Mapping the Smart Tourism Experience Landscape: A Systematic Literature Review

Mapping the Smart Tourism Experience Landscape: A Systematic Literature Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mapping the Smart Tourism Experience Landscape: A Systematic Literature Review Chahat Malhotra, Shradha Jain, Dr. Anju Shukla This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8530210/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 19 You are reading this latest preprint version Abstract The tourist industry has seen a substantial transformation due to the growing use of digital technologies, which has made the Smart tourist Experience (STE) a key area of study. The literature on the technological aspects that enable smart experiences, the factors that influence visitor engagement, and the identification of ongoing research gaps is still scattered, despite the tremendous growth in scholarly interest in STE. The current work uses the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria to conduct a systematic scoping review in order to solve this problem. To compile the body of knowledge on smart tourist experiences, a thorough search and screening of peer-reviewed literature published in prestigious academic databases was conducted. Artificial intelligence, the Internet of Things, big data analytics, mobile technologies, augmented and virtual reality, and integrated smart platforms are among the major technological aspects that the assessment highlights as supporting STE. The study also classifies important STE antecedents at the individual, technological, and destination levels, including travelers' digital preparedness, perceived utility, system interactivity, and smart destination infrastructure. The results also highlight significant gaps in the body of existing work, such as a lack of focus on ethical, privacy, and sustainability issues, inadequate theoretical integration, underrepresentation of emerging economies, and little empirical validation. This study presents a future research agenda to further theoretical development and empirical investigation in smart tourism studies, as well as an organized understanding of the smart tourist experience through the consolidation of scattered research. Smart Tourism Experience (STE) Smart Tourism Digital Technologies PRISMA-ScR Technological Dimensions Antecedents Systematic Literature Review Figures Figure 1 Figure 2 Figure 3 1. Introduction Smart tourism has become a buzzword and popular topic due to the growth of intelligent systems and technology (Park, Lee, Yoo, & Nam, 2016 ; Wang, Li, Zhen, & Zhang, 2016 ). One way to conceptualize smart tourism is as an advancement of e-tourism (Gretzel, Sigala, et al., 2015 ; Xiang & Fesenmaier, 2017 ). Smart tourism is unique in that it uses the Internet of Things (IoT) and AI to combine the physical and digital worlds, whereas e-tourism refers to the use of ICTs in the processes carried out by tourism organizations and among many players to improve business strategy and organizational performance (Buhalis, 2003 ). Additionally, smart tourism includes the changes that experiences have undergone in recent years and the pervasiveness of omnipresent connectivity (Gretzel, Reino, Kopera, & Koo, 2015 ; Gretzel, Sigala, et al., 2015 ). Also, smart tourism is considered as an ‘ecosystem’, constituted by a smart business network, smart destinations and a smart technologies infrastructure (Gretzel, Reino, et al., 2015 ). Additionally, smart tourism is viewed as an "ecosystem" made up of smart locations, smart business networks, and smart technology infrastructure (Gretzel, Reino, et al., 2015 ). The ubiquitous tour information service that travelers receive when traveling is known as "smart tourism." The culmination of the shared characteristics of smart travel is the tour information service. Smart tourism does not, however, encompass all information services. Smart tourism can only relate to the ubiquitous tour-in-formation service that is offered to individual tourists through initiatives based on their unique needs(Y. Li et al., 2017 ). According to existing literature, STE is a multifaceted notion that is shaped by the smooth integration of smart technologies like location-based services, augmented and virtual reality, mobile applications, the Internet of Things (IoT), artificial intelligence, and big data analytics (T. H. Lee & Jan, 2023 ). Travelers become active co-creators of value instead of passive consumers thanks to these technologies, which allow destinations to provide context-aware, interactive, and personalized experiences(Tsang & Au, 2024 )(L. Huang & Lau, 2020 ). Crucially, researchers contend that smartness in tourism is only achieved when travellers recognize and enjoy concrete advantages from technological applications rather than being a feature of technology itself (Tsang & Au, 2024 ). Additionally, the research states that four characteristics make up a smart tourism experience: accessibility, informativeness, interactivity, and customisation (Tsang & Au, 2024 ). Additionally, the research states that four characteristics make up a smart tourism experience: accessibility, informativeness, interactivity, and customisation (Tsang & Au, 2024 ). Even if the amount of research on smart tourism is increasing, there is still a lack of coherence in the literature regarding the conceptualization, operationalization, and empirical analysis of smart tourist experiences. The definitions of STE, the technological aspects highlighted, and the theoretical frameworks used in previous research vary greatly, ranging from experience-centric and stimulus-organism-response frameworks to technology acceptance models. Furthermore, few attempts have been made to systematically map the antecedents, mediators, and outcomes of STE in an integrated manner, despite the fact that numerous research look at specific technologies or outcomes including satisfaction, engagement, and behavioral intentions(T. H. Lee & Jan, 2023 ). STE research has a wide range of methodologies, including mixed-methods designs, survey-based quantitative studies, qualitative approaches, and new experimental and design-oriented procedures (Tsang & Au, 2024 ). However, the lack of a thorough synthesis of methodological trends restricts the creation of cumulative knowledge and the comparability of results between investigations. Additionally, rather than specifically focusing on the experiential aspect of smart tourism, current assessments typically concentrate on smart locations or smart tourism in general. This chapter provides an organized and transparent mapping of the Smart Tourism Experience research landscape by using a PRISMA-ScR-based systematic literature review in response to these limitations. In particular, four research questions serve as the chapter's compass: (1) What is the conceptualization of Smart Tourism Experience in the literature currently in publication? (2) What aspects of technology affect the Smart Tourism Experience? (3) In STE research, what methodological techniques have been used? (4) Which Smart Tourism Experience antecedents, mediators, and outcomes have been found? This chapter seeks to advance the understanding of Smart Tourism Experience in an increasingly technology-driven tourism environment by synthesizing and organizing previous research through these guiding questions, highlighting theoretical and methodological gaps, and suggesting future research directions(Tsang & Au, 2024 ). 2. Methodology 2.1Research Design With a focus on identifying technological features, antecedents, and research gaps, this study used a scoping review methodology to methodically map and synthesize the body of existing literature on Smart Tourism Experience (STE). Because smart tourism research is young, diverse, and conceptually fragmented, a scoping review was deemed relevant. A scoping review allows the assessment of the scope, features, and conceptual boundaries of the literature where empirical evidence is still few, much like previous studies looking at emerging research domains (Botor & Tuliao, 2023 ). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR), which has been used in similar scoping reviews (Botor & Tuliao, 2023 ), served as the guide for the review protocol to guarantee transparency, rigor, and reproducibility in the review process (Tricco et al., 2018 ). The Fig. 1 represents the full process followed while including articles in our review study. 2.2 Search Strategy Using Web of Science, a significant academic database that is frequently utilized in management, tourism, and hospitality research, a thorough literature search was carried out. The search strategy was meticulously created and improved in accordance with the methodology recommended by Botor and Tuliao ( 2023 ) to guarantee accuracy and pertinence to the research goals. The literature search was limited to research that addressed Smart Tourism Experience, in keeping with the review's clear emphasis. In order to prevent conceptual dilution and guarantee that only directly relevant research was found, the search was carried out using the single core keyword phrase "smart tourism experience." No other or different keywords pertaining to more general concepts of technology-enabled or digital tourism were used. Because the Web of Science database is known for indexing reputable, peer-reviewed articles and was thought to be suitable for upholding methodological rigor and consistency, the search was limited to that database. Additionally, in accordance with suggested procedures for scoping reviews, backward reference searching was done by looking through the reference lists of the chosen publications to find any other pertinent studies (Botor & Tuliao, 2023 ). 2.3 Eligibility Criteria and Study Selection Studies that specifically looked at smart tourism or technology-enabled tourism experiences and addressed technological aspects, antecedents, or important factors influencing the tourist experience were included in the review. To maintain academic rigor and uniformity, only English-language peer-reviewed journal publications were taken into consideration. On the other hand, studies that were published as editorials, book reviews, or conference abstracts, failed to conceptualize tourist experience as a key outcome variable, or only concentrated on smart city efforts with no direct connection to tourism were disqualified. In order to preserve the caliber and dependability of the evaluated literature, articles that lacked adequate conceptual foundation or methodological clarity were also eliminated from the study. In accordance with the PRISMA-ScR methodology (Tricco et al., 2018 ) and previous scoping review applications (Botor & Tuliao, 2023 ), the research selection technique comprised three stages: duplication removal, title and abstract screening, and full-text assessment. To guarantee compliance with the qualifying requirements, any questions raised throughout the screening process were carefully reevaluated. 2.4 Data Charting and Synthesis A structured extraction approach was used to methodically chart data from the final set of included studies. The author or authors, the year of publication, the journal source, the research design, the theoretical underpinnings, the technological focus, the discovered antecedents, and the main conclusions pertaining to the smart tourist experience were all retrieved. The analysis integrated theme synthesis with descriptive numerical mapping (e.g., publication patterns, methodological methods), in accordance with Botor and Tuliao ( 2023 ). Key technological aspects of STE (such as artificial intelligence, the Internet of Things, big data analytics, mobile technologies, and immersive technologies) were categorized using thematic analysis, which was also used to arrange antecedents at the person, technological, and destination levels. 2.5 Identification of Research Gaps The included papers were critically analyzed to find deficiencies pertaining to methodological rigor, theoretical integration, regional representation, and developing ethical and sustainability concerns in accordance with the goals of scoping reviews. In line with gap identification techniques employed in earlier scoping reviews, special focus was given to the predominance of conceptual studies, the lack of empirical validation, and the underrepresentation of developing economies (Botor & Tuliao, 2023 ). This process facilitated the development of a structured future research agenda for advancing smart tourism experience research. 3. Findings of the review of Literature 3.1Conceptualization, and Growing Importance of Smart Tourism Experience The results and findings of literature review clearly reveals that the concept of STE has its roots associated with previous research on e-tourism, the tourism services which are driven by ICT, and smart city growth and development, where technology was seen only as a mere tool for enhancing operational efficiency and information dissemination rather than creation of experience (Buhalis, 2003 ; Buhalis & Law, 2008; Wang et al., 2013 ). The old researches had laid emphasis on the application of digital and destination management platforms along with mobile technologies to assist tourist in making decisions and service delivery, positioning tourists primarily as technology users within digitally mediated environments (Xiang & Gretzel, 2010; Wang et al., 2013 ). But due to the expansion of smart city initiatives and growth of technologies such as IoT, big data, and ubiquitous connectivity became very important and significant, tourism researcher started expanding these ideas to destination contexts, laying the foundation for the emergence of smart tourism and also the, smart tourism experience (Gretzel et al., 2015 ; Buhalis & Amaranggana, 2015). The findings have also clearly highlighted that STE has been progressively conceptualized as a multidimensional, dynamic, and experience-oriented construct and not just the outcome of applications of modern technologies. Foundational researches have also redefined the concept of STE as the outcome of interactions among tourists, smart technologies, and destination environments, with special focus on personalization, contextual intelligence, interactivity, and real-time adaptability as essential experiential attributes (Neuhofer et al., 2015; Gretzel et al., 2015 ; Wang et al., 2016 ). Then in next phase research started extending this conceptualization through inclusion of experiential dimensions like some of them are enjoyment, learning, immersion, trust, and co-creation, emphasizing that smartness is considered meaningful only when tourists perceive tangible experiential value from application of modern technologies (Koo et al., 2017 ; Femenia-Serra & Neuhofer, 2018; Shin & Perdue, 2019). The findings also throw clear light on strong convergence in the literature indicating that STE as a process-oriented phenomenon that unfolds across the pre-trip, on-site, and post-trip phases, enabled by intelligent systems that has the immense ability of sensing, learning, and adapting to the demands of tourist (Gretzel et al., 2015 ; Xiang et al., 2021). Another significant finding shows that why smart tourism experience is increasingly gaining attention as a research topic. The review also illustrates that rapid technological advancemen specially the widespread usage of smartphones, social media, recommendation systems based on AI, and location-based services has prominently transformed the tourist behaviour and expectations, leading to the creaton of demand for seamless, personalized, and purposeful experiences (Wang et al., 2013 ; Neuhofer et al., 2015; Xiang et al., 2021). Since the users and tourists have become more digitally empowered and experience-oriented, the scholars have started recognizing STE as a critical mechanism through which destinations could improve the levels of satisfaction, engagement, and competitive advantage (Buhalis & Amaranggana, 2015; Koo et al., 2017 ). Moreover, STE had acquired importance because of its alignment with service-dominant logic and experience economy perspectives, which emphasize value co-creation, active participation, and experiential outcomes rather than passive consumption (Vargo & Lusch, 2008; Neuhofer et al., 2015). The findings of the study have clearly shed light on increasing attention of researchers towards the concept of STE which is basically driven by its importance to broader destination-level challenges related to sustainability, crowd management, inclusivity, and governance. The literature progressively positions STE as a strategic framework for leveraging technology to balance satisfaction of users with destination management objectives, such as diminishing congestion, optimum utilization of resources, and enhancing quality of life for residents (Gretzel et al., 2015 ; Buhalis & Amaranggana, 2015; Stankov & Gretzel, 2021 ). Consequently, STE has evolved with time a central research construct that connects technological innovation, tourist behavior, experiential value, and sustainable destination growth and development. Overall, the findings states that STE has completely changed from a technology-driven concept to a holistic, human-centred research domain. Its growing significance in the research domain depicts the growing recognition that understanding tourism in smart destinations not only need the examination of technological abilities but also analysing how these technologies assit in shaping the tourists’ perceptions, emotions, behaviours, and co-created experiences across the entire travel journey. 3.2 Geographical Distribution of Smart Tourism Experience Research The above figure (2) illustrates the geographical distribution of research contributions in context of STE, clearly shedding light on the uneven concentration of research studies across various countries. China is the most important contributor, indicating a strong research focus on STE which is because of drastic and quick changes in digital infrastructure development, smart city initiatives, and large-scale adoption of technologies related to tourism. Spain and the United States follow, symbolizes their developed tourism economies where STE is closely linked to destination competitiveness, tourist management, and experience personalization. On the same side we cannot ignore the prominent contribution of South Korea’ who underscores its leadership in ICT innovation and technology-driven tourism services, which has completely changed and reshaped the immersive and intelligent tourism experiences. There are some studies conducted in England’s which shows the sustained academic interest in smart tourism in context of such as digital heritage, experience design, and urban tourism innovation. Other nations like Australia, India, Malaysia, Serbia, and Portugal show comparatively lower but emerging contributions, indicating their engagement with STE research, with special emphasis on sustainability, smart destination development, and technology adoption related problems. Overall, the figure clearly indicates that STE research is being conducted in developed nations followed by developing and smaller tourism markets which are slowly but trying to expand their scholarly focus. 3.3 Most Influential Authors in Smart Tourism Experience Studies The Fig. 3 is presenting the most influential authors in context of STE research depicting their frequency of contributions within articles that has been reviewed. Chung N. emerges as the leading author, indicating his sustained scholarly influence on redefining the concept of STE and its conceptualization and empirical analysis of STE, especially in areas such as technology acceptance, smart destination characteristics, and digitally mediated experiences of users and tourist. Authors such as Femenia-Serra F., Gretzel U., Vars-Bidal J. A., and Koo C. follow closely, highlighting their prominent roles in advancing theoretical frameworks and empirical results in context of experience co-creation, smart technologies, and tourist behaviour in smart environments. The presence of Shen S. W., Sotiriadis M., and Stankov U. depicts increasing scholarly engagement with STE from perspectives including digital innovation, destination management, and experiential value creation. Meanwhile, authors such as Au W. C. W. and Celda-Bernabeu M. A., though contributing fewer publications, but still clearly indicated their emerging voices addressing intelligence-oriented and governance-related dimensions of STE. 3.4 Methodological Distribution of Smart Tourism Experience Studies The methodological review of selected smart tourism experience studies indicates a strong dominance of quantitative research approaches, particularly survey-based Structural Equation Modelling (SEM) and Partial Least Squares SEM (PLS-SEM) techniques. These methods are widely applied to analyze the complex relationships among smart tourism technologies, destination attributes, and tourists’ cognitive, affective, and behavioural outcomes. This is being represented in Table 1 Survey-based SEM / PLS-SEM approaches are the most frequently adopted, used in studies conducted by Tsang ( 2024 ), Lee and Jan ( 2023 ), Huang and Lau ( 2020 ), Ghaderi et al. ( 2018 ), and Pradhan and Oh (2018) as shown in Table 1 and in many more studies also. These studies highlight the suitability of SEM techniques for theory testing and prediction in smart tourism contexts. Quantitative cross-sectional survey designs also feature prominently, with researchers such as Chung, Tyan, and Han (2016), Kim et al. (2020), and Wang et al. ( 2016 ) utilising structured questionnaires to capture tourists’ perceptions and behavioural intentions at a single point in time. Such designs allow for efficient data collection from various tourist. Only few researches have adopted mixed-method research designs, combining quantitative surveys with qualitative interviews or content analysis to gain deeper insights into tourist experiences and sustainability outcomes (Lee & Jan, 2023 ; Buhalis & Sinarta, 2019). These approaches enrich empirical findings by integrating numerical data with contextual interpretations. Experimental designs are primarily used in studies examining technology-mediated experiences, such as mobile applications, augmented reality, and proactive smartphone systems. Notable examples include Tussyadiah and Wang ( 2016 ) and Bogicevic et al. (2019), who employed experimental manipulations to assess tourists’ emotional and behavioural responses. Finally, emerging research has begun to utilise big data analytics and computational methods, analysing large-scale user-generated content and digital footprints through techniques such as text mining and sentiment analysis. Studies by Lan et al. ( 2021 ) and Li et al. ( 2017 ) demonstrate the growing relevance of data-driven approaches in capturing real-time and large-scale smart tourism experiences. Table 1 Methodological Distribution of Smart Tourism Experience Research Methodology Representative Citations Survey-based SEM / PLS-SEM Tsang, N. K. F. (2024). Journal of Hospitality & Tourism Research; Lee, T. H., & Jan, F. H. (2023). Tourism Management; Huang, L., & Lau, N. ( 2020 ). Sustainability; Ghaderi, Z., et al. ( 2018 ). Asia Pacific Journal of Tourism Research; Pradhan, M. K., & Oh, J. (2018). Sustainability. Quantitative cross-sectional survey Chung, N., Tyan, I., & Han, H. (2016). Journal of Travel Research; Kim, J., Lee, C. K., & Preis, M. W. (2020). Tourism Management; Wang, D., Xiang, Z., & Fesenmaier, D. R. (2016). Journal of Travel Research. Mixed-method research design Lee, T. H., & Jan, F. H. (2023). Sustainability; Buhalis, D., & Sinarta, Y. (2019). Journal of Travel Research. Experimental design Tussyadiah, I. P., & Wang, D. (2016). Journal of Travel Research; Bogicevic, V., et al. (2019). Tourism Management. Big data analytics / computational methods Lan, F. Y., et al. (2021). Frontiers in Psychology; Li, X., Pan, B., Law, R., & Huang, X. (2017). Tourism Management. 