Strategic behavior for hotel standby upgrade programs: Empirical evidence and pricing implications

Abstract

AbstractMany hotels have recently started to offer room upgrades digitally after the completion of booking to replace traditional front‐desk upselling during check‐in. Quickly becoming popular for upselling the premium rooms that may otherwise go unsold, standby upgrade—an availability‐based, discounted premium room upgrade—is a prominent example. However, customers, in particular loyalty members, may become knowledgeable about standby upgrades through repeated interactions with this technology, and act strategically, that is, initially choose a standard room with the expectation of being offered a premium room discount through standby upgrades. Consequently, while enjoying the benefits of this program, hotels may face the potential cannibalization of premium sales due to such strategic behavior and need to adjust their pricing accordingly. Using a major hotel chain's 16‐month booking and standby upgrades data, we empirically investigate the existence and extent of strategic customers in the context of standby upgrades. After showing preliminary evidence of potential strategic behavior, we develop a maximum likelihood estimator to estimate the percentage of customers who are strategic. This estimator captures the sequential nature of customer decision‐making for standby upgrades (booking decision, clicking the standby upgrades offer, and requesting an upgrade) through a Sequential Logit Model. We find evidence of strategic behavior in three (out of eight) hotels examined. Considering both a weak‐form and a strong‐form strategic behavior, our estimates suggest that 12%–42% of the loyalty customers act strategically in these three properties. We then propose a new pricing policy to help hoteliers maximize their premium room revenues from direct bookings and standby upgrade requests. This policy recommends a discounted full price, but also a higher standby upgrade price for loyalty customers, which can bring a revenue improvement of up to 19% over a policy ignoring the strategic behavior and 34% over a policy assuming that all customers are strategic—two reasonable benchmarks without an estimate of the fraction of strategic customers. Our research, thus, provides insights for technology managers on the potential customer behavioral challenges that a hotel may face with the adoption of a disruptive digital technology, and how existing policies may need to be adjusted for the technology to be successful.