How can we help you to optimise prices and revenue?
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Revenue management practice has grown significantly in the past three decades, and is now considered an indispensable part of hotels’ marketing and operating strategies. Hotel revenue management policies have been developed with the aim of profitably matching or managing a fluctuating demand, with the hotel’s constrained and perishable capacity.
1. Room Rate Pricing Decision-Making
This is achieved by employing a range of room pricing and allocation tools, addressing core revenue management concepts such as: the reservation of a portion of the capacity for higher value customers at a later date; efficient price discrimination practices to extract as much of the consumer surplus as possible; overbooking policies to offset no shows; late cancelations; and early departures. As an extremely important strategic and tactical tool in revenue management, room rate pricing commonly is inherently competitor-oriented.
This is not only dangerous since discounting wars lurk when recessions arise, it is also suboptimal as hotels guests determine booking choices on the basis of perceived value, and consequently pricing directly affects demand and consequently revenue. However, in order to set room rates on the basis of perceived value, research is needed. Such research in the international hotel industry currently takes the form mostly of an intuitive or subjective assessment by the revenue management team.
This research line aims to develop expertise about the application of conjoint analysis to set value-informed room rates in hotel revenue management. Conjoint analysis is an experimental research method for measuring, analysing and predicting booking behaviour regarding the attributes of hotel service products. The method captures choice behaviour in a detailed mathematical model capable of predicting choice behaviour of each individual hotel guest and for every possible hotel service product variation.
With the model, among others, predictions can be made about market share, revenue and profit. As conjoint analysis suffers from certain drawbacks, limiting straightforward application to hotel room pricing, Mr. Bjorn Arenoe, a well-known conjoint analysis expert, joined the chair to explore new ideas to make conjoint analysis applicable to hotel revenue management practice and education.
2. Hotel Revenue Management Forecasting
Knowing how to enhance and maintain accurate forecasts is a crucial task for revenue managers, and the automated systems they employ. Within the task of achieving the greatest accuracy, hotels select the most accurate forecasting models when they start using a Revenue Management System (RMS), and continually monitor forecast accuracy.
When the accuracy is unsatisfactory, data, forecasting models and/or their parameters, as well as the use of subjective forecasts and adjustments to the forecasts, are all scrutinized. Interestingly, when hotels face elevated levels of risk and distress, such as a liquidity challenge, or intensified competition in highly volatile markets, more pressure is placed on the revenue manager to ensure that the forecasts are accurate. In practice it is, therefore, not unusual that RMS are overridden in an attempt to enhance revenue management performance. The question then arises as to whether these subjective adjustments add value. In other words, do the subjective adjustments by revenue managers improve or diminish the accuracy of the sophisticated computer generated forecasts? In this research line, both machine and manual forecasts are investigated to bring to the forefront fundamental and practical issues associated with the challenge of hotel forecasting accuracy assessment.
A ‘Grounded’ Approach to chose Research Lines In 2011 an extensive explorative study (project 'zero') was carried out to identify important emergent topics in Revenue Management. Literature was reviewed, 13 online LinkedIn discussion groups (with 26,727 members and 1,669 revenue management discussions) were analysed, and 46 revenue managers (Marriott Worldwide) took part in an anonymous on-line discussion platform. In other words, multiple research traditions were reviewed; and existing academic debates and future directions suggested by RM researchers were combined with the topics, debates and concerns voiced by industry professionals. The results were reported in papers presented at EuroCHRIE 2010 and APacCHRIE 2011 and led to the choice for two long-term research lines: (1) conjoint analysis and (2) forecasting.