Dynamic pricing with demand disaggregation for hotel revenue management

Artikel

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Journal: Journal of Heuristics ; ISSN: 1572-9397 ; Volume: 27 ; Year: 2021 ; Issue: 5 ; Pages: 869-885 ; New York, NY: Springer US

Klassifikation und Themen

• Klassifikation: Mathematik
• Thema: Hotel revenue management ; COVID-19 ; Dynamic pricing ; Demand elasticity ; Concave programming

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Bandalouski, Andrei M. ; Egorova, Natalja G. ; Kovalyov, Mikhail Y. ; Pesch, Erwin ; Tarim, S. Armagan
• Ereignis: Veröffentlichung
• (wer): Springer US
• (wo): New York, NY
• (wann): 2021

Weitere Informationen

• DOI: doi:10.1007/s10732-021-09480-2
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