Search Results (19)

(1) This study aims to quantify differences between platforms and countries by comparing Hilton’s ratings on Booking.com and Google.com in the V4 countries. (2) Data were collected directly from Booking.com and Google.com for selected Hilton hotels. Descriptive statistics were used to process and analyze the data, and a paired Student’s T-test was used to compare standard deviations between platforms. (3) The analysis showed that these differences can be applied not only to subjective preferences but also to sociotechnical devices, including cultural platforms and their associated norms and user expectations. Additionally, factors such as price, food quality, and atmosphere were shown to influence overall guest satisfaction, with ratings approximately indicating satisfaction or dissatisfaction. (4) From a practical perspective, these insights can help hotel managers optimize their online communication strategy, tailor content to different platforms, and manage their reputation more effectively. Overall, the findings highlight that effectively managing online reviews is key to establishing trust, increasing satisfaction, and ensuring the long-term success of the Hilton brand in diverse sociocultural contexts. Future research should focus on sociotechnical aspects and the impact of seasonal or marketing campaigns on reviews to gain a more comprehensive understanding of the dynamics of online reviews in the hospitality industry. Full article

Generation Z (Gen Z; born 1997–2012) is reshaping global tourism through digital fluency, ethical awareness, and a desire for authentic, sustainable travel experiences. This study surveys 413 Gen Z travelers across France, Portugal, Romania, and the USA to map their booking behaviors, information sources, transport modes, accommodations, dining practices, and leisure activities. The findings reveal a strong preference for independent online bookings and social-media-influenced destination choices (Instagram, TikTok), with air and car travel being used for long-distance journeys and walking/public transit being used for local journeys. Accommodation spans commercial hotels and private rentals, while informal, local dining and nature- or culture-centered leisure prevail. Chi-square tests were performed to identify differences between countries. To reveal distinct traveler segments and their country’s modulations towards sustainability, a hierarchical cluster analysis was performed. The results uncover four segments: “Tech-Active, Nature-Oriented Minimalists” (32.3% in France); “Moderate Digital Planners” (most frequent across all countries, particularly dominant among Romanian respondents); “Disengaged and Indecisive Travelers” (overrepresented in the USA); and “Culturally Inclined, Selective Sustainability Seekers” (>30% in France/Portugal). Although sustainability is widely valued, only some segments of the studied population consistently act on these values. The results suggest that engaging Gen Z requires targeted, value-driven digital strategies that align platform design with the cohort’s diverse sustainability commitments. Full article

Understanding and promoting guest satisfaction is central to the economic sustainability of the hospitality industry. Satisfaction influences consumers’ booking intentions, hotel choice, loyalty, and the reputation and performance of accommodation establishments. Thus, accurate decision making by hotel managers relies on trustworthy and easily accessible information on the variables that affect guest satisfaction. Nowadays, this information is available through reviews and ratings provided by online platforms, such as TripAdvisor. Indeed, much research into guest satisfaction uses TripAdvisor reviews. However, this study aims to analyse guest satisfaction using only TripAdvisor ratings. These ratings can be more succinct and tractable indicators than reviews. A sample of 118 hotels in Cape Verde and the Azores, two archipelagos belonging to Macaronesia, and a descriptive, predictive, and discriminant methodology are employed for this purpose. Four main results are obtained. First, the rated items on TripAdvisor are consistent with the scientific literature on this topic. Second, TripAdvisor ratings are valid and reliable. Third, TripAdvisor ratings can predict guest satisfaction based on the perceived quality of hotel services. Fourth, there are significant differences in ratings depending on the tourism destination chosen. These results are of interest to researchers, tourists, as well as hotel, destination, and platform managers. Full article

Despite free access to complete information regarding hotel quality and reference prices, consumers perceive significant price differences across different online platforms. We explore how perceived price dispersion on online travel agency platforms influences consumer purchase intention through mental account theory and propose a psychological mechanism explaining why consumers may tolerate and even embrace price discrepancies. Study 1 employs a scenario-based experiment that manipulates differing levels of price dispersion for the same hotel booking, demonstrating that higher PPD significantly amplifies perceived transaction utility and, in turn, acquisition utility. Study 2 corroborates these findings through an online survey with judgment sampling, highlighting that consumers—despite access to comprehensive OTA information—are often motivated, rather than deterred, by price discrepancies; multiple variable combinations were tested to ensure robust findings. This study challenges traditional marketing theories suggesting that price dispersion signals market unfairness and reduces consumers’ purchasing intention; instead, it mentally stimulates consumers. This perception enhances transaction and acquisition utility, positively impacting purchase intention. We also offer a robust model for mechanism study and provide insights for leveraging price dispersion as a cost-less promotional strategy, potentially increasing consumer engagement without additional marketing expenditure. We contribute to the literature by integrating the mental account theory into the context of online marketplaces and developing a price dispersion model with psychological utility in the consumer decision-making process. Full article

