Crowd-Driven Competitive Intelligence: Understanding the Relationship Between Local Market Competition and Online Rating Distributions

Crowdsourced online mean ratings of local businesses are increasingly being used to infer the market power of a business. An important consideration in making this inference is whether two identically rated businesses (e.g., 4 stars) encounter the same local competitive dynamics if they face contrasting local market competition. To analyze this, the authors combine demographic, socioeconomic, and Yelp restaurant reviews for 372 isolated markets in the United States. The empirical estimates demonstrate that an increase in overall competition—measured as total number of businesses in a market—leads to a broader range and to a decrease in the average of a market’s mean rating distribution. This implies that two restaurants with equal mean ratings differ substantially in the way they are affected by local competition depending on whether they are located in a large or in a small market. For example, a larger market has proportionately more lower rated restaurants, whereas higher rated restaurants have relatively fewer comparable substitutes and face less competition in such a market. Therefore, restaurants with identical mean ratings should ideally be assessed differently if they operate across markets with dissimilar numbers of competitors.

• 저널Information Systems Research · 30(3) · 980–994
• 토픽Digital Marketing and Social Media · Sociology and Political Science
• DOI10.1287/isre.2019.0845
• 저자Dominik Gutt, Philipp Herrmann, Mohammad Saifur Rahman