Knowledge that Transforms

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.

AbstractContrary to the stereotype that the period between CEOs is a hiatus, interim and acting executives serve during an important strategic window. A model is presented to illustrate the dynamics of short‐term leadership, including the precipitating circumstances for the temporary administration, the tasks of short‐term leadership, and the moderating factors seen to affect the selection and success of the next chief executive. Researchers and practitioners are urged to consider more carefully the potential that a well‐managed interregnum has to repair damage from a traumatic departure, buffer between administrations, and prepare the organization to accept and work with new leadership. © 1995 by John Wiley & Sons, Inc.

Parallel streams of theory and research regarding entrepreneurship and careers has led to a dearth of comprehensive theories regarding the careers of entrepreneurs. This article describes four core dimensions of theory that are essential in developing a comprehensive theory of entrepreneurial careers: (1) a theory of career choice; (2) a theory of career socialization; (3) a theory of career orientation; and (4) a theory of career progression from entry to exit. A general model is presented that articulates various aspects of theory building along each of these four dimensions. Implications for both theory and practice regarding entrepreneurial careers is also discussed.

This paper Integrates three major traditions of economic thought into a model of entrepreneurial decision making. Several testable hypotheses are formulated, and the model Is estimated using a 33-year sample of aggregate time-series data for the U.S.