Social commerce plays a significant role in various aspects of the hotel industry. By using social commerce platforms such as Facebook, Instagram, and hotel booking websites, hotels can enhance their brand visibility, engage more effectively with guests, and stimulate hotel bookings. Nonetheless, prior research reported a lack of studies in this area, namely social commerce in the context of domestic tourism. Drawing on Stimuli–Organism–Response (SOR) theory as being a well-established framework in social commerce research, this study seeks to examine the impact of social commerce on hotel booking intentions, both directly and indirectly, by considering the mediating effects of both brand image and customer engagement. This research used an online survey questionnaire as a tool for collecting primary data from domestic tourists in Egypt during the period from January to April 2024. The study sample encompassed 315 participants who were recruited using the convenience sampling technique. Using Smart PLS 4.0 software, Structural Equation Modeling was performed to examine the proposed model and hypotheses. The results highlighted the significant impact of social commerce on both hotel brand image and customer engagement, which in turn encouraged booking intentions among potential domestic guests. The results also supported the significant mediating effect of hotel brand image and customer engagement in the relationship between social commerce and hotel booking intentions. This study provides some theoretical contributions to the literature of hospitality management by addressing notable gaps in knowledge. This study also suggests some practical implications for industry executives that support their social commerce techniques and boost booking intentions and behavior among domestic tourists such as creating visually attractive content, sponsoring virtual mega events, actively interacting with social media followers, and incorporating booking functionalities in social media platforms. In so doing, hotels can boost their sustainable marketing practices to target a promising market segment by exploiting Web 2.0 capabilities. Full article

Sustainable practices are becoming increasingly important to tourists and hotel guests. As a result, destinations, hotels, and booking platforms are implementing eco-friendly practices and displaying sustainable badges to communicate their efforts to guests. While the use of sustainable badges increases the visibility of eco-friendly hotels, it is unclear whether they actually influence guests’ choices. This study aimed to explore the effects of the presence of sustainable badges and the awareness of sustainable practices on tourists’ attitudes and behavioral intentions using an experimental design. People who previously used a hotel-booking platform were randomly assigned to four hotel-booking scenarios with the manipulated presence of sustainable badges and awareness about sustainable practices on the website. The data analysis techniques included an analysis of variance, moderation, and a mediation analysis. The study’s results provided empirical evidence that the presence of a sustainable badge could have a positive impact on guests’ attitudes toward a hotel and intentions to book a hotel. These results contributed to the body of knowledge on the impact of sustainable practices, addressed an attitude–behavior gap between tourists’ attitudes and behavioral intentions, and provided valuable insights for destination management organizations, hotel managers, booking platforms, and policymakers interested in promoting sustainable tourism practices. Full article

Recommender systems have become indispensable tools in the hotel hospitality industry, enabling personalized and tailored experiences for guests. Recent advancements in large language models (LLMs), such as ChatGPT, and persuasive technologies have opened new avenues for enhancing the effectiveness of those systems. This paper explores the potential of integrating ChatGPT and persuasive technologies for automating and improving hotel hospitality recommender systems. First, we delve into the capabilities of ChatGPT, which can understand and generate human-like text, enabling more accurate and context-aware recommendations. We discuss the integration of ChatGPT into recommender systems, highlighting the ability to analyze user preferences, extract valuable insights from online reviews, and generate personalized recommendations based on guest profiles. Second, we investigate the role of persuasive technology in influencing user behavior and enhancing the persuasive impact of hotel recommendations. By incorporating persuasive techniques, such as social proof, scarcity, and personalization, recommender systems can effectively influence user decision making and encourage desired actions, such as booking a specific hotel or upgrading their room. To investigate the efficacy of ChatGPT and persuasive technologies, we present pilot experiments with a case study involving a hotel recommender system. Our inhouse commercial hotel marketing platform, eXclusivi, was extended with a new software module working with ChatGPT prompts and persuasive ads created for its recommendations. In particular, we developed an intelligent advertisement (ad) copy generation tool for the hotel marketing platform. The proposed approach allows for the hotel team to target all guests in their language, leveraging the integration with the hotel’s reservation system. Overall, this paper contributes to the field of hotel hospitality by exploring the synergistic relationship between ChatGPT and persuasive technology in recommender systems, ultimately influencing guest satisfaction and hotel revenue. Full article

