A DYNAMIC MODEL OF OWNER ACCEPTANCE IN PEER-TO-PEER SHARING MARKETS

Abstract

Online peer-to-peer (P2P) sharing marketplaces enable property owners to share their idle resource to renters who are in need of the resource. A natural question facing an owner, when a renter delivers a rental request, is whether the request should be accepted or not. In this thesis, we develop a dynamic structural framework of the acceptance decisions by owners in the context of P2P sharing, and apply it to a unique dataset from a leading P2P car sharing platform in China. Our model accommodates two key features: (1) demand for a particular car will be affected by its availability state; and (2) owners are heterogeneous in their preferences in terms of the reservation requests. We find that the longer rentals and rentals starting earlier are more preferred. Then we conduct two counterfactual experiments to provide practical implication for managers and platforms. Lastly, we discuss the limitation and future direction.