Status: Invited for revision at MIS Quarterly
(Joint work with Siva Viswanathan, Rajshree Agarwal and Shun Ye)
An investigation of Airbnb’s mechanism design (Instant Booking) that mitigates information asymmetry and improves outcomes for a (deserving) sub-section of population
Screening, a mechanism for alleviating information asymmetry, is considered a necessity for online peer to peer market platforms, but has also raised concerns of increased discriminatory or biased behaviors in the sharing economy. However, left unexamined is the recent phenomenon where providers of goods and services may voluntarily forgo screening, even though it increases the risks and costs associated with “lemons.” We examine when and who may choose to forgo screening, and the impact this may have on their performance outcomes. We answer these research questions on the Airbnb platform, which recently instituted an “Instant Book” feature that enables hosts to forgo the screening of guests seeking lodging. Utilizing a unique panel dataset of all the listings in New York City between August 2015 and February 2017, we employ propensity score matching combined with difference-in-difference analysis to examine switching and re-switching behaviors of hosts. Our study provides evidence of the economic benefits of forgoing screening from increased occupancy even as reviewer ratings decline, and shows these effects to be stronger for African American and female hosts. We discuss the strategic and social welfare implications of these findings, in the context of the current conversation regarding discrimination and bias in the sharing economy.