Researchers from the University of Portsmouth have devised a new method to rank hotels more accurately.
The new method will help hotel operators to maximise their revenue by providing more information on the areas that customers care about. Customers also benefit from a more accurate and trusted rating of a hotel’s performance.
Online customer reviews have become increasingly important for people when booking hotel rooms. Online review platforms typically provide an overall rating by combining customer ratings of several individual criteria and then computing an average of these scores.
The way they aggregate individual ratings into the overall rating is very simplistic, some platforms just do an arithmetic average of individual ratings. The problem is that it provides an equal weighting to each individual criteria and doesn’t differentiate between important and non-important hotel characteristics. Also a hotel could compensate a low score in one aspect with a high score in another.
Our new model is an innovative approach that prioritises attributes and overcomes the simplistic use of an overall average. This approach helps operators to better understand the attributes that play a leading role in terms of revenue maximisation.
The new model relaxes some of the assumptions made by this average approach and reflects a customer’s decision process more accurately by providing different weighting to attributes that are more important to customers.
The results found the roles of staff and location as the most important criteria for hotels to maximise their revenue. The higher up the rankings a hotel appears, the more bookings they get and in turn, increase their revenue.
The findings also showed that, contrary to previous research, location is not particularly key when it comes to ranking a hotel’s performance. This could be because customers already know the location of a hotel when booking so their evaluation might refer to more intangible aspects of the location, such as street noise, that are more difficult to assess prior to booking.
Improving aspects that are important to customers will be beneficial to hotels as long as the improvements are cost-efficient. For instance, improving facilities, which appears to be essential for increasing revenue, might be costlier than improving cleanliness.
Co-author of the study Dr Marta Nieto-García, Lecturer in the Marketing and Sales Subject Group at the University of Portsmouth, said: “Our new model is an innovative approach that prioritises attributes and overcomes the simplistic use of an overall average.
“From a managerial perspective, this approach helps operators to better understand the attributes that play a leading role in terms of revenue maximisation. Improving those aspects that are important to customers will be beneficial to hotels as long as the improvements are cost-efficient. For instance, improving facilities, which appears to be essential for increasing revenue, might be costlier than improving cleanliness. After considering which dimensions customers rank higher, each hotel should conduct careful cost benefit evaluations to decide on which attributes it should invest resources and how best those attributes could be improved.
After considering which dimensions customers rank higher, each hotel should conduct careful cost benefit evaluations to decide on which attributes it should invest resources and how best those attributes could be improved.
The researchers combined two independent data sources, online ratings from Booking.com (overall and individual ratings against six criteria – cleanliness, comfort, facilities, location, staff and value for money) and RevPAR (revenue per available room) data from the global data company STR. Data was taken from 709 hotels across 14 European cities. They then used Preference Ranking Organisation METHod for Enrichment of Evaluations (PROMETHEE), a multi-criteria decision analysis system that identifies the pros and the cons of several criteria and provides a ranking of them.
This revealed significant correlation between ratings and RevPAR in cleanliness, comfort, facilities, location, staff, with facilities the most significant, followed by staff.
Dr Nieto-García said: “Individual ratings reflect the attributes that customers consider relevant for their hotel choice. Through the use of our new model it is possible to offer a more accurate overall rating that accounts for the importance of the single individual attributes. This would result in more informed decision for customers and improved RevPAR for hotels.”
Individual ratings reflect the attributes that customers consider relevant for their hotel choice. Through the use of our new model it is possible to offer a more accurate overall rating that accounts for the importance of the single individual attributes. This would result in more informed decision for customers and improved RevPAR for hotels.
The study, co-authored by Marta Nieto-Garcia, Giampaolo Viglia and Alessio Ishizaka from the Faculty of Business and Law at the University of Portsmouth, is published in the International Journal of Hospitality Management. It also involved Giuliano Resce from the Università degli Studi Roma in Italy and Nicoletta Occhiocupo from the IQS School of Management in Spain.
Dr Nieto-García said: “However, we recognise that the study looked at just one platform (Booking.com) and could be expanded to validate the findings across different platforms (such as Tripadvisor). Also, the results are from European cities only and collected at a single point in time, so we could look whether this is relevant to other continents as well as enrich the current contributions with longitudinal data.”