The Effects of Online Review Platforms on Restaurant Revenue, Consumer Learning, and Welfare

Limin Fang ()
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Limin Fang: Strategy and Business Economics Division, Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada

Management Science, 2022, vol. 68, issue 11, 8116-8143

Abstract: This paper quantifies the effects of online review platforms on restaurant revenue and consumer welfare. Using a novel data set containing revenues and information from major online review platforms in Texas, I show that online review platforms help consumers learn about restaurant quality more quickly. The effects on learning show up in restaurant revenues. Specifically, doubling the review activity increases the revenue of a high-quality independent restaurant by 5%–19% and decreases that of a low-quality restaurant by a similar amount. These effects vary widely across restaurants’ locations. Restaurants around highway exits are affected twice as much as those in nonhighway areas, implying that reviews are more useful to travelers and tourists than locals. The effects also decline as restaurants age, consistent with the diminishing value of information in learning. In contrast, chain restaurants are affected to a much lesser degree than independent restaurants. Building on this evidence, I develop a structural demand model with aggregate social learning. Counterfactual analyses indicate that online review platforms raise consumer welfare much more for tourists than for locals. By encouraging consumers to eat out more often at high-quality independent restaurants, online review platforms increased the total industry revenue by 3.0% over the period from 2011–2015.

Keywords: consumer learning; online review platforms; random coefficient demand models; differentiated products (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:68:y:2022:i:11:p:8116-8143

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