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The main purpose of this study is to explore the effect of three dimensions of “home feeling” – home-as-practical, home-as-social and home-as-attachment – on the online rating of homestays and additionally considers the accommodation’s attribute performance and level of sharing.

To achieve the research aims, more than 9,738,335 items of user-generated content concerning 743,953 Airbnb listings covering 35 cities were collected as the study data. These data are analyzed through hierarchical regression.

The results show that all three dimensions of home feeling positively affect the online rating; all three dimensions negatively moderate the relationship between attribute performance and online rating; the size of the moderating effect of each dimension on the relationship between attribute performance and online rating gradually increases in the order home-as-practical, home-as-social and home-as-attachment; and as the level of sharing increases, the moderating effect of home feeling on the relationship between attribute performance and online rating diminishes.

This study contributes to the literatures on the role of home feeling in homestays, the online rating of homestays and the motivations of guests who choose different room types. The findings of this study can help hosts better understand the formation of online rating of homestays, make targeted improvements in rooms and services and create a home feeling for specific degrees of sharing. This in turn will help them to improve the online rating of their homestays, establish an excellent online reputation and, ultimately, increase sales.

This study advances knowledge by confirming three dimensions of home feeling not only have direct positive impacts on online rating but also mitigate the impact of attribute performance on online rating. This effect differs significantly in magnitude with the degree of sharing.

Growing health concerns amid the COVID-19 pandemic have led guests to focus on various aspects of hotel cleanliness. This study aims to investigate whether customers’ perceived importance of hotel cleanliness during their stay depends on local pandemic severity and moderators of the pandemic–cleanliness relationship.

Based on TripAdvisor data from 26,519 reviews in 2020 for 2,024 hotels across the USA, this study evaluated the importance of hotel cleanliness using the estimated coefficient of the cleanliness score in a regression of overall hotel rating scores.

Results of a multilevel ordered logit model confirmed that a more difficult local pandemic situation rendered cleanliness more important during hotel stays. Additionally, the effect of the pandemic was more pronounced among specific groups: men and travelers with more expertise, and guests staying in hotels without COVID-19 protocols for linen cleaning, with a lower average rating, with a larger size and in a more urbanized location.

This study represents a pioneering effort to assess how pandemics shape people’s (perceived) importance of cleanliness during hotel stays based on revealed data. Despite potential managerial relevance, a number of the moderating variables included in this study, such as traveler expertise and hotel location, have never been studied within the context of cleanliness perceptions during a pandemic.

Sustainable tourism is becoming more popular all over the world. Eco-friendly (green) hotels are properties that are friendly to the environment and are becoming increasingly popular among green travellers. Electronic word-of-mouth is a technique of communicating with consumers in order to share their experiences, and it is a significant marketing tool for hotels. This paper aims to identify the main themes shared in online reviews by tourists visiting eco-friendly hotels, and which of these themes were associated with satisfaction and dissatisfaction ratings.

The research used qualitative content analyses to analyse 1,202 user-generated content of the top 10 hotels in UK shared by guests on an online platform.

The analyses revealed nine themes in descriptions of airline travel experiences. These are “hotel amenities”, “services”, “location”, “staff”, “eco” (eco-friendly activities), “value” and “recommend/revisit” (intentions). Negative comments are associated with the “bathroom”, “mattress”, “water”, “bed”, “price”, “shower”, “Wi-Fi” and “restaurant” concepts.

This study differs from previous research in which it aims to address a void in the literature on the shortcomings of research focused on finding the dominant themes expressed in online reviews by tourists visiting eco-friendly hotels, and it does so using data mining approach.

This study aims to examine the role of experiential familiarity in determining the competitiveness of hotel chains. It does so by comparing the attribute-performance perceptions of guests who had and had not previously stayed at a property belonging to a specific hotel chain. It also examines how far such perceptions shape word-of-mouth and future purchase intentions.

Data were collected from 1,016 Finnish leisure tourists in 2021 using an online questionnaire, providing a representative sample of Finnish domestic leisure tourists.

