Li, Xiang2017-10-092017-10-092017-06https://hdl.handle.net/11299/190538University of Minnesota Ph.D. dissertation. June 2017. Major: Industrial and Systems Engineering. Advisor: Saif Benjaafar. 1 computer file (PDF); vii, 136 pages.This thesis studies the product sharing manifestation of the sharing and on-demand economy. It consists of two essays, one on peer-to-peer (P2P) product sharing and the other on business-to-consumer (B2C) product sharing. The first essay describes an equilibrium model of P2P sharing or collaborative consumption, where individuals with varying usage levels make decisions about whether or not to own a product. Owners are able to generate income from renting their products to non-owners while non-owners are able to access these products through renting on as needed basis. We characterize equilibrium outcomes, including ownership and usage levels, consumer surplus, and social welfare. We compare each outcome in systems with and without collaborative consumption. Our findings indicate that collaborative consumption can result in either lower or higher ownership and usage levels, with higher ownership and usage levels more likely when the cost of ownership is high. Our findings also indicate that consumers always benefit from collaborative consumption, with individuals who, in the absence of collaborative consumption, are indifferent between owning and not owning benefitting the most. We study both profit maximizing and social welfare maximizing platforms and compare equilibrium outcomes under both in terms of ownership, usage, and social welfare. We find that a not-for-profit platform would always charge a lower price and, therefore, lead to lower ownership and usage than a for-profit platform. We also examine the robustness of our results by considering several extensions to our model. The second essay characterizes the optimal inventory repositioning policy for a class of B2C product sharing networks. We consider a B2C product sharing network with a fixed number of rental units distributed across multiple locations. The units are accessed by customers without prior reservation and on an on-demand basis. Customers are provided with the flexibility to decide on how long to keep a unit and where to return it. Because of the randomness in demand, rental periods and return locations, there is a need to periodically reposition inventory away from some locations and into others. In deciding on how much inventory to reposition and where, the system manager balances potential lost sales with repositioning costs. We formulate the problem into a Markov decision process and show that the problem in each period is one that involves solving a convex optimization problem. The optimal policy in each period can be described in terms of a well-specified region over the state space. Within this region, it is optimal not to reposition any inventory while, outside the region, it is optimal to reposition some inventory but only such that the system moves to a new state that is on the boundary of the no-repositioning region. We provide a simple check for when a state is in the no-repositioning region, which also allows us to compute the optimal policy more efficiently.enCollaborative ConsumptionInventory NetworkInventory RepositioningMarkov Decision ProcessOn-Demand EconomySharing EconomyThesis or Dissertation