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INTRODUCTION
Revenue management is the science of managing a limited amount of supply to maximize revenue, by dynamically controlling the price/quantity offered. Revenue management systems have recently gained significant worldwide adoption in the hotel industry, at least for higher-rated hotels. The typical hotel guest has probably noticed in the past few years a progressively evolving level of dynamism in quoted room prices. This is indicative of the sophisticated nature of the algorithms behind these reservation systems. However, the hotel revenue management models are still in their infancy, and there is a need for further development and improvement of these systems. Because of the sheer number of worldwide hotels every per cent of revenue improvement will add up considerably for the top line and much more so for the bottom line because of the thin margins in this industry.
Hotel revenue systems can be partitioned into two major groups (Ingold et al , 2000; Talluri and Van Ryzin, 2005; Abdel aziz et al , 2011). In the first group, the quantity control approach, the rooms are segmented by categories, such as by rate, guest type, room type and/or length of stay. Each category has a fixed price, but the number of rooms allocated to the category is dynamically controlled in a way that maximizes revenue. The other group, the dynamic pricing approach, groups all similar rooms in one category, and applies a price that is continually adjusted with time based on the supply and demand variations. The dynamic price is set so as to maximize revenue, taking into account the hotel occupancy, and the current and expected demand. The dynamic pricing approach is particularly prevalent in some online hotel reservations. The online nature makes updating the price periodically quite manageable. Thus, it is expected that the dynamic pricing approach will in the future overcome the quantity-based approach in adoption.
In this paper we propose a novel dynamic pricing approach. It is based on having a seasonal reference price, and control variables in the form of multipliers. Each multiplier will adjust the price up or down around the reference price based on certain influencing variables (for example, hotel occupancy, time until arrival). The parameters of these multipliers are optimized. The goal is to maximize the revenue, taking...