Decision Analysis with Geographically Varying Outcomes: Preference Models and Illustrative Applications

Jay Simon (), Craig W. Kirkwood () and L. Robin Keller ()
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Jay Simon: Defense Resources Management Institute, Naval Postgraduate School, Monterey, California 93943
Craig W. Kirkwood: W. P. Carey School of Business, Arizona State University, Tempe, Arizona 85287
L. Robin Keller: The Paul Merage School of Business, University of California, Irvine, California 92697

Operations Research, 2014, vol. 62, issue 1, 182-194

Abstract: This paper presents decision analysis methodology for decisions based on data from geographic information systems. The consequences of a decision alternative are modeled as distributions of outcomes across a geographic region. We discuss conditions that may conform with the decision maker's preferences over a specified set of alternatives; then we present specific forms for value or utility functions that are implied by these conditions. Decisions in which there is certainty about the consequences resulting from each alternative are considered first; then probabilistic uncertainty about the consequences is included as an extension. The methodology is applied to two hypothetical urban planning decisions involving water use and temperature reduction in regional urban development, and fire coverage across a city. These examples illustrate the applicability of the approach and the insights that can be gained from using it.

Keywords: decision analysis; geographic information systems; multiattribute utility; multiattribute value; additive independence; preferential independence; homogeneity (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:62:y:2014:i:1:p:182-194

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