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Abstract
It is by now almost accepted as a stylized fact that offering deal promotion (such as via Groupon or LivingSocial) deteriorates local merchants’ online reputations (e.g., the average of Yelp review ratings). However, in this paper we show that the stylized fact is not true in certain circumstances. We theorize that the valence and volume of prior reviews can play an important moderating role in the effect of deal promotion. Empirically, we show that restaurants with a relatively low prior average rating and a relatively small review volume have improved their online reputations by offering Groupon promotion. The proportion of such restaurants is substantial. The findings are robust to multiple identification strategies and econometric specifications. The results underscore the substantial heterogeneity in the effect of deal promotion on local merchants’ online reputations. Merchants need to understand the moderating role of prior reviews (e.g., the valence and volume of prior reviews) and design appropriate strategies to maximize the returns from offering deal promotion.
Acknowledgments
The author is grateful to the editor in chief and four anonymous reviewers who provided constructive comments and suggestions on earlier versions of this article. The author is also grateful to the HEC Foundation and HEC Leadership Center for financial support.
Notes
4. The author is grateful to an anonymous reviewer for pointing out the additional mechanism through which the relatively less favorable valence and small volume of prior reviews can positively moderate the effect of deal promotion.
5. They are Atlanta, Boston, Chicago, Dallas, Detroit, Houston, Las Vegas, Los Angeles, Miami, New Orleans, New York, Orlando, Philadelphia, San Diego, San Francisco, San Jose, Seattle, Tallahassee, and Washington, DC.
6. We use the restaurant information (e.g., name, street address, zip code, and phone number) to search the restaurants’ profiles on Yelp.com.
7. In order for a restaurant’s Yelp profile to be confidently identified, we require that (a) the restaurant deal must have a single physical location for redemption, and (b) the restaurant must have only a single Yelp profile.
8. In the preliminary study we exclude the deals from restaurants whose Yelp profiles indicate that they had closed by February 2013. Including these closed restaurants produces qualitatively similar results. We include them in the main analysis as a robustness check.
9. The figures 3.5 and 20 are just one set of cutoffs. We use different sets of cutoffs and find similar results.
10. In fact we collect more pretreatment covariates beyond those presented in . We do not include the other covariates in the PSM because they are less associated with the decision of offering a Groupon promotion.
11. We also fit a logistic model and the results are similar.
Additional information
Notes on contributors
Xitong Li
Xitong Li ([email protected]) is an assistant professor in the department of Information Systems and Operations Management, HEC Paris, France. He received his Ph.D. in management from the MIT Sloan School of Management, and his Ph.D. in engineering from Tsinghua University. His research interests include the economic and social impacts of using online data and information, and innovative technologies using online data and services. His research has appeared, or is forthcoming, in Journal of Management Information Systems, ACM Transactions on Internet Technology, IEEE Communications Magazine, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Systems, Man, and Cybernetics, and other leading journals and conference proceedings. He won the Best Paper award at the 46th Hawaii International Conference on System Sciences (HICSS).