IS Atlas
mksci·2017년 8월 21일

The Effect of Calorie Posting Regulation on Consumer Opinion: A Flexible Latent Dirichlet Allocation Model with Informative Priors

Dinesh Puranam, Vishal Narayan, Vrinda Kadiyali

Marketing Science

105
피인용
8.7
FWCI
25
IS/마케팅/OM 탑저널 피인용
47
IS/마케팅/OM 탑저널 참고문헌
01Abstract

In 2008, New York City mandated that all chain restaurants post calorie information on their menus. For managers of chain and standalone restaurants, as well as for policy makers, a pertinent goal might be to monitor the impact of this regulation on consumer conversations. We propose a scalable Bayesian topic model to measure and understand changes in consumer opinion about health (and other topics). We calibrate the model on 761,962 online reviews of restaurants posted over eight years. Our model allows managers to specify prior topics of interest such as “health” for a calorie posting regulation. It also allows the distribution of topic proportions within a review to be affected by its length, valence, and the experience level of its author. Using a difference-in-differences estimation approach, we isolate the potentially causal effect of the regulation on consumer opinion. Following the regulation, there was a statistically small but significant increase in the proportion of discussion of the health topic. This increase can be attributed largely to authors who did not post reviews before the regulation, suggesting that the regulation prompted several consumers to discuss health in online restaurant reviews. Data and the online appendix are available at https://doi.org/10.1287/mksc.2017.1048 .

02연구 흐름

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03비슷한 논문

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04이후 연구

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05선행 연구

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06서지 정보