Smart Tourism Research Articles

Smart tourism transformation of the Şi̇le district: strategic aspects through a SWOT analysis

PurposeThis study aims to evaluate the smart destination potential of the Şile district by identifying its strengths, weaknesses, opportunities and threats related to smart city applications.Design/methodology/approachA comprehensive SWOT analysis was conducted using data from participants and relevant documentation to assess the feasibility of smart tourism initiatives in Şile.FindingsThe analysis reveals that Şile, due to its proximity to Istanbul, has significant potential to develop into a smart tourism destination. Key strengths include its natural attractions, while challenges revolve around infrastructure limitations.Research limitations/implicationsThe study is limited to the Şile district and may not be generalizable to other regions. Future research could expand the scope to include comparative studies with other potential smart tourism destinations.Originality/valueThis research contributes to the growing body of literature on smart tourism by offering strategic recommendations tailored to the unique context of Şile, a district with significant but underutilized potential.

Navigating overtourism destinations: Leveraging smart tourism solutions for sustainable travel experience

<p>This paper explores the integration of artificial intelligence (AI) and smart tourism technologies to address the multifaceted challenges of overtourism in tourist destinations. Overtourism leads to significant environmental degradation, strains local resources, and diminishes visitor satisfaction, ultimately threatening the sustainability of these destinations. Destinations can enhance sustainability and tailor travel experiences by utilizing cutting-edge technologies like the Internet of Things (IoT), augmented reality (AR), virtual reality (VR), and big data analytics. These technologies offer innovative solutions to optimize resource use, enhance visitor engagement, and promote responsible tourism practices. The study underscores the potential of smart tourism technologies to manage tourist flows, reduce environmental impacts, and improve the overall quality of life for local communities. Strategic planning, substantial investment, and collaboration among various stakeholders, including government agencies, local communities, and the private sector, are essential for the successful implementation of these solutions. The findings highlight the critical role of technological innovation in fostering a balanced and sustainable future for tourism, ensuring that destinations can thrive economically while preserving their cultural and natural heritage. This research provides valuable insights for policymakers and tourism managers aiming to mitigate the adverse effects of overtourism through the adoption of AI and smart tourism technologies.</p>

Research on Jiangxi Cultural Wisdom Tourism Industry Strategy Based on OHDSI General Data Model and Digital Art Empowerment

With the rapid development and wide application of a new round of information technologies, such as the global Internet of Things, the new generation of mobile Internet, cloud computing, etc., informatization has opened a new stage of smart tourism (ST), and ST has become the main trend of tourism development in China at present and for a long time to come. Tourism industry has become one of the important pillar industries in Jiangxi, and it plays an increasingly prominent role in stimulating and supporting economic and social development. Wisdom tourism is an important means to improve tourism service, tourism management and tourism marketing, and an important starting point to promote the upgrading of tourism industry in Jiangxi Province, and to achieve carry-over and leapfrog development and overtaking at corners. This paper is constantly improving and updating on the basis of data warehouse integration mechanism. Under the data warehouse mechanism, through the effective integration of spatial data, virtual reality data and dynamic data, a comprehensive data warehouse oriented to tourism promotion, scenic spot management and department management is formed. It aims to promote the rapid implementation of ST, bring tourists a comfortable tourism experience, save costs and improve efficiency for tourism service providers.

How Artificial Intelligence (AI) Is Powering New Tourism Marketing and the Future Agenda for Smart Tourist Destinations

Artificial intelligence (AI) is a disruptive technology that is being used by smart tourist destinations (STDs) to develop new business models and marketing services to increase tourists’ experiences and sales, revenue, productivity, and efficiency and STDs. However, the adoption of AI applications and platforms requires a high economic budget for STDs that want to integrate this digital tool into their future agenda and tourism development plans, especially when they set them up for marketing plans and operational processes. This iterative technology needs regular maintenance as well, leading to recurring costs and specialised crews in advanced technologies and marketing activities. This study aims to show the impact of AI advancements on STDs’ tourism marketing to enhance the quality of services and illustrate their future agenda to improve tourists’ experiences. A comprehensive literature review on AI technology and STDs has been conducted to illustrate new tourism marketing in their future agenda. Moreover, this study presents real examples of AI technology in a tourism context to better understand the potential of this digital tool. The findings of the current study support the idea that AI is a multipurpose tool that helps manage, monitor, and analyse sales information; revenue management; minimise prediction errors; streamline operations; and develop better marketing strategies, optimising economic resources, reducing marketing costs, and responding dynamically to changing needs for tourists and residents in STDs. Furthermore, the investment in AI technologies by STDs helps enhance the quality of products and services, and attract new investments, which benefit the regional economies and population’s quality of life. This study is the first to address the use of AI to improve tourist marketing in STDs, which is its primary uniqueness. Also, this study identifies new opportunities and initiatives through AI that can be developed to help tourism marketing in STDs.

