Mobile Food Ordering Apps, Restaurant Performance, and Customer Satisfaction

Abstract

Mobile food ordering apps (MFOAs) have become increasingly prevalent in the food service industry. This study investigated the links between intensity of MFOA use, restaurant performance, and customer satisfaction in dine-in restaurants using real transaction data and crowdsourced reviews. Our distinctive datasets stem from a renowned chain of restaurants in China as well as from Da Zhong Dian Ping (referred to as the Chinese equivalent of Yelp), spanning the years 2018 to 2021. Using a high-dimensional fixed effects model, we found that the intensive use of MFOA is positively correlated with an increase in restaurant dine-in revenue through higher table turnovers. However, MFOA is negatively correlated with dine-in restaurant consumer satisfaction, which was associated with lack of adequate, favorable, and high-quality comments. We also conducted several heterogeneity analyses to investigate how selected restaurant characteristics may moderate these effects. Thus, our study provides valuable theoretical insights and practical implications for academia and food service practitioners.