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Price Effects in Online Product Reviews: An Analytical Model and Empirical Analysis

MIS Quarterly, Vol. 34, No. 4, pp. 809-831

53 Pages Posted: 12 Oct 2008 Last revised: 5 Aug 2014

Xinxin Li

University of Connecticut - Department of Operations & Information Management

Lorin M. Hitt

University of Pennsylvania - Operations & Information Management Department

Date Written: February 5, 2010

Abstract

Consumer reviews may reflect not only perceived quality but also the difference between quality and price (perceived value). In markets where product prices change frequently, these price-influenced reviews may be biased as a signal of product quality when used by consumers possessing no knowledge of historical prices. In this paper, we develop an analytical model that examines the impact of price-influenced reviews on firm optimal pricing and consumer welfare. We quantify the price effects in consumer reviews for different formats of review systems using actual market prices and online consumer ratings data collected for the digital camera market. Our empirical results suggest that unidimensional ratings, commonly used in most review systems, can be substantially biased by price effects. In fact, unidimensional ratings are more closely correlated with ratings of product value than ratings of product quality compared to reviews provided by more complex systems separating ratings into different components. Our findings suggest the importance for firms to account for these price effects in their overall marketing strategy and suggest that review systems could better serve consumers by explicitly expanding review dimensions to separate perceived value and perceived quality.

Keywords: online product reviews, review bias, price effects, empirical analysis, optimal pricing

JEL Classification: C23, C40, D42, D60, D80, L10, L86, M31

Suggested Citation

Li, Xinxin and Hitt, Lorin M., Price Effects in Online Product Reviews: An Analytical Model and Empirical Analysis (February 5, 2010). MIS Quarterly, Vol. 34, No. 4, pp. 809-831. Available at SSRN: https://ssrn.com/abstract=1282303 or http://dx.doi.org/10.2139/ssrn.1282303

Xinxin Li (Contact Author)

University of Connecticut - Department of Operations & Information Management ( email )

368 Fairfield Road
Storrs, CT 06269-2041
United States
(860) 486-3062 (Phone)

Lorin Hitt

University of Pennsylvania - Operations & Information Management Department ( email )

571 Jon M. Huntsman Hall
Philadelphia, PA 19104
United States
215-898-7730 (Phone)
215-898-3664 (Fax)

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