ABSTRACT The increasing elderly population has led to growing attention towards the grey segments in the travel and tourism industry. This study explores the relationship between job burnout, pilgrimage experience desire, and intention to travel among elderly working employees. Additionally, the study checks the mediating effect of relaxation desire and religiosity on job burnout and pilgrimage experience desire. The study utilised a combination of online and offline surveys to collect a sample of 476 elderly employees working in India. Utilising PLS-SEM, the study found that job burnout positively impacts pilgrimage experience desire, religiosity, and relaxation desire. Moreover, findings reveal that the desire for relaxation and religiosity positively mediate the relationship between job burnout and the desire for pilgrimage experience. The study also found that the desire for relaxation and the pilgrim experience impacts the intention to travel among elderly working employees. The study’s implications are not limited to negative travel motives among grey segments but also add value to the pilgrimage and religiosity sector in the tourism context. The study offers practical implications for employers, tourism marketers, and the travel industry, suggesting travel programmes and packages tailored to the grey segment, including incentives focused on spiritual and relaxation experiences.

ABSTRACT Tourism simultaneously contributes to the causes of climate change and suffers from its consequences. While it supports global economies through employment, it faces growing risks from rising temperatures, extreme weather, and disrupted seasonal patterns. At the same time, tourism’s built environment intensifies climate change through energy use emissions and waste impacts. The link between tourism, the built environment, and climate change has become a critical area of research, understanding the correlations between these factors and their implications. A mixed-methods review of peer-reviewed studies (2003–2025) reveals that 95% of examined tourism infrastructure lacks climate-adaptive building features, highlighting the urgency of sustainable retrofitting design solutions. This study provides a three-part analysis of sustainable design: (1) it identifies key sustainability and resilience strategies; (2) it explores the conceptual frameworks underpinning them; and (3) it assesses the barriers to implementation. Throughout, the analysis highlights how these elements advance integrated environmental, social, and economic outcomes. Despite limitations of existing research, an integrative framework emerges that combines sustainable design, community participation, and policy innovation.

ABSTRACT Sentiment analysis plays a crucial role in extracting valuable insights from tourists reviews. Existing sentiment analysis techniques designed for general text often fall short when applied to tourism-related comments. This paper proposes an innovative deep learning-based approach for analysing comments in tourism. We utilise a BERT-based word embedding technique to capture vector representations of each preprocessed tweet. We use three deep learning methods, namely BERT, LSTM, and BiLSTM, which are commonly employed in various text processing tasks, for classifying sentiment in tourism tweets. Therefore, the proposed sentiment analysis methods include BERT and two combined methods: BERT-LSTM and BERT-BiLSTM. We tune the hyperparameters of the proposed deep learning methods and assess their performance by evaluating precision, recall, accuracy, and F1-score. Our research findings reveal that the proposed BERT model outperforms other methods on the benchmark dataset, achieving an impressive precision rate of 96.17%, a recall of 96%, an accuracy of 96%, and an F1-score of 96%. Besides, the other proposed deep learning methods outperform previous methods on the mentioned criteria. The results demonstrate the effectiveness of the proposed methods in accurately classifying sentiments in tourism-related tweets.

ABSTRACT This article explores why destinations find the transition to sustainable tourism challenging. Through a composite and layered approach drawing together complexity theory, transition management and path dependency theory, the conditions that cause resistance to sustainability, including within policymaking, are identified. Two Mediterranean destinations having the highest tourism intensity act as case studies: coastal Croatia and Malta. The study, first, using the lens of complexity theory, historical policy and performance data, determines that both destinations have complex tourism systems. Through transition management theory, it then examines the destinations’ typology of transition. Complementing the historical data, themes from stakeholder focus groups inform the categorisation of transition and identify Croatia’s and Malta’s persistent problems. This directs the study to the root causes for the slow transition, imposing path dependency or triggering path plasticity. No evidence was found for path creation to sustainability. These findings, informed by the theoretical lenses, shed light on four main conditions: path-dependence, inconsistent transition policies, extractive approaches for growth prioritization, and persistent problems that make the shift to sustainability challenging, compounded by policy-makers’ assumptions. The study signals broader governance issues for the sustainable management of Mediterranean destinations.

ABSTRACT On-site visitor surveys are widely used in tourism research but often criticised for limited representativeness, as data collection is usually constrained to specific locations and times. Despite this concern, few studies have systematically tested whether temporally stratified on-site surveys can approximate the representativeness of nationwide samples. This study addresses this gap by comparing discrete choice experiment (DCE) results from visitors surveyed at Wuling National Forest Recreation Area with those from a nationwide population survey in Taiwan. Using mixed logit and Swait – Louviere tests, we examine whether temporal stratification improves the alignment of on-site samples with the broader population in terms of willingness-to-pay estimates for environmental and recreational attributes. The findings demonstrate that survey timing significantly influences representativeness, with certain periods producing results more consistent with nationwide samples. Theoretically, this contributes to advancing knowledge on sampling bias and scale heterogeneity in visitor research. Practically, it provides actionable guidance for researchers and park managers on optimising survey design when resources for year-round data collection are limited. Limitations include reliance on pre-existing questionnaires and the restriction of sampling to defined periods, which may limit generalizability. Future studies are encouraged to replicate this approach across different sites and survey instruments.

