Optimizing Product Launches in the Presence of Strategic Consumers

Tuesday, December 9, 2014 - 4:00pm to Wednesday, December 10, 2014 - 3:55pm

Event Calendar Category

LIDS Seminar Series

Speaker Name

Ilan Lobel

Affiliation

NYU

Building and Room number

32-141

A technology firm launches newer generations of a given product over time. At any moment, the firm decides whether to release a new version of the product that captures the current technology level at the expense of a fixed launch cost. Consumers are forward-looking and purchase newer models only when it maximizes their own future discounted surpluses.  We start by assuming that consumers have a common valuation for the product and consider two product launch settings. In the first setting, the firm does not announce future release technologies and the equilibrium of the game is to release new versions cyclically with a constant level of technology improvement that is optimal for the firm. In the second setting, the firm is able to precommit to a schedule of technology releases and the optimal policy generally consists of alternating minor and major technology launch cycles. We verify that the difference in profits between the commitment and no-commitment scenarios can be significant, varying from 4% to 12%. Finally, we generalize our model to allow for multiple customer classes with different valuations for the product, demonstrating how to compute equilibria in this case and numerically deriving insights for different market compositions. Joint work with Jigar Patel, Gustavo Vulcano and Jiawei Zhang.

Ilan Lobel is an Assistant Professor of Information, Operations and Management Sciences at the NYU Stern School of Business. He obtained his Ph.D. in Operations Research from MIT, where he was a member of LIDS. Before joining NYU, he was a post-doctoral researcher at the Microsoft Research New England Lab. His research focuses on issues related to operations and new technologies, with a particular emphasis on questions of pricing, learning and contract design in dynamic and networked markets.