A Dynamic Model of Owner Acceptance in Peer-to-Peer Sharing Markets

Dai Yao, Chuang Tang, Junhong Chu

Research output: Journal article publicationJournal articleAcademic researchpeer-review


Peer-to-peer (P2P) sharing marketplaces enable sharing of idle resources. When a renter requests an owner’s
resource, the owner needs to decide whether to accept the request: accepting it helps him fill up the idle
periods of the resource and generate a payoff, but reduces the flexibility to serve a future request for a longer
duration. This paper develops a framework to uncover the trade-offs faced by owners on these platforms
when making acceptance decisions, which can be used by owners to optimize their decisions and by platforms
to improve their operations. The model explicitly accommodates two types of owners: some are attentive
to the availability states of their cars and forward-looking, while others myopically make the acceptance
decisions. Applying the model to unique data from a leading P2P car sharing platform in China, we obtain
similar sizes of both types of owners, and find that female, experienced, and younger owners are more likely
to be strategic. The results also reveal the differentiated preferences of the two types of owners towards their
renters. Building on model estimates, we calibrate the option value of each day in the future (i.e., the value of
having the day available) for strategic owners, and find it to first increase, then decrease. Two counterfactual
analyses are conducted. The first analysis shows that if the platform imposes a minimum rental duration,
strategic owners may become more reluctant to accept requests, even if the current availability state entails a
higher expected payoff. The second analysis shows that with better understanding of its owners, the platform
can greatly improve the matching efficiency by optimal (re)allocation of rental requests, a move that benefits
almost all participants in the business.
Original languageEnglish
JournalMarketing Science
Publication statusAccepted/In press - 8 Mar 2022

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