3.4 Research Approach Classification in Smart Tourism Experience Studies The analysis of the selected articles on STE proves a dominant inclination toward empirical research as depicted in table (2). From the total articles which has been reviewed, 55 articles had employed empirical methodological approach, while 33 articles are theoretical or conceptual in nature. This distribution highlights several significant trends in the evolution of STE as a prominent construct for research. First, the higher number of empirical researches proves a growing and emerging emphasis on data-driven investigation and real-world application of smart technologies within tourism contexts. These studies primarily focus on examining tourists’ perceptions, behavioural intentions, satisfaction, engagement, and experience related results driven by the applications of smart technologies like mobile applications, augmented reality, Internet of Things (IoT), big data analytics, and artificial intelligence. The empirical dominance reflects the maturity of the field, where conceptual ideas are increasingly being tested and validated across diverse tourism settings. In literature the existence of 34 theoretical studies signifies the foundational role of conceptual development in STE research. These studies contribute by proposing conceptual frameworks, defining dimensions of smart tourism experiences, integrating interdisciplinary theories and identifying future research directions. However, their comparatively lower number symbolizes the requirement of further efforts for building theories, particularly to address the quickly evolving nature of smart technologies and tourist–technology interactions. Third, the imbalance between empirical and theoretical studies indicates that while researchers are actively measuring and modelling STE, theoretical consolidation remains limited. There is scope for developing integrative and unified theoretical models that can comprehensively explain the cognitive, emotional, and behavioural mechanisms underlying smart tourism experiences. Overall, the findings suggest that STE research is transitioning from a conceptual emergence phase to an empirical validation phase, yet future studies should aim to strengthen theoretical frameworks and adopt mixed-method approaches to achieve deeper and more holistic insights into smart tourism phenomena. Table 2 Research approach classification Research Approach No. of Articles Empirical 55 Theoretical 34 3.5 Journal Distribution of Smart Tourism Experience Research The journal-wise analysis of the finally included articles in our review study on STE indicates a balanced yet interdisciplinary publication pattern across tourism and non-tourism journals which is being clearly represented with the help of table (3). In totally reviewed articles, 45 articles were published in tourism-focused journals, while 44 articles were published in non-tourism journals, indicating the cross-disciplinary nature of construct of STE. Within tourism journals, the journal Tourism emerges as the most prominent outlet, contributing nine articles, followed closely by Current Issues in Tourism (9) and Asia Pacific Journal of Tourism Research (8). Other leading tourism journals such as Tourism Management Perspectives (4), Tourism Management (3), and Annals of Tourism Research (3) also depicts the researcher’s interest in STE related research. Additionally, hospitality and marketing-oriented journals, including the Journal of Hospitality and Tourism Research, Journal of Travel and Tourism Marketing, and related outlets, reflect the emerging importance of smart technologies in enhancing tourist experiences and service encounters. In contrast, a substantial number of studies are published in non-tourism journals, highlighting the interdisciplinary foundations of STE. The journal Sustainability dominates this category with 20 articles, focussing on the strong linkage between smart tourism, sustainable development, and smart destinations. Other influential non-tourism outlets such as Journal of Travel Research (3), Frontiers in Psychology (2), and Service Industries Journal (2) indicate the integration of psychological, service, and consumer behaviour perspectives. Furthermore, publications in technology-oriented journals such as Information Systems Frontiers and Soft Computing underscore the role of digital technologies, data analytics, and intelligent systems in shaping STE. Overall, the results indicates that STE related studies is not limited to traditional tourism and hospitality journals but is progressively disseminated across sustainability, psychology, service management, and information systems domains. Table 3 Here Journal-wise Distribution of Smart Tourism Experience Studies Category Journal Name Number of Articles Tourism Journals (45) Tourism 9 Current Issues in Tourism 9 Asia Pacific Journal of Tourism Research 8 Tourism Management Perspectives 4 Tourism Management 3 Annals of Tourism Research 3 Journal of Hospitality and Tourism Research 2 Journal of Hospitality Tourism and Research 2 Journal of Travel and Tourism Marketing 2 Non-Tourism Journals (44) Sustainability 20 Journal of Travel Research 3 Frontiers in Psychology 2 Service Industries Journal 2 Information Systems Frontiers 1 Soft Computing 1 Journal of Destination Marketing and Management 1 3.6 Antecedents 3.6.1 ICT infrastructure in the context of STE serves as the basic technologies that integrates physical and digital components to enable creation of value through improved service in deliveries and enhanced personalization. It consists of comprehensive hardware such as servers, mobile devices, IoT sensors, and network equipment; software including CRM systems, PMS platforms, and cloud computing; and network connectivity like WiFi, 5G, and real-time synchronization protocols that ensure ubiquitous accessibility across all touchpoints. In initial or first stage of smart tourism evolution, ICT put emphasis on digital technology adoption, moving toward sustainable smart tourism development (SSTD) that combines ICT with environmental practices, and ultimately post-smart tourism destinations (PSTD) emphasizing local wisdom and humanistic approaches assisted by developed infrastructure such as cloud computing, IoT, and end-user devices(Cerdá-Mansilla et al., 2024). 3.6.2 Smart destination readiness in smart tourism is defined as the destinations' preparedness with ICT infrastructures specially the IoT, AI, and big data for seamless, customized visitor experiences(Diaz et al., 2024 ). It comprises of traveller readiness via role clarity and capability, positively influencing ease of use and enjoyment in tools such as geotagging (Chung et al., 2017 ). Core dimensions comprise of accessibility, enjoyment, protection, and interactivity, driving technology satisfaction and behavioural intentions of tourist and users, moderated by cultural differences (Diaz et al., 2024 ). Effective readiness enables explorative (discovery) and exploitative (booking) uses, boosting travel satisfaction and sustainable co-creation (C. D. Huang et al., 2017 ). Gaps in readiness creates problems in adaptability, emphasizing governance, privacy safeguards, and introduction to sustainable smart tourism (P. Li, 2025 ). 3.6.3Governance and institutional support serve as important antecedents to STE by making of national policies and strategies, funding infrastructure, and multi-stakeholder platforms that enable ICT integration, big data analytics, and real-time service delivery, as exemplified by China's National Tourism Administration (CNTA) through its 2011 smart tourism initiative and 2014 "Year of Smart Travel" campaign, which aligned with smart city investments exceeding 0.5 trillion Yuan by 2025 to build predictive platforms for traffic flow, customized suggestions and recommendations, and sharing of appropriate information among government bodies, organizations, residents, and tourists (Q. Jia et al., 2022 ), while ICT governance enhances the abilities of making decisions, innovation, and stakeholder knowledge distribution, directly enriching tourist perceptions of accessibility, enjoyment, and interactivity that foster biospheric values and site-specific environmentally suitable behaviours in destinations like Taiwan's Yangmingshan and Sun-Moon-Lake national parks, ultimately enhancing destination competitiveness and sustainability despite challenges like diversified financing and regulatory requirements.(T. H. Lee & Jan, 2023 ) (Benkraiem et al., 2024 ). 3.6.4 Tourist technology readiness (TR) , defined as individuals' propensity to embrace and effectively use new technologies for reaching goals in work and home life through optimism (positive view of technology's control/flexibility) and innovativeness (tendency to be a technology pioneer), serves as a key antecedent to smart tourism experiences (STE) by predisposing tourists to perceive smart technologies as useful and easy to use, thereby enhancing their overall STE dimensions like aesthetics, hedonic enjoyment, learning, and trust(Chung et al., 2015 ) In AR heritage contexts, TR positively influences perceived usefulness of AR applications, leading to favourable attitudes toward AR usage and destination revisit intentions via the Technology Readiness and Acceptance Model (TRAM), as tourists with high TR (optimism/innovativeness) are more prepared to adopt AR for enriched experiences(Chung et al., 2015 ). (Jeong & Shin, 2020 ).TR's role in smart tourism/STT adoption indirectly through technology acceptance frameworks, noting tourists' readiness affects STE attributes (e.g., interactivity, personalization) and outcomes like satisfaction/loyalty in US smart cities and nature-based destinations(Jeong & Shin, 2020 )(X. Chen et al., 2025 ) highlights TR implicitly via emotional arousal moderating AI technologies' impact on STE, where tech-ready tourists better engage with interaction/personalization/co-creation/privacy features for superior smart experiences.(X. Chen et al., 2025 ) (Femenia-Serra, Neuhofer, et al., 2019)conceptualizes "smart tourists" as those with high TR who share data, use STs intensively, and co-create via smart ecosystems, positioning TR as foundational for dynamic STE in smart destinations(Femenia-Serra, Neuhofer, et al., 2019). Studies have shown domestic traveller’s TR directly predicts STT satisfaction/behavioural intentions, underscoring TR as a precondition for positive STE across cultures(Shin et al., 2023a )(Gretzel et al., 2015 ) lacks explicit TR mention but aligns with readiness influencing STE via tech adoption barriers. (Gretzel et al., 2015 ). 3.6.5 Digital literacy is defined as the ability to efficiently access, evaluate, prominently assess, and creatively utilize digital technologies, platforms, and information to navigate, customize, and co-create enriched experiences within smart tourism ecosystems(Jeong & Shin, 2020 )(Femenia-Serra, Neuhofer, et al., 2019). This encompasses foundational ICT skills such as smartphone/app operation, AR/VR interfaces, IoT sensor interaction, and location-based services, alongside higher-order capabilities including data credibility evaluation, privacy/security management, real-time information synthesis, and dynamic stakeholder co-creation through Smart Tourism Technologies (STTs)(Jeong & Shin, 2020 )(Femenia-Serra, Neuhofer, et al., 2019)(Gretzel et al., 2015 ). In smart tourism contexts, digitally literate tourists demonstrate high STT familiarity (average 5–6 technologies used, 95% smartphone adoption), enabling them to leverage key STT attributes—informativeness (β = 0.22), interactivity (β = 0.53), and personalization (β = 0.28)—to transform passive technology exposure into memorable smart tourism experiences (STEs)(Jeong & Shin, 2020 ). Femenia-Serra et al. conceptualize these individuals as "smart tourists" who exhibit trust in intelligent systems, willingly share personal data for hyper-personalized services despite privacy concerns, and actively participate in IoT-enabled, ubiquitous connectivity ecosystems (Femenia-Serra, Neuhofer, et al., 2019). Additional evidence reinforces this antecedent role: skills gaps block big data/IoT value co-creation (Gretzel et al., 2015 ); literacy prevents information overload in nature-based STE contexts(T. H. Lee & Jan, 2022 ) ; digital proficiency predicts cross-country STT satisfaction and loyalty (Shin et al., 2023a ); and literacy activates AI-driven personalization pathways moderated by emotional arousal(X. Chen et al., 2025 ). Thus, digital literacy bridges robust ICT infrastructure with tourist agency, enabling the full realization of smart tourism's experiential promise across all touchpoints. 3.6.6 Perceived usefulness (PU) in smart tourism refers to tourists ‘perceptions that Smart Tourism Technologies (STTs) like AI chatbots, IoT parking systems, VR headsets, and ubiquitous information services improves the efficiency of travellers, customization, convenience, and overall experience quality, serving as a major TAM antecedent driving technology adoption, satisfaction, and memorable STE (Ionescu & Sârbu, 2024 ). PU significantly predicts satisfaction (β = 0.168, p < 0.001) across tourist segments with highest ratings for AI (4.70) and IoT (4.30), differ by areas (Transylvania AI = 4.80) and enhancing the revisit intentions (χ²=46.83, p < 0.01)(Ionescu & Sârbu, 2024 ).(Y. Li et al., 2017 )conceptualizes PU through "smart" ubiquitous information services (cloud/IoT integration) enabling anytime/anywhere personalized navigation and co-creation, revolutionizing passive tourism into autonomous, value-added STEs beyond traditional services (Y. Li et al., 2017 )embeds PU within smart destination ecosystems (big data, AR/VR) where it moderates technology-heritage fusion, driving tourist satisfaction, loyalty, and sustainable experiential value in cultural contexts . 3.6.7 Trust & Security Perception in smart tourism context is defined as the tourists' confidence in the reliability, privacy protection, and data safety of Smart Tourism Technologies (STTs), acting as a prominent moderator that promotes positive engagement with technology ecosystems while mitigating risks of data breaches and privacy violations to facilitate memorable STEs(Cerdá-Mansilla et al., 2024). Trust and security perceptions are very crucial for all types of stakeholder collaboration in smart destinations, where DMO should ensure transparency in handling information and data to build mutual confidence among tourists/locals, preventing exclusion from smart services (Cerdá-Mansilla et al., 2024)emphasizes blockchain/edge computing for privacy-preserved data in big data tourism platforms, positioning trust as foundational for secure IoT/cloud interactions enabling personalized services(Q. Jia et al., 2022 )(Yang & Wang, 2025 ) highlights metaverse tourism's privacy related problems from cross-border data flows, indicating need for trust mechanisms to secure financial/personal data during VR/AR experiences(Yang & Wang, 2025 ) identifies security as metaverse barriers, with propositions for secure avatars and blockchain to foster immersive STEs without any risks . 3.6.8 Spatiotemporal behaviours refer to the comprehensive travel characteristics derived from users' digital footprints captured through geotagged Flickr photographs, representing their "photo trail" across urban destinations. These behaviours integrate spatial dimensions—geographic coordinates of photos map-matched to street networks—and temporal dimensions—sequential timestamps of photo captures—to reconstruct complete travel trajectories(Mor et al., 2023 ). Spatiotemporal behaviours refer to the comprehensive travel characteristics derived from users' digital footprints captured through geotagged Flickr photographs, representing their "photo trail" across urban destinations. These behaviours integrate spatial dimensions—geographic coordinates of photos map-matched to street networks—and temporal dimensions—sequential timestamps of photo captures—to reconstruct complete travel trajectories (Liu et al., 2017 ; Domènech et al., 2020 ). 3.6.9 Urban morphology describes the physical street network structure of cities that shapes tourist movement patterns, analyzed through graph theory centrality measures (closeness and betweenness) derived from OpenStreetMap data, with photo geolocations map-matched to network segments. Urban morphology describes the physical street network structure of cities that shapes tourist movement patterns, analyzed through graph theory centrality measures (closeness and betweenness) derived from OpenStreetMap data, with photo geolocations map-matched to network segments (Crucitti et al., 2006 ; Porta et al., 2006 ; Boeing, 2019 ). 3.6.10 Tourism Empowerment in the context of smart tourism experience refers to the process through which tourists can attain significant control, competence, and confidence over their travel decisions and experiences through the application of smart tourism technologies, which provide real-time information, customization, and better interactive experience that improves autonomy and purposeful engagement at smart destinations (Jeong & Shin, 2020 ). Smart tourism experiences empower tourists by enabling easy access to reliable, context-aware, and location-based information, giving them access to plan itineraries, navigate destinations effectively, and taking better decisions that improve convenience and satisfaction during all phases of travel(Gretzel et al., 2015 ). Through attributes like accessibility, informativeness, interactivity, and personalization, smart tourism technologies facilitate tourists’ active participation and co-creation of experiences, shifting tourists from passive customers to empowered actors who shape their own experiences in real time (Jeong & Shin, 2020 ). Empowerment is further strengthened as smart tourism experiences foster learning, aesthetic appreciation, and hedonic enjoyment, which enhance tourists’ cognitive and emotional engagement and deepen their understanding of destinations and local environments(T. H. Lee & Jan, 2023 ). In nature-based and sustainable tourism contexts, empowered tourists develop stronger biospheric values through technology-mediated learning and interpretation, which increases their sense of responsibility and ability to act in environmentally responsible ways. Moreover, trust, security, and privacy embedded in smart tourism systems are critical to empowerment, as tourists are more willing to share data and rely on smart services when they perceive platforms as secure and trustworthy, thereby reinforcing confidence and independence in decision-making(Jeong & Shin, 2020 ). Overall, smart tourism experience empowers tourists by integrating technological support, experiential enrichment, and learning opportunities, enabling them to actively control their journeys, co-create value, and engage more responsibly and meaningfully with destinations (T. H. Lee & Jan, 2022 ). The list of prominent antecedents identified in review of literature is depicted in table (4) below- Table 4 Antecedents of STE Antecedent Citation of prominent Authors ICT Infrastructure (Tsang & Au, 2024 ), (L. Huang & Lau, 2020 ),(Lim et al., 2017 ), (Kusumastuti et al., 2024 ), p15, (Cerdá-Mansilla et al., 2024), (Neuhofer et al., 2015),(S. X. Chen et al., 2024 ),(S. Jia et al., 2025 ), (P. Lee et al., 2020 ), (Ivars-Baidal et al., 2021 ) Smart Destination Readiness (Chung et al., 2017 ), (Diaz et al., 2024 ), (Z. Chen, 2025 ), (Suanpang & Pothipassa, 2024 ),(Natarajan et al., 2025 ) ,(C. D. Huang et al., 2017 ),(P. Lee et al., 2020 ), (Ivars-Baidal et al., 2021 ), (X. Chen et al., 2025 ) Governance & Institutional Support (T. H. Lee & Jan, 2023 ), (Q. Jia et al., 2022 ), (Yang & Wang, 2025 ),(Chung et al., 2015 ), (Ionescu & Sârbu, 2024 ),(Cham et al., 2024 ), (Jovicic, 2019 ),(P. Lee et al., 2020 ) Tourist Technology Readiness (Tsang & Au, 2024 ), (T. H. Lee & Jan, 2022 ), (Gretzel et al., 2015 ), (Fang et al., 2024 ),(Jeong & Shin, 2020 ), (Zhu et al., 2024 ), (X. Chen et al., 2025 ), (Shin et al., 2023a ), (Femenia-Serra, Neuhofer, et al., 2019), (Jeong & Shin, 2020 ) Digital Literacy (Chung et al., 2017 ), (Diaz et al., 2024 ),(Z. Chen, 2025 ), (Suanpang & Pothipassa, 2024 ), (Natarajan et al., 2025 ), (Neuhofer et al., 2015), (Nguyen et al., 2023 ),(Femenia-Serra, Neuhofer, et al., 2019),(Stankov et al., 2025) (S. X. Chen et al., 2024 ) Perceived Usefulness (L. Huang & Lau, 2020 ), p8, (Kusumastuti et al., 2024 ), (Chung et al., 2015 ), (Ionescu & Sârbu, 2024 ), (Y. Li et al., 2017 ), (Nguyen et al., 2023 ), p,(Jeong & Shin, 2020 ) Trust & Security Perception (Q. Jia et al., 2022 ),(Q. Jia et al., 2022 ),(Yang & Wang, 2025 ),(Cerdá-Mansilla et al., 2024),(C. D. Huang et al., 2017 ),(S. X. Chen et al., 2024 ), (S. Jia et al., 2025 ),(Gretzel & Koo, 2021 ) Stakeholder Collaboration (T. H. Lee & Jan, 2023 ),(Diaz et al., 2024 ), (Z. Chen, 2025 ), (Suanpang & Pothipassa, 2024 ),(Natarajan et al., 2025 ), (Neuhofer et al., 2015), (X. Chen et al., 2025 ), (Shin et al., 2023a ), (P. Lee et al., 2020 ), (Ivars-Baidal et al., 2021 ) Co-creation Orientation (Tsang & Au, 2024 ) Tourist Empowerment (T. H. Lee & Jan, 2022 ), (Gretzel et al., 2015 ),(Fang et al., 2024 ), (Jeong & Shin, 2020 ),(Zhu et al., 2024 ), (X. Chen et al., 2025 ),(Shin et al., 2023a ), (Femenia-Serra, Neuhofer, et al., 2019) Innovation Orientation of Destination (Chung et al., 2017 ),(Q. Jia et al., 2022 ), (Yang & Wang, 2025 ), (Cerdá-Mansilla et al., 2024),(C. D. Huang et al., 2017 ), (S. X. Chen et al., 2024 ),(S. Jia et al., 2025 ), (P. Lee et al., 2020 ) Regulatory & Policy Support (Suanpang & Pothipassa, 2024 ),(Natarajan et al., 2025 ),(Neuhofer et al., 2015), p25, (Cham et al., 2024 ), (Jovicic, 2019 ) (Jovicic, 2019 ), (Behera et al., 2024 ) Organizational Readiness of Tourism Firms (Diaz et al., 2024 ), (Z. Chen, 2025 ), (Chung et al., 2015 ), (Ionescu & Sârbu, 2024 ), (Y. Li et al., 2017 ), (Behera et al., 2024 ), (Femenia-Serra & Ivars-Baidal, 2021 ) spatiotemporal behaviours (Mor et al., 2023 ) Urban morphology (Mor et al., 2023 ) 3.7 Technological Dimensions The list of prominent Technological dimensions identified in review of literature is depicted in table (5) below- Table 5 Dimensions of STE Technological Dimension Citation of prominent Authors Personalization (Tsang & Au, 2024 ),(T. H. Lee & Jan, 2023 ),(Diaz et al., 2024 ), (Gretzel et al., 2015 ), (Kusumastuti et al., 2024 ),(Natarajan et al., 2025 ) (Neuhofer et al., 2015), (S. Jia et al., 2025 ), (Femenia-Serra, Neuhofer, et al., 2019), (Stankov et al., 2025), (Jeong & Shin, 2020 ) ,(Cuesta-Valiño et al., 2020 ),(Balakrishnan et al., 2023 ) Informativeness (Afolabi et al., 2021 ), (Azis et al., 2020 ),(Balakrishnan et al., 2023 ) Interactivity (Chung et al., 2017 ), (T. H. Lee & Jan, 2022 ),(Lim et al., 2017 ), (Yang & Wang, 2025 ), (Chung et al., 2015 ), (Ionescu & Sârbu, 2024 ), (Y. Li et al., 2017 ), (Cham et al., 2024 ), (Femenia-Serra, Neuhofer, et al., 2019), (Jeong & Shin, 2020 )(Balakrishnan et al., 2023 ) Real-time data services/ Real – time information systems (Tsang & Au, 2024 ),(L. Huang & Lau, 2020 ), (Q. Jia et al., 2022 ), (Z. Chen, 2025 ), (Suanpang & Pothipassa, 2024 ), (Cerdá-Mansilla et al., 2024),(C. D. Huang et al., 2017 ),(S. X. Chen et al., 2024 ), (Nguyen et al., 2023 ), (Jeong & Shin, 2020 ), (Ivars-Baidal et al., 2021 ), (Cimbaljević et al., 2019 ) ,(Cuesta-Valiño et al., 2020 ),(Shen, Sotiriadis, & Zhou, 2020 ) Context Awareness (T. H. Lee & Jan, 2023 ), (Diaz et al., 2024 ), (Gretzel et al., 2015 ), (Fang et al., 2024 ),(Jeong & Shin, 2020 ) ,(Zhu et al., 2024 ), (X. Chen et al., 2025 ), (Shin et al., 2023a ), (Jovicic, 2019 ),(Femenia-Serra, Neuhofer, et al., 2019),(Stankov et al., 2025) Connectivity (Chung et al., 2017 ), (T. H. Lee & Jan, 2022 ), (Lim et al., 2017 ),(Kusumastuti et al., 2024 ),(Natarajan et al., 2025 ), (Neuhofer et al., 2015),(S. X. Chen et al., 2024 ), (S. Jia et al., 2025 ), (P. Lee et al., 2020 ), (Ivars-Baidal et al., 2021 ) Ubiquity (Y. Li et al., 2017 ) AI-based Intelligence / Automation (L. Huang & Lau, 2020 ), (Q. Jia et al., 2022 ),(Yang & Wang, 2025 ) ,(Chung et al., 2015 ), (Ionescu & Sârbu, 2024 ),(Y. Li et al., 2017 ) ,(P. Li, 2025 ), (Pai et al., 2020 ), (Wu et al., 2025 ),(Stankov et al., 2025) Immersive Technologies (AR/VR/XR) (Diaz et al., 2024 ), (Z. Chen, 2025 ),(Suanpang & Pothipassa, 2024 ), (Natarajan et al., 2025 ),(Zhu et al., 2024 ), p25, (Shin et al., 2023a ),(Jovicic, 2019 ), (Stankov et al., 2025),(Stankov et al., 2025),(Behera et al., 2024 ),(X. Chen et al., 2025 ),(González-Rodríguez et al., 2020 ), (Paliwal et al., 2024 ), (Pradhan et al., 2018 ), (Tribe & Mkono, 2017 )(Tribe & Mkono, 2017 ) Data Integration / Big Data Analytics p3, (Gretzel et al., 2015 ), (Fang et al., 2024 ), (Jeong & Shin, 2020 ),(Neuhofer et al., 2015), (X. Chen et al., 2025 ),(Cham et al., 2024 ), (Pai et al., 2020 ), (Wu et al., 2025 ), (Ivars-Baidal et al., 2021 ),(Kou et al., 2024),(Santos-Júnior et al., 2020 ),(Khan et al., 2017 ),(Mandić & Kennell, 2021 ),(Encalada et al., 2017 ),(Pradhan et al., 2018 ), (Lan et al., 2021 ), (Bastidas-Manzano et al., 2021 ), (Shen, Sotiriadis, & Zhang, 2020 ) Accessibility Technologies (Lim et al., 2017 ), (Kusumastuti et al., 2024 ), (Cerdá-Mansilla et al., 2024), (C. D. Huang et al., 2017 ), p28,(Nguyen et al., 2023 ), (Gretzel & Koo, 2021 ), (Zhang et al., 2022 ), (Ivars-Baidal et al., 2021 ),(Balakrishnan et al., 2023 ) ,(Uysal et al., 2020 ) Smart Interfaces / Mobile Applications (Tsang & Au, 2024 ), (L. Huang & Lau, 2020 ), (Q. Jia et al., 2022 ), (Yang & Wang, 2025 ),(Ionescu & Sârbu, 2024 ) ,(Y. Li et al., 2017 ), (Cham et al., 2024 ),(Femenia-Serra, Neuhofer, et al., 2019), (Jeong & Shin, 2020 ),, (Shen, Sotiriadis, & Zhang, 2020 ) ,(da Costa Liberato et al., 2018 )1,(Huertas et al., 2021 ) ,(P. Lee et al., 2020 ) ,(Gajdošík, 2020 ),(Nolich et al., 2019 ),(Anaya & Lehto, 2020 ),(Stankov & Filimonau, 2019),(Gelter et al., 2021 ) ,(M. Lee, 2022 ), (Tussyadiah & Wang, 2016 ), (Ghaderi et al., 2018 ) ,(Neuhofer et al., 2015) ,(C. D. Huang et al., 2017 ),(Femenia-Serra, Perles-Ribes, et al., 2019),(Lamsfus et al., 2015 ) Phygital Experience Enablement (Natarajan et al., 2025 ),(Zhu et al., 2024 ), (S. X. Chen et al., 2024 ),(S. Jia et al., 2025 ), (Pai et al., 2020 ),(Stankov et al., 2025) Virtual Platforms / Metaverse Technologies (Shin et al., 2023a ), (Jovicic, 2019 ),(Gretzel & Koo, 2021 ),(Behera et al., 2024 ), (S. Lee et al., 2024 ) 3.7.1 Personalization is used to define the extent of information which smart tourism technologies provide to ensure satisfaction of tourists in planning the requirements of personal trips(Tsang & Au, 2024 ). Personalization in smart tourism significantly enhances travellers' memorable experiences by delivering tailored, interactive services that align with individual preferences, outperforming mere accessibility(Shin et al., 2023b ). Personalisation of STT has a positive relationship with tourists STT experience at heritage sites. Co-created tourism experiences through demand-supply interactions elevate quality of life by integrating physical settings with relational assets for diverse travellers(Balakrishnan et al., 2023 ). "Designing tourism experiences that enhance one’s quality of life implies designing for diversity of the travelling population. 