Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/287243 
Erscheinungsjahr: 
2021
Quellenangabe: 
[Journal:] Journal of Heuristics [ISSN:] 1572-9397 [Volume:] 27 [Issue:] 5 [Publisher:] Springer US [Place:] New York, NY [Year:] 2021 [Pages:] 869-885
Verlag: 
Springer US, New York, NY
Zusammenfassung: 
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.
Schlagwörter: 
Hotel revenue management
COVID-19
Dynamic pricing
Demand elasticity
Concave programming
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