Title: "Relative Risk Value Models"
Authors: Jianmin Jia Chinese University of Hong Kong and James Dyer University of Texas
Date: May 1996
Status: accepted for publication European Journal of Operational Research

In this paper we propose a relative risk-value model and derive a relative measure of risk for the lotteries with positive-outcomes. Under a condition called relative risk independence, a decision could be made by explicitly trading off between the relative measure of risk and a measure of value, which can either be consistent with some expected utility models or represent nonexpected utility preferences. Specifically, this type of risk-value model is associated with power (or linear plus power) and logarithmic (or linear plus logarithmic) functions. We address some prescriptive and descriptive implications of our relative risk-value framework, and show that our generalized relative risk-value model is very flexible for modeling individuals' preferences and can explain many decision paradoxes.

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