3.7.2 Informativeness in the smart tourism experience refers to the ability of smart technologies to provide accurate, timely, credible, and comprehensive information that supports tourists’ decision-making before and during travel (Azis et al., 2020 ). Through digital platforms, AR/VR, and mobile applications, informativeness reduces uncertainty, enhances experience quality, and enables value co-creation, leading to higher satisfaction and positive behavioural outcomes (Afolabi et al., 2021 ) (H. Lee et al., 2018 ). 3.7.3 Ubiquity in context of STE refers to the omnipresent availability of customized tourism information and services across time, space, media, and devices, enabling tourists to acquire seamless and real- time experiences which provides support system throughout the entire travelling journey. This ubiquitous information service composed of the vital essence of smart tourism (Y. Li et al., 2017 ). 3.7.5 Real-time information systems in smart tourism deliver instantaneous data on traffic, weather, and events through apps like Google Maps and city guides, which assist thetraellers and users to take well planned decisions during their process of travelling (Jeong & Shin, 2020 ). These platforms improve the experiences by giving live updates that decreases the stress related to travels and optimizing their travelling routes in smart destinations(Jeong & Shin, 2020 ). They merge and combine IoT sensors and mobile connectivity to provide dynamic tourist data, assisting customized navigation and activity planning within the smart tourism ecosystem(Jeong & Shin, 2020 ).Real-time abilities from ubiquitous computing enable seamless interaction between tourists and destinations, fostering context-aware engagements. 3.7.6 Context awareness in smart tourism experience refers to the capability of smart tourism systems to sense, interpret, and respond to tourists’ real-time situations by integrating location awareness, time awareness, personalisation awareness, and environmental–situational awareness. Through this integration, smart systems deliver location-specific services, time-sensitive information, personalised recommendations, and contextually relevant guidance, enabling adaptive, meaningful, and immersive tourism experiences throughout the travel journey(T. H. Lee & Jan, 2023 )(Diaz et al., 2024 ). 3.7.7 Connectivity in smart tourism experience refers to the seamless digital linkage among tourists, destinations, service providers, and smart technologies through interconnected networks that enable continuous information exchange and service integration (Natarajan et al., 2025 ). It allows tourists to remain constantly connected to tourism services, platforms, and other stakeholders via mobile devices and networked infrastructures, facilitating real-time access to information and support throughout the travel journey(Neuhofer et al., 2015). Connectivity also enables the integration of heterogeneous systems and stakeholders within a destination, supporting coordinated service delivery, co-creation of experiences, and enhanced interaction between tourists and smart tourism ecosystems (S. X. Chen et al., 2024 ). 3.7.8 AI-based intelligence in smart tourism enhances experiences through technologies like artificial intelligence (AI), enabling intelligent services, expert systems, decision aids, and automatic agents for personalized recommendations and real-time interactions (Yang & Wang, 2025 ). It powers metaverse tourism via computer vision for object/face recognition, body tracking, and scene understanding, alongside data science for cooperative work support and digital twins for monitoring/prognostics, creating immersive virtual-real blends across imitation (VR replicas), intensification (AR overlays), interaction (MR exchanges), and integration (seamless synthetic universes) (Yang & Wang, 2025 ) Big data integration with AI processes massive tourism data from tourists/devices/operations for predictive analytics, traffic forecasting, and personalized services like route optimization and demand analysis. 3.7.9 Big data analytics in smart tourism experience refers to the systematic collection, processing, and analysis of large volumes of heterogeneous data generated by tourists, destinations, and smart technologies to understand tourist behaviour and preferences. It enables smart tourism systems to transform real-time and historical data into actionable insights that support personalised recommendations, adaptive services, and experience co-creation(T. H. Lee & Jan, 2023 ). Through big data analytics, destinations can enhance decision-making, predict tourist needs, optimise service delivery, and continuously improve experiential value by aligning tourism offerings with tourists’ contextual and behavioural patterns (T. H. Lee & Jan, 2023 ). 3.7.10 Immersive technologies in smart tourism experiences refers to advanced tools like augmented reality (AR), virtual reality (VR), and mixed reality (MR) enhanced by AI, which create engaging, personalized interactions that boost tourist satisfaction, perceived value, and loyalty through dimensions such as enjoyment and immersion. In one of the study conducted by, Abou-Shouk et al. (2024) note that perceived ease of use, enjoyment, immersion, usefulness, and attitude toward technology predict immersive technology adoption, positively affecting tourists' perceived value, engagement, satisfaction, and loyalty in tourism contexts. Similarly, Holdack et al. (2020) highlight how the fun and immersive features of smart technologies, including AR tours and gamified experiences, increase engagement and satisfaction. 3.7.11 Accessibility represents the extent to which a tourist finds the information offered at the destination accessible using smart tourism technologies, informativeness represents the extent to which smart tourism technologies provide accurate and sincere information; inter activity represents the extent to which a tourist engages in reciprocal communication with other stakeholders via smart tourism technologies. 3.7.12 Phygital Experience -Enablement in smart tourism refers to the seamless fusion of physical and virtual realms, primarily through Metaverse technologies that create immersive "Phygital experiences" allowing tourists to traverse between physical heritage sites and their virtual counterparts(S. Jia et al., 2025 ). This integration leverages AR, VR, MR, and AI to augment real-world visits with digital overlays—such as virtual guides delivering context-aware narratives or historical recreations—while enabling pre-travel virtual tours that build realistic expectations and post-travel virtual returns for deeper engagement (S. Jia et al., 2025 ). In the context of smart tourism experiences, it transforms heritage destinations by boosting brand equity via entertainment, interaction, trendiness, novelty, and intimacy in Metaverse environments (Natarajan et al., 2025 ). These phygital elements address challenges like authenticity preservation and overtourism by dispersing crowds through virtual alternatives, as seen in examples like Tencent's MR/3D cultural immersions or VR heritage recreations, ultimately driving physical visits through heightened spatial presence quality and perceived augmentation (Natarajan et al., 2025 )(S. Jia et al., 2025 ). 3.7.13 Virtual platforms and metaverse technologies in smart tourism integrate AR, VR and mobile platforms to create immersive, connected and interactive tourist experiences within smart tourism cities(Gretzel & Koo, 2021 ). They link physical places with virtual content through QR codes and VR services, enabling realistic destination experiences even without travel and enriching on-site visits(Gretzel & Koo, 2021 ). Such platforms also support virtual tours and tourist–resident interactions beyond physical boundaries (Gretzel & Koo, 2021 ). These smart technologies act as supporting products that enhance interactivity, personalization and memorability of tourism experiences (Shen, Sotiriadis, & Zhou, 2020 ). 3.8 Outcomes of Smart Tourism Experience The literature review of articles of STE generates a wide variety of tourist-centric, destination-level, and societal outcomes, with most evidence pointing to beneficial impacts and outcomes, alongside emerging concerns. A dominant positive result is tourist satisfaction and experience quality, repeatedly confirmed across empirical studies. For example, (Z. Chen, 2025 ),Some studies report that smart technologies such as mobile apps, IoT-enabled services, and real-time information prominently improve the perceived quality of tourism experiences and satisfaction, generally mediated by perceived usefulness and enjoyment(Cerdá-Mansilla et al., 2024). Empirical results in (Z. Chen, 2025 ) (Suanpang & Pothipassa, 2024 ) show strong positive relationship coefficients between STE and satisfaction, depicting that smartness has direct impact on enhancing tourists’ affective evaluations of their journeys. Closely related is perceived value and positive attitude, where some studies have clearly indicated that functional, emotional, and epistemic values derived from smart services significantly shape favourable attitudes toward smart destinations and platforms(Tsang & Au, 2024 ) (L. Huang & Lau, 2020 ). The most prominent and importantly supported outcome is behavioural intention, consisting of revisit intention, loyalty, and positive word-of-mouth. Studies which are empirically conducted demonstrated that higher levels of STE essentially predict revisit intention and recommendation behaviour, with satisfaction and destination image acting as mediators (Zhu et al., 2024 ). Similarly, some studies proves that improvements in destination image and smart destination brand equity, suggests the technologically enriched experiences strengthen tourists’ cognitive and affective images of destinations(Neuhofer et al., 2015). Empirical evidence shows that perceived smartness has positive impact on outcomes of destination attachment and loyalty intentions(Neuhofer et al., 2015). Several studies emphasize personalization, immersion, and co-creation as experiential outcomes enabled by AI, big data, and AR/VR. Some studies argue that smart systems facilitate tailored itineraries and interactive content, which enhance engagement and tourists’ sense of co-creating value(X. Chen et al., 2025 ),(Jeong & Shin, 2020 ). Empirical findings indicate that personalization significantly increases engagement and hedonic value, which in turn boost satisfaction(Jeong & Shin, 2020 ). This aligns with service-dominant logic, where tourists become active participants rather than passive consumers. Beyond individual tourists, STE also generates organizational and destination performance outcomes. Some studies report improved service efficiency, operational effectiveness, and decision-making quality for tourism providers through real-time data analytics and smart infrastructure(Yang & Wang, 2025 ). At the macro level show that STE supports sustainable tourism development, better crowd management, energy efficiency, and optimized resource use(Kusumastuti et al., 2024 ), (Chung et al., 2015 ) (Shen, Sotiriadis, & Zhou, 2020 ). Empirical results suggest that smart technologies have a significant positive effect on perceived sustainability performance of destinations(Chung et al., 2015 ). Further, reiew provides evidence that smart services enhance accessibility and inclusiveness, improving experience quality for elderly and disabled tourists, thereby contributing to residents’ and visitors’ quality of life. However, despite these benefits, the literature also identifies negative and paradoxical outcomes of STE. One of the studies reveals that excessive technology mediation may reduce existential authenticity, mindfulness, and emotional immersion, as tourists become more screen-focused than place-focused(Tribe & Mkono, 2017 ). Empirical results show a negative relationship between technology intensity and perceived authenticity(Tribe & Mkono, 2017 ). Similarly, (Tussyadiah & Wang, 2016 ) some authors argues that algorithm-driven recommendations, while improving efficiency and convenience, can limit serendipity, exploration, and experiential learning, potentially standardizing tourist experiences. Issues of privacy risk, security concerns, and technostress are highlighted in(Pradhan et al., 2018 ) in some studies. These studies empirically show that perceived risk and digital fatigue have significant negative effects on trust and, indirectly, on satisfaction and usage intention, even when the overall utility of smart systems remains high. One of the studies further reports symptoms of over-dependence on smart devices, leading to cognitive overload and reduced enjoyment at certain stages of the journey(Anaya & Lehto, 2020 ). These findings suggest a “double-edged sword” effect of smartness in tourism experiences. Overall, the empirical evidence across the reviewed papers confirms that STE leads to higher satisfaction, perceived value, positive attitudes, loyalty intentions, destination image, personalization, co-creation, efficiency, and sustainability outcomes (Tsang & Au, 2024 ),(Diaz et al., 2024 ), (Z. Chen, 2025 ), (Suanpang & Pothipassa, 2024 ),(Zhu et al., 2024 ),(Neuhofer et al., 2015) ,(X. Chen et al., 2025 )(Chung et al., 2015 ). At the same time, studies caution against unintended consequences such as loss of authenticity, reduced mindfulness, privacy concerns, technostress, and diminished serendipity (Tribe & Mkono, 2017 )(Tussyadiah & Wang, 2016 ),(Pradhan et al., 2018 ), (Anaya & Lehto, 2020 ). These mixed outcomes indicate that while smart tourism technologies substantially enrich tourist experiences, their design and implementation must balance technological augmentation with human-centered, ethical, and experiential considerations to ensure long-term value creation. 3.9 Mediators identified in the Study 3.9.1. User Engagement In one of the study, user engagement is depicted as a vital psychological mechanism through which Metaverse-based smart tourism dimensions (e.g., immersion, social interaction, personalization) which impacts on tourists’ experience quality and behavioural responses. The study explains that engagement shows a true picture of tourists’ active participation, interaction, and involvement in virtual and digital environments, which in turn improves the perceived experience and value co-creation. Although, in a literature review, it clearly pointed out that user engagement serves as a mediator linking Metaverse affordances to results like enhanced experience, satisfaction, and intention of usage.(Z. Chen, 2025 ). 3.9.2. Digital Immersion The study byZ. Chen, 2025 has also provided with the framework of digital immersion as a mechanism through which VR/AR-driven smart destination digital environments affect tourists’ emotions and experience related outcomes. Immersion explains how technological realism and presence translate into stronger experiential impact, making it a mediating experiential state between smart technologies and tourists’ evaluations. 3.9.3. Social Interaction Social interaction on digital and social media platforms is discussed as another and significant mediating pathway. The study argues that smart platforms enable interaction beyond physical boundaries or barriers, which fosters community feeling and co-creation, thereby improving the overall STE and outcomes related to it.(Z. Chen, 2025 ). 3.9.4. Personalization The review emphasizes personalized experiences enabled by AI and data analytics as a mechanism translating smart system capabilities into higher satisfaction and perceived value. Personalization operates as a mediator by aligning services with tourists’ preferences, thereby improving experience outcomes. 3.9.5. Perceived Enjoyment One of the studies which quantitatively analyses the STE, perceived enjoyment and experiential value are modelled as mediators between smart technology attributes and dimensions (e.g., interactivity, vividness) and behavioural intentions such as revisit or recommendation(Jeong & Shin, 2020 ). The findings show that smart features significantly enhance enjoyment, which in turn drives favourable intentions confirming a mediating effect. 3.9.6. Co-creation Focusing on smart tourism and technology driven co-creation, level of tourist involvement and value co-creation are considered as mediators linking smart service design with outcomes such as satisfaction, loyalty, and memorable experiences. The empirical results indicate that smart features significantly increase engagement, which then enhances experience-related outcomes(X. Chen et al., 2025 ). 3.9.7. Satisfaction Some Studies empirically gives assistance to tourist or users satisfaction as a core mediator. Smart or immersive experience dimensions positively influence satisfaction, which subsequently drives behavioural intentions such as revisit intention and word-of-mouth. Satisfaction thus explains how experience perceptions are converted into post-consumption behaviours.(X. Chen et al., 2025 ) (Jeong & Shin, 2020 ). 3.10 Major Research Gaps identified through Literature review and suggested Future Directions The literature review on smart tourism reveals critical research gaps categorized into contextual, methodological, behavioural, theoretical, and technological types, limiting the field's maturation and practical application. Contextual gaps are related to the underexplored settings and integrations, such as lack of cross-cultural and longitudinal studies that are not capable enough tp acquire and examine diverse tourist behaviours across global destinations (T. H. Lee & Jan, 2022 ). For example-one study has clearly pointed out the absence of traveller-centric research in varied geographic and cultural contexts, while one of the study notes limited holistic stakeholder perspectives including locals and managers beyond tourist views(Cerdá-Mansilla et al., 2024). Methodological gaps include overreliance on cross-sectional surveys and self-reported data via PLS-SEM, lacking mixed-methods, experimental designs, or longitudinal tracking of adoption evolution(Tsang & Au, 2024 ),(T. H. Lee & Jan, 2023 ) (T. H. Lee & Jan, 2022 )specifically critiques the scarcity of empirical validation for antecedents like ICT infrastructure and learning orientation, with inadequate scale development across destinations. Behavioural gaps focus on unexamined psychological and post-adoption dynamics, such as hedonic motivations, emotional mediators, technology attachment, authenticity perceptions, and environmentally responsible behaviours(Fang et al., 2024 )(Chung et al., 2017 ). Studies like (Tsang & Au, 2024 ), and (L. Huang & Lau, 2020 ) identify shortcomings in linking user readiness to long-term outcomes like continued usage and loyalty. Theoretical gaps involve fragmented frameworks, with overemphasis on technology acceptance models (TAM) without integrating socio-technical systems, sustainability theories, or multi-stakeholder value co-creation (Lim et al., 2017 )(Gretzel et al., 2015 ). Some of the studies underscore the need for unified models incorporating psychological well-being and governance structures(Jeong & Shin, 2020 ). Technological gaps highlight underexplored emerging innovations, including AI-driven analytics, IoT integration, metaverse platforms, big data for sustainability, and their ethical/privacy implications (Diaz et al., 2024 ), (Z. Chen, 2025 ),(Suanpang & Pothipassa, 2024 ),(Q. Jia et al., 2022 ) points to immature monitoring systems and heterogeneous data fusion in smart platforms. These gaps collectively impede robust theory-building and evidence-based smart tourism implementation. Addressing them requires strategic future directions to advance scholarly and practical contributions. Future research should prioritize longitudinal, multi-country empirical studies using mixed-methods to validate smart tourism scales and track technology adoption trajectories across developing and developed economies, directly responding to methodological and contextual gaps in (T. H. Lee & Jan, 2022 ). Scholars must integrate behavioural dimensions through traveller-centric designs, examining hedonic experiences, emotional involvement, authenticity, and post-adoption sustainability via advanced mediators like value co-creation and immersion(Chung et al., 2017 ) (T. H. Lee & Jan, 2022 ),(Fang et al., 2024 ). Theoretical advancements can emerge from interdisciplinary frameworks blending TAM with socio-technical systems theory and circular economy models, incorporating stakeholder views for holistic ecosystems as suggested in some studies (Lim et al., 2017 )(Cerdá-Mansilla et al., 2024). Technological explorations should focus on generative AI, IoT-big data synergies metaverse-virtual-real integrations, and blockchain for privacy governance, with ethical audits and digital divide assessments in underrepresented contexts (Diaz et al., 2024 ), (Z. Chen, 2025 ),(Suanpang & Pothipassa, 2024 ). Comparative analyses of smart versus traditional tourism, including subsector-specific applications (e.g., heritage sites, night tourism), will bridge some studies gaps(Zhu et al., 2024 ). Experimental designs testing AR/VR interventions and qualitative inquiries into FOMO moderation or avatar behaviours can enrich future studies insights. Policymakers and practitioners should collaborate on pilot implementations in smart destinations, evaluating long-term impacts on loyalty, WOM, and low-carbon outcomes. By pursuing these directions, researchers can transform smart tourism from technology-centric to human-centred, sustainable paradigms, fostering inclusivity. 