Dynamics of New Product Introduction in Closed Rental Systems
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Date: 04-22-2008
Start Time:
1:00pm
End Time: 2:00pm
Speaker: Sunil Kumar, Stanford University
Location: Uris 333
ABSTRACT
We study a rental system where a fixed number of heterogeneous users rent one product at a time from a collection of re-usable products. The online DVD rental firm Netflix provides the motivation. We assume that rental durations of each user are i.i.d. with finite mean. We study transient behavior in this system following the introduction of a new product that is desired by all the users. We represent the usage process for this new product in terms of an empirical distribution. This allows us to characterize the asymptotic behavior of the usage process as the number of users increases without bound, via appropriate versions of Glivenko-Cantelli and Donsker’s theorems. Analyzing the usage process, we demonstrate that an increase in the variability of the rental duration distribution can actually help the firm by allowing it to set lower capacity levels to provide a desired quality of service. Moreover, we show that the firm is better off by not imposing any return deadlines.
Joint with: Achal Bassamboo, Kellogg School of Management, Northwestern University and Ramandeep S. Randhawa, McCombs School of Business, The University of Texas at Austin.
BIO
Sunil Kumar joined the Operations, Information, and Technology area in 1996, having obtained a PhD in Electrical Engineering from the University of Illinois at Urbana-Champaign. He teaches MBA courses in Operations Management and Information Systems as well as PhD courses in Dynamic Optimization and Stochastic Networks. He has co-authored more than two dozen research articles and edits the Stochastic Models area for the journal Operations Research.
Professor Kumar’s research focuses on analyzing mathematical models of operations. Examples of such operations include manufacturing facilities, services, call centers, as well as peering arrangements between service providers on the internet. All the operations he studies are affected significantly by stochastic variability. He analyzes these operations using a class of models called stochastic network models and obtains both performance estimates as well as policy prescriptions. He is interested particularly in the study of operations that are used by rational customers who act in their self interest. The tools developed for analyzing operations find application in other domains in business. Professor Kumar explores two such domains: mathematical finance and formal models of decision-making.
For the most part, Professor Kumar’s research lies at the intersection of business and the engineering discipline of operations research. He collaborates on research with faculty and PhD students from both business and engineering schools. He has served as an operations consultant to a few Bay Area companies. He is the co-developer of Littlefield Technologies, a factory simulator intended to complement courses in operations management. Littlefield Technologies is now a commercial product used at over two dozen institutions.