Acceptance of information technology: User acceptance model for expert systems.

Abstract

Expert Systems are a type of Information Systems that explicitly embody expert knowledge and provide advice that rivals human experts. These systems pose fundamental challenges for management and may potentially have a profound impact in the workplace. Understanding the role of user acceptance in the process of implementing systems within organizations is of great importance to researchers and practitioners because user acceptance is a pivotal factor in determining the success or failure of the system. Based on the analysis and synthesis of literature that spans several fields, a model is developed to improve our understanding and prediction of user acceptance of Expert Systems. Using the Theory of Reasoned Action as an organizing framework, several hypotheses were developed. A questionnaire was developed to measure the variables and test the hypotheses of the model. Using a sample of 94 users and non-users from two of the largest accounting firms in the U.S., the model was tested using multiple regression techniques. The results confirmed several hypotheses. Intentions were the only determinant of the frequency of system use. Intentions were associated with social norms encouraging system use. Social norms were associated with beliefs regarding management and peer pressure to use the system. Beliefs regarding the impacts of system use on job performance and valued skills were associated with attitudes to use the system. Beliefs regarding the impacts of system use on valued skills were associated with intentions to use the system, controlling for the effect of attitudes. Ease of system use was associated with beliefs of impacts of system use on job performance and on attitudes towards system use. Individual characteristics, other than age, had no significant association with beliefs. Other hypotheses were not confirmed. General attitudes were not found to associate with intentions to use the system, however, cognitive attitudes, a subset of attitudes, were found to associate with intentions to use the system. The data show that the much anticipated fearful reactions by employees did not materialize. The findings are also consistent with the view that the role of attitudes and social norms in influencing use and intentions depends on the degree of volitional control over the behavior. The model may also be used as a useful tool to understand the process of user acceptance for technologies that pose challenges similar to the ones posed by Expert Systems.