Wednesday, October 3, 2018 - 9:00am - 9:45am
Georgia Perakis (Massachusetts Institute of Technology)
The growing trend in online shopping in recent years has given rise to a wealth of data that was not available before and hence providing retailers new opportunities to personalize their services to individual customers such as personalized services include targeted promotions. As a side benefit, knowledge of individual customer behavior can also help improve sales forecasting. To develop consumer targeted strategies, we first need to develop a demand forecasting model that captures trends between customers (or groups of consumers).
Friday, October 5, 2018 - 11:45am - 12:30pm
Omar Besbes (Columbia University)
Pricing is central to many industries and academic disciplines ranging from Operations Research to Computer Science and Economics. In this talk, we study data-driven optimal pricing in low informational environments. We analyze how a decision-maker should price based on a single sample of the willingness-to-pay (WTP) of customers. The decision-maker's objective is to select a general pricing policy with maximum competitive ratio when the WTP distribution is only known to belong to some broad set.
Thursday, October 4, 2018 - 2:00pm - 2:45pm
Xin Chen (University of Illinois at Urbana-Champaign)
We consider a joint pricing and inventory control problem with positive replenishment lead times. Although this fundamental problem has been extensively studied in the literature, the structure of the optimal policy remains poorly understood. In this work, we propose a class of so-called constant-order contingent pricing policies with provable performance. Under such a policy, a constant-order amount of new inventory is ordered every period and a pricing decision is made based on the on-hand inventory.
Friday, May 18, 2018 - 11:00am - 11:30am
Ankur Mani (University of Minnesota, Twin Cities)
In this paper, we focus on the issue of price discrimination based upon position of individuals in the social network. The problem of price discrimination based upon position in the social network has received significant attention in recent years. However, the question of interest in the research has been to characterize and identify optimal prices and profits in deterministic networks and the complexity of computing optimal prices.
Wednesday, May 16, 2018 - 11:00am - 11:30am
Sherwin Doroudi (University of Minnesota, Twin Cities)
We consider a call center that can offload (or co-source) some or all of its arriving customers to an external provider. These customers are impatient—in the sense that they will eventually abandon the queue if left unserved—and arrive according to a non-stationary but known arrival pattern during a finite time horizon. By co-sourcing customers, the call center can reduce delays and curtail customer abandonment, however for each customer the call center co-sources, the call center must pay the external provider a price based on the time of transfer.
Tuesday, June 15, 2010 - 2:30pm - 3:30pm
Erhan Bayraktar (University of Michigan)
We solve the problem of pricing and optimal exercise of American call-type options in markets which do not necessarily admit an equivalent local martingale measure. This resolves an open question proposed by Fernholz and Karatzas [Stochastic Portfolio Theory: A Survey, Handbook of Numerical Analysis, 15:89-168, 2009].

Joint work with Kostas Kardaras and Hao Xing. Available at

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