Benchmarking the utility theory: a data envelopment approach

Benchmarking the utility theory: a data envelopment approach PurposeThe purpose of this paper is to benchmark alternatives of decision problems that include risk and uncertainty considering different risk attitudes via a new data envelopment analysis (DEA) decision model.Design/methodology/approachA new utility function of strict bounds is applied in a data envelopment model to evaluate all possible stochastic alternatives (i.e. gambles). The amount of risk in the alternatives is measured by a newly introduced risk ratio (RR). Each alternative is considered as a decision making unit (DMU). The alternatives efficiency frontier is found via linear optimization of the DEA model.FindingsIn contrast to literature studies of binary decision alternatives, here, benchmarking is conducted to evaluate multiple decision alternatives with unbounded utility of the payoffs along with a new DEA decision model. Different surveys and studies have been used to validate the model. DEA could demonstrate the ability to uncover relationships that remain hidden for other methodologies. The resulting rankings remarkably conform to those elicited by subjects.Social implicationsIndividuals of different wealth backgrounds evaluate risky decision problems differently.Originality/valueThe paper contributes to the existing research by benchmarking multiple alternatives as compared to the literature research which usually assesses binary problems. Instead of using explicit utilities, the model implements the efficiencies along with a new utility function and a new RR. The introduction of DEA to such a decision field is found to be successful in benchmarking numerous alternatives under different risk attitudes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Benchmarking: An International Journal Emerald Publishing

Benchmarking the utility theory: a data envelopment approach

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1463-5771
DOI
10.1108/BIJ-11-2015-0105
Publisher site
See Article on Publisher Site

Abstract

PurposeThe purpose of this paper is to benchmark alternatives of decision problems that include risk and uncertainty considering different risk attitudes via a new data envelopment analysis (DEA) decision model.Design/methodology/approachA new utility function of strict bounds is applied in a data envelopment model to evaluate all possible stochastic alternatives (i.e. gambles). The amount of risk in the alternatives is measured by a newly introduced risk ratio (RR). Each alternative is considered as a decision making unit (DMU). The alternatives efficiency frontier is found via linear optimization of the DEA model.FindingsIn contrast to literature studies of binary decision alternatives, here, benchmarking is conducted to evaluate multiple decision alternatives with unbounded utility of the payoffs along with a new DEA decision model. Different surveys and studies have been used to validate the model. DEA could demonstrate the ability to uncover relationships that remain hidden for other methodologies. The resulting rankings remarkably conform to those elicited by subjects.Social implicationsIndividuals of different wealth backgrounds evaluate risky decision problems differently.Originality/valueThe paper contributes to the existing research by benchmarking multiple alternatives as compared to the literature research which usually assesses binary problems. Instead of using explicit utilities, the model implements the efficiencies along with a new utility function and a new RR. The introduction of DEA to such a decision field is found to be successful in benchmarking numerous alternatives under different risk attitudes.

Journal

Benchmarking: An International JournalEmerald Publishing

Published: Mar 6, 2017

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