Exploring the impact of artificial intelligence technologies on tourists’ smart experiences: the moderating role of emotional arousal level

ABSTRACT This study aims to explore how Artificial Intelligence (AI) technologies affect tourists’ smart experiences and the role of emotional arousal level in this relationship. Drawing from the appraisal theory of emotion, a conceptual framework is proposed to test hypotheses about the connections between AI technologies, emotional arousal level, and tourists’ smart experiences. This study utilized an online survey to collect 301 questionnaires from tourists who experienced AI technologies in four Chinese smart tourism destinations. The results obtained through the structural equation modeling method suggest that four factors – interaction, personalization, co-creation, and privacy – positively impact tourists’ smart experiences. Additionally, the study finds that tourists’ emotional arousal level is a moderator between AI technologies and tourists’ smart experiences. The findings provide theoretical and practical implications for smart tourism destinations and researchers to use AI technologies to enhance tourists’ smart experiences at smart tourism destinations.

Conclusion: sustainability, smart tourism destinations and evolving visitor preferences

PurposeThe primary aim of this themed issue is to highlight the incorporation of sustainability principles in the progress of tourism and the monitoring of tourists' evolving preferences, all within the sustainability framework and smart tourism destinations. The strategic question underlying this theme issue is how can we interpret, relate and monitor the rapidly evolving visitor preferences within sustainability and smart tourism destinations?Design/methodology/approachThis issue’s critical outcomes as they relate to the strategic question are reviewed, with reference to the contributions made to knowledge, policy and practice and the implications for future applied research concerning sustainability, smart tourism destinations and evolving visitor preferences.FindingsArising from the analysis and synthesis of recommendations, the following themes were proposed as critical concentration points for rapidly evolving visitor preferences within sustainability and smart tourism destinations: as in all areas of life, sustainability will continue to be a prominent concept in the tourism sector. Smart solutions and the use of technology have also been identified as determining factors in creating sustainable destinations. On the other hand, changing and evolving tourist preferences are emerging as a driving force for smart destinations and sustainability. Tourism destinations must take steps toward sustainability by considering the changing visitor structure, evolving demands and needs. Some articles in this special issue also analyze tourist demands and sustainability efforts of destinations in specific destinations and provide invaluable insights.Originality/valueAs it is essential for all stakeholders of the tourism industry to achieve competitiveness while securing sustainability, this particular article suggests ways for the industry as a whole, its players, destination administrations, local and national policymakers and other major stakeholders of the tourism industry to address some issues faced by the industry. Factors such as changing customer structure, use of technology and increasing environmental awareness make it necessary for destination management and all players individually to take vital measures. This paper and the collection of articles in this thematic issue offer crucial insights for academics, professionals and decision-makers in creating a complete framework to assess, connect and regularly track changing visitor preferences. The papers include recommendations for creating robust tourism locations that effectively tackle challenges, promote inclusion and prepare for future advancements. This is achieved by examining the convergence of sustainability, smart tourism and changing tourist tastes.

Antecedents the adoption of tour itineraries from smart travel apps: an integration of experiential consumption theory and innovation resistance theory

Purpose The purpose of this study investigate the antecedents the adoption of tour itineraries from smart travel apps. Travelers are progressively expanding their smart travel planning applications to organize their trip-related activities. With the help of these apps, users achieve their favorite tour itineraries and choose their preferred destinations. Design/methodology/approach This study aimed to examine the results of smart tour itineraries on travelers and elucidate the motivations for their continual use and why travel experts are increasingly using smart tour itineraries. Innovation resistance and experiential consumption theories were used in this study. SmartPLS 3.2.8 was used to consider 682 valid samples using structural equation modeling (SEM). Findings This analysis identified the following crucial factors: usage, value, risk and traditional barriers. Moreover, utilitarian and hedonic values significantly affected barriers. Finally, theoretical and practical suggestions are presented along with future research directions. Originality/value This study encompasses the tender of innovation resistance theory to travel itineraries by integrating experiential consumption theory in the context of smart tourism apps.

