A Data-Driven Approach to Modeling Choice
Author(s)Farias, Vivek F.; Jagabathula, Srikanth; Shah, Devavrat
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We visit the following fundamental problem: For a 'generic' model of consumer choice (namely, distributions over preference lists) and a limited amount of data on how consumers actually make decisions (such as marginal preference information), how may one predict revenues from offering a particular assortment of choices? This problem is central to areas within operations research, marketing and econometrics. We present a framework to answer such questions and design a number of tractable algorithms (from a data and computational standpoint) for the same.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Laboratory for Information and Decision Systems; Sloan School of Management
Advances in Neural Information Processing Systems (NIPS) 22
Neural Information Processing Systems Foundation
Farias, Vivek F., Srikanth Jagabathula, and Devavrat Shah. "A Data-Driven Approach to Modeling Choice." Advances in Neural Information Processing Systems 22 (NIPS 2009).
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