3.11 Other findings The study explains that smart tourism experience is shaped by multiple types of intelligence embedded within destination systems, collectively enhancing how tourists perceive and interact with smart destinations. Swarm intelligence enables different technological systems to work collaboratively, creating seamless and integrated services that improve overall travel fluidity and coordination. Sensory intelligence allows destinations to sense tourists and environmental conditions through sensors and tracking technologies, enabling real-time awareness of location, crowd levels, and situational contexts that support smoother navigation and management. Communication intelligence enhances smart tourism experiences by delivering timely, proactive, and relevant information to tourists, reducing uncertainty and cognitive effort during travel. Empathetic intelligence strengthens the experiential dimension by allowing systems to recognize tourists’ needs and emotions, offering personalized and context-sensitive responses that create a more humanized and supportive experience. Learning intelligence enables destinations to adapt and improve over time by analysing accumulated tourist data, leading to increasingly accurate recommendations and personalized services that evolve with repeated use. Mechanical intelligence supports smart tourism by automating routine service tasks, improving efficiency and convenience, although its perceived smartness may decline as automation becomes commonplace. Reactive intelligence ensures immediate system responses to real-time changes in tourist context, such as language preferences or environmental conditions, reinforcing perceptions of responsiveness and adaptability. Finally, memory intelligence underpins personalization and long-term service optimization by storing and retrieving tourist data, while simultaneously highlighting the importance of trust, privacy, and secure data governance in sustaining positive smart tourism experiences(Au & Tsang, 2022). 4. Implications of the Study 4.1 Theoretical Implications In line with the research question on conceptual and thematic ground, the current study contributes to the theory by elucidating smart tourism experience to be more of an intelligence-driven and experience-based phenomenon instead of being merely a technology formation. As its results underline, smart tourism experience is a result of interacting between technological infrastructures (e.g., sensing, communication, learning and memory intelligence) and cognitive, emotional, and behavioral involvement of tourists. The synthesis of major themes like experience co-creation, personalization, empowerment, smart destination attributes make the study relevant to developing theory by aligning smart tourism experience incorporating experiential and service-dominant logic models. However, the types of intelligence signify the necessity of a theoretical framework that goes beyond the linear technology-outcome associations and offers systemic approaches that consider the dynamic relationships among tourists, technologies and destinations. 4.2 Methodological Implications To answer the research question about intellectual and geographical structures, the paper presents the significance of bibliometric methods in charting the development and organization of the research on smart tourism experience. This analysis shows that the number of publications and citations is concentrated in particular countries and among the few researchers, which indicates the possibility of an epistemic basis and homogeneity of the methodology. This is an indication that future studies should consider diversification of methods such as qualitative, mixed method, and longitudinal designs to understand more of the experiential and contextual aspects of smart tourism. Moreover, the use of secondary data sources implies the possibilities of primary data collection with the help of real-time digital footprints, sensor data, and immersive technologies to improve reflected lived smart tourism experiences. 4.3 Practical Implications The research question regarding application and relevance, the results can be used practically by destination managers and policy makers who are interested in improving smart tourism experiences. The prevalence of experience-related themes points to the fact that smart tourism investments should focus on the experience value development, but not on technology implementation. To provide personalized, responsive and emotionally engaging experiences, destination managers ought to combine various types of intelligences; sensory intelligence, communication intelligence and empathetic intelligence. The geographical insights can enable the policy makers to recognize the loopholes in the smart tourism development of emerging and developing destinations and devise policies that encourage the development of smart tourism activities in an inclusive and context-sensitive manner. Moreover, trust, data privacy and governance are given priority and present the necessity to build ethical and transparent data management systems to continue the positive experience of smart tourism. 4.4 Implications for Tourists and Experience Design The study also has an impact on the concept of tourists as active participants in the smart tourism ecosystems. The results support the argument that smart tourism experience empowers the tourists by increasing the sense of autonomy, decision making, and co-creation opportunities. Experience designers must thus work on user-friendly smart solutions that facilitate learning, emotional interaction, and smooth interaction throughout the tourist experience. With the smart technologies aligned to the needs, preferences, and values of the tourists, destinations can help them become more engaged, satisfied, and loyal. 5. Limitations of the Study The study has some of the limitations which should be taken into account. First, the study includes only the publications in the major academic databases, so the inclusion of the studies on the regional level is possible, i.e., in the journals, conferences, or reports published by the industries, which might introduce a limitation to the inclusivity of the results. Second, the bibliometric method is concerned with the patterns of publication and citation, which are indicators of scholarly impact, but do not necessarily reflect the practical importance or practical realization of smart tourism experiences. Third, the research is mainly based on quantitative indicators and thematic explanations, which can ignore subtle contextual, cultural and experience variability between destinations. Fourth, current and quickly changing smart tourism technology implies that recent technological advances (e.g., generative AI, extended reality, improved data analysis) are not necessarily well-represented in the reviewed literature. Lastly, the empirical study fails to test the causality between smart tourism attributes and tourist outcomes, and, therefore, does not allow the researcher to make behavioural or performance-based conclusions. 6. Conclusion This paper provides the conceptual, thematic, methodological, and geographical layers of this literature through a synthesis of the concept of smart tourism experience. Through the use of a bibliometric analysis and content-based analysis, the paper highlights how smart tourism experience has been modified into an experience-co-creation, tourist-empowerment, and intelligent destination system multidimensional phenomenon. The results indicate that the researches on smart tourism experience are influenced by different methodological methods such as conceptual frameworks, quantitative empirical research, qualitative research as well as mixed-method research designs due to maturity and methodological diversification of the study. It is further indicated that the methodological classification tables used reveal the domineering research designs and data sources and also reveal research imbalances in terms of methodological selection within and across regions and themes. It is also revealed in the analysis that the research on smart tourism experience is geographically clustered in technologically developed and tourism-related nations, with China, Spain, the United States, and South Korea becoming the major contributors. This difference in spatial distribution corresponds with access to digital infrastructure and smart destination programs; therefore, it can be assumed that technological preparedness has a great impact on scholarly output. Also, the naming of a few prominent writers and significant works highlight the presence of a comparatively limited circle of academic interest in determining theoretical orientation, research priorities, and methodology choice in the discipline. Also, the literature indicates that the trends in methodologies are strongly correlated with the themes of the study, and quantitative designs are predominant in the studies on the adoption of technology, evaluation of the experience, and behavioral consequences, whereas qualitative and conceptual works are helpful in the development of the theory and conceptualization of experiences. The combination of these insights allows the study to collate the fragmented knowledge, as well as it offers the well-organized basis of further empirical and methodological progress. On the whole, the results assist in gaining a more profound insight into the way the problem of smart tourism experience is regarded, in which direction research activities are focused, and how the methodological choices are determined to impact the formation of knowledge, which can also be regarded as the valuable source of guidance that the scholar can use to create a strong and context-specific study in the growing field. Declarations Ethics Approval and Consent to Participate This study is based exclusively on a systematic scoping review of previously published and publicly available peer-reviewed literature. As no primary data were collected and no human participants were directly involved, ethical approval and informed consent were not required for this research. Consent for Publication Not applicable. Competing Interests The authors declare that they have no competing interests. Funding Not Applicable Author Contribution All authors contributed substantially to the conception and design of the study.- **Conceptualization:** All authors- **Methodology and review protocol:** All authors- **Literature search and screening:** All authors- **Writing – original draft:** All authors- **Writing – review and editing:** All authors Data Availability All articles reviewed are obtained from publicly available peer-reviewed journal articles indexed in the Web of Science database. The list of included studies and relevant extracted information are available from the corresponding author upon reasonable request. References Afolabi OO, Ozturen A, Ilkan M (2021) Effects of privacy concern, risk, and information control in a smart tourism destination. 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2","display":"","copyAsset":false,"role":"figure","size":35724,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8530210/v1/f0bef99546d0f24ccb1bba2d.png"},{"id":100076672,"identity":"d9a7cdfd-d01c-4d74-9f1f-174889ab088a","added_by":"auto","created_at":"2026-01-12 17:34:35","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":160925,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8530210/v1/743ca214424369c14f12e4c9.jpg"},{"id":100381990,"identity":"ffe25bfa-85f0-4210-8f90-4f316acfc0b4","added_by":"auto","created_at":"2026-01-16 10:40:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2309967,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8530210/v1/9ab3b8ae-809f-4629-b2d5-50bb01a1ec6a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mapping the Smart Tourism Experience Landscape: A Systematic Literature Review","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eSmart tourism has become a buzzword and popular topic due to the growth of intelligent systems and technology (Park, Lee, Yoo, \u0026amp; Nam, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wang, Li, Zhen, \u0026amp; Zhang, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). One way to conceptualize smart tourism is as an advancement of e-tourism (Gretzel, Sigala, et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Xiang \u0026amp; Fesenmaier, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Smart tourism is unique in that it uses the Internet of Things (IoT) and AI to combine the physical and digital worlds, whereas e-tourism refers to the use of ICTs in the processes carried out by tourism organizations and among many players to improve business strategy and organizational performance (Buhalis, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Additionally, smart tourism includes the changes that experiences have undergone in recent years and the pervasiveness of omnipresent connectivity (Gretzel, Reino, Kopera, \u0026amp; Koo, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Gretzel, Sigala, et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Also, smart tourism is considered as an \u0026lsquo;ecosystem\u0026rsquo;, constituted by a smart business network, smart destinations and a smart technologies infrastructure (Gretzel, Reino, et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Additionally, smart tourism is viewed as an \"ecosystem\" made up of smart locations, smart business networks, and smart technology infrastructure (Gretzel, Reino, et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The ubiquitous tour information service that travelers receive when traveling is known as \"smart tourism.\" The culmination of the shared characteristics of smart travel is the tour information service. Smart tourism does not, however, encompass all information services. Smart tourism can only relate to the ubiquitous tour-in-formation service that is offered to individual tourists through initiatives based on their unique needs(Y. Li et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). According to existing literature, STE is a multifaceted notion that is shaped by the smooth integration of smart technologies like location-based services, augmented and virtual reality, mobile applications, the Internet of Things (IoT), artificial intelligence, and big data analytics (T. H. Lee \u0026amp; Jan, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Travelers become active co-creators of value instead of passive consumers thanks to these technologies, which allow destinations to provide context-aware, interactive, and personalized experiences(Tsang \u0026amp; Au, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)(L. Huang \u0026amp; Lau, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Crucially, researchers contend that smartness in tourism is only achieved when travellers recognize and enjoy concrete advantages from technological applications rather than being a feature of technology itself (Tsang \u0026amp; Au, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, the research states that four characteristics make up a smart tourism experience: accessibility, informativeness, interactivity, and customisation (Tsang \u0026amp; Au, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, the research states that four characteristics make up a smart tourism experience: accessibility, informativeness, interactivity, and customisation (Tsang \u0026amp; Au, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Even if the amount of research on smart tourism is increasing, there is still a lack of coherence in the literature regarding the conceptualization, operationalization, and empirical analysis of smart tourist experiences. The definitions of STE, the technological aspects highlighted, and the theoretical frameworks used in previous research vary greatly, ranging from experience-centric and stimulus-organism-response frameworks to technology acceptance models. Furthermore, few attempts have been made to systematically map the antecedents, mediators, and outcomes of STE in an integrated manner, despite the fact that numerous research look at specific technologies or outcomes including satisfaction, engagement, and behavioral intentions(T. H. Lee \u0026amp; Jan, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSTE research has a wide range of methodologies, including mixed-methods designs, survey-based quantitative studies, qualitative approaches, and new experimental and design-oriented procedures (Tsang \u0026amp; Au, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, the lack of a thorough synthesis of methodological trends restricts the creation of cumulative knowledge and the comparability of results between investigations. Additionally, rather than specifically focusing on the experiential aspect of smart tourism, current assessments typically concentrate on smart locations or smart tourism in general.\u003c/p\u003e \u003cp\u003eThis chapter provides an organized and transparent mapping of the Smart Tourism Experience research landscape by using a PRISMA-ScR-based systematic literature review in response to these limitations. In particular, four research questions serve as the chapter's compass:\u003c/p\u003e \u003cp\u003e(1) What is the conceptualization of Smart Tourism Experience in the literature currently in publication?\u003c/p\u003e \u003cp\u003e(2) What aspects of technology affect the Smart Tourism Experience?\u003c/p\u003e \u003cp\u003e(3) In STE research, what methodological techniques have been used?\u003c/p\u003e \u003cp\u003e(4) Which Smart Tourism Experience antecedents, mediators, and outcomes have been found?\u003c/p\u003e \u003cp\u003eThis chapter seeks to advance the understanding of Smart Tourism Experience in an increasingly technology-driven tourism environment by synthesizing and organizing previous research through these guiding questions, highlighting theoretical and methodological gaps, and suggesting future research directions(Tsang \u0026amp; Au, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1Research Design\u003c/h2\u003e \u003cp\u003eWith a focus on identifying technological features, antecedents, and research gaps, this study used a scoping review methodology to methodically map and synthesize the body of existing literature on Smart Tourism Experience (STE). Because smart tourism research is young, diverse, and conceptually fragmented, a scoping review was deemed relevant. A scoping review allows the assessment of the scope, features, and conceptual boundaries of the literature where empirical evidence is still few, much like previous studies looking at emerging research domains (Botor \u0026amp; Tuliao, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR), which has been used in similar scoping reviews (Botor \u0026amp; Tuliao, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), served as the guide for the review protocol to guarantee transparency, rigor, and reproducibility in the review process (Tricco et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e represents the full process followed while including articles in our review study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Search Strategy\u003c/h2\u003e \u003cp\u003eUsing Web of Science, a significant academic database that is frequently utilized in management, tourism, and hospitality research, a thorough literature search was carried out. The search strategy was meticulously created and improved in accordance with the methodology recommended by Botor and Tuliao (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) to guarantee accuracy and pertinence to the research goals. The literature search was limited to research that addressed Smart Tourism Experience, in keeping with the review's clear emphasis. In order to prevent conceptual dilution and guarantee that only directly relevant research was found, the search was carried out using the single core keyword phrase \"smart tourism experience.\" No other or different keywords pertaining to more general concepts of technology-enabled or digital tourism were used. Because the Web of Science database is known for indexing reputable, peer-reviewed articles and was thought to be suitable for upholding methodological rigor and consistency, the search was limited to that database. Additionally, in accordance with suggested procedures for scoping reviews, backward reference searching was done by looking through the reference lists of the chosen publications to find any other pertinent studies (Botor \u0026amp; Tuliao, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Eligibility Criteria and Study Selection\u003c/h2\u003e \u003cp\u003eStudies that specifically looked at smart tourism or technology-enabled tourism experiences and addressed technological aspects, antecedents, or important factors influencing the tourist experience were included in the review. To maintain academic rigor and uniformity, only English-language peer-reviewed journal publications were taken into consideration. On the other hand, studies that were published as editorials, book reviews, or conference abstracts, failed to conceptualize tourist experience as a key outcome variable, or only concentrated on smart city efforts with no direct connection to tourism were disqualified. In order to preserve the caliber and dependability of the evaluated literature, articles that lacked adequate conceptual foundation or methodological clarity were also eliminated from the study.\u003c/p\u003e \u003cp\u003eIn accordance with the PRISMA-ScR methodology (Tricco et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and previous scoping review applications (Botor \u0026amp; Tuliao, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), the research selection technique comprised three stages: duplication removal, title and abstract screening, and full-text assessment. To guarantee compliance with the qualifying requirements, any questions raised throughout the screening process were carefully reevaluated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Charting and Synthesis\u003c/h2\u003e \u003cp\u003eA structured extraction approach was used to methodically chart data from the final set of included studies. The author or authors, the year of publication, the journal source, the research design, the theoretical underpinnings, the technological focus, the discovered antecedents, and the main conclusions pertaining to the smart tourist experience were all retrieved.\u003c/p\u003e \u003cp\u003eThe analysis integrated theme synthesis with descriptive numerical mapping (e.g., publication patterns, methodological methods), in accordance with Botor and Tuliao (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Key technological aspects of STE (such as artificial intelligence, the Internet of Things, big data analytics, mobile technologies, and immersive technologies) were categorized using thematic analysis, which was also used to arrange antecedents at the person, technological, and destination levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Identification of Research Gaps\u003c/h2\u003e \u003cp\u003eThe included papers were critically analyzed to find deficiencies pertaining to methodological rigor, theoretical integration, regional representation, and developing ethical and sustainability concerns in accordance with the goals of scoping reviews. In line with gap identification techniques employed in earlier scoping reviews, special focus was given to the predominance of conceptual studies, the lack of empirical validation, and the underrepresentation of developing economies (Botor \u0026amp; Tuliao, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This process facilitated the development of a structured future research agenda for advancing smart tourism experience research.