Spatial layout optimization model integrating layered attention mechanism in the development of smart tourism management

Tourism demand projection is paramount for both corporate operations and destination management, facilitating tourists in crafting bespoke, multifaceted itineraries and enriching their vacation experiences. This study proposes a multi-layer self attention mechanism recommendation algorithm based on dynamic spatial perception, with the aim of refining the analysis of tourists’ emotional inclinations and providing precise estimates of tourism demand. Initially, the model is constructed upon a foundation of multi-layer attention modules, enabling the semantic discovery of proximate entities to the focal scenic locale and employing attention layers to consolidate akin positions, epitomizing them through contiguous vectors. Subsequently, leveraging tourist preferences, the model forecasts the likelihood of analogous attractions as a cornerstone for the recommendation system. Furthermore, an attention mechanism is employed to refine the spatial layout, utilizing the forecasted passenger flow grid to infer tourism demand across multiple scenic locales in forthcoming periods. Ultimately, through scrutiny of data pertaining to renowned tourist destinations in Beijing, the model exhibits an average MAPE of 8.11%, markedly surpassing benchmarks set by alternative deep learning models, thereby underscoring its precision and efficacy. The spatial layout optimization methodology predicated on a multi-layer attention mechanism propounded herein confers substantive benefits to tourism demand prognostication and recommendation systems, promising to elevate the operational standards and customer contentment within the tourism sector.

Enabling personalized smart tourism with location-based social networks

With the rapid advance of mobile internet, communication technology and the Internet of Things (IoT), the tourism industry is undergoing unprecedented transformation. Smart tourism offers users personalized and customized services for travel planning and recommendations. Location-based social networks (LBSNs) play a crucial role in smart tourism industry by providing abundant data sources through their social networking attributes. However, applying LBSNs to smart tourism is a challenge due to the need to deal with complex multi-source information modeling and tourism data sparsity. In this article, to fully harness the potential of LBSNs using deep learning technologies, we propose an knowledge-driven personalized recommendation method for smart tourism. Representation learning techniques can effectively modeling the contextual information (e.g., time, space, and semantics) in LBSNs, while the data augmentation strategy of contrastive learning techniques can explore user personalized travel behaviors and alleviate data sparsity. To demonstrate the effectiveness of the proposed approach, we conducted a case study on trip recommendation. Furthermore, the patterns of human mobility are revealed by exploring the effect of contextual data and tourist potential preferences.

Design and Optimization of Tourism Information Management System Based on Artificial Intelligence

This study aims to implement a tourism information management system based on the concept of Smart Tourism. As the people's living conditions have improved, the traditional model of tourism management failed to match the customers' demands, because it has some flaws such as low efficiency. Integrating AI with tourism management helps to meet clients' needs with smarter and more comfortable accommodations before, during, and after their trip. This study optimizes the artificial neural network (ANN) by utilizing long short-term memory (LSTM) to address its inherent faults, such as delayed convergence, easy oscillation, and falling into local minima. The experimental findings demonstrate that this algorithm achieves a recall rate of 99.6% and a prediction accuracy of 98.2%. This algorithm offers some useful recommendations for tourist management while avoiding the pitfalls of more conventional algorithms. In addition, this study extends the idea of "smart tourism" to particular forms of tourist informatization, which has the potential to boost the tourism industry's overall development level by facilitating structural upgrades and transformations.

Analysis of Research Trends and Issues in Smart Tourism: A Comparative Study between South Korea and China

Analysis of Research Trends and Issues in Smart Tourism: A Comparative Study between South Korea and China

A Study on Analysis of local government ordinancesfor promoting and activating smart tourism

A Study on Analysis of local government ordinancesfor promoting and activating smart tourism

OPTIMIZING THE OPERATION OF SMART CITIES TO INCREASE SUSTAINABLE TOURISM ATTRACTIVENESS

The article describes the main aspects of the development of smart tourism in nine smart cities. Analysis of the results of questionnaires assessing the state of the digital economy and the level of development of information and communication technologies in the tourism sector. The main trends and directions of development were assessed, as well as recommendations for optimizing the operation of smart cities to increase tourist attractiveness were proposed. In addition, the purpose of this article is not only to increase the tourist attractiveness, but also to ensure the sustainability of urban infrastructure, preserve environmental safety and improve the quality of life of the population. The economic consequences of reasonable tourism activities in the city, job creation opportunities and investment attractiveness were also taken into account. The results of the study show that with the help of intelligent technologies, it is possible to improve tourist information systems, expand digital services and increase the mobility of urban infrastructure.

A Theoretical Discussion on the Flow of Tourist Population and the Development of Tourism Market in Heilongjiang Province

This paper deeply discusses the basic law of tourist population flow and its influence on the development of tourism market in Heilongjiang Province. Under the background of the vigorous development of global tourism, the flow of tourist population, as the core element of tourism activities, has an important impact on the prosperity and sustainable development of regional tourism market, such as seasonal, spatial distribution and interactive effects. Through the detailed analysis of Heilongjiang tourism market, this paper reveals the market size, resource characteristics, challenges and problems of this market under the action of tourist population flow. Further, this paper analyzes the dual impact of tourist population flow on Heilongjiang tourism market, including the positive effect of promoting local economy, cultural exchange and industrial development, and the negative effect of environmental pressure, over-exploitation of resources and decline of service quality. At the same time, this paper puts forward some strategic suggestions to promote the sustainable development of Heilongjiang tourism market, including rational planning of tourist population flow, strengthening the protection and development of tourism resources, promoting the development of smart tourism, and strengthening regional cooperation and linkage. These suggestions are intended to provide theoretical basis and practical guidance for the scientific planning and management of Heilongjiang's tourism market, and help it achieve long-term prosperity and sustainable development.

