Enhancing Customer Experiences through Home Sharing: Evidence from Attraction Review Analytics

Abstract

Home sharing changes how people travel and profoundly impacts local markets. This paper investigates how home sharing affects customer experience in local travel attractions. Using unique data from a major home sharing platform and markets with abundant travel attractions, we leverage an empirical opportunity and machine learning techniques to explore the impact of home sharing on customer experience and its mechanism. We find that home sharing generates significant and positive effects on the customer experience at attractions. The mechanism is mainly through local hosts’ support, including saving tips, attraction knowledge, and travel planning. Also, the positive effect especially manifests in travelers' evaluation of attraction admission, guided tours, ticket purchase, and the overall travel experience. In terms of ultimate revenue, home sharing benefits local attractions with more visits. Collectively, these findings speak to the controversy of home sharing and provide timely implications for attraction administrators, policymakers, and practitioners who increasingly embrace emerging home sharing in the local economy.

Keywords: Platform-based markets, sharing economy, home sharing, travel attractions, customer experience, difference-in-differences, propensity score matching, machine learning