Assessing Expert Systems Impact on Users’ Jobs

Abstract:

A comprehensive list of ten major expert systems (ES) related factors likely to affect users’ jobs has been defined, including problem importance, problem difficulty, developer skill, domain expert quality, user characteristics, user satisfaction, shell quality, user involvement, management support, and system usage. Impact on the job has been defined in terms of eleven items dealing with changes in job importance, amount of work, accuracy requirements, skills needed, job appeal, feedback about performance, freedom in how to do the job, opportunity for advancement, job security, relation with peers, and job satisfaction. Data were collected on sixty-nine expert systems developed through IBM’s Corporate Manufacturing Expert Systems Project Center in San Jose, California. The results show that the major variables having the most impact on users’ jobs are problem importance, problem difficulty, domain expert quality, user satisfaction with the ES, shell quality, and user involvement in ES development. Based on the results, recommendations are made for corporate and ES development managers to increase the likelihood that ES will have a desirable impact on users’ jobs.

Key Words and Phrases::

• expert systems
• job impact of technology
• success factors

Additional information

Notes on contributors

Youngohc Yoon

Youngohc Yoon is an Assistant Professor in the Department of Computer Information Systems at Southwest Missouri State University. She received her M.S. from the University of Pittsburgh and her Ph.D. from the University of Texas at Arlington. She has recently published articles in the Journal of Neural Network Computing, Data Bases, Information and Management, Journal of Operation Research Society, and Expert Systems. Dr. Yoon is a member of the Decision Sciences Institute, International Neural Network Society, American Association for Artificial Intelligence, ACM, SIGBDP, and IEEE Computer Society.

Tor Guimaraes

Tor Guimaraes holds the J.E. Owen Chair of Excellence in Information Systems at Tennessee Technological University. He has a Ph.D. in MIS from the University of Minnesota. He was a Professor and Chairman of the MIS Department at St. Cloud State University and earlier was an Assistant Professor at Case-Western Reserve University. He has spoken at numerous professional meetings and consulted with many leading organizations including TRW, American Greetings, AT&T, IBM and the D.O.D. He has published many articles in Information Systems Research, Communications of the ACM, MIS Quarterly, Decision Sciences, OMEGA, Computers and Operations Research, Information and Management, and Database.