Online platform entry and food safety risk: Evidence from the Chinese restaurant industry

Abstract The online food delivery (OFD) industry has witnessed substantial global expansion. In this study, we examine how OFD platforms in China affect the food safety conditions of restaurants. Given the difficulty quantifying food safety, we first propose a machine learning approach to construct a restaurant‐specific food safety risk indicator based on online customer reviews. The approach features high‐frequency continuous measurements with complete geographic coverage. We also conducted an event study and found that the food safety risk in restaurants decreased significantly in response to OFD platforms, with the effects concentrated in the five quarters including the entry period. Our mechanism analysis suggests that this improvement might come from extended market information, strengthened market competition, and heightened supervision and regulation. The impact is also more pronounced for chain restaurants, restaurants that are relatively popular and expensive, and restaurants offering low‐risk food items.