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Narratives and Valuations

Authors: Dor Morag; George Loewenstein;

Narratives and Valuations

Abstract

Although the significance of narrative thinking has been increasingly recognized by social scientists, very little empirical research has documented its consequences for economically significant outcomes. The current paper addresses this gap in one important domain: valuations. In three experiments, participants were given the opportunity to sell an item they owned (mug in Study 1, hat in Studies 2 and 3) using an incentive-compatible procedure (multiple price list). Prior to making selling decisions, participants were randomly assigned to either a narrative treatment, in which they were asked to tell the story of their item, or a list treatment, in which they were asked to list the characteristics of their item. The narrative treatment led to significantly higher selling prices and increased rates of participants refusing all offered prices. We further explore potential mechanisms, and the impact of different types of narratives, by analyzing self-reported classifications of, and employing natural language processing techniques on, participants’ narratives. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Funding for the studies came from Loewenstein’s personal research fund provided by Carnegie Mellon University. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01076 .

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Keywords

willingness to accept, ddc:330, experimental, narratives, decision-making, valuations

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Average
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