A Quantifiable Risky Decision Model: Incorporating Individual Memory into Informational Cascade

Fei Wang; Jiuchang Wei; Dingtao Zhao

doi:10.1002/sres.2294

A Quantifiable Risky Decision Model: Incorporating Individual Memory into Informational Cascade

Systems Research and Behavioral Science ◽

10.1002/sres.2294 ◽

2014 ◽

Vol 31 (4) ◽

pp. 537-553 ◽

Cited By ~ 2

Author(s):

Fei Wang ◽

Jiuchang Wei ◽

Dingtao Zhao

Keyword(s):

Decision Model ◽

Risky Decision ◽

Individual Memory ◽

Informational Cascade

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Benchmarking the utility theory: a data envelopment approach

Benchmarking An International Journal ◽

10.1108/bij-11-2015-0105 ◽

2017 ◽

Vol 24 (2) ◽

pp. 318-340 ◽

Cited By ~ 4

Author(s):

Doraid Dalalah ◽

Wasfi Al-Rawabdeh

Keyword(s):

Utility Function ◽

Decision Model ◽

Linear Optimization ◽

Decision Problems ◽

Risk Attitudes ◽

Data Envelopment ◽

Risky Decision ◽

Content Type ◽

Decision Making Unit ◽

Decision Alternatives

Purpose The 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/approach A 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. Findings In 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 implications Individuals of different wealth backgrounds evaluate risky decision problems differently. Originality/value The 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.

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