Customer Choice Modeling with Group Dynamics and Ancillary Pricing

收益管理（RM）是一门通过定价和库存策略来提高收益的艺术和科学。RM模型最初是在20世纪70年代放松管制后在航空业发展起来的，如今已应用于广泛而多样化的行业，包括酒店、汽车租赁、零售和现场娱乐。尽管RM的核心一直保持不变，但在过去的几十年里，数学建模和技术已经发生了巨大的变化。一个最近的建模发展和主要动机提出的研究计划是考虑客户选择和战略消费者行为。******提出的研究计划包括两个问题，扩展客户的选择和战略行为：(i)小团体预订；（ii）辅助服务的定价和库存控制。第一个重要的应用和主要动机是现场娱乐（例如剧院，音乐会，体育场馆），客户要求一组连续的座位。虽然表演艺术在加拿大是一个价值数十亿美元的产业，但营业利润率非常低，甚至为负；不包括音乐剧的戏剧。关于辅助服务的问题是由传统的RM行业（航空公司、酒店、汽车租赁）和最近产生二次收入的趋势引起的。典型的例子是航空公司的行李费，2015年为美国航空公司创造了38亿美元的收入。另一个鼓舞人心的例子是，加拿大广播电视和电信委员会最近对有线电视进行了拆封和定价管制，消费者现在可以选择基本套餐和附加频道。******第一个提案主题的目标是为小团体预订导出最优动态容量分配策略。这个问题包括：随着时间的推移，希望购买易腐服务的容量的随机群体大小；剧院座位。对于每个请求，决策者选择价格差异容量的一个子集来提供；例如选择要提供的行。目标是使总预期收益最大化。除了分析建模外，本研究还包括现场娱乐的实证数据分析。******第二个提案主题的目标是推导辅助服务的最优动态定价和库存分配策略。该问题包括卖方提供主要服务以及一组多个辅助服务；例如机票和行李服务，优先座位；或基础有线电视和额外频道的菜单。随着时间的推移，客户到达并请求主要服务和辅助服务的子集。卖方必须为每个请求决定价格和提供哪些辅助服务。目标是使总预期收益最大化。将对航空公司辅助服务和加拿大有线电视套餐进行实证数据分析。******

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.******