Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287243 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Heuristics [ISSN:] 1572-9397 [Volume:] 27 [Issue:] 5 [Publisher:] Springer US [Place:] New York, NY [Year:] 2021 [Pages:] 869-885
Publisher: 
Springer US, New York, NY
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.
Subjects: 
Hotel revenue management
COVID-19
Dynamic pricing
Demand elasticity
Concave programming
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.