Decision Sciences Journal
Volume 28, Number 3
Summer 1997
Complexity Factors and Intuition-based Methods for Facility
Network Design
Morgan Swink
Operations Management Department, School of Business, Indiana
University, Bloomington, IN 47405
E. Powell Robinson, Jr.
Department of Business Analysis & Research, College of Business
Administration, Texas A&M University, College Station, TX
77843-4217
ABSTRACT
Logistics managers frequently utilize decision support systems
(DSS) to make facility network design decisions. Many DSS do not
provide optimization capabilities, but instead rely on scenario
evaluation as a means for developing solutions. We experimentally
assessed the performances of decision makers, including experienced
managers, who used four variants of a scenario evaluation-based DSS
to solve realistically sized network design problems of varying
complexities. Complexity factors included DSS attributes, problem
size, network types, and demand dispersion patterns. Decision
makers' performances were assessed relative to optimal solutions.
Overall, the decision makers generated relatively high-quality
solutions using the DSS variants. The type of design problem solved
did not significantly impact problem-solving performance. However,
performance degraded and variability in solution quality escalated
as problem size was increased. The availability of incremental
solution cost improvement cues in the DSS significantly improved
solution quality and reduced performance variability. Iconic
graphic enhancements to the DSS did not consistently affect
performance. However, significant interactions existed among the
effects of DSS graphics capabilities, DSS information cues, and
problem attributes.
Subject Areas: Decision Support Systems, Facility Location,
and Logistics Planning.
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