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Findings of the review of Literature","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1Conceptualization, and Growing Importance of Smart Tourism Experience\u003c/h2\u003e\n \u003cp\u003eThe results and findings of literature review clearly reveals that the concept of STE has its roots associated with previous research on e-tourism, the tourism services which are driven by ICT, and smart city growth and development, where technology was seen only as a mere tool for enhancing operational efficiency and information dissemination rather than creation of experience (Buhalis, \u003cspan class=\"CitationRef\"\u003e2003\u003c/span\u003e; Buhalis \u0026amp; Law, 2008; Wang et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). The old researches had laid emphasis on the application of digital and destination management platforms along with mobile technologies to assist tourist in making decisions and service delivery, positioning tourists primarily as technology users within digitally mediated environments (Xiang \u0026amp; Gretzel, 2010; Wang et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). But due to the expansion of smart city initiatives and growth of technologies such as IoT, big data, and ubiquitous connectivity became very important and significant, tourism researcher started expanding these ideas to destination contexts, laying the foundation for the emergence of smart tourism and also the, smart tourism experience (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Buhalis \u0026amp; Amaranggana, 2015).\u003c/p\u003e\n \u003cp\u003eThe findings have also clearly highlighted that STE has been progressively conceptualized as a multidimensional, dynamic, and experience-oriented construct and not just the outcome of applications of modern technologies. Foundational researches have also redefined the concept of STE as the outcome of interactions among tourists, smart technologies, and destination environments, with special focus on personalization, contextual intelligence, interactivity, and real-time adaptability as essential experiential attributes (Neuhofer et al., 2015; Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Wang et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e). Then in next phase research started extending this conceptualization through inclusion of experiential dimensions like some of them are enjoyment, learning, immersion, trust, and co-creation, emphasizing that smartness is considered meaningful only when tourists perceive tangible experiential value from application of modern technologies (Koo et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Femenia-Serra \u0026amp; Neuhofer, 2018; Shin \u0026amp; Perdue, 2019). The findings also throw clear light on strong convergence in the literature indicating that STE as a process-oriented phenomenon that unfolds across the pre-trip, on-site, and post-trip phases, enabled by intelligent systems that has the immense ability of sensing, learning, and adapting to the demands of tourist (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Xiang et al., 2021).\u003c/p\u003e\n \u003cp\u003eAnother significant finding shows that why smart tourism experience is increasingly gaining attention as a research topic. The review also illustrates that rapid technological advancemen specially the widespread usage of smartphones, social media, recommendation systems based on AI, and location-based services has prominently transformed the tourist behaviour and expectations, leading to the creaton of demand for seamless, personalized, and purposeful experiences (Wang et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e; Neuhofer et al., 2015; Xiang et al., 2021). Since the users and tourists have become more digitally empowered and experience-oriented, the scholars have started recognizing STE as a critical mechanism through which destinations could improve the levels of satisfaction, engagement, and competitive advantage (Buhalis \u0026amp; Amaranggana, 2015; Koo et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Moreover, STE had acquired importance because of its alignment with service-dominant logic and experience economy perspectives, which emphasize value co-creation, active participation, and experiential outcomes rather than passive consumption (Vargo \u0026amp; Lusch, 2008; Neuhofer et al., 2015).\u003c/p\u003e\n \u003cp\u003eThe findings of the study have clearly shed light on increasing attention of researchers towards the concept of STE which is basically driven by its importance to broader destination-level challenges related to sustainability, crowd management, inclusivity, and governance. The literature progressively positions STE as a strategic framework for leveraging technology to balance satisfaction of users with destination management objectives, such as diminishing congestion, optimum utilization of resources, and enhancing quality of life for residents (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e; Buhalis \u0026amp; Amaranggana, 2015; Stankov \u0026amp; Gretzel, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consequently, STE has evolved with time a central research construct that connects technological innovation, tourist behavior, experiential value, and sustainable destination growth and development.\u003c/p\u003e\n \u003cp\u003eOverall, the findings states that STE has completely changed from a technology-driven concept to a holistic, human-centred research domain. Its growing significance in the research domain depicts the growing recognition that understanding tourism in smart destinations not only need the examination of technological abilities but also analysing how these technologies assit in shaping the tourists\u0026rsquo; perceptions, emotions, behaviours, and co-created experiences across the entire travel journey.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Geographical Distribution of Smart Tourism Experience Research\u003c/h2\u003e\n \u003cp\u003eThe above figure (2) illustrates the geographical distribution of research contributions in context of STE, clearly shedding light on the uneven concentration of research studies across various countries. China is the most important contributor, indicating a strong research focus on STE which is because of drastic and quick changes in digital infrastructure development, smart city initiatives, and large-scale adoption of technologies related to tourism. Spain and the United States follow, symbolizes their developed tourism economies where STE is closely linked to destination competitiveness, tourist management, and experience personalization. On the same side we cannot ignore the prominent contribution of South Korea\u0026rsquo; who underscores its leadership in ICT innovation and technology-driven tourism services, which has completely changed and reshaped the immersive and intelligent tourism experiences. There are some studies conducted in England\u0026rsquo;s which shows the sustained academic interest in smart tourism in context of such as digital heritage, experience design, and urban tourism innovation. Other nations like Australia, India, Malaysia, Serbia, and Portugal show comparatively lower but emerging contributions, indicating their engagement with STE research, with special emphasis on sustainability, smart destination development, and technology adoption related problems. Overall, the figure clearly indicates that STE research is being conducted in developed nations followed by developing and smaller tourism markets which are slowly but trying to expand their scholarly focus.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Most Influential Authors in Smart Tourism Experience Studies\u003c/h2\u003e\n \u003cp\u003eThe Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e is presenting the most influential authors in context of STE research depicting their frequency of contributions within articles that has been reviewed. Chung N. emerges as the leading author, indicating his sustained scholarly influence on redefining the concept of STE and its conceptualization and empirical analysis of STE, especially in areas such as technology acceptance, smart destination characteristics, and digitally mediated experiences of users and tourist. Authors such as Femenia-Serra F., Gretzel U., Vars-Bidal J. A., and Koo C. follow closely, highlighting their prominent roles in advancing theoretical frameworks and empirical results in context of experience co-creation, smart technologies, and tourist behaviour in smart environments. The presence of Shen S. W., Sotiriadis M., and Stankov U. depicts increasing scholarly engagement with STE from perspectives including digital innovation, destination management, and experiential value creation. Meanwhile, authors such as Au W. C. W. and Celda-Bernabeu M. A., though contributing fewer publications, but still clearly indicated their emerging voices addressing intelligence-oriented and governance-related dimensions of STE.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Methodological Distribution of Smart Tourism Experience Studies\u003c/h2\u003e\n \u003cp\u003eThe methodological review of selected smart tourism experience studies indicates a strong dominance of quantitative research approaches, particularly survey-based Structural Equation Modelling (SEM) and Partial Least Squares SEM (PLS-SEM) techniques. These methods are widely applied to analyze the complex relationships among smart tourism technologies, destination attributes, and tourists\u0026rsquo; cognitive, affective, and behavioural outcomes. This is being represented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003cp\u003eSurvey-based SEM / PLS-SEM approaches are the most frequently adopted, used in studies conducted by Tsang (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), Lee and Jan (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), Huang and Lau (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), Ghaderi et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), and Pradhan and Oh (2018) as shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and in many more studies also. These studies highlight the suitability of SEM techniques for theory testing and prediction in smart tourism contexts.\u003c/p\u003e\n \u003cp\u003eQuantitative cross-sectional survey designs also feature prominently, with researchers such as Chung, Tyan, and Han (2016), Kim et al. (2020), and Wang et al. (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) utilising structured questionnaires to capture tourists\u0026rsquo; perceptions and behavioural intentions at a single point in time. Such designs allow for efficient data collection from various tourist.\u003c/p\u003e\n \u003cp\u003eOnly few researches have adopted mixed-method research designs, combining quantitative surveys with qualitative interviews or content analysis to gain deeper insights into tourist experiences and sustainability outcomes (Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Buhalis \u0026amp; Sinarta, 2019). These approaches enrich empirical findings by integrating numerical data with contextual interpretations.\u003c/p\u003e\n \u003cp\u003eExperimental designs are primarily used in studies examining technology-mediated experiences, such as mobile applications, augmented reality, and proactive smartphone systems. Notable examples include Tussyadiah and Wang (\u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) and Bogicevic et al. (2019), who employed experimental manipulations to assess tourists\u0026rsquo; emotional and behavioural responses.\u003c/p\u003e\n \u003cp\u003eFinally, emerging research has begun to utilise big data analytics and computational methods, analysing large-scale user-generated content and digital footprints through techniques such as text mining and sentiment analysis. Studies by Lan et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Li et al. (\u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) demonstrate the growing relevance of data-driven approaches in capturing real-time and large-scale smart tourism experiences.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMethodological Distribution of Smart Tourism Experience Research\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMethodology\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRepresentative Citations\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurvey-based SEM / PLS-SEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTsang, N. K. F. (2024). Journal of Hospitality \u0026amp; Tourism Research; Lee, T. H., \u0026amp; Jan, F. H. (2023). Tourism Management; Huang, L., \u0026amp; Lau, N. (\u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Sustainability; Ghaderi, Z., et al. (\u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). Asia Pacific Journal of Tourism Research; Pradhan, M. K., \u0026amp; Oh, J. (2018). Sustainability.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eQuantitative cross-sectional survey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChung, N., Tyan, I., \u0026amp; Han, H. (2016). Journal of Travel Research; Kim, J., Lee, C. K., \u0026amp; Preis, M. W. (2020). Tourism Management; Wang, D., Xiang, Z., \u0026amp; Fesenmaier, D. R. (2016). Journal of Travel Research.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed-method research design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLee, T. H., \u0026amp; Jan, F. H. (2023). Sustainability; Buhalis, D., \u0026amp; Sinarta, Y. (2019). Journal of Travel Research.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExperimental design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTussyadiah, I. P., \u0026amp; Wang, D. (2016). Journal of Travel Research; Bogicevic, V., et al. (2019). Tourism Management.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBig data analytics / computational methods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLan, F. Y., et al. (2021). Frontiers in Psychology; Li, X., Pan, B., Law, R., \u0026amp; Huang, X. (2017). Tourism Management.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Research Approach Classification in Smart Tourism Experience Studies\u003c/h2\u003e\n \u003cp\u003eThe analysis of the selected articles on STE proves a dominant inclination toward empirical research as depicted in table (2). From the total articles which has been reviewed, 55 articles had employed empirical methodological approach, while 33 articles are theoretical or conceptual in nature. This distribution highlights several significant trends in the evolution of STE as a prominent construct for research.\u003c/p\u003e\n \u003cp\u003eFirst, the higher number of empirical researches proves a growing and emerging emphasis on data-driven investigation and real-world application of smart technologies within tourism contexts. These studies primarily focus on examining tourists\u0026rsquo; perceptions, behavioural intentions, satisfaction, engagement, and experience related results driven by the applications of smart technologies like mobile applications, augmented reality, Internet of Things (IoT), big data analytics, and artificial intelligence. The empirical dominance reflects the maturity of the field, where conceptual ideas are increasingly being tested and validated across diverse tourism settings.\u003c/p\u003e\n \u003cp\u003eIn literature the existence of 34 theoretical studies signifies the foundational role of conceptual development in STE research. These studies contribute by proposing conceptual frameworks, defining dimensions of smart tourism experiences, integrating interdisciplinary theories and identifying future research directions. However, their comparatively lower number symbolizes the requirement of further efforts for building theories, particularly to address the quickly evolving nature of smart technologies and tourist\u0026ndash;technology interactions.\u003c/p\u003e\n \u003cp\u003eThird, the imbalance between empirical and theoretical studies indicates that while researchers are actively measuring and modelling STE, theoretical consolidation remains limited. There is scope for developing integrative and unified theoretical models that can comprehensively explain the cognitive, emotional, and behavioural mechanisms underlying smart tourism experiences. Overall, the findings suggest that STE research is transitioning from a conceptual emergence phase to an empirical validation phase, yet future studies should aim to strengthen theoretical frameworks and adopt mixed-method approaches to achieve deeper and more holistic insights into smart tourism phenomena.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eResearch approach classification\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eResearch Approach\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo. of Articles\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmpirical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTheoretical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Journal Distribution of Smart Tourism Experience Research\u003c/h2\u003e\n \u003cp\u003eThe journal-wise analysis of the finally included articles in our review study on STE indicates a balanced yet interdisciplinary publication pattern across tourism and non-tourism journals which is being clearly represented with the help of table (3). In totally reviewed articles, 45 articles were published in tourism-focused journals, while 44 articles were published in non-tourism journals, indicating the cross-disciplinary nature of construct of STE.\u003c/p\u003e\n \u003cp\u003eWithin tourism journals, the journal Tourism emerges as the most prominent outlet, contributing nine articles, followed closely by Current Issues in Tourism (9) and Asia Pacific Journal of Tourism Research (8). Other leading tourism journals such as Tourism Management Perspectives (4), Tourism Management (3), and Annals of Tourism Research (3) also depicts the researcher\u0026rsquo;s interest in STE related research. Additionally, hospitality and marketing-oriented journals, including the Journal of Hospitality and Tourism Research, Journal of Travel and Tourism Marketing, and related outlets, reflect the emerging importance of smart technologies in enhancing tourist experiences and service encounters.\u003c/p\u003e\n \u003cp\u003eIn contrast, a substantial number of studies are published in non-tourism journals, highlighting the interdisciplinary foundations of STE. The journal Sustainability dominates this category with 20 articles, focussing on the strong linkage between smart tourism, sustainable development, and smart destinations. Other influential non-tourism outlets such as Journal of Travel Research (3), Frontiers in Psychology (2), and Service Industries Journal (2) indicate the integration of psychological, service, and consumer behaviour perspectives. Furthermore, publications in technology-oriented journals such as Information Systems Frontiers and Soft Computing underscore the role of digital technologies, data analytics, and intelligent systems in shaping STE.\u003c/p\u003e\n \u003cp\u003eOverall, the results indicates that STE related studies is not limited to traditional tourism and hospitality journals but is progressively disseminated across sustainability, psychology, service management, and information systems domains.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHere Journal-wise Distribution of Smart Tourism Experience Studies\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eJournal Name\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of Articles\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTourism Journals (45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTourism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent Issues in Tourism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsia Pacific Journal of Tourism Research\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTourism Management Perspectives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTourism Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnnals of Tourism Research\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJournal of Hospitality and Tourism Research\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJournal of Hospitality Tourism and Research\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJournal of Travel and Tourism Marketing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-Tourism Journals (44)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSustainability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJournal of Travel Research\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFrontiers in Psychology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eService Industries Journal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInformation Systems Frontiers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSoft Computing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJournal of Destination Marketing and Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6 Antecedents\u003c/h2\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.1 ICT infrastructure\u003c/strong\u003e in the context of STE serves as the basic technologies that integrates physical and digital components to enable creation of value through improved service in deliveries and enhanced personalization. It consists of comprehensive hardware such as servers, mobile devices, IoT sensors, and network equipment; software including CRM systems, PMS platforms, and cloud computing; and network connectivity like WiFi, 5G, and real-time synchronization protocols that ensure ubiquitous accessibility across all touchpoints. In initial or first stage of smart tourism evolution, ICT put emphasis on digital technology adoption, moving toward sustainable smart tourism development (SSTD) that combines ICT with environmental practices, and ultimately post-smart tourism destinations (PSTD) emphasizing local wisdom and humanistic approaches assisted by developed infrastructure such as cloud computing, IoT, and end-user devices(Cerd\u0026aacute;-Mansilla et al., 2024).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.2 Smart destination readiness\u003c/strong\u003e in smart tourism is defined as the destinations\u0026apos; preparedness with ICT infrastructures specially the IoT, AI, and big data for seamless, customized visitor experiences(Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). It comprises of traveller readiness via role clarity and capability, positively influencing ease of use and enjoyment in tools such as geotagging (Chung et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Core dimensions comprise of accessibility, enjoyment, protection, and interactivity, driving technology satisfaction and behavioural intentions of tourist and users, moderated by cultural differences (Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Effective readiness enables explorative (discovery) and exploitative (booking) uses, boosting travel satisfaction and sustainable co-creation (C. D. Huang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Gaps in readiness creates problems in adaptability, emphasizing governance, privacy safeguards, and introduction to sustainable smart tourism (P. Li, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.3Governance and institutional support\u003c/strong\u003e serve as important antecedents to STE by making of national policies and strategies, funding infrastructure, and multi-stakeholder platforms that enable ICT integration, big data analytics, and real-time service delivery, as exemplified by China\u0026apos;s National Tourism Administration (CNTA) through its 2011 smart tourism initiative and 2014 \u0026quot;Year of Smart Travel\u0026quot; campaign, which aligned with smart city investments exceeding 0.5 trillion Yuan by 2025 to build predictive platforms for traffic flow, customized suggestions and recommendations, and sharing of appropriate information among government bodies, organizations, residents, and tourists (Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), while ICT governance enhances the abilities of making decisions, innovation, and stakeholder knowledge distribution, directly enriching tourist perceptions of accessibility, enjoyment, and interactivity that foster biospheric values and site-specific environmentally suitable behaviours in destinations like Taiwan\u0026apos;s Yangmingshan and Sun-Moon-Lake national parks, ultimately enhancing destination competitiveness and sustainability despite challenges like diversified financing and regulatory requirements.