that they perceive, as well as providing strategies for effective performance. The findings provide only partial support for the research model. Self-efficacy exerted a strong influence on performance in both models. In addition, behavior modeling was found to be more effective than the traditional method for training in Lotus 1-2-3, resulting in higher self-efficacy and higher performance. For WordPerfect, however, modeling did not significantly influence performance. This finding was unexpected, and several possible explanations are explored in the discussion. Of particular surprise were the negative relationships found between outcome expectations and performance. Outcome expectations were expected to positively influence performance, but the results indicated a strong negative effect. Measurement limitations are presented as the most plausible explanation for this result, but further research is necessary to provide conclusive explanations.

The Technology Acceptance Model and two variations of the Theory of Planned Behavior were compared to assess which model best helps to understand usage of information technology. The models were compared using student data collected from 786 potential users of a computer resource center. Behavior data was based on monitoring 3,780 visits to the resource center over a 12-week period. Weighted least squares estimation revealed that all three models performed well in terms of fit and were roughly equivalent in terms of their ability to explain behavior. Decomposing the belief structures in the Theory of Planned Behavior provided a moderate increase in the explanation of behavioral intention. Overall, the results indicate that the decomposed Theory of Planned Behavior provides a fuller understanding of behavioral intention by focusing on the factors that are likely to influence systems use through the application of both design and implementation strategies.