Dynamic pricing for hotel revenue management using price multipliers

In this article we propose a new dynamic pricing approach for the hotel revenue management problem. The proposed approach is based on having ‘price multipliers’ that vary around ‘1’ and provide a varying discount/premium over some seasonal reference price. The price multipliers are a function of certain influencing variables (for example, hotel occupancy, time until arrival). We apply an optimization algorithm for determining the parameters of these multipliers, the goal being to maximize the revenue, taking into account current demand, and the demand‐price sensitivity of the hotel's guest. The optimization algorithm makes use of a Monte Carlo simulator that simulates all the hotel's processes, such as reservations arrivals, cancellations, duration of stay, no shows, group reservations, seasonality and trend, as faithfully as possible. We have tested the proposed approach by successfully applying it to the revenue management problem of Plaza Hotel, Alexandria, Egypt, as a case study.