Essays in Service Operations Management

The first two chapters of this thesis focus on the operation of rental businesses, which provides a novel and increasingly significant application of a supply chain and service operation. According to IBISWorld industry reports, at least fifteen different rental industries in the United States have annual revenues exceeding $1 billion. Furthermore, the consumer trend of \access over ownership" has spurred the creation of new and disruptive business models such as Rent the Runway, which rents designer dresses by mail to over 2 million users. However, existing operations management literature oers little support to rental operations subject to complex demand characteristics and the loss of rental units due to customer damage or purchase.</p

Managing Rentals with Usage-Based Loss

Motivated by new and innovative rental business models, this paper develops a novel discrete-time model of a rental operation with random loss of inventory due to customer use. The inventory level is chosen before the start of a finite rental season, and customers not immediately served are lost. Our analysis framework uses stochastic comparisons of sample paths to derive structural results that hold under good generality for demands, rental durations, and rental unit lifetimes. Considering different \recirculation rules | i.e., which rental unit to choose to meet each demand | we prove the concavity of the expected profit function and identify the optimal recirculation rule. A numerical study clarifies when considering rental unit loss and recirculation rules matters most for the inventory decision: Accounting for rental unit loss can increase the expected profit by 7% for a single season and becomes even more important as the time horizon lengthens. We also observe that the optimal inventory level in response to increasing loss probability is non-monotonic. Finally, we show that choosing the optimal recirculation rule over another simple policy allows more rental units to be profitably added, and the profit-maximizing service level increases by up to 6 percentage points

The Pennsylvania Adoption Exchange Improves Its Matching Process

The Pennsylvania Adoption Exchange (PAE) helps case workers who represent children in state custody by recommending prospective families for adoption. We describe PAE's operational challenges using case worker surveys and analyze child outcomes through a regression analysis of data collected over multiple years. A match recommendation spreadsheet tool implemented by PAE incorporates insights from this analysis and allows PAE managers to better utilize available information. Using a discrete-event simulation of PAE, we justify the value of a statewide adoption network and demonstrate the importance of better information about family preferences for increasing the percentage of children who are successfully adopted. Finally, we detail a series of simple improvements that PAE achieved through collecting more valuable information and aligning incentives for families to provide useful preference information.Slaugh2_Penn_adoption_exchange.pdf: 228 downloads, before Aug. 1, 2020

The Pennsylvania Adoption Exchange Improves Its Matching Process

he Pennsylvania Adoption Exchange (PAE) helps case workers representing children in state custody by recommending prospective families for adoption. We describe PAE's operational challenges using case worker surveys and a regression analysis of data on child outcomes over multiple years. Using a discrete-event simulation of PAE, we justify the value of a statewide adoption network and demonstrate the importance of the family preference information quality on the percentage of children who successfully nd adoptive placements. Finally, we detail a series of simple improvements implemented by PAE to increase the adoptive placement rate through collecting more valuable information, improving the family ranking algorithm, and aligning incentives for families to provide useful preference information.</p