This Systematic Literature Review (SLR) explores visitor motivation, on-site image, satisfaction, and overall experience within heritage tourism, focusing particularly on India’s ASI-protected monuments. The review combines results from more than 50 studies listed in Scopus and points out important reasons why people visit, such as learning about culture, feeling nostalgic, and having emotional connections, and shows how these reasons relate to tourist satisfaction and the image of the destination. The analysis reveals significant theoretical fragmentation, limited attention to emotive factors like existential authenticity, and the frequent exclusion of Indian ASI sites in mainstream research. While the field is shifting toward data-driven models like PLS-SEM, there remains a lack of longitudinal and mixed-method research designs. The review provides practical recommendations for policymakers, emphasising improved heritage interpretation, digital engagement, and site infrastructure. Advocating for interdisciplinary approaches, it encourages integrating psychological, technological, and cultural perspectives, aligning research with heritage policy and sustainability goals, and advancing both scholarly understanding and practical heritage management.
This editorial article maps the accumulated knowledge structure of Enlightening Tourism. A Pathmaking Journal (ET) and translates it into a forward-looking research agenda for the journal’s renewed editorial phase. The article is grounded in a corpus of 143 ET articles, organised into 53 pre-Scopus articles published between 2011 and 2017 and 90 Scopus-indexed articles published between 2018 and 2026. Author keywords were analysed through co-word analysis, keyword co-occurrence networks, Greedy Modularity clustering, robustness comparison with Louvain community detection, Callon strategic diagramming and Future Research Initiatives (FRI) simulations. This methodological integration represents a distinctive contribution of the paper: rather than using bibliometric mapping only to describe the journal’s past, it combines retrospective knowledge-structure analysis with forward-looking FRI simulations to identify under-connected concepts that may inform future research directions, editorial priorities and scholarly development. The results identify 565 unique keywords, 66 retained keywords occurring at least twice, 115 co-occurrence linkages and 11 thematic clusters. Tourism, satisfaction, sustainable tourism and sustainability emerge as basic themes; hotels, India and Antalya appear as niche themes; and sustainable development and COVID-19 occupy the emerging or declining quadrant. The FRI simulations indicate that destination image, tourism marketing, performance, customer satisfaction, travel motivation, perceived risk and smart destinations may operate as bridging concepts for future research. We argue that the next stage of ET should not be understood as a break with its past, but as a disciplined transformation of its accumulated knowledge into a clearer intellectual direction. Pathmaking tourism scholarship is proposed as a way of studying how destinations, firms, communities, ecosystems and institutions create, transform and govern responsible development pathways under conditions of uncertainty, technological change and societal transition. In this renewed phase, ET will prioritise manuscripts that move beyond tourism as an empirical setting and use tourism to advance theory, methods, evidence, policy and responsible practice
This study examines how TikTok content shapes Generation Z’s travel decision-making by exploring the roles of perceived destination image, Fear of Missing Out (FOMO), and perceived overtourism within the Stimulus–Organism–Response (S-O-R) framework. A quantitative survey of 300 international Gen Z tourists aged 18–27 with prior travel experience or intentions to visit Thailand was conducted, and structural equation modeling (SEM) was used to test the hypothesized relationships. Findings reveal that the informativeness of TikTok travel content significantly enhances both perceived destination image and FOMO. While destination image strongly predicts destination choice intention and mediates the relationship between informativeness and intention, FOMO does not exert a significant direct effect on travel decisions. Notably, perceived overtourism moderates two key pathways: it weakens the positive impact of informativeness on destination image and diminishes the effect of destination image on choice intention. These results highlight the cognitive primacy of destination image in Gen Z’s travel planning and underscore the moderating role of sustainability concerns. The study advances theoretical understanding of digital media’s influence on tourism behavior and offers practical implications for destination marketers seeking to engage socially conscious travelers through content strategies that balance inspiration with responsibility.
New communications technologies can enhance both the tourist experience and the efficiency of tourism organisations and destinations. Even though smart hospitality can contribute to brand differentiation, improved performance, and increased client satisfaction, its study has been neglected in previous and fundamentally quantitative and consumer-centred investigations from the supplier perspective within the European context, despite the key role of smart hospitality in the tourism ecosystem. Hotel managers were interviewed in depth, at a mature tourism destination, and their different views, from a micro perspective, on smart hospitality and its implications for practitioners, governmental agencies, and academia were brought to light. The conclusions are that greater effort at all levels is needed to incentivise smart hospitality.
This study examines the main factors influencing the adoption of location-based mobile services (LBS) powered by beacon technology in the tourism sector. Using logistic regression models and neural networks, specifically the multilayer perceptron (MLP), this research identifies eleven significant variables driving the adoption process. Among these, system quality, trust, perceived ease of use, perceived usefulness, and service quality stand out as the most influential factors. The MLP model demonstrated superior performance with a classification accuracy of 99.14% and an area under the curve (AUC) of 0.947, highlighting the exceptional predictive capability of non-parametric models over traditional logistic regression. These findings underscore the importance of system trust and reliability in driving users' adoption of beacon-based applications. Additionally, this study provides valuable insights for marketing professionals and tourism stakeholders, suggesting that enhancing user trust, improving system quality, and simplifying the user experience can positively impact LBS figures in the tourism sector. The results provide a solid foundation for leveraging advanced predictive models to improve the operational efficiency of digital solutions in tourism.