The results indicate that the competitiveness of different hotel chains depends on a small number of key attributes. Differentiation between hotel chains can be seen from the results. Previous guests rate hotel chain attributes more highly than non-previous guests. Behavioral intentions do not differ between previous and non-previous guests, but how many times a person has stayed in the hotel chain significantly influences behavioral intentions. The results provide strategic levers that hotel chains can use to enhance their competitiveness.

Hotels should invest in attributes that have the biggest positive impact on customer behavior. These will be different for different hotel chains. By understanding these differences, it is possible to communicate relevant attributes to customers through marketing and develop hotel features that will drive revisit intention and word-of-mouth marketing.

This study found that while certain hotel attributes had a significant shaping effect on guests’ performance ratings, there were no decisive differences between those with or without experiential familiarity with the hotel chain.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

This study aims to integrate reviewers’ and readers’ discrepant perspectives on extremely negative reviews. Specifically, this study examines the relationship between negative emotion intensity levels and reviews helpfulness on two platforms: integrated websites and social networking sites (SNS) to emphasize the role of platform types on customers’ purchase decisions.

This research adopts a mixed-method approach of business intelligence approach and quasi-experimental design. Study 1 performed text mining and Welch’s t-test to compare reviewers’ negative emotion intensity levels on two platforms. Study 2 adopted a 2*2 factorial quasi-experimental design to examine how intense negative emotions impact the perceived reviews helpfulness on two platforms. A 3*2 factorial design in Study 3 also tested social tie strength’s moderating effect between the intensity of negative emotions and review helpfulness.

The current study reveals that integrated website reviewers tend to express more extreme negative emotions than SNS reviewers. SNS and integrated website readers deem reviews that embed severe negative emotions as less helpful. The moderating role of social tie strength between extremely negative emotions on review helpfulness was insignificant in the study.

This study enriches the online review literature by comparing writers’ and readers’ perspectives on online reviews with extremely negative emotions across two online platform types: integrated websites and SNS. From the writers’ perspective, this study highlights anonymity and the presence of an audience as essential factors that reviewers consider in selecting an online review platform to express themselves. This research also sheds light on how readers’ perspectives on extremely negative reviews conflict with the presumptions of writers of extremely negative reviews on integrated websites by demonstrating that content embedding extremely negative emotions is less helpful regardless of platform type.

This research provides online negative review management strategies to platform and hotel managers. The findings suggest hotel and review platform managers should consider adopting review alignment or monitoring systems based on negative emotions intensity levels since readers on both platforms perceive reviews embedding extremely negative emotions as less helpful. Additionally, hotel managers can progress promotions to guests who share online reviews on SNS since SNS reviewers are more likely to attenuate their extremely negative emotions when writing reviews.

This research innovatively provides a comprehensive overview of negative reviews’ production and consumption process from reviewers’ and readers’ perspectives. This research also provides practitioners insight into the nature of two different platform types and the management of negative reviews on these platforms.

The interviews were conducted with the respondents (the founder and Manager of De Cyber Hotel). Other data were obtained through the websites of the relevant businesses.

Siti Alia and her friends established De Cyber Hotel in January 2019. It was incorporated as a Malaysian private limited company in Cyberjaya, Selangor. Siti Alia was appointed as the hotel manager and was responsible for managing the hotel’s day-to-day operations and financial matters. Being a new budget hotel, competing with other established hotels was quite difficult. De Cyber Hotel used brochures and word-of-mouth for its promotion activities and mainly depended on walk-in guests. Siti Alia knew she had to take immediate action to ensure the hotel’s survival and could no longer rely on walk-in guests. Hence, to increase the occupancy and revenue rate, on 27 March 2019, De Cyber Hotel management decided to accept an offer from ABC Digital Booking to implement a digital booking mechanism and form a partnership for at least a year. ABC Digital Booking provided an online system to enable the listing and booking of budget accommodations and partnered with hotels to provide similar guest experiences across countries. After working and collaborating for 10 months with ABC Digital Booking, Siti Alia had to decide whether De Cyber Hotel should continue its alliance with ABC Digital Booking. Hence, she had to think thoroughly and consider the advantages and disadvantages, as well as the impact of her decision on the business.

