No abstract

Repeat customers are crucial for business success. Previous studies have mainly focused on those factors that affect repeat patronage but ignored how repeat customers reevaluate the same service provider after consumption. We obtained a dataset containing 637,748 reviews of restaurants in New York City and used a generalized difference-in-differences design to further explore the rating behavior of local repeat customers. The results of this study contribute to theories of customer satisfaction, repeat patronage, and customer location in the context of user-generated content as repeat customers are found to be sensitive to quality variations. Such sensitivity is even accentuated by local customers. Relevant practical implications for restaurant managers are also drawn from the results.

Existing studies have found that online search is a revealed measure for investor attention and a useful predictor of stock returns. We study the heterogeneity in retail investor attention by comparing search conducted on weekdays vs. weekends and investigate the price pressure channel and information processing channel for stock return predictability. According to the information processing channel, weekends afford retail investors more time for the intensive cognitive analysis necessary to make better predictions. Alternatively, weekend search might better capture the price pressure from retail investors’ trading activities. We provide empirical results that support the information processing channel. We first show that weekend search, rather than weekday search, predicts large-cap stock returns in both the cross-section and time series. Additionally, our findings on retail trading activity contradict the price pressure channel in that weekday search, rather than weekend search, leads to a subsequent retail order imbalance. Overall, our study contributes to the literature on the predictive power of online search on stock returns, which has mainly focused on the price pressure channel, which yields significant results for small-cap stocks only.