Dynamic pricing with demand disaggregation for hotel revenue management

Andrei M. Bandalouski, Natalja G. Egorova, Mikhail Y. Kovalyov, Erwin Pesch () and S. Armagan Tarim
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Andrei M. Bandalouski: National Academy of Sciences of Belarus
Natalja G. Egorova: National Academy of Sciences of Belarus
Mikhail Y. Kovalyov: National Academy of Sciences of Belarus
Erwin Pesch: University of Siegen
S. Armagan Tarim: University College Cork

Journal of Heuristics, 2021, vol. 27, issue 5, No 4, 869-885

Abstract: Abstract 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.

Keywords: Hotel revenue management; COVID-19; Dynamic pricing; Demand elasticity; Concave programming (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10732-021-09480-2

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