The Moderating Effect of Smart Tourism Technologies: Tourist Destination Loyalty Success in Dili (Timor Leste)

The research focuses on testing and analyzing the influence of several components of tourist destination loyalty, namely tourist satisfaction, experience quality, and smart tourist technologies which as a moderator variable. The research uses a quantitative method to see the influence of each variable. The respondents of the research are from various backgrounds, with a total of 317 visitors (210 women) and (107 men) who have visited tourist attractions of places historical locations in Dili (Timor Leste). The processing data use SEM-PLS, and the results of processing data show that all hypotheses significantly influence (direct) and (indirect hypotheses: smart tourist satisfaction is able to be a good moderator variable between experience quality and tourist satisfaction). The theory implication as a development of behavior and smart technologies theory, as well as the practical implication of being a strategic policy maker for stakeholders. The novelty of the research is that experience quality is in the form of physical and non-physical experiences that have positive emotions that are felt and shared with everyone so that there is satisfaction for visitors and tourist attractions.

Technological Use from the Perspective of Cultural Heritage Environment: Augmented Reality Technology and Formation Mechanism of Heritage-Responsibility Behaviors of Tourists

This paper explores the integration of augmented reality (AR) technology within the realm of cultural heritage tourism, particularly its influence on the development of tourists’ heritage-responsibility behaviors. Addressing the recovery and development of Chinese domestic tourism in the post-pandemic period, smart tourism technology innovations have been explored. The research demonstrates that AR, by surpassing physical and temporal constraints, fosters a deeper synthesis of traditional and contemporary cultures, thereby enriching the comprehension of national history and cultural heritage. Employing the stimulus–organism–response (SOR) theory, a theoretical framework is established to elucidate the causal links from AR attributes to perceived usefulness, enjoyment, and behavioral intentions. The analysis reveals that the interactivity, vividness, and novelty of AR significantly augment perceived usefulness and enjoyment, although augmentation quality does not notably impact enjoyment. Both perceived usefulness and enjoyment significantly drive the intention to recommend. This study offers valuable theoretical insights and practical recommendations for the strategic deployment of AR in the sustainable development of cultural heritage tourism.

Effect of smart tourism technology experience (STTE) on tourist satisfaction and tourist happiness in Bordeaux: the mediation role of self-gratification

Effect of smart tourism technology experience (STTE) on tourist satisfaction and tourist happiness in Bordeaux: the mediation role of self-gratification

스마트관광 척도개발: 컨벤션산업을 중심으로

Purpose: Based on the existing discussions on smart tourism, this study intends to develop a scale by using both qualitative and quantitative methods of the compositional dimensions and sub-elements of smart tourism in the convention industry. Through this, the concept and components of smart tourism in the convention are clearly defined and organized, and a theoretical frame that will be the basis for smart tourism-related research is presented. Methods: Based on web crawling, this study first performed a cluster analysis by matching data to the Nvivo program, and second, an FGI and expert opinion survey were conducted to derive an item pool through qualitative analysis. Third, using the derived item pool, exploratory factor analysis and confirmatory factor analysis were performed using the data collected through the survey to secure reliability and validity. Results: The final derived compositional dimensions were finally derived in five dimensions: technology integration, convenience, information, smart infrastructure, and reliability, and a total of 15 questions were derived, 3 questions each for the lower dimensions. Conclusion: The results of this study provide the following theoretical and practical implications. Theoretically, it laid the foundation for systematically understanding the convergence of smart tourism and the convention industry. In practice, it is possible to lay the foundation for providing personalized services by analyzing participant's preferences and behavioral data, thereby increasing participants' satisfaction and willingness to re-engage.

Integrating Generative AI and IoT for Sustainable Smart Tourism Destinations

This paper aims to develop a groundbreaking approach to fostering inclusive smart tourism destinations by integrating generative artificial intelligence (Gen AI) with natural language processing (NLP) and the Internet of Things (IoT) into an intelligent platform that supports tourism decision making and travel planning in smart tourism destinations. The acquisition of this new technology was conducted using Agile methodology through requirements analysis, system architecture analysis and design, implementation, and user evaluation. The results revealed that the synergistic combination of these technologