Identifying local bias on peer-to-peer rental platforms

Prior studies have documented local bias in online product and online crowdfunding markets. By collecting a unique longitudinal dataset covering 91,693 Airbnb properties, we find evidence that local bias also exists in peer-to-peer rental platforms. We also prove that local bias has a negative consequence on guest satisfaction and property reputation. In addition, a focus on moderating effects reveals that (a) local bias is less prominent in properties with high prices, and (b) uploading detailed host descriptions can suppress the appearance of local bias and reduce its negative consequences on the online ratings of properties. Therefore, information asymmetry at least partially drives this phenomenon. The findings contribute to the literature and platforms in practice.