Special Issue "Online Reviews in Tourism and Hospitality: Different Methods and Applications"

Marisol B. Correia (Guest editor), Nuno António (Guest editor), Filipa Perdigão Ribeiro (Guest editor)

Research output: Contribution to journalSpecial issuepeer-review


Dear Colleagues, Over the past few years, the widespread use of web 2.0 platforms has been causing radical changes in the promotion of tourist destination, by following the clear strategy of incorporating user-generated content (UGC). Online reviews (ORs) are a form of UGC that reflects evaluations and comments about the visitor’s own experience, as well as about the destination itself. UGC can equate to electronic word of mouth (eWOM); both are crucial in shaping the image and reputation of destinations and are considered more reliable than official sources because they are regarded as genuine and not focused on business (De Ascaniis and Cantoni, 2017). Thus, ORs are increasingly recognized as an important component in the construction of a destination’s image (Yeoh, Othman, and Ahmad, 2013), and while consumer (traveller) empowerment has risen in terms of travel choices and destinations, the role of hospitality and tourism-related firms in influencing consumers’ travel decisions has diminished (O’Connor, 2010). The analysis of ORs has been carried out for more than a decade and for various sectors of activity, but in particular for tourism and even more for hospitality. According to Schuckert, Liu, and Law (2015), over half of the academic articles related to online reviews in tourism and hospitality published in academic journals between 2004 and 2013 focused on hotels. Recent studies prove the potential of UGC to assist hoteliers, and more resources are recommended to be employed in research on ORs (Antonio, de Almeida, Nunes, Batista, and Ribeiro, 2018). For example, Kwok, Xie, and Richards (2017) point out that online hotel ratings create a rich resource of both quantitative and qualitative data whereby reviewers or commenters and review readers can consider their options as both tourists and consumers. On the other hand, managers can rely on data analytical techniques to consider outcomes in terms of consumer decision-making and business performance. Therefore, a consequence of the popularity of online hotel ratings is that ORs constitute a new and increasingly important element of the marketing communication mix and have growing implications for both theory and practice (Phillips, Antonio, Almeida, and Nunes, 2018). Of the many online reviews platforms for tourism and hospitality, we can highlight TripAdvisor, Expedia, Booking.com, Yelp, and Yahoo!. Several studies that compare and examine these platforms have concluded that ORs vary considerably in terms of their linguistic characteristics, semantic features, sentiment, rating, and usefulness as well as in the relationships between these features (Xiang, Du, Ma, and Fan, 2017). In addition to the quantitative features of valence (rating of OR), volume (total number of ORs) ,and variance (level of inconsistency of reviewers’ opinion), consumers are also allowed to provide textual comments about their experience with a particular business (Kwok, Xie, and Richards, 2017). However, although ORs have two evaluation components, the quantitative ratings, and the qualitative text written by the user, most research on ORs has been focusing solely on the quantitative component, even though it would seem that the qualitative component has the potential to provide a richer overview of ORs (Duan, Yu, Cao, and Levy, 2016). For the quantitative and qualitative research of ORs, different methods have been used in recent literature, such as data mining, association rules, natural language processing, text mining, naïve bayes, linear regression, deep learning, etc. (Ribeiro, Antonio, & Correia, 2020; Saura, Palos-Sanchez, and Grilo, 2019), but there are a wide range of methods and techniques that can be used and explored from various fields, such as data science and information technology, and in particular, from machine learning, statistics, and big data, among others. However, to focus on the qualitative component of ORs or even on both components—quantitative and qualitative—mixed-method approaches could be an interesting possibility. For this purpose, this Special Issue intends to provide a forum to discuss the methods and techniques that can be used for both quantitative and qualitative approaches to ORs analysis, as well as to identify new trends and developments in this area, including the possibility of exploring their applications in the hospitality and tourism industry.
Original languageEnglish
JournalInformation (Switzerland)
Publication statusPublished - 1 Mar 2021


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