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Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.

The main purposes of this article are twofold: (1) to investigate the unexplored connections among destination gender personality, destination stereotypes, brand attachment and destination brand love and (2) to examine the moderating role of destination involvement in the association between destination stereotypes and destination brand attachment (DBA).

The conceptual model is evaluated using qualitative methods (i.e. three focus groups, six academic experts and a pilot study). In addition, using an empirical study with 610 international travelers who visited Egypt selected by systematic random sampling, 8 hypotheses were analyzed and tested using structural equation modeling (SEM) by AMOS 23, confirmatory factor analyses and exploratory factor analyses.

The study’s results suggest that destination gender plays a vital role in enhancing stereotypes, stereotypes positively affect attachment and DBA positively affects destination brand love. Finally, the results show that destination involvement moderates the dual influence of the warmth and competence of stereotypes on destination attachment.

The research supports the contention that social perception mechanisms are crucial in destination brand perception. It offers new understandings of the association between customers' destination brand perceptions and their responses to destinations.

This paper contributes to the travel literature by analyzing a novel model of destination gender personality, stereotypes, DBA and destination brand love using both social role (SR) theory and a stereotype content model (SCM). Besides attempting this task, it explores the moderating role of destination involvement in the association between stereotypes and destination attachment using the elaboration likelihood model.

Tourists with different cultural backgrounds think and behave differently. Accurately capturing and correctly understanding cultural differences will help tourist destinations in product/service planning, marketing communication and attracting and retaining tourists. This research employs Hofstede's cultural dimensions theory to analyse the variations in destination image perceptions of Chinese-speaking and English-speaking tourists to Xiamen, a prominent tourist attraction in China.

The evaluation utilizes a two-stage approach, incorporating LDA and BERT-BILSTM models. By leveraging text mining, sentiment analysis and t-tests, this research investigates the variations in tourists' perceptions of Xiamen across different cultures.

The results reveal that cultural disparities significantly impact tourists' perceived image of Xiamen, particularly regarding their preferences for renowned tourist destinations and the factors influencing their travel experience.

This research pioneers applying natural language processing methods and machine learning techniques to affirm the substantial differences in the perceptions of tourist destinations among Chinese-speaking and English-speaking tourists based on Hofstede's cultural theory. The findings furnish theoretical insights for destination marketing organizations to target diverse cultural tourists through precise marketing strategies and illuminate the practical application of Hofstede's cultural theory in tourism and hospitality.

This paper aims to measure the intention to use digital marketing strategies to enhance the performance of tourism business as well as the extent of digital renovation applications in tourism for sustainable business in a new normal era.

This paper is an insight from the existing relevant literature on the tourism business from time immemorial. The conceptual framework of this study is designed based on previous studies of digital marketing practices for tourism businesses. Furthermore, data were collected from 270 respondents, of which the valid response rate is 72.97%. Partial least square (PLS)-structural equation modeling (SEM) is used to validate the conceptual framework and hypotheses testing.

Among the nine hypotheses path, seven were supported. This study result shows that perceived usefulness, perceived ease of use, social media marketing and tourism business performance are critical factors for adopting digital marketing in tourism. Thus, tourism service providers' intention has a positive impact to meet the expectation of tourists and adoption of digital marketing.

The study's results will assist tourism researchers and service providers in understanding an authentic relationship between digital practices of tourism business and tourist satisfaction. In addition, the legacy of tourism business through digital marketing empowers the owner and community.

The study is the first to explore the relationship between tourism business performance and digital marketing during the new normal era for the empowerment of local community and expanded business in tourism sector.

The purpose of this paper is to investigate the unexplored part of the historical evolution of travel agencies in Spain, from the end of the 20th century to the 21st century. When examining promotion strategies, the study focuses on the change in marketing and public relations strategies based on the incorporation of information and communication technologies and, in particular, the use of the internet.

This study draws on a qualitative analysis of the different strategies used by traditional agencies and online agencies in Spain from the mid-19th century to the present. This analysis shows how traditional communication strategies survived at the beginning of the 21st century, together with other more innovative ones, while some disappeared, being eliminated by the new online travel agencies, which created a particular conception of marketing and communication. This paper is divided into the following parts: the introduction; the beginnings of travel agency promotion in the 20th century; the evolution of promotion in travel agencies since the late 20th century; communication innovation at the beginning of the 21st century; online travel agencies; and conclusions.

This study shows that although online agencies did not manage to position themselves with a large turnover, they generated advantages and sharpened their imagination to create a new, more economical advertising model, eliminating the costs of public relations and advertising campaigns. In addition, they allowed clients to have greater independence when making their reservations, while enabling them to monitor the tastes of potential and real clients and add blogs so that consumers could express their degree of satisfaction with the product or services provided by the agency.

The focus of attention is the travel agency sector in Spain and, more specifically, communication. Studies on travel agencies and their marketing have been very scarce and partial, impeding professionals in the tourism sector from having a broad vision to direct their promotional and public relations actions. The originality of this article lies in its making a comparison between two different visions of tourism marketing and, specifically, of travel agencies, that is, the traditional vision and the innovative one. It thus helps all professionals in the sector to value and improve their marketing and communication strategies.

This study aims to examine hotel guests’ acceptance of technology agency – the extent to which they would let artificial intelligence (AI)-based systems make decisions for them when staying in hotels. The examination was conducted through the prism of several antecedents of acceptance of technology agency, including perceived ethics, benefits, risks and convenience orientation.

