Individual Differences and Decision-Making Using Various Levels of Aggregation of Information

Abstract:

This research investigated the effects of aggregation level on decisionmaking performance and confidence. The study made use of experienced territory managers as subjects. As part of their regular job responsibilities, they had all carried out a task closely resembling the one in this experiment. The research sought to identify patterns of decision-making suggesting that individual differences play an important role. With an average of 6.8 years of experience, 104 territory managers in a manufacturing firm planned the coming year’s product distribution. Each manager received reports for two hypothetical territories that differed in their level of aggregation. Confidence in their plans was related to experience and to decisionmaking style, but not to preference. Decision-makers almost always preferred detailed data, while summary data appeared to better serve heuristic planners and detailed data better served analytic planners.

Key Words and Phrases::

• Cognitive styles
• aggregation of information
• confidence in decision-making

Additional information

Notes on contributors

Albert L. Lederer

Albert L. Lederer is an Assistant Professor in the Joseph M. Katz Graduate School of Business at the University of Pittsburgh. He has a Ph.D. in Industrial and Systems Engineering from the Ohio State University, an M.S. in Computer and Information Sciences from Ohio State, and a B. A. in Psychology from the University of Cincinnati. He has spent over ten years in industry in the mis field and has published articles on mis in the MIS Quarterly, Information and Management, Sloan Management Review, Interfaces, Journal of Systems Management, and several other journals. He currently serves as the consulting editor for the new journal, Computers in Personnel.

George L. Smith

George L. Smith, Jr. is Professor and Chair of the Department of Industrial and Systems Engineering at the Ohio State University. He has a B.S.I.E. degree from Pennsylvania State University, M.S. degrees in Industrial Engineering and in Psychology from Lehigh University, and a Ph.D. in Industrial Engineering and Management from Oklahoma State University. He is a Fellow of the Human Factors Society and the Institute of Industrial Engineers. Dr. Smith is the author of Work Measurement: A Systems Approach, and has taught and practiced professionally in the areas of work measurement, human performance, work design, and labor management.