Stochastic model for hotel room pricing and upgrading

Yihua Li (), Lila Rasekh (), Xiubin Bruce Wang () and Qing Miao ()
Additional contact information
Yihua Li: United Airlines
Lila Rasekh: Sears Holdings Corporation
Xiubin Bruce Wang: Texas A&M University
Qing Miao: Norfolk Southern Railway

Journal of Revenue and Pricing Management, 2016, vol. 15, issue 6, No 6, 500-508

Abstract: Abstract Hotel revenue management concerns allocation of limited rooms to demands from different price categories. Hotel rooms fall into groups of different amenities, each having its according prices. Sometimes, due to shortage of rooms in one category, a demand may be offered a room in a higher category but at the same lower price, called upgrading. Overbooking is also practiced because of late cancelation and no shows. Usually, upgrading is done separately from pricing optimization, which can lead to suboptimal solutions. This paper develops a deterministic linear programming (DLP) model to simultaneously consider hotel room pricing and allocation including overbooking and upgrading through a process that specifically deals with room categories. We further extend our DLP model to a stochastic one to address the uncertainties of demands. Numerical tests are carefully conducted to show the models are effective, and the system has been successfully implemented at several resort hotels.

Keywords: revenue and pricing management; stochastic; integer programming; room pricing; overbooking and upgrading (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1057/s41272-016-0066-9

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