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Reviews and self-selection bias with operational implications

Chen, Ningyuan, Li, Anran ORCID: 0000-0001-7001-2240 and Talluri, Kalyan (2021) Reviews and self-selection bias with operational implications. Management Science, 67 (12). pp. 7472-7492. ISSN 0025-1909

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Identification Number: 10.1287/mnsc.2020.3892

Abstract

Reviews for products and services written by previous consumers have become an influential input to the purchase decision of customers. Many service businesses monitor the reviews closely for feedback as well as detecting service flaws, and they have become part of the performance review for servicemanagers with rewards tied to improvement in the aggregate rating. Many empirical papers have documented a bias in the aggregate ratings, arising because of customers' inherent self-selection in their choices and bounded rationality in evaluating previous reviews. Although there is a vast empirical literature analyzing reviews, theoretical models that try to isolate and explain the bias in ratings are relatively few. Assuming consumers simply substitute the average rating that they see as a proxy for quality, we give a precise characterization of the self-selection bias on ratings of an assortment of products when consumers confound ex ante innate preferences for a product or service with ex post experience and service quality and do not separate the two. We develop a parsimonious choice model for consumer purchase decisions and show that the mechanism leads to an upward bias, which is more pronounced for niche products. Based on our theoretical characterization, we study the effect on pricing and assortment decisions of the firm when potential customers purchase based on the biased ratings. Our results give insights into how quality, prices, and customer feedback are intricately tied together for service firms.

Item Type: Article
Additional Information: Funding Information: History: Accepted by David Simchi-Levi, operations management. Funding: The research of N. Chen is partly supported by the Natural Sciences and Engineering Research Council [Discovery Grant RGPIN-2020-04038]. Publisher Copyright: © 2021 INFORMS Inst.for Operations Res.and the Management Sciences. All rights reserved.
Divisions: Management
Date Deposited: 19 Mar 2024 14:27
Last Modified: 14 Jun 2024 07:42
URI: http://eprints.lse.ac.uk/id/eprint/122421

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