A thorough literature review provided the foundation of the structural model, which was tested using confirmatory factor analysis, followed by structural equation modeling. Data were collected from 400 US hotel guests.

The most important determinant of acceptance of technology agency was perceived ethics, followed by benefits. Risks of using AI-based systems to make decisions for consumers had a negative impact on acceptance of technology agency. In addition, perceived loss of competence and unpredictability had relatively strong impacts on risks.

The results provide a conceptual foundation for research on systems that make decisions for consumers. As AI is increasingly incorporated in the business models of hotel companies to make decisions, ensuring that the decisions are perceived as ethical and beneficial for consumers is critical to increase the utilization of such systems.

Most research on AI in hospitality is either conceptual or focuses on consumers’ intentions to stay in hotels that may be equipped with AI technologies. Occupying a unique position within the literature, this study discusses the first time AI-based systems that make decisions for consumers. The value of this study stems from the examination of the main concept of technology agency, which was never examined in hospitality.

This study aims to explore the social networks and network interactions of bed-and-breakfast (B&B) entrepreneurs in rural China. In addition, it evaluates how such network interactions relate to rural resilience.

In-depth interviews were performed in two locations: Ningbo and Dujiangyan, China. Purposive sampling was combined with snowball sampling to select interviewees. The 154 interviews involved 29 B&B owners and relevant social actors. All codes and data were analyzed using the discourse analysis framework.

The B&B owners’ social networks were identified based on strategic goals, revealing a business operation network, business development network and business citizenship network. Challenges in seeking financial support for rural B&Bs during the pandemic were specified along with network interactions. The institutional adaptation approach was used to evaluate network interaction in rural B&B business. It was argued that other networks would react based on primary network members’ goal compatibility and the effectiveness of the primary network in addressing obstacles.

This study indicates that the rural B&B entrepreneurs’ interactions with various networks could influence on business resilience, community resilience as well as rural resilience.

By combining the institutional adaptation typology with social network theory, this study generates a new typology of network interactions for rural B&Bs. The typology helps to explain how and why B&B entrepreneurs make decisions and provides a broader scope of social networks involved in these business operations.

This study, rooted in affordance-actualization theory and communication theory, aims to critically examine how ChatGPT influences users’ transition from new adopters to loyal advocates within the context of travel decision-making. It incorporates constructs including communication quality, personalization, anthropomorphism, cognitive and emotional trust (ET), loyalty and intention to adopt into a comprehensive model.

This study used quantitative methods to analyze data from 477 respondents, collected online through a self-administered questionnaire by Embrain, a leading market research company in South Korea. Lavaan package within R studio was used for evaluating the measurement model through confirmatory factor analysis and using structural equation modeling to examine the proposed hypotheses.

The findings reveal a pivotal need for enhancing ChatGPT’s communication quality, particularly in terms of accuracy, currency and understandability. Personalization emerges as a key driver for cognitive trust, while anthropomorphism significantly impacts ET. Interestingly, the study unveils that in the context of travel recommendations, users’ trust in ChatGPT predominantly operates at the cognitive level, significantly impacting loyalty and subsequent adoption intentions.

The findings of this research provide valuable insights for improving Generative AI (GenAI) technology and management practices in travel recommendations.

As one of the few empirical research papers in the burgeoning field of GenAI, this study proposes a highly explanatory model for the process from affordance to actualization in the context of using ChatGPT for travel recommendations.

This study aims to explore families that travel with children, as focuses on vulnerabilities, resource constraints and service exclusion through the lens of transformative service research (TSR). This paper investigates: how the experienced vulnerability of these families is shaped by structural, interpersonal and intrapersonal constraints, and how the constraints influence the family tourist-resource interaction in the air travel service encounter.

In total, 2,855 reviews of the family tourists with children were analyzed with text mining, t-test and multidimensional scaling using the interpretive language R to answer the research questions with analyses on unstructured (e.g. text) and structured (e.g. consumer rating) data.

The findings of the empirical investigation answered how experienced vulnerability is shaped by structural, interpersonal and intrapersonal resource constraints and the types of family tourist-resource interaction in the travel service encounter to understand the resource constraints. The findings of this paper help examine family tourism experiences from a value formation perspective to unfold how stakeholders interact to form value while increasing and decreasing their well-being by the value of co-creation and co-destruction.

This research helps advance the TSR’s service inclusion framework by enabling opportunities, offering choice, relieving suffering and fostering happiness with empirical findings in travel service encounters. These findings are particularly insightful to family tourists with children struggling with unfair access and treatment in aeromobility service encounters, which may help enhance the well-being of individuals and communities.

This study aims to analyze the moderating roles of familiarity, generation and gender on the impacts of coronavirus fear-uncertainty on the destination image and visiting intentions post-COVID-19.

This paper seeks to provide evidence for a research conclusion by conducting a survey of 431 potential travelers of various nationalities who visited Egypt. The data were examined using structural equation modeling with a multigroup analysis and PROCESS MACRO.

The findings indicated that the links between coronavirus fear-uncertainty, the destination image and intention to visit were significantly different from one gender and generation group to another. Moreover, it showed that destination familiarity moderates the negative effects of coronavirus fear-uncertainty on the destination image and intention to visit.

To the best of the authors’ knowledge, this paper is the first to explore the moderating role of destination familiarity, generation and gender in the effects post-COVID-19 of coronavirus fear-uncertainty on the destination image and travelers’ intention to visit using generational cohort theory and gender schema theory.