The number of reviews from customers on travel websites and platforms is quickly increasing. They provide people with the ability to write reviews about their experience with respect to service quality, location, room, and cleanliness, thereby helping others before booking hotels. Many people fail to consider hotel bookings because the numerous reviews take a long time to read, and many are in a non-native language. Thus, hotel businesses need an efficient process to analyze and categorize the polarity of reviews as positive, negative, or neutral. In particular, low-resource languages such as Thai have greater limitations in terms of resources to classify sentiment polarity. In this paper, a sentiment analysis method is proposed for Thai sentiment classification in the hotel domain. Firstly, the Word2Vec technique (the continuous bag-of-words (CBOW) and skip-gram approaches) was applied to create word embeddings of different vector dimensions. Secondly, each word embedding model was combined with deep learning (DL) models to observe the impact of each word vector dimension result. We compared the performance of nine DL models (CNN, LSTM, Bi-LSTM, GRU, Bi-GRU, CNN-LSTM, CNN-BiLSTM, CNN-GRU, and CNN-BiGRU) with different numbers of layers to evaluate their performance in polarity classification. The dataset was classified using the FastText and BERT pre-trained models to carry out the sentiment polarity classification. Finally, our experimental results show that the WangchanBERTa model slightly improved the accuracy, producing a value of 0.9225, and the skip-gram and CNN model combination outperformed other DL models, reaching an accuracy of 0.9170. From the experiments, we found that the word vector dimensions, hyperparameter values, and the number of layers of the DL models affected the performance of sentiment classification. Our research provides guidance for setting suitable hyperparameter values to improve the accuracy of sentiment classification for the Thai language in the hotel domain. Full article

This study offers a comprehensive examination of the literature surrounding technology and tools in the hospitality industry. A bibliometric analysis was performed on 709 Scopus-indexed publications from 2000 to January 2023, with a focus on identifying key players, institutions, research trends, and the co-occurrence of keywords. The results shed light on the scientific landscape of technology and tools in the hospitality sector, emphasizing the significance of big data and the customer experience in the sharing economy. The study also presents the architecture of new software that offers guests the ability to customize their hotel stay, classified as part of the first cluster in the co-occurrence of keywords analysis. This approach highlights the growing importance of big data and customer experience and makes a valuable contribution to the field by offering a tool for hotel booking customization. Furthermore, the study underscores the importance of collaboration between academic institutions and private companies in providing a mutually beneficial platform that exceeds the expectations of both hotels and guests. Full article

The sharing economy has risen rapidly in the past decade. The development of shared accommodation encourages more hotels and guesthouses to attract customers through online accommodation-sharing platforms, which has become a meaningful way to fight against the competition of the traditional hotel industry. In this condition, what the hosts are concerned about most is how to attract customers’ attention through the platform display to increase reservations. Based on construal level theory, this paper explores how hosts’ information displayed on online accommodation-sharing platforms determines consumers’ booking behavior by influencing their psychological distance. We use machine learning methods to mine the raw data and extract the representational factors of psychological distance. Based on the data-driven behavior decision-making approach, we collected valid large-scale fine-grained secondary actual consumption data from Airbnb, the world’s leading online accommodation-sharing platform, and scientifically and intelligently processed the data using machine learning methods, then tested the hypotheses using the regression analysis software STATA15. Our findings suggest that both social distance and temporal distance have a negative impact on booking behavior of guests. In detail, subject diversity, perspective taking, and facial attractiveness in the dimension of social distance positively influence guests’ booking behavior; instant bookable in the temporal distance dimension positively affects booking behavior, while response time has a negative effect. This study contributes to the literature by empirically examining psychological distance in the booking behavior of guests in shared accommodation through the processing and analysis of actual consumption data. The findings have important practical implications for how shared accommodation service providers and sharing economy platform managers can operate better. Full article

Within the fast paced digital transformation of the tourism and hospitality sector, the modalities of booking a tourist accommodation have been radically transformed by the uptake of digital business models and digital platforms. This study examines the underlying mechanisms and key specificities of digital business models for two of the sector’s sub-segments—hotel accommodation bookings and yacht charter accommodation bookings. Based on the literature review findings, the case study method was applied in relation to key digital business models relevant for hotel bookings. On the other end, in relation to the yacht charter segment and its digital business models, an empirical research was conducted, encompassing a final sample of 162 yacht charter agencies from 42 countries worldwide. The analyzed digital business models have multiple similarities, while there are specific differences between the two hospitality segments. Even though digital business models are highly important in both segments, they are generally more developed and sophisticated in the hotel segment, which is related to the segment’s sheer size, in comparison with the younger and smaller yacht charter segment. The novelty is reflected in shedding more light on the characteristics of digital business models in the fast-developing yacht charter segment, including through an empirical study. Full article