(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) (Benkraiem et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.4 Tourist technology readiness (TR)\u003c/strong\u003e, defined as individuals\u0026apos; propensity to embrace and effectively use new technologies for reaching goals in work and home life through optimism (positive view of technology\u0026apos;s control/flexibility) and innovativeness (tendency to be a technology pioneer), serves as a key antecedent to smart tourism experiences (STE) by predisposing tourists to perceive smart technologies as useful and easy to use, thereby enhancing their overall STE dimensions like aesthetics, hedonic enjoyment, learning, and trust(Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) In AR heritage contexts, TR positively influences perceived usefulness of AR applications, leading to favourable attitudes toward AR usage and destination revisit intentions via the Technology Readiness and Acceptance Model (TRAM), as tourists with high TR (optimism/innovativeness) are more prepared to adopt AR for enriched experiences(Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).TR\u0026apos;s role in smart tourism/STT adoption indirectly through technology acceptance frameworks, noting tourists\u0026apos; readiness affects STE attributes (e.g., interactivity, personalization) and outcomes like satisfaction/loyalty in US smart cities and nature-based destinations(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)(X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) highlights TR implicitly via emotional arousal moderating AI technologies\u0026apos; impact on STE, where tech-ready tourists better engage with interaction/personalization/co-creation/privacy features for superior smart experiences.(X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) (Femenia-Serra, Neuhofer, et al., 2019)conceptualizes \u0026quot;smart tourists\u0026quot; as those with high TR who share data, use STs intensively, and co-create via smart ecosystems, positioning TR as foundational for dynamic STE in smart destinations(Femenia-Serra, Neuhofer, et al., 2019). Studies have shown domestic traveller\u0026rsquo;s TR directly predicts STT satisfaction/behavioural intentions, underscoring TR as a precondition for positive STE across cultures(Shin et al., \u003cspan class=\"CitationRef\"\u003e2023a\u003c/span\u003e)(Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) lacks explicit TR mention but aligns with readiness influencing STE via tech adoption barriers. (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.5 Digital literacy\u003c/strong\u003e is defined as the ability to efficiently access, evaluate, prominently assess, and creatively utilize digital technologies, platforms, and information to navigate, customize, and co-create enriched experiences within smart tourism ecosystems(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)(Femenia-Serra, Neuhofer, et al., 2019). This encompasses foundational ICT skills such as smartphone/app operation, AR/VR interfaces, IoT sensor interaction, and location-based services, alongside higher-order capabilities including data credibility evaluation, privacy/security management, real-time information synthesis, and dynamic stakeholder co-creation through Smart Tourism Technologies (STTs)(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)(Femenia-Serra, Neuhofer, et al., 2019)(Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). In smart tourism contexts, digitally literate tourists demonstrate high STT familiarity (average 5\u0026ndash;6 technologies used, 95% smartphone adoption), enabling them to leverage key STT attributes\u0026mdash;informativeness (\u0026beta;\u0026thinsp;=\u0026thinsp;0.22), interactivity (\u0026beta;\u0026thinsp;=\u0026thinsp;0.53), and personalization (\u0026beta;\u0026thinsp;=\u0026thinsp;0.28)\u0026mdash;to transform passive technology exposure into memorable smart tourism experiences (STEs)(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Femenia-Serra et al. conceptualize these individuals as \u0026quot;smart tourists\u0026quot; who exhibit trust in intelligent systems, willingly share personal data for hyper-personalized services despite privacy concerns, and actively participate in IoT-enabled, ubiquitous connectivity ecosystems (Femenia-Serra, Neuhofer, et al., 2019). Additional evidence reinforces this antecedent role: skills gaps block big data/IoT value co-creation (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e); literacy prevents information overload in nature-based STE contexts(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) ; digital proficiency predicts cross-country STT satisfaction and loyalty (Shin et al., \u003cspan class=\"CitationRef\"\u003e2023a\u003c/span\u003e); and literacy activates AI-driven personalization pathways moderated by emotional arousal(X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). Thus, digital literacy bridges robust ICT infrastructure with tourist agency, enabling the full realization of smart tourism\u0026apos;s experiential promise across all touchpoints.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.6 Perceived usefulness (PU)\u003c/strong\u003e in smart tourism refers to tourists \u0026lsquo;perceptions that Smart Tourism Technologies (STTs) like AI chatbots, IoT parking systems, VR headsets, and ubiquitous information services improves the efficiency of travellers, customization, convenience, and overall experience quality, serving as a major TAM antecedent driving technology adoption, satisfaction, and memorable STE (Ionescu \u0026amp; S\u0026acirc;rbu, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). PU significantly predicts satisfaction (\u0026beta;\u0026thinsp;=\u0026thinsp;0.168, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) across tourist segments with highest ratings for AI (4.70) and IoT (4.30), differ by areas (Transylvania AI\u0026thinsp;=\u0026thinsp;4.80) and enhancing the revisit intentions (\u0026chi;\u0026sup2;=46.83, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)(Ionescu \u0026amp; S\u0026acirc;rbu, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).(Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)conceptualizes PU through \u0026quot;smart\u0026quot; ubiquitous information services (cloud/IoT integration) enabling anytime/anywhere personalized navigation and co-creation, revolutionizing passive tourism into autonomous, value-added STEs beyond traditional services (Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)embeds PU within smart destination ecosystems (big data, AR/VR) where it moderates technology-heritage fusion, driving tourist satisfaction, loyalty, and sustainable experiential value in cultural contexts .\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.7 Trust \u0026amp; Security Perception\u003c/strong\u003e in smart tourism context is defined as the tourists\u0026apos; confidence in the reliability, privacy protection, and data safety of Smart Tourism Technologies (STTs), acting as a prominent moderator that promotes positive engagement with technology ecosystems while mitigating risks of data breaches and privacy violations to facilitate memorable STEs(Cerd\u0026aacute;-Mansilla et al., 2024). Trust and security perceptions are very crucial for all types of stakeholder collaboration in smart destinations, where DMO should ensure transparency in handling information and data to build mutual confidence among tourists/locals, preventing exclusion from smart services (Cerd\u0026aacute;-Mansilla et al., 2024)emphasizes blockchain/edge computing for privacy-preserved data in big data tourism platforms, positioning trust as foundational for secure IoT/cloud interactions enabling personalized services(Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)(Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) highlights metaverse tourism\u0026apos;s privacy related problems from cross-border data flows, indicating need for trust mechanisms to secure financial/personal data during VR/AR experiences(Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) identifies security as metaverse barriers, with propositions for secure avatars and blockchain to foster immersive STEs without any risks .\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.8 Spatiotemporal behaviours\u003c/strong\u003e refer to the comprehensive travel characteristics derived from users\u0026apos; digital footprints captured through geotagged Flickr photographs, representing their \u0026quot;photo trail\u0026quot; across urban destinations. These behaviours integrate spatial dimensions\u0026mdash;geographic coordinates of photos map-matched to street networks\u0026mdash;and temporal dimensions\u0026mdash;sequential timestamps of photo captures\u0026mdash;to reconstruct complete travel trajectories(Mor et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Spatiotemporal behaviours refer to the comprehensive travel characteristics derived from users\u0026apos; digital footprints captured through geotagged Flickr photographs, representing their \u0026quot;photo trail\u0026quot; across urban destinations. These behaviours integrate spatial dimensions\u0026mdash;geographic coordinates of photos map-matched to street networks\u0026mdash;and temporal dimensions\u0026mdash;sequential timestamps of photo captures\u0026mdash;to reconstruct complete travel trajectories (Liu et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Dom\u0026egrave;nech et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.9 Urban morphology\u003c/strong\u003e describes the physical street network structure of cities that shapes tourist movement patterns, analyzed through graph theory centrality measures (closeness and betweenness) derived from OpenStreetMap data, with photo geolocations map-matched to network segments. Urban morphology describes the physical street network structure of cities that shapes tourist movement patterns, analyzed through graph theory centrality measures (closeness and betweenness) derived from OpenStreetMap data, with photo geolocations map-matched to network segments (Crucitti et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Porta et al., \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Boeing, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.6.10 Tourism Empowerment\u003c/strong\u003e in the context of smart tourism experience refers to the process through which tourists can attain significant control, competence, and confidence over their travel decisions and experiences through the application of smart tourism technologies, which provide real-time information, customization, and better interactive experience that improves autonomy and purposeful engagement at smart destinations (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Smart tourism experiences empower tourists by enabling easy access to reliable, context-aware, and location-based information, giving them access to plan itineraries, navigate destinations effectively, and taking better decisions that improve convenience and satisfaction during all phases of travel(Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Through attributes like accessibility, informativeness, interactivity, and personalization, smart tourism technologies facilitate tourists\u0026rsquo; active participation and co-creation of experiences, shifting tourists from passive customers to empowered actors who shape their own experiences in real time (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Empowerment is further strengthened as smart tourism experiences foster learning, aesthetic appreciation, and hedonic enjoyment, which enhance tourists\u0026rsquo; cognitive and emotional engagement and deepen their understanding of destinations and local environments(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). In nature-based and sustainable tourism contexts, empowered tourists develop stronger biospheric values through technology-mediated learning and interpretation, which increases their sense of responsibility and ability to act in environmentally responsible ways. Moreover, trust, security, and privacy embedded in smart tourism systems are critical to empowerment, as tourists are more willing to share data and rely on smart services when they perceive platforms as secure and trustworthy, thereby reinforcing confidence and independence in decision-making(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Overall, smart tourism experience empowers tourists by integrating technological support, experiential enrichment, and learning opportunities, enabling them to actively control their journeys, co-create value, and engage more responsibly and meaningfully with destinations (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eThe list of prominent antecedents identified in review of literature is depicted in table (4) below-\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eAntecedents of STE\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAntecedent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCitation of prominent Authors\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eICT Infrastructure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (L. Huang \u0026amp; Lau, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Lim et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Kusumastuti et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), p15, (Cerd\u0026aacute;-Mansilla et al., 2024), (Neuhofer et al., 2015),(S. X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (P. Lee et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Ivars-Baidal et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmart Destination Readiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Chung et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) ,(C. D. Huang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e),(P. Lee et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Ivars-Baidal et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), (X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGovernance \u0026amp; Institutional Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), (Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Ionescu \u0026amp; S\u0026acirc;rbu, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Cham et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Jovicic, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e),(P. Lee et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTourist Technology Readiness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Fang et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Zhu et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Shin et al., \u003cspan class=\"CitationRef\"\u003e2023a\u003c/span\u003e), (Femenia-Serra, Neuhofer, et al., 2019), (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDigital Literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Chung et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Neuhofer et al., 2015), (Nguyen et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e),(Femenia-Serra, Neuhofer, et al., 2019),(Stankov et al., 2025) (S. X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived Usefulness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(L. Huang \u0026amp; Lau, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), p8, (Kusumastuti et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Ionescu \u0026amp; S\u0026acirc;rbu, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Nguyen et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), p,(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrust \u0026amp; Security Perception\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e),(Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e),(Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Cerd\u0026aacute;-Mansilla et al., 2024),(C. D. Huang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e),(S. X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Gretzel \u0026amp; Koo, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStakeholder Collaboration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e),(Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Neuhofer et al., 2015), (X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Shin et al., \u003cspan class=\"CitationRef\"\u003e2023a\u003c/span\u003e), (P. Lee et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Ivars-Baidal et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo-creation Orientation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTourist Empowerment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e),(Fang et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Zhu et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Shin et al., \u003cspan class=\"CitationRef\"\u003e2023a\u003c/span\u003e), (Femenia-Serra, Neuhofer, et al., 2019)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInnovation Orientation of Destination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Chung et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e),(Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Cerd\u0026aacute;-Mansilla et al., 2024),(C. D. Huang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (S. X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (P. Lee et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegulatory \u0026amp; Policy Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Neuhofer et al., 2015), p25, (Cham et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Jovicic, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e) (Jovicic, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), (Behera et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOrganizational Readiness of Tourism Firms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Ionescu \u0026amp; S\u0026acirc;rbu, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Behera et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Femenia-Serra \u0026amp; Ivars-Baidal, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003espatiotemporal behaviours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Mor et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban morphology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Mor et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.7 Technological Dimensions\u003c/h2\u003e\n \u003cp\u003eThe list of prominent Technological dimensions identified in review of literature is depicted in table (5) below-\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDimensions of STE\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTechnological Dimension\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCitation of prominent Authors\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePersonalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e),(Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Kusumastuti et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) (Neuhofer et al., 2015), (S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Femenia-Serra, Neuhofer, et al., 2019), (Stankov et al., 2025), (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) ,(Cuesta-Vali\u0026ntilde;o et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Balakrishnan et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eInformativeness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Afolabi et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), (Azis et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Balakrishnan et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInteractivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Chung et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e),(Lim et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Ionescu \u0026amp; S\u0026acirc;rbu, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Cham et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Femenia-Serra, Neuhofer, et al., 2019), (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)(Balakrishnan et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReal-time data services/ Real \u0026ndash; time information systems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(L. Huang \u0026amp; Lau, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Cerd\u0026aacute;-Mansilla et al., 2024),(C. D. Huang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e),(S. X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Nguyen et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Ivars-Baidal et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), (Cimbaljević et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e) ,(Cuesta-Vali\u0026ntilde;o et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Shen, Sotiriadis, \u0026amp; Zhou, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eContext Awareness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), (Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Fang et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) ,(Zhu et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Shin et al., \u003cspan class=\"CitationRef\"\u003e2023a\u003c/span\u003e), (Jovicic, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e),(Femenia-Serra, Neuhofer, et al., 2019),(Stankov et al., 2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConnectivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Chung et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Lim et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e),(Kusumastuti et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Neuhofer et al., 2015),(S. X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (P. Lee et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Ivars-Baidal et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUbiquity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAI-based Intelligence / Automation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(L. Huang \u0026amp; Lau, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e),(Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) ,(Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Ionescu \u0026amp; S\u0026acirc;rbu, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) ,(P. Li, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Pai et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Wu et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Stankov et al., 2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImmersive Technologies (AR/VR/XR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Zhu et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), p25, (Shin et al., \u003cspan class=\"CitationRef\"\u003e2023a\u003c/span\u003e),(Jovicic, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e), (Stankov et al., 2025),(Stankov et al., 2025),(Behera et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Gonz\u0026aacute;lez-Rodr\u0026iacute;guez et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Paliwal et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Pradhan et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), (Tribe \u0026amp; Mkono, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)(Tribe \u0026amp; Mkono, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eData Integration / Big Data Analytics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep3, (Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Fang et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Neuhofer et al., 2015), (X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Cham