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Dynamic pricing with demand disaggregation for hotel revenue management

  • In this paper we present a novel approach to the dynamic pricing problem for hotel businesses. It includes disaggregation of the demand into several categories, forecasting, elastic demand simulation, and a mathematical programming model with concave quadratic objective function and linear constraints for dynamic price optimization. The approach is computationally efficient and easy to implement. In computer experiments with a hotel data set, the hotel revenue is increased by about 6% on average in comparison with the actual revenue gained in a past period, where the fixed price policy was employed, subject to an assumption that the demand can deviate from the suggested elastic model. The approach and the developed software can be a useful tool for small hotels recovering from the economic consequences of the COVID-19 pandemic.

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Document Type:Article
Author:Erwin PeschORCiD, Andrei M. Bandalouski, Natalja G. Egorova, Mikhail Y. KovalyovORCiD, S. Armagan Tarim
Center:Center for Advanced Studies in Management (CASiM)
Parent Title (English):Journal of Heuristics
Year of Completion:2021
First Page:869
Last Page:885
Tag:COVID-19; Concave programming; Demand elasticity; Dynamic pricing; Hotel revenue management
Content Focus:Academic Audience
Peer Reviewed:Yes
Rankings:AJG Ranking / 3
VHB Ranking / B
SJR Ranking / Q2
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International