ABSTRACT This study explores how hotel employees in Vietnam engage with NanoMindfulness, brief, improvised, and embodied strategies that help regulate emotions and sustain resilience in demanding service environments. Unlike structured mindfulness programmes, NanoMindfulness refers to spontaneous acts of awareness embedded in routine tasks and workplace interactions. Semi-structured interviews with fourteen employees across front office, guest services, housekeeping, food and beverage, and human resources generated a rich qualitative dataset. Thematic analysis identified five interconnected themes: adapting practices to situational context, ritualising small actions, anchoring awareness in the body, using micro-transitions to reset attention, and balancing mindfulness as both composure and transformation. Practices ranged from pausing before greeting guests to using hand-washing as a boundary between tasks. Notably, front-of-house staff emphasised emotional regulation during guest interactions, while back-of-house staff relied on bodily grounding during physically intensive routines, underscoring the importance of operational context. These findings extend workplace well-being research by documenting culturally grounded and occupationally specific forms of mindfulness in an emerging economy setting. For hospitality organisations, the study highlights the value of recognising and legitimising informal, context-sensitive practices that employees already use, thereby fostering resilience and supporting sustainable well-being.

ABSTRACT This research investigates the impact of destination image, perceived value, and psychological well-being on domestic tourists’ behavioural intentions, integrating direct, mediated, and serially mediated effects into a unified framework. The study employed the Stimulus-Organism-Response (S-O-R) theory and adopted a quantitative research design using statistical methods for data analysis. Da Nang, a coastal tourism city in central Vietnam, served as the destination site. Data were collected through a structured questionnaire using a purposive sampling method, resulting in 409 valid responses from domestic tourists who had visited Da Nang. Partial least squares structural equation modelling (PLS-SEM) was used to test the hypotheses. Results revealed that psychological well-being plays a pivotal mediating role, amplifying the influence of destination image on behavioural intentions, both individually and as part of a serial mediation with perceived value. This study enhances the literature by shedding light on the critical role of psychological well-being in shaping tourists’ decisions and offers practical insights for tourism managers, providing a foundation for strategies to attract and retain tourists and foster sustainable destination development.

ABSTRACT The aim of this paper is to study public tourism officials’ intention to use a smart destination system and to compare it with the perceptions of other stakeholders (tourists and tourism businesses). Local government tourism officials are key stakeholder in the tourism ecosystem that has received little academic attention. The TAM model is used as theoretical background. The case of the network of smart destinations of a Spanish mediterranean region is studied. An online questionnaire was administered to a sample of 50 public tourism officials. A structural equation model was used. The findings shows that perceived usefulness and satisfaction positively affected attitude, which is a key antecedent of intention of use. However, the marked influence of subjective norms could counterbalance attitude. The 360-degree view of stakeholders’ intention to use a smart destination shows that tourism officials and tourists are mainly concerned about the usefulness of a smart system, while tourism companies are mainly concerned about ease of use. Attitude and subjective norms are important for all stakeholders.

ABSTRACT While the relationship between music, place, and tourism has been well-documented, there is a noticeable gap in understanding how tourists’ sensory perceptions, particularly auditory perceptions of music, influence their overall tourism experience. The study adopted mixed research methods to address this question. In the qualitative phase, we utilised co-occurrence network analysis to identify musicscapes derived from the lyrics of Inner Mongolian grassland songs. Furthermore, in the quantitative phase, we exam­ined the relationships among musicscape, cultural involvement, and tourism experience quality, based on 420 valid questionnaires collected from visitors during the peak tour­ism season in July 2021 at the Xilamuren Grassland. The findings reveal that Grassland songs include eight distinct types of musicscapes, and the perception of these land­scapes positively influences cultural involvement, which, in turn, significantly enhances the evaluation of tourism experience quality. Cultural involvement partially mediates the relationship between musicscape perception and tourism experience quality. This study highlights the adaptability of music as a tourism soundscape, enriches the under­standing of tourism landscape appeal across diverse cultural contexts, and underscores the practical importance of incorporating music into sensory marketing and travel desti­nation experience design.

ABSTRACT By predicting the trajectory of emerging technologies and identifying their potential application, tourism enterprises can secure a first-mover advantage in innovation and capitalise on niche market opportunities. However, existing research primarily examines the application and efficacy of mature technologies, whereas limited attention has been devoted to exploring the potential of emerging technologies. To address this gap, this study develops a framework for identifying technology that may disrupt tourism in the future through large language models (LLMs) and machine learning. Results indicate that tourism-related areas including smart destinations, immersive displays, low-altitude aviation, marine tourism, outdoor travel, heritage preservation, and tourism transportation will experience disruptive technological change. Such technological advancements are expected to enable more intelligent, seamless, authentic, and personalised travel experiences. These findings provide insights to inform policy-making in tourism innovation and guide the strategic realignment of corporate research and development (R&D) investment.