et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Pai et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Wu et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Ivars-Baidal et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e),(Kou et al., 2024),(Santos-J\u0026uacute;nior et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Khan et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e),(Mandić \u0026amp; Kennell, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e),(Encalada et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e),(Pradhan et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), (Lan et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), (Bastidas-Manzano et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), (Shen, Sotiriadis, \u0026amp; Zhang, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccessibility Technologies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Lim et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Kusumastuti et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Cerd\u0026aacute;-Mansilla et al., 2024), (C. D. Huang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), p28,(Nguyen et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), (Gretzel \u0026amp; Koo, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e), (Zhang et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Ivars-Baidal et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e),(Balakrishnan et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) ,(Uysal et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmart Interfaces / Mobile Applications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (L. Huang \u0026amp; Lau, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e), (Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Ionescu \u0026amp; S\u0026acirc;rbu, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e) ,(Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e), (Cham et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Femenia-Serra, Neuhofer, et al., 2019), (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),, (Shen, Sotiriadis, \u0026amp; Zhang, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) ,(da Costa Liberato et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e)1,(Huertas et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) ,(P. Lee et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) ,(Gajdo\u0026scaron;\u0026iacute;k, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Nolich et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e),(Anaya \u0026amp; Lehto, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Stankov \u0026amp; Filimonau, 2019),(Gelter et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) ,(M. Lee, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e), (Tussyadiah \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e), (Ghaderi et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) ,(Neuhofer et al., 2015) ,(C. D. Huang et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e),(Femenia-Serra, Perles-Ribes, et al., 2019),(Lamsfus et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhygital Experience Enablement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Zhu et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (S. X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Pai et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e),(Stankov et al., 2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVirtual Platforms / Metaverse Technologies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(Shin et al., \u003cspan class=\"CitationRef\"\u003e2023a\u003c/span\u003e), (Jovicic, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e),(Gretzel \u0026amp; Koo, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e),(Behera et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (S. Lee et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.1 Personalization\u003c/strong\u003e is used to define the extent of information which smart tourism technologies provide to ensure satisfaction of tourists in planning the requirements of personal trips(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Personalization in smart tourism significantly enhances travellers\u0026apos; memorable experiences by delivering tailored, interactive services that align with individual preferences, outperforming mere accessibility(Shin et al., \u003cspan class=\"CitationRef\"\u003e2023b\u003c/span\u003e). Personalisation of STT has a positive relationship with tourists STT experience at heritage sites. Co-created tourism experiences through demand-supply interactions elevate quality of life by integrating physical settings with relational assets for diverse travellers(Balakrishnan et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u0026quot;Designing tourism experiences that enhance one\u0026rsquo;s quality of life implies designing for diversity of the travelling population.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.2 Informativeness\u003c/strong\u003e in the smart tourism experience refers to the ability of smart technologies to provide accurate, timely, credible, and comprehensive information that supports tourists\u0026rsquo; decision-making before and during travel (Azis et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Through digital platforms, AR/VR, and mobile applications, informativeness reduces uncertainty, enhances experience quality, and enables value co-creation, leading to higher satisfaction and positive behavioural outcomes (Afolabi et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) (H. Lee et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.3 Ubiquity\u003c/strong\u003e in context of STE refers to the omnipresent availability of customized tourism information and services across time, space, media, and devices, enabling tourists to acquire seamless and real- time experiences which provides support system throughout the entire travelling journey. This ubiquitous information service composed of the vital essence of smart tourism (Y. Li et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.5 Real-time information systems\u003c/strong\u003e in smart tourism deliver instantaneous data on traffic, weather, and events through apps like Google Maps and city guides, which assist thetraellers and users to take well planned decisions during their process of travelling (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). These platforms improve the experiences by giving live updates that decreases the stress related to travels and optimizing their travelling routes in smart destinations(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). They merge and combine IoT sensors and mobile connectivity to provide dynamic tourist data, assisting customized navigation and activity planning within the smart tourism ecosystem(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).Real-time abilities from ubiquitous computing enable seamless interaction between tourists and destinations, fostering context-aware engagements.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.6 Context awareness\u003c/strong\u003e in smart tourism experience refers to the capability of smart tourism systems to sense, interpret, and respond to tourists\u0026rsquo; real-time situations by integrating location awareness, time awareness, personalisation awareness, and environmental\u0026ndash;situational awareness. Through this integration, smart systems deliver location-specific services, time-sensitive information, personalised recommendations, and contextually relevant guidance, enabling adaptive, meaningful, and immersive tourism experiences throughout the travel journey(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e)(Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.7 Connectivity\u003c/strong\u003e in smart tourism experience refers to the seamless digital linkage among tourists, destinations, service providers, and smart technologies through interconnected networks that enable continuous information exchange and service integration (Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). It allows tourists to remain constantly connected to tourism services, platforms, and other stakeholders via mobile devices and networked infrastructures, facilitating real-time access to information and support throughout the travel journey(Neuhofer et al., 2015). Connectivity also enables the integration of heterogeneous systems and stakeholders within a destination, supporting coordinated service delivery, co-creation of experiences, and enhanced interaction between tourists and smart tourism ecosystems (S. X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.8 AI-based intelligence\u003c/strong\u003e in smart tourism enhances experiences through technologies like artificial intelligence (AI), enabling intelligent services, expert systems, decision aids, and automatic agents for personalized recommendations and real-time interactions (Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). It powers metaverse tourism via computer vision for object/face recognition, body tracking, and scene understanding, alongside data science for cooperative work support and digital twins for monitoring/prognostics, creating immersive virtual-real blends across imitation (VR replicas), intensification (AR overlays), interaction (MR exchanges), and integration (seamless synthetic universes) (Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) Big data integration with AI processes massive tourism data from tourists/devices/operations for predictive analytics, traffic forecasting, and personalized services like route optimization and demand analysis.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.9 Big data analytics\u003c/strong\u003e in smart tourism experience refers to the systematic collection, processing, and analysis of large volumes of heterogeneous data generated by tourists, destinations, and smart technologies to understand tourist behaviour and preferences. It enables smart tourism systems to transform real-time and historical data into actionable insights that support personalised recommendations, adaptive services, and experience co-creation(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Through big data analytics, destinations can enhance decision-making, predict tourist needs, optimise service delivery, and continuously improve experiential value by aligning tourism offerings with tourists\u0026rsquo; contextual and behavioural patterns (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.10 Immersive technologies\u003c/strong\u003e in smart tourism experiences refers to advanced tools like augmented reality (AR), virtual reality (VR), and mixed reality (MR) enhanced by AI, which create engaging, personalized interactions that boost tourist satisfaction, perceived value, and loyalty through dimensions such as enjoyment and immersion. In one of the study conducted by, Abou-Shouk et al. (2024) note that perceived ease of use, enjoyment, immersion, usefulness, and attitude toward technology predict immersive technology adoption, positively affecting tourists\u0026apos; perceived value, engagement, satisfaction, and loyalty in tourism contexts. Similarly, Holdack et al. (2020) highlight how the fun and immersive features of smart technologies, including AR tours and gamified experiences, increase engagement and satisfaction.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.11 Accessibility\u003c/strong\u003e represents the extent to which a tourist finds the information offered at the destination accessible using smart tourism technologies, informativeness represents the extent to which smart tourism technologies provide accurate and sincere information; inter activity represents the extent to which a tourist engages in reciprocal communication with other stakeholders via smart tourism technologies.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.12 Phygital Experience\u003c/strong\u003e -Enablement in smart tourism refers to the seamless fusion of physical and virtual realms, primarily through Metaverse technologies that create immersive \u0026quot;Phygital experiences\u0026quot; allowing tourists to traverse between physical heritage sites and their virtual counterparts(S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). This integration leverages AR, VR, MR, and AI to augment real-world visits with digital overlays\u0026mdash;such as virtual guides delivering context-aware narratives or historical recreations\u0026mdash;while enabling pre-travel virtual tours that build realistic expectations and post-travel virtual returns for deeper engagement (S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). In the context of smart tourism experiences, it transforms heritage destinations by boosting brand equity via entertainment, interaction, trendiness, novelty, and intimacy in Metaverse environments (Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). These phygital elements address challenges like authenticity preservation and overtourism by dispersing crowds through virtual alternatives, as seen in examples like Tencent\u0026apos;s MR/3D cultural immersions or VR heritage recreations, ultimately driving physical visits through heightened spatial presence quality and perceived augmentation (Natarajan et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)(S. Jia et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003e\u003cstrong\u003e3.7.13 Virtual platforms and metaverse technologies\u003c/strong\u003e in smart tourism integrate AR, VR and mobile platforms to create immersive, connected and interactive tourist experiences within smart tourism cities(Gretzel \u0026amp; Koo, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). They link physical places with virtual content through QR codes and VR services, enabling realistic destination experiences even without travel and enriching on-site visits(Gretzel \u0026amp; Koo, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). Such platforms also support virtual tours and tourist\u0026ndash;resident interactions beyond physical boundaries (Gretzel \u0026amp; Koo, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). These smart technologies act as supporting products that enhance interactivity, personalization and memorability of tourism experiences (Shen, Sotiriadis, \u0026amp; Zhou, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003c/span\u003e\n \u003ch2\u003e3.8 Outcomes of Smart Tourism Experience\u003c/h2\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003cp\u003eThe literature review of articles of STE generates a wide variety of tourist-centric, destination-level, and societal outcomes, with most evidence pointing to beneficial impacts and outcomes, alongside emerging concerns. A dominant positive result is tourist satisfaction and experience quality, repeatedly confirmed across empirical studies. For example, (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),Some studies report that smart technologies such as mobile apps, IoT-enabled services, and real-time information prominently improve the perceived quality of tourism experiences and satisfaction, generally mediated by perceived usefulness and enjoyment(Cerd\u0026aacute;-Mansilla et al., 2024). Empirical results in (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) (Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e) show strong positive relationship coefficients between STE and satisfaction, depicting that smartness has direct impact on enhancing tourists\u0026rsquo; affective evaluations of their journeys. Closely related is perceived value and positive attitude, where some studies have clearly indicated that functional, emotional, and epistemic values derived from smart services significantly shape favourable attitudes toward smart destinations and platforms(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e) (L. Huang \u0026amp; Lau, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe most prominent and importantly supported outcome is behavioural intention, consisting of revisit intention, loyalty, and positive word-of-mouth. Studies which are empirically conducted demonstrated that higher levels of STE essentially predict revisit intention and recommendation behaviour, with satisfaction and destination image acting as mediators (Zhu et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Similarly, some studies proves that improvements in destination image and smart destination brand equity, suggests the technologically enriched experiences strengthen tourists\u0026rsquo; cognitive and affective images of destinations(Neuhofer et al., 2015). Empirical evidence shows that perceived smartness has positive impact on outcomes of destination attachment and loyalty intentions(Neuhofer et al., 2015).\u003c/p\u003e\n \u003cp\u003eSeveral studies emphasize personalization, immersion, and co-creation as experiential outcomes enabled by AI, big data, and AR/VR. Some studies argue that smart systems facilitate tailored itineraries and interactive content, which enhance engagement and tourists\u0026rsquo; sense of co-creating value(X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Empirical findings indicate that personalization significantly increases engagement and hedonic value, which in turn boost satisfaction(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). This aligns with service-dominant logic, where tourists become active participants rather than passive consumers.\u003c/p\u003e\n \u003cp\u003eBeyond individual tourists, STE also generates organizational and destination performance outcomes. Some studies report improved service efficiency, operational effectiveness, and decision-making quality for tourism providers through real-time data analytics and smart infrastructure(Yang \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e). At the macro level show that STE supports sustainable tourism development, better crowd management, energy efficiency, and optimized resource use(Kusumastuti et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e) (Shen, Sotiriadis, \u0026amp; Zhou, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Empirical results suggest that smart technologies have a significant positive effect on perceived sustainability performance of destinations(Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Further, reiew provides evidence that smart services enhance accessibility and inclusiveness, improving experience quality for elderly and disabled tourists, thereby contributing to residents\u0026rsquo; and visitors\u0026rsquo; quality of life.\u003c/p\u003e\n \u003cp\u003eHowever, despite these benefits, the literature also identifies negative and paradoxical outcomes of STE. One of the studies reveals that excessive technology mediation may reduce existential authenticity, mindfulness, and emotional immersion, as tourists become more screen-focused than place-focused(Tribe \u0026amp; Mkono, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Empirical results show a negative relationship between technology intensity and perceived authenticity(Tribe \u0026amp; Mkono, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Similarly, (Tussyadiah \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e) some authors argues that algorithm-driven recommendations, while improving efficiency and convenience, can limit serendipity, exploration, and experiential learning, potentially standardizing tourist experiences.\u003c/p\u003e\n \u003cp\u003eIssues of privacy risk, security concerns, and technostress are highlighted in(Pradhan et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e) in some studies. These studies empirically show that perceived risk and digital fatigue have significant negative effects on trust and, indirectly, on satisfaction and usage intention, even when the overall utility of smart systems remains high. One of the studies further reports symptoms of over-dependence on smart devices, leading to cognitive overload and reduced enjoyment at certain stages of the journey(Anaya \u0026amp; Lehto, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). These findings suggest a \u0026ldquo;double-edged sword\u0026rdquo; effect of smartness in tourism experiences.\u003c/p\u003e\n \u003cp\u003eOverall, the empirical evidence across the reviewed papers confirms that STE leads to higher satisfaction, perceived value, positive attitudes, loyalty intentions, destination image, personalization, co-creation, efficiency, and sustainability outcomes (Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e), (Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Zhu et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Neuhofer et al., 2015) ,(X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e)(Chung et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). At the same time, studies caution against unintended consequences such as loss of authenticity, reduced mindfulness, privacy concerns, technostress, and diminished serendipity (Tribe \u0026amp; Mkono, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)(Tussyadiah \u0026amp; Wang, \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e),(Pradhan et al., \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), (Anaya \u0026amp; Lehto, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). These mixed outcomes indicate that while smart tourism technologies substantially enrich tourist experiences, their design and implementation must balance technological augmentation with human-centered, ethical, and experiential considerations to ensure long-term value creation.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e3.9 Mediators identified in the Study\u003c/h2\u003e\n \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\n \u003ch2\u003e3.9.1. User Engagement\u003c/h2\u003e\n \u003cp\u003eIn one of the study, user engagement is depicted as a vital psychological mechanism through which Metaverse-based smart tourism dimensions (e.g., immersion, social interaction, personalization) which impacts on tourists\u0026rsquo; experience quality and behavioural responses. The study explains that engagement shows a true picture of tourists\u0026rsquo; active participation, interaction, and involvement in virtual and digital environments, which in turn improves the perceived experience and value co-creation. Although, in a literature review, it clearly pointed out that user engagement serves as a mediator linking Metaverse affordances to results like enhanced experience, satisfaction, and intention of usage.(Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\n \u003ch2\u003e3.9.2. Digital Immersion\u003c/h2\u003e\n \u003cp\u003eThe study byZ. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e has also provided with the framework of digital immersion as a mechanism through which VR/AR-driven smart destination digital environments affect tourists\u0026rsquo; emotions and experience related outcomes. Immersion explains how technological realism and presence translate into stronger experiential impact, making it a mediating experiential state between smart technologies and tourists\u0026rsquo; evaluations.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e\n \u003ch2\u003e3.9.3. Social Interaction\u003c/h2\u003e\n \u003cp\u003eSocial interaction on digital and social media platforms is discussed as another and significant mediating pathway. The study argues that smart platforms enable interaction beyond physical boundaries or barriers, which fosters community feeling and co-creation, thereby improving the overall STE and outcomes related to it.(Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e\n \u003ch2\u003e3.9.4. Personalization\u003c/h2\u003e\n \u003cp\u003eThe review emphasizes personalized experiences enabled by AI and data analytics as a mechanism translating smart system capabilities into higher satisfaction and perceived value. Personalization operates as a mediator by aligning services with tourists\u0026rsquo; preferences, thereby improving experience outcomes.