Customer Choice Modeling with Group Dynamics and Ancillary Pricing

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Revenue Management (RM) is the art and science of improving the contribution through pricing and inventory strategies. Originally developed in the airline industry following deregulation in the 1970ies, RM models are today applied in a vast and diverse mix of industries, including hotel, car rental, retail and live entertainment. Although the core of RM has remained the same, the mathematical modeling and technology has evolved tremendously over the past decades. One recent modeling development and primary motivation for the proposed research program is consideration of customer choice and strategic consumer behavior. The proposed research program consists of two issues that extend customer choice and strategic behavior: (i) small group bookings; (ii) pricing and inventory control of ancillary services. Important applications and main motivation for the first are live entertainment (eg theater, concerts, sports venues), where customers request a set of contiguous seats. Although performing arts is a multi-billion dollar industry in Canada, the operating profit margin is very small and even negative; eg theater excluding musicals. The issue regarding ancillary services is motivated by traditional RM industries (airlines, hotel, car rental), and the recent trend to generate secondary revenue. The archetypical example is airline baggage fees, which generated $3.8B in revenues for US airlines in 2015. Another motivating example is the recent de-bundle and pricing regulation of cable-TV by the Canadian Radio-television and Telecommunications Commission, where consumers are now offered a base-package and an option for add-on channels. The objective of the first proposal topic is to derive optimal dynamic capacity allocation policies for small group bookings. The problem consists of random group sizes arriving over time that wish to purchase capacity of a perishable service; eg theater seats. For each request the decision maker selects a subset of price-differentiated capacity to make available; eg selects rows to offer. The objective is to maximize total expected revenue. In addition to analytical modeling the research consists of empirical data analysis of live entertainment. The objective of the second proposal topic is to derive optimal dynamic pricing and inventory allocation policies for ancillary services. The problem consists of a seller offering a primary service together with a set of multiple ancillary services; eg airfare and baggage service, preferred seating; or base cable-tv and menu of extra channels. Customers arrive over time and request the primary service and a subset of the ancillary services. The seller must for each request decide on the prices and which ancillary services to make available. The objective is to maximize total expected revenue. Empirical data analysis will be conducted on airline ancillary services and Canadian cable-TV packages.