2/18/21 | 4:15pm | Online only

Guillermo Gallego

Professor
Hong Kong University of Science and Technology

Abstract: We present bounds and heuristics for personalized, multi-product pricing problems. Under mild conditions we show that the best price in the direction of a positive vector results in profits that are guaranteed to be at least as large as a fraction of the profits from optimal personalized pricing. The fraction depends on the factor and a set of optimal price vectors for the different customer types. Using a factor vector with equal components results in uniform pricing and has exceedingly mild sufficient conditions for the bound to hold. A robust factor is presented that achieves the best possible performance guarantee. As an application, our model yields a tight lower-bound on the performance of linear pricing relative to optimal personalized non-linear pricing, and suggests effective non-linear price heuristics relative to personalized solutions. Heuristic to cluster customer types are also developed with the goal of improving performance by allowing each cluster to price along its own factor. Numerical results are presented for a variety of demand models that illustrate the tradeoffs between using an economically motivated factors and the robust factors, and the tradeoffs between using a clustering heuristic with a worst case performance of two and a machine learning clustering algorithm. In our experiments economically motivated factors coupled with machine learning clustering heuristics performed significantly better than other combinations.

Bio: Professor Guillermo Gallego is the Department Head of Industrial Engineering and Decision Analytics, and also the Crown Worldwide Professor of Engineering at The Hong Kong University of Science and Technology.

Prior to his appointment in January 2016, Prof Gallego was the Liu Family Professor at the Department of Industrial Engineering and Operations Research at Columbia University, where he served as the Department Chairman from 2002-2008. He was named a Manufacturing and Service Operations Management Society (MSOM) Fellow in 2013, an INFORMS Fellow in 2012 and has been the recipient of many awards including the Revenue Management Historical Prize (2011), the Revenue Management Practice Prize (2012), the INFORMS Impact Prize (2016), the Management Science Best Paper Award (2017) and the MSOM Best OM paper in OR (2019).

Prof Gallego’s research interests are Dynamic Pricing and Revenue Optimization, Supply Chain Management, Electronic Commerce, and Inventory Theory. He has published influential papers in the leading journals of his field where he has also occupied a variety of editorial positions. His work has been supported by numerous industrial and government grants. In addition to theoretical research, Prof Gallego has developed strong collaboration with global corporations such as Disney World, Hewlett Packard, IBM, Lucent Technologies, Nomis Solutions, and Sabre Airline Solutions. He has also worked with government agencies such as the National Research Council, the National Science Foundation in United States and the Ireland Development Agency. His graduate students are associated with prestigious universities and occupy leading roles in their chosen fields. He spent his 1996-97 sabbatical at Stanford University and was a visiting scientist at the IBM Watson Research Center from 1999-2003. Prof Gallego received both his PhD degree (1988) and MS degree (1987) in Operations Research and Industrial Engineering from Cornell University.