Persuading Risk-Conscious Agents: A Geometric Approach

Jerry Anunrojwong (), Krishnamurthy Iyer and David Lingenbrink ()
Additional contact information
Jerry Anunrojwong: Graduate School of Business, Columbia Business School, New York, New York 10027
David Lingenbrink: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853

Operations Research, 2024, vol. 72, issue 1, 151-166

Abstract: We consider a persuasion problem between a sender and a receiver where utility may be nonlinear in the latter’s belief; we call such receivers risk conscious . Such utility models arise when the receiver exhibits systematic biases away from expected utility maximization, such as uncertainty aversion (e.g., from sensitivity to the variance of the waiting time for a service). Because of this nonlinearity, the standard approach to finding the optimal persuasion mechanism using revelation principle fails. To overcome this difficulty, we use the underlying geometry of the problem to develop a convex optimization framework to find the optimal persuasion mechanism. We define the notion of full persuasion and use our framework to characterize conditions under which full persuasion can be achieved. We use our approach to study binary persuasion , where the receiver has two actions and the sender strictly prefers one of them at every state. Under a convexity assumption, we show that the binary persuasion problem reduces to a linear program and establish a canonical set of signals where each signal either reveals the state or induces in the receiver uncertainty between two states. Finally, we discuss the broader applicability of our methods to more general contexts, and we illustrate our methodology by studying information sharing of waiting times in service systems.

Keywords: Market Analytics and Revenue Management; Bayesian persuasion; information design; risk consciousness (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/opre.2023.2438 (application/pdf)

Related works:
Working Paper: Persuading Risk-Conscious Agents: A Geometric Approach (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:72:y:2024:i:1:p:151-166

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().