Date of Award
Open Access Dissertation
Moore School of Business
Sale of products with a probabilistic nature, where customers do not know which product they will receive at the time of service, has become popular over the recent years. In the revenue management literature, there has been a growing interest in understanding these modern approaches using analytical techniques. On the other hand, customer-centric revenue management has been replacing the long-standing inventory-centric approach because of the availability of rich data sets by focusing on understanding and predicting customer behavior and then optimizing price and/or quantity related decisions. In this dissertation, we take a customer-centric approach and do not only provide analytical results, but also empirically investigate how customers make their decisions, which is crucial in order to implement appropriate strategies.
We first focus on an innovative hotel revenue management practice called standby upgrades, i.e., a practice where the guest is only charged for the discounted upgrade if it is available at the time of arrival. In particular, Chapter 2 discusses how to optimally price standby upgrades and evaluates their benefits through an analytical model. Chapter 3 uses a major hotel chain’s booking and standby upgrades data to investigate the extent of strategic guest behavior through empirical analysis. Then, we focus on another innovative revenue management practice, but in the mega event industry, called team-specific ticket options. Chapter 4 studies fans’ decision-making process for the 2015 College Football season using a unique data set.
Yılmaz, Ö.(2017). Innovative Revenue Management Practices with Probabilistic Elements. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/4236