Purpose: This study examines the influencing factors of smart technology use behaviour (STUB), influencing tourist satisfaction and enhancing revisit intention for the Chinese tourism destination. Further, the moderating role of place attachment on the relationship between STUB, tourist satisfaction and revisit intention has been examined.Design/methodology/approach: The study employs quantitative methodology by incorporating the planned behaviour theory to develop the hypotheses. Using an online survey link, 409 responses were collected from the tourists employing a non-probability convenience random sampling technique.Findings: The partial least squire-structural equation modelling (PLS-SEM) results show that social influence significantly affects STUB, tourist satisfaction and revisit intention. Also, the anticipated positive behaviour has positive and significantly affects STUB and revisit intention. Finally, the findings show that tourist satisfaction significantly affects revisit intention in the tourist destinations in China.Research limitations/implications: A quantitative research design was applied, employing a random sampling technique, and surveys were conducted with tourists only in current research. However, future research can incorporate a wide range of methodology by collecting data from other tourism stakeholders to have an in-depth evaluation of repeat visitation behaviour. Future research can enhance the current conceptual framework by including other relevant variables like negative anticipated emotions at other locations, as the current study was conducted in the Chinese context.Originality/value: This research adds value to the tourism destination to formulate tourist satisfaction and revisit intention. Implications are provided for a more nuanced understanding and effective planning in tourism destinations while considering smart technology use.

Purpose: This study investigates the impact of smart technology, artificial intelligence, robotics and algorithms (STARA) on green performance (GP) in hospitality organisations, the mediating role of green human resource management (GHRM), employees’ green commitment (EGC), and the moderating role of green psychological climate (GPC) in the hospitality industry landscape of Malaysia. Design/methodology/approach: The study uses a quantitative survey-based, cross-sectional approach. PLS-SEM has been applied to analyse the direct and indirect relationships. Using the non-probability sampling method, a purposive sampling technique was used to collect 240 data points from top- and mid-level managers of five-star hotels in Malaysia. Findings: This study identified that STARA positively influences green HRM and EGC, impacting green performance. However, STARA does not positively impact GP. Moreover, the study identified a significant mediation effect of EGC and GHRM practices between STARA and GP and a moderation effect of GPC between green HRM and EGC. Practical implications: The study can provide valuable insights for the government and policymakers to update their policies for sustainable development using high-end technologies. It will also help the relevant stakeholders and think tanks assess the current status and commitment to several sustainable goals. Originality/value: By integrating the dynamic capability theory (DCT) and the social cognitive theory (SCT), this study proposed a new framework incorporating STARA capabilities with GHRM, GPC and EGC, which is novel in the body of understanding. It provides novel moderated-mediation evidence and bolsters existing insights.

With rapid AI advancements, AI chatbots have become vital for hotels to enhance customer experience and optimize marketing strategies. This chapter examines AI chatbot integration in hotel marketing, its impact on customer experience, and implementation strategies. Through literature and case studies, it highlights AI chatbots' roles and challenges in hotel marketing and offers strategic solutions to technical, user acceptance, management, operational, and socio-cultural issues. AI chatbots personalize services, boost operational efficiency, and enhance customer satisfaction and loyalty by understanding and responding to customer needs. They provide instant information and solutions, offering more humane and efficient services. Additionally, AI chatbots help hotel management better understand customer behavior and preferences, leading to accurate market positioning and service optimization. This chapter explores how AI chatbots transform guest engagement and marketing in the hotel industry and provides strategic recommendations and a research agenda for further exploration.

The rapid advancements in ICTs and the rise of Web 3.0 have revolutionized the tourism industry, reshaping the creation and delivery of experiences through digital co-creation. This article explores how these technologies facilitate active tourist participation in developing travel experiences, with a focus on the Malaysian tourism sector. Using the Service-Dominant (S-D) logic framework, it highlights the shift from traditional goods-dominant logic to a service-oriented approach, fostering a more interactive and collaborative environment. Digital platforms like social media and travel blogs play a crucial role in personalizing experiences and building a sense of community. The integration of AI and IoT further enhances authenticity and personalization. The article also addresses challenges in data management, the need for a supportive organizational culture, and opportunities for innovative tourism products and sustainable development. Future research should examine the long-term impacts of digital co-creation on tourism.

This study uses protection motivation theory as its theoretical foundation to examine the relationships between crowding experience, cognitive appraisal, risk perception, and protection behavioral intention. Data were gathered from 361 tourists who had experienced crowding situations. Structural equation modeling was then used to test a proposed conceptual model. The results indicate significant relationships between coping appraisal, risk perception, and tourists' protection intention. Risk perception, meanwhile, was found to fully mediate the relationship between crowding experience and protection behavior intention. Implications for tourism management include the need to promote not only awareness of overcrowding but also readiness among tourists to adapt to overcrowded conditions. More and better information is needed on the potential for overcrowding and its associated risks before tourists respond regarding protective behavior change.