Decision Sciences Journal
Volume 29, Number 1
Winter 1998
A Simulation of Partial Information Use in Decision Making: Implications
for DSS Design
Ahmer S. Karim
School of Business, University of San Diego, San Diego,
CA 92110-2492
James C. Hershauer
Department of Management, College of Business, Arizona State University,
Tempe, AZ 85287-4006
William C. Perkins
Accounting and Information Systems, School of Business, Indiana University,
Bloomington, IN 47405
Abstract: Information matrices are often the output produced by a
decision support system. These matrices are a common method for expressing
a decision situation under different decision-making scenarios. The decisions
involved in designing a decision support system to generate the information
matrix are important and involve several cost and benefit components. A
designer needs guidance in making effective design decisions in this context.
Such guidance can be provided by considering the relationships among specific
design decisions, costs, and benefits. The general objective of this study
is to provide a comprehensive framework for this purpose. This study is
the first to develop and present a comprehensive cost-benefit framework
for evaluating design decisions for a variety of scenarios.
The specific objective of this research is to provide guidance regarding
the number of available information dimensions to incorporate in a computer-based
decision aid. Simulation experiments are conducted with a completely specified
model based on the cost-benefit framework (including needed assumptions)
to evaluate how many information dimensions to include for a specific information
matrix size to achieve a balance between information use costs and decision
quality. Based upon extensive simulation analyses for a hypothetical decision
maker, the practical guideline found for designers is to include only the
top half of the relevant information dimensions in any specific decision
support system. Over a large number of repeating choice decisions, the savings
in cognitive effort and information gathering costs clearly offset relatively
minor losses in decision quality.
Subject Areas: Computer-based Decision Aids, Decision Processes,
Decision Support Systems, Human Information Processing, and Simulation Methodology.
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