How Incumbents Beat Disruption? Evidence from Hotels’ Responses to Home Sharing’s Entry Leveraging Quasi-experiments and Machine Learning

Abstract

The disruption of sharing economy services to incumbent firms has attracted growing attention. Yet, the literature is silent on how incumbents respond to the rivalry and the resulted consequences. We investigate incumbent hotels’ adjustment on quality after home sharing’s entry using management responses, an online reputation marketing strategy to address feedback in customer reviews. Our method integrates quasi-experiments and machine learning to not only estimate hotels’ response to home sharing’s entry but also unveil the mechanism. We provide evidence on distinct responses to home sharing’s entry across different hotel price segments, which lead to divergent performance outcomes in terms of customer satisfaction and sales. Hotels that respond more actively to customer reviews demonstrate improved quality in service areas where home sharing typically leads - including the check-in/out process, cleanliness, excursion opportunity, and room condition -and receive higher sales. In contrast, hotels that respond less appear to lose to not only home sharing but also peer hotels that respond more to reviews. We provide implications on how incumbents should react to technological and business model disruptions.

Keywords: Sharing economy, Incumbent firms, Management responses, Difference-in-differences, Machine learning