I will be joining the Wharton School Department of Operations, Information and Decisions in July 2016.
My work aims to combine theoretical and empirical research to impact the practice of operations management.
Job Market Paper
Online retail reduces the costs of obtaining information about a product's price and availability and of flexibly timing a purchase. Consequently, consumers can strategically time their purchases, weighing the costs of monitoring and the risk of inventory depletion against prospectively lower prices. At the same time, firms can observe and exploit their customers' monitoring behavior. Using a dataset tracking customers of a North American specialty retail brand, we present empirical evidence that monitoring products online associates with successfully obtaining discounts. We develop a structural model of consumers' dynamic monitoring to find substantial heterogeneity. Our estimation results have important implications for retail operations. The randomized markdown policy benefits retailers by combining price commitment with the exploitation of the heterogeneity in consumers' monitoring costs. Our finding combines the effects of pricing and inventory management: optimal inventory levels are drastically higher under the randomized markdown policy. We also discuss targeting customers with price promotions using online histories and the implications of reducing consumers' monitoring costs.
The best service firms expand and sustain their customer bases and profits organically through word of mouth and customer retention. We propose a customer-flow model fashioned after classical service operations models that focuses on the effects of customer retention, usage frequency, and growth (RFG). Using a dataset encompassing the daily, weekly, and monthly usership time series for services in the app economy, we empirically demonstrate the importance of RFG: first, we use cross-sectional variation to show that service-quality outcomes, namely customer retention and usage frequency, drive an app's customer-acquisition growth as potently as its viral features; second, newly released apps score increasingly higher in growth over our sample period owing to improvements in service quality. Finally, we present evidence of an experience curve, analogous to the manufacturing experience curve, whereby service events drive advances in service quality and RFG.