1 Introduction
The intangibility of services creates uncertainty and insecurity for consumers, so they seek to obtain supplementary information to that provided by service suppliers, which helps to reduce that uncertainty. Tourism services have found in this ecosystem of online reviews an ideal environment for their development [1].
Travel-related platforms such as TripAdvisor or Online Travel Agencies such as Booking.com have become an indispensable source of information where most users consult them before booking a hotel. In fact, many tourists are unwilling to make a lodging reservation if there are no online reviews [2].
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Online Travel Reviews (OTR), defined as “narratives, opinions, pictures, and ratings posted on travel related websites” [3], determine the level of quality perceived by potential customers. There are studies in the hotel sector that have been able to measure how variations in the ratings of accommodations have effects on the levels of occupancy and prices of hotels [1].
Nevertheless, the use and analysis of this information is not without certain complexity for various reasons: each platform collects and displays information differently, they use different scoring scales, they use different adjectives to arbitrarily, they delete the oldest reviews or not, or even, what is the representativeness of visitors that write reviews, cultural differences are observed [1, 2, 4].
There is not a single standard to measure the quality of a hotel based on online reviews, and there is also a problem of lack of transparency in the algorithm used to calculate the average score on some platforms.
Well-known websites such as Kayak or Trivago provide a global accommodation score based on a kind of arithmetic mean of scores from various websites, while private companies offer similar global indices to their clients (Reviewpro, Olery, etc.). However, it is important to note that the calculation method for this overall score is not disclosed to the public (referred to as a secret algorithm). As a result, different platforms yield divergent global scores, all with the purported goal of providing an accurate and reliable global index [1]. Moreover, various national and international organizations have decided to address the challenges posed by the topic: Norway and Switzerland documented models of guest review integration into hotel classification, and regions of the United Arab Emirates, Germany and Australia tried to integrate online scores in their traditional stars system [5]. However, only the system implemented in Australia (with a global score calculated using a "secret algorithm" from a private company) is currently still in operation.
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In 2014, reports from the United Nations World Tourism Organization [5] and the European Commission were published, offering a general vision and analysis of what was considered a matter of great importance to the sector [6]. Each of them focused on one of the aspects of debate around this phenomenon. Likewise, the European Commission has included specific references to online reviews in its Directive on Unfair Commercial Practices [7], while the ISO-20488 standard on online reviews was created in 2018 [8].
The aim of this study is to determine which reviews and which systems should be considered for the calculation of a future reliable global index that allows consumers, professionals and public bodies to compare accommodation establishments in a reliable way.
2 Methodology
For our research, a Delphi method is proposed as it allows to obtain reliable consensus from a group of experts, particularly in the context of problem-solving [9] with experts on accommodation online reviews from the academia, consultants, and hotel managers.
3 Results
It is expected to reach a consensus among academic experts, consultants and hotel managers consulted to determine which criteria to use when creating a transparent algorithm or global index to establish an overall accommodation score from online reviews. They will be asked about a series of specific issues, which will be decisive in the calculation of the algorithm.
3.1 Criteria for Scales Homogenization
Travel review sites use different rating scales. While TripAdvisor uses a rating of 1–5, others use a 10-point scale, or different scoring systems (e.g., HolidayCheck, 1–6, Agoda 2–10), that bring in ratings discrepancies among platforms as the design of the scale could influence the final score [4, 10]. Which scale should be used? And how the homogenization should be implemented?
3.2 Reviews Oldness
There are platforms such as Expedia and Booking.com that delete the reviews after three years since they were written, although they keep them longer if the hotel has few reviews. Google and TripAdvisor do not delete the old reviews, except on TripAdvisor that allows a business to remove all the past reviews only if they implemented structural changes such as new management, or total renovation of the lobby [11]. A decision should be made regarding the age of the reviews taken into consideration to calculate the global score.
3.3 Verified Reviews
There is a difference between platforms that only allow verified authors to write reviews through the reservation they have made and those in which anyone can write a review. Should we allow not verified reviews? What weight should each platform have to establish a global index?
3.4 Writing Reviews System
The way in which users fill out their experience is also significant, as are the changes in the platforms themselves over time. In this sense, TripAdvisor requests a general score first, followed by the title and contents of the review and, at the end, a rating for specific facets of the service (e.g., service, location, rooms, cleanliness, sleep quality). Instead, other platforms do not ask for a global rating, but request users to value several facets (e.g., cleanliness, comfort, facilities, staff, value for money, location) and then create a global score with the arithmetic average of these facets. Should we consider the global scores obtained by different systems in an equivalent way?
3.5 Reviews with Score, Text, or Image
There are platforms that allow users to publish a review indicating only the numerical score, while others force consumers to write a minimum of characters to publish it. In addition, some allow to publish images and videos together with the review. Should all reviews have the same weight? Or those that do not have a minimum of explanation, should they be given less weight? And to those who also provide images, should they be given more weight?
3.6 Minimum Reviews
Some platforms do not publish the average score of an accommodation establishment until it has achieved a minimum number of reviews, such as Booking.com, which only considers publishing the score if there are 5 reviews, but other platforms publish the average score from the first review. Should a minimum number of reviews be considered, equivalent to a minimum sample in a survey, to consider it appropriate to assign an overall score to a hotel?
3.7 Admitted Platforms to Calculate the Global Index
Not all platforms are used in the same way in different parts of the world, nor do they all have the same number of reviews or the same popularity. Some platforms should weight more than others? Do they have to have a minimum number of reviews to be able to enter in the global index? Should they be regional index worldwide? Should they be platforms used worldwide? Platforms must comply with legal systems, but what legislation (ISO-20488)? is it feasible? Should a series of objective parameters be established for websites to be accepted?
3.8 Reviewer Experience
There are users who have seniority and experience in writing reviews online. Should reviews from these reviewers carry more weight than reviews from new users? Should reviews from users who have only written one review on a website be accepted? Would it eliminate some of the potential fraud of writing fake reviews on platforms where the user is not verified?
3.9 Void Reviews and Reviewers
Sometimes there are organized attacks or inclusion of mass reviews that should be invalidated, in addition there are also reviewers suspected of attacking businesses or helping to increase reputation by buying reviews. Should all reviews from suspicious reviewers be invalidated? Do mass review entries have to be canceled?
4 Conclusions
In recent years, the traditional system of hotel stars has been surpassed by the scores of online reviews, despite the relative trust that many users have in online reviews [12]. Different organizations have suggested or promoted the implementation of a global score based on the reviews that would complement or replace the traditional star system. But this cannot be done using a "secret algorithm" that nobody knows which reviews include or the overall weight of each review or website.
The initial approach of our research involves making a series of decisions that lead to the creation of a global index that is perceived as fair, credible, transparent and useful for the accommodation sector. After this first step, an algorithm could be created, this time totally transparent, which could be applied to any accommodation in the world, even being established as a quality standard by public bodies, at the same level as the hotel star system.
Future research should focus on studying the level of acceptance that the algorithm, designed based on this study, could have within the sector. Similar investigations could also be implemented for other tourist services, such as restaurants, which also have a great dependence on online reviews, without there being a global index implemented either.
Acknowledgment
This research has been funded by the Spanish Ministry of Science and Innovation MCIN/AEI/https://doi.org/10.13039/501100011033/ FEDER, UE within the RevTour project Id PID2022-138564OA-I00, the Gastrotur Project Id TUR-RETOS2022-017, and by the INDEST-UdL within the ResTur project for the call 2023CRINDESTABC.
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