Translating risk perception for standard risk analyses

Thomas J. Monroe, Mario G. Beruvides

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

It is well established that there is a difference between how people actually make decisions when faced with choices involving uncertainty (i.e., risk) and how classical risk models expect decisions to be evaluated. Typically, these two paradigms have been handled separately under positive behavior-based decision theories, such as Prospect Theory, which accounts for intuition, and under normative economic theories, such as expected utility, which yields the expected value rule of probability times outcome. The Entropy Decision Risk Model (EDRM) provides a translation between the positive decision-making under uncertainty (DMUU) domain and the normative domain. This paper reviews the foundations of EDRM and then provides several sample applications to a number of real-world examples involving complex choices of gains and losses, as well as choices involving extremely small probabilities. Specifically, it demonstrates that EDRM can be used to translate subject perception of risk into terms of objective probabilities, thereby permitting analysis using standard tools, and then back again into the decision-maker’s frame of reference.

Original languageEnglish
Title of host publicationProceedings of the 2020 IISE Annual Conference
EditorsL. Cromarty, R. Shirwaiker, P. Wang
PublisherInstitute of Industrial and Systems Engineers, IISE
Pages730-735
Number of pages6
ISBN (Electronic)9781713827818
StatePublished - 2020
Event2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020 - Virtual, Online, United States
Duration: Nov 1 2020Nov 3 2020

Publication series

NameProceedings of the 2020 IISE Annual Conference

Conference

Conference2020 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2020
CountryUnited States
CityVirtual, Online
Period11/1/2011/3/20

Keywords

  • Decision making under uncertainty
  • Entropy
  • Information Theory
  • Intuition
  • Prospect Theory
  • Risk

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