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\n \u003ch2\u003e3.9.5. Perceived Enjoyment\u003c/h2\u003e\n \u003cp\u003eOne of the studies which quantitatively analyses the STE, perceived enjoyment and experiential value are modelled as mediators between smart technology attributes and dimensions (e.g., interactivity, vividness) and behavioural intentions such as revisit or recommendation(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). The findings show that smart features significantly enhance enjoyment, which in turn drives favourable intentions confirming a mediating effect.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e\n \u003ch2\u003e3.9.6. Co-creation\u003c/h2\u003e\n \u003cp\u003eFocusing on smart tourism and technology driven co-creation, level of tourist involvement and value co-creation are considered as mediators linking smart service design with outcomes such as satisfaction, loyalty, and memorable experiences. The empirical results indicate that smart features significantly increase engagement, which then enhances experience-related outcomes(X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\n \u003ch2\u003e3.9.7. Satisfaction\u003c/h2\u003e\n \u003cp\u003eSome Studies empirically gives assistance to tourist or users satisfaction as a core mediator. Smart or immersive experience dimensions positively influence satisfaction, which subsequently drives behavioural intentions such as revisit intention and word-of-mouth. Satisfaction thus explains how experience perceptions are converted into post-consumption behaviours.(X. Chen et al., \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e) (Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\n \u003ch2\u003e3.10 Major Research Gaps identified through Literature review and suggested Future Directions\u003c/h2\u003e\n \u003cp\u003eThe literature review on smart tourism reveals critical research gaps categorized into contextual, methodological, behavioural, theoretical, and technological types, limiting the field\u0026apos;s maturation and practical application. Contextual gaps are related to the underexplored settings and integrations, such as lack of cross-cultural and longitudinal studies that are not capable enough tp acquire and examine diverse tourist behaviours across global destinations (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). For example-one study has clearly pointed out the absence of traveller-centric research in varied geographic and cultural contexts, while one of the study notes limited holistic stakeholder perspectives including locals and managers beyond tourist views(Cerd\u0026aacute;-Mansilla et al., 2024). Methodological gaps include overreliance on cross-sectional surveys and self-reported data via PLS-SEM, lacking mixed-methods, experimental designs, or longitudinal tracking of adoption evolution(Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e) (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e)specifically critiques the scarcity of empirical validation for antecedents like ICT infrastructure and learning orientation, with inadequate scale development across destinations. Behavioural gaps focus on unexamined psychological and post-adoption dynamics, such as hedonic motivations, emotional mediators, technology attachment, authenticity perceptions, and environmentally responsible behaviours(Fang et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e)(Chung et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). Studies like (Tsang \u0026amp; Au, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), and (L. Huang \u0026amp; Lau, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) identify shortcomings in linking user readiness to long-term outcomes like continued usage and loyalty. Theoretical gaps involve fragmented frameworks, with overemphasis on technology acceptance models (TAM) without integrating socio-technical systems, sustainability theories, or multi-stakeholder value co-creation (Lim et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)(Gretzel et al., \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Some of the studies underscore the need for unified models incorporating psychological well-being and governance structures(Jeong \u0026amp; Shin, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Technological gaps highlight underexplored emerging innovations, including AI-driven analytics, IoT integration, metaverse platforms, big data for sustainability, and their ethical/privacy implications (Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e),(Q. Jia et al., \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e) points to immature monitoring systems and heterogeneous data fusion in smart platforms.\u003c/p\u003e\n \u003cp\u003eThese gaps collectively impede robust theory-building and evidence-based smart tourism implementation. Addressing them requires strategic future directions to advance scholarly and practical contributions.\u003c/p\u003e\n \u003cp\u003eFuture research should prioritize longitudinal, multi-country empirical studies using mixed-methods to validate smart tourism scales and track technology adoption trajectories across developing and developed economies, directly responding to methodological and contextual gaps in (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Scholars must integrate behavioural dimensions through traveller-centric designs, examining hedonic experiences, emotional involvement, authenticity, and post-adoption sustainability via advanced mediators like value co-creation and immersion(Chung et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e) (T. H. Lee \u0026amp; Jan, \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e),(Fang et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Theoretical advancements can emerge from interdisciplinary frameworks blending TAM with socio-technical systems theory and circular economy models, incorporating stakeholder views for holistic ecosystems as suggested in some studies (Lim et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e)(Cerd\u0026aacute;-Mansilla et al., 2024). Technological explorations should focus on generative AI, IoT-big data synergies metaverse-virtual-real integrations, and blockchain for privacy governance, with ethical audits and digital divide assessments in underrepresented contexts (Diaz et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), (Z. Chen, \u003cspan class=\"CitationRef\"\u003e2025\u003c/span\u003e),(Suanpang \u0026amp; Pothipassa, \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Comparative analyses of smart versus traditional tourism, including subsector-specific applications (e.g., heritage sites, night tourism), will bridge some studies gaps(Zhu et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Experimental designs testing AR/VR interventions and qualitative inquiries into FOMO moderation or avatar behaviours can enrich future studies insights. Policymakers and practitioners should collaborate on pilot implementations in smart destinations, evaluating long-term impacts on loyalty, WOM, and low-carbon outcomes. By pursuing these directions, researchers can transform smart tourism from technology-centric to human-centred, sustainable paradigms, fostering inclusivity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\n \u003ch2\u003e3.11 Other findings\u003c/h2\u003e\n \u003cp\u003eThe study explains that smart tourism experience is shaped by multiple types of intelligence embedded within destination systems, collectively enhancing how tourists perceive and interact with smart destinations. Swarm intelligence enables different technological systems to work collaboratively, creating seamless and integrated services that improve overall travel fluidity and coordination. Sensory intelligence allows destinations to sense tourists and environmental conditions through sensors and tracking technologies, enabling real-time awareness of location, crowd levels, and situational contexts that support smoother navigation and management. Communication intelligence enhances smart tourism experiences by delivering timely, proactive, and relevant information to tourists, reducing uncertainty and cognitive effort during travel. Empathetic intelligence strengthens the experiential dimension by allowing systems to recognize tourists\u0026rsquo; needs and emotions, offering personalized and context-sensitive responses that create a more humanized and supportive experience. Learning intelligence enables destinations to adapt and improve over time by analysing accumulated tourist data, leading to increasingly accurate recommendations and personalized services that evolve with repeated use. Mechanical intelligence supports smart tourism by automating routine service tasks, improving efficiency and convenience, although its perceived smartness may decline as automation becomes commonplace. Reactive intelligence ensures immediate system responses to real-time changes in tourist context, such as language preferences or environmental conditions, reinforcing perceptions of responsiveness and adaptability. Finally, memory intelligence underpins personalization and long-term service optimization by storing and retrieving tourist data, while simultaneously highlighting the importance of trust, privacy, and secure data governance in sustaining positive smart tourism experiences(Au \u0026amp; Tsang, 2022).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4. Implications of the Study","content":"\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Theoretical Implications\u003c/h2\u003e \u003cp\u003eIn line with the research question on conceptual and thematic ground, the current study contributes to the theory by elucidating smart tourism experience to be more of an intelligence-driven and experience-based phenomenon instead of being merely a technology formation. As its results underline, smart tourism experience is a result of interacting between technological infrastructures (e.g., sensing, communication, learning and memory intelligence) and cognitive, emotional, and behavioral involvement of tourists. The synthesis of major themes like experience co-creation, personalization, empowerment, smart destination attributes make the study relevant to developing theory by aligning smart tourism experience incorporating experiential and service-dominant logic models. However, the types of intelligence signify the necessity of a theoretical framework that goes beyond the linear technology-outcome associations and offers systemic approaches that consider the dynamic relationships among tourists, technologies and destinations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Methodological Implications\u003c/h2\u003e \u003cp\u003eTo answer the research question about intellectual and geographical structures, the paper presents the significance of bibliometric methods in charting the development and organization of the research on smart tourism experience. This analysis shows that the number of publications and citations is concentrated in particular countries and among the few researchers, which indicates the possibility of an epistemic basis and homogeneity of the methodology. This is an indication that future studies should consider diversification of methods such as qualitative, mixed method, and longitudinal designs to understand more of the experiential and contextual aspects of smart tourism. Moreover, the use of secondary data sources implies the possibilities of primary data collection with the help of real-time digital footprints, sensor data, and immersive technologies to improve reflected lived smart tourism experiences.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Practical Implications\u003c/h2\u003e \u003cp\u003eThe research question regarding application and relevance, the results can be used practically by destination managers and policy makers who are interested in improving smart tourism experiences. The prevalence of experience-related themes points to the fact that smart tourism investments should focus on the experience value development, but not on technology implementation. To provide personalized, responsive and emotionally engaging experiences, destination managers ought to combine various types of intelligences; sensory intelligence, communication intelligence and empathetic intelligence. The geographical insights can enable the policy makers to recognize the loopholes in the smart tourism development of emerging and developing destinations and devise policies that encourage the development of smart tourism activities in an inclusive and context-sensitive manner. Moreover, trust, data privacy and governance are given priority and present the necessity to build ethical and transparent data management systems to continue the positive experience of smart tourism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Implications for Tourists and Experience Design\u003c/h2\u003e \u003cp\u003eThe study also has an impact on the concept of tourists as active participants in the smart tourism ecosystems. The results support the argument that smart tourism experience empowers the tourists by increasing the sense of autonomy, decision making, and co-creation opportunities. Experience designers must thus work on user-friendly smart solutions that facilitate learning, emotional interaction, and smooth interaction throughout the tourist experience. With the smart technologies aligned to the needs, preferences, and values of the tourists, destinations can help them become more engaged, satisfied, and loyal.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Limitations of the Study","content":"\u003cp\u003eThe study has some of the limitations which should be taken into account. First, the study includes only the publications in the major academic databases, so the inclusion of the studies on the regional level is possible, i.e., in the journals, conferences, or reports published by the industries, which might introduce a limitation to the inclusivity of the results. Second, the bibliometric method is concerned with the patterns of publication and citation, which are indicators of scholarly impact, but do not necessarily reflect the practical importance or practical realization of smart tourism experiences. Third, the research is mainly based on quantitative indicators and thematic explanations, which can ignore subtle contextual, cultural and experience variability between destinations. Fourth, current and quickly changing smart tourism technology implies that recent technological advances (e.g., generative AI, extended reality, improved data analysis) are not necessarily well-represented in the reviewed literature. Lastly, the empirical study fails to test the causality between smart tourism attributes and tourist outcomes, and, therefore, does not allow the researcher to make behavioural or performance-based conclusions.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis paper provides the conceptual, thematic, methodological, and geographical layers of this literature through a synthesis of the concept of smart tourism experience. Through the use of a bibliometric analysis and content-based analysis, the paper highlights how smart tourism experience has been modified into an experience-co-creation, tourist-empowerment, and intelligent destination system multidimensional phenomenon. The results indicate that the researches on smart tourism experience are influenced by different methodological methods such as conceptual frameworks, quantitative empirical research, qualitative research as well as mixed-method research designs due to maturity and methodological diversification of the study. It is further indicated that the methodological classification tables used reveal the domineering research designs and data sources and also reveal research imbalances in terms of methodological selection within and across regions and themes.\u003c/p\u003e \u003cp\u003eIt is also revealed in the analysis that the research on smart tourism experience is geographically clustered in technologically developed and tourism-related nations, with China, Spain, the United States, and South Korea becoming the major contributors. This difference in spatial distribution corresponds with access to digital infrastructure and smart destination programs; therefore, it can be assumed that technological preparedness has a great impact on scholarly output. Also, the naming of a few prominent writers and significant works highlight the presence of a comparatively limited circle of academic interest in determining theoretical orientation, research priorities, and methodology choice in the discipline.\u003c/p\u003e \u003cp\u003eAlso, the literature indicates that the trends in methodologies are strongly correlated with the themes of the study, and quantitative designs are predominant in the studies on the adoption of technology, evaluation of the experience, and behavioral consequences, whereas qualitative and conceptual works are helpful in the development of the theory and conceptualization of experiences. The combination of these insights allows the study to collate the fragmented knowledge, as well as it offers the well-organized basis of further empirical and methodological progress. On the whole, the results assist in gaining a more profound insight into the way the problem of smart tourism experience is regarded, in which direction research activities are focused, and how the methodological choices are determined to impact the formation of knowledge, which can also be regarded as the valuable source of guidance that the scholar can use to create a strong and context-specific study in the growing field.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics Approval and Consent to Participate\u003c/h2\u003e\n\u003cp\u003eThis study is based exclusively on a systematic scoping review of previously published and publicly available peer-reviewed literature. As no primary data were collected and no human participants were directly involved, ethical approval and informed consent were not required for this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors contributed substantially to the conception and design of the study.- **Conceptualization:** All authors- **Methodology and review protocol:** All authors- **Literature search and screening:** All authors- **Writing \u0026ndash; original draft:** All authors- **Writing \u0026ndash; review and editing:** All authors\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eAll articles reviewed are obtained from publicly available peer-reviewed journal articles indexed in the Web of Science database. The list of included studies and relevant extracted information are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAfolabi OO, Ozturen A, Ilkan M (2021) Effects of privacy concern, risk, and information control in a smart tourism destination. Economic Research-Ekonomska Istrazivanja 34(1):3119\u0026ndash;3138. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/1331677X.2020.1867215\u003c/span\u003e\u003cspan address=\"10.1080/1331677X.2020.1867215\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnaya GJ, Lehto X (2020) Traveler-facing technology in the tourism experience: a historical perspective. 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Curr Issues Tourism 27(23):4374\u0026ndash;4388. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13683500.2023.2298349\u003c/span\u003e\u003cspan address=\"10.1080/13683500.2023.2298349\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"sn-business-and-economics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"43546","submissionUrl":"https://submission.nature.com/new-submission/43546/3","title":"SN Business \u0026 Economics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Smart Tourism Experience (STE), Smart Tourism, Digital Technologies, PRISMA-ScR, Technological Dimensions, Antecedents, Systematic Literature Review","lastPublishedDoi":"10.21203/rs.3.rs-8530210/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8530210/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe tourist industry has seen a substantial transformation due to the growing use of digital technologies, which has made the Smart tourist Experience (STE) a key area of study. The literature on the technological aspects that enable smart experiences, the factors that influence visitor engagement, and the identification of ongoing research gaps is still scattered, despite the tremendous growth in scholarly interest in STE. The current work uses the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) criteria to conduct a systematic scoping review in order to solve this problem. To compile the body of knowledge on smart tourist experiences, a thorough search and screening of peer-reviewed literature published in prestigious academic databases was conducted. Artificial intelligence, the Internet of Things, big data analytics, mobile technologies, augmented and virtual reality, and integrated smart platforms are among the major technological aspects that the assessment highlights as supporting STE. The study also classifies important STE antecedents at the individual, technological, and destination levels, including travelers' digital preparedness, perceived utility, system interactivity, and smart destination infrastructure. The results also highlight significant gaps in the body of existing work, such as a lack of focus on ethical, privacy, and sustainability issues, inadequate theoretical integration, underrepresentation of emerging economies, and little empirical validation. This study presents a future research agenda to further theoretical development and empirical investigation in smart tourism studies, as well as an organized understanding of the smart tourist experience through the consolidation of scattered research.\u003c/p\u003e","manuscriptTitle":"Mapping the Smart Tourism Experience Landscape: A Systematic Literature Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 17:34:30","doi":"10.21203/rs.3.rs-8530210/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-04T22:12:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-02T17:00:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-30T15:58:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-24T18:58:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-22T09:25:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-21T18:23:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"85414054552202077451607140245273904237","date":"2026-01-19T07:05:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121546970273684839588984133148337095270","date":"2026-01-18T11:56:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112943076412336135689443289182787738979","date":"2026-01-18T11:48:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"161884465431218992638021991049263736599","date":"2026-01-16T16:32:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-16T14:32:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"24962748900931044545656618838526479679","date":"2026-01-16T13:33:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191016707005609185767587725178342179885","date":"2026-01-16T12:17:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53818713197461241365018744597131597534","date":"2026-01-12T07:00:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-08T12:33:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-08T10:53:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-07T10:12:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-07T10:08:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"SN Business \u0026 Economics","date":"2026-01-06T10:22:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"sn-business-and-economics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"43546","submissionUrl":"https://submission.nature.com/new-submission/43546/3","title":"SN Business \u0026 Economics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"63dd3560-4ecd-4ec5-913c-7f645973fd71","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-19T12:53:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 17:34:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8530210","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8530210","identity":"rs-8530210","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}