Undergraduate Integrated Case Studies, Seminar in Management, Risk Management and Corporate Governance, Management Accounting, Financial Accounting, Strategic Management. Postgraduate Organizational Behaviour, Management Accounting and Controls, Strategic Management Accounting, Marketing Management, Hospitality Strategic Management, Entrepreneurship Development.

The main goal of this paper is to identify the attributes of consumer experience in Michelin-starred restaurants and to estimate their effects on restaurant ratings.

A sample of 70,233 online reviews of 224 Spanish Michelin-starred restaurants were analysed with the latent Dirichlet allocation algorithm. A sentiment analysis and a logistic regression analysis were also employed to estimate the effect of attributes on restaurant ratings.

Customer attention, food quality, decor and ambience and value for money are frequently used to define restaurant experience. However, it is shown in this study that the experience in a Michelin-starred restaurant goes beyond the evaluation of those four attributes. Furthermore, the effect of the factors that were identified on customer satisfaction differed depending on the restaurant ratings.

The findings are linked to the context of Spanish Michelin-starred restaurants. It is also assumed in this study that online reviews are based on truthful opinions.

Restaurant managers should primarily focus on customer attention and food quality to achieve customer satisfaction. In addition, those restaurants with an error-free service and a highly appreciated wine list among diners are more likely to achieve the culinary excellence that deserves a 5-star rating on TripAdvisor.

The attributes of the restaurant experience are frequently identified in literature reviews. Research based on text-mining analyses of customer reviews to discover a posteriori the factors that define a restaurant experience is scarce, and particularly difficult to find in the context of Michelin-starred restaurants.

This paper aims to classify tourist accommodation using data from Booking.com and TripAdvisor and analyse the extent to which the different segments identified differ in terms of being adults-only.

In total, 1,535 properties located in nine Spanish sun and beach destinations were examined using a latent class cluster analysis (LCCA). The bias-adjusted three-step approach was used to investigate the differences between belonging to adults-only accommodation or not among the identified clusters.

Results show that adults-only accommodation tends to belong to the cluster with higher online ratings. In small Spanish islands, adults-only hotels account for a large share (more than 25%) of hotels.

It was not possible to analyse whether the higher rating was due to the accommodation being better or due to the tourists being more satisfied with their stay.

In urban destinations, the model is not widely used. However, in coastal destinations, it is becoming more than a novelty or a new trend.

In small Spanish islands, people traveling with children are becoming a minority. Families may feel discriminated against and express dissatisfaction with this situation in the future.

This study covers the gap in the academic literature on this growing hotel segment.

This study aims to explore the perspectives of patrons and the underlying factors influencing luxury consumption in British Michelin-starred restaurants. While numerous studies have investigated consumers' purchase behavior of luxury items, there is limited research focusing on the utilization of premium restaurant services. Additionally, the hospitality literature has rarely addressed the emergence of discreet luxury consumption. Therefore, this research aims to examine the experiences of British Michelin-starred restaurants by incorporating online reviews from some of the most renowned establishments in the country. The initial objective of this study was to identify the predominant themes within British Michelin-starred restaurant experiences. Furthermore, the authors sought to analyze whether these main themes varied across different market segments based on guest types.

Using text mining tools, the authors analyzed a sample of 4,393 online reviews. Qualitative data analysis was conducted using the Leximancer program, which identified the dominant themes. Additionally, the authors performed an analysis to identify the major narratives associated with different types of guests.

The results of this analysis demonstrate that guests express a high level of satisfaction with their experiences at British Michelin-starred restaurants. The dominant themes within the narratives include food, wine, restaurant, time, reservation and innovation. It is important to note that these narratives vary depending on the type of guest.

Previous studies have highlighted the importance of market segmentation in Michelin-starred restaurants. This research addresses this need by specifically categorizing British Michelin-starred restaurants based on traveler type and the main concerns of their customers. The extensive data the authors collected and the authors' approach to utilizing guests' testimonials instead of traditional surveys contribute significantly to the field of academia and restaurant management.