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.
Highlights
A rapid development in the fields of information technologies and e-commerce has supported the use of dynamic pricing approaches in hotels and the research interest in this area
The software and the materials in this paper provide an opportunity for small hotels to use optimization techniques to aid their recovery from the economic consequences of the COVID-19 lockdown
We describe a dynamic pricing approach for a hotel revenue management problem with multi-products
Summary
A rapid development in the fields of information technologies and e-commerce has supported the use of dynamic pricing approaches in hotels and the research interest in this area. Practical hotel revenue management (HRM) systems, that use dynamic pricing, are described by Koushik et al (2012) and Pekgun et al (2013). Our approach to the HRM problem includes the determination of input parameters for the subsequent mathematical analysis, disaggregation of the demand into several categories, demand forecasting for the reference price, simulation of the demand-price relations, and a mathematical programming model for dynamic price optimization. 6. While the optimization model assumes an exact solution, it is developed based on heuristic reasoning, our approach to the hotel dynamic pricing is heuristic in general. The paper concludes with a short summary of the results and suggestions for future research
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