The aim of this study is to develop a new performance evaluation tool that is stringently applied to the hotel chains, considering the associated ethical marketing dimensions to measure its proper strategic, tactical, and operational role and impact within hospitality marketing management plans, campaigns, and strategies implemented. A Delphi technique was conducted as the selected research qualitative method, comprising three rounds. A total of 23 panel participants, such as directors and managers of marketing, e-commerce, sales, and branding, completed all three rounds. Two major areas of ethical marketing, internal and external, both divided into five dimensions, each with underlying items, were found to comprise the ethical marketing model for luxury hotel chains: (1) internal area of marketing (with five dimensions: integration, training, equal opportunities, performance evaluation, and smart policies) and (2) external area of marketing (with five dimensions: stakeholders, booking platforms and CRM, marketing plan, digital marketing campaigns, and social media platforms). The study concludes with useful insights and remarks. The generalisability of the results may be limited owning to the partial or not full applicability across all luxury hotel chains. The model still needs to be empirically applied in luxury hotel chains to enrich its robustness, covering a wider spread of four- and five-star luxury hotels. There is a growing potential for researchers, hotel decision makers, and marketing and sales managers and directors to achieve many advantages and benefits from the proposed model, supporting the efforts for ethical marketing theory and practice, such as hotel brand positioning strategies and formulation of more targeted and finely tuned ethical marketing strategies, tactics, and plans. This is the first study to develop and validate a performance evaluation tool of ethical marketing for luxury hotel chains. This pioneering approach extends the scope into ethical marketing because this model has never been used in this area. Full article

The widespread use of the Internet has changed consumer buying behavior, especially among tourists, considering the intangibility of the tourist product. Although globally the modern tourist is a consumer of the new online market, there is a lack of studies addressing the level of development of the hotel business in relation to online bookings by residents of tourist destinations. Furthermore, this article analyzes the factors that impact the use of e-commerce by these residents in the acquisition of tourist accommodation services. A conceptual model was adopted, using the constructs “social influence” and “price” of the unified theory of acceptance and use of technology 2 (UTAUT2), also including “trust” and “perceived risk”. An electronic questionnaire was used to collect data from a sample of 195 residents of Fortaleza, Ceará, Brazil. Data analysis included descriptive statistics, exploratory factor analysis, Fisher’s exact test, and multiple linear regression. The results show that price and social influence are the most significant constructs associated with booking a hotel online, while trust does not influence the use of the Internet. As practical implications, the findings of this study provide important information for hotel managers, as they allow a better understanding of the profile of respondents who book online, as well as which factors influence online behaviors, contributing to increasing the knowledge of digital platforms in the consumer market and, consequently, the development of the hospitality sector. Full article

The unprecedented crisis faced by the hotel industry due to the COVID-19 pandemic has brought about changes in guests’ perceptions of service quality attributes. In view of the need to monitor this environment, this study is dedicated to identifying the main negative topics related to the quality of hotel services in Brazil and the impacts of the COVID-19 pandemic on guests’ perception of these topics. For this purpose, a set of 866,048 online hotel reviews were collected from the Booking.com platform. Initially, data were analyzed through topic modeling to identify the attributes addressed by guests in their evaluations. Subsequently, an average comparison method was used to evaluate the impact of the pandemic on the evaluation scores of each attribute. A total of 13 topics related to five attributes of hotel service quality were identified. The topics related to room cleaning and check-in were the most negatively impacted by the COVID-19 pandemic, with the largest drops in average evaluation scores. Full article

The tourism industry can significantly benefit from the blockchain since its implementation can build trust among stakeholders and improve customer satisfaction. However, most of the existing tourism-specified blockchain platforms are single-chains that provide business support for enterprises without guaranteeing transaction information privacy. Besides, these platforms are specified to a single use case and lack interoperability with other platforms to support heterogenous tourism services. This paper aims to address this issue by introducing a multi-chain architecture that utilizes multiple blockchains to enhance processing capability and provide various business services for the tourism industry. The proposed multi-chain architecture improves the interoperability between the activities in different chains by providing functional requirements in practical applications and supports the inter-ledger application. In addition, the private blockchain will be made available to allow users to access the network through central authorization. It also increases the transaction processing capability by distributing multiple tasks across the chains for large-scale applications. To demonstrate the usability and efficiency of the developed approach, a case study on hotel booking is conducted using the blockchain frameworks Winding Tree and Hyperledger Fabric. A comprehensive evaluation experiment is conducted, and the results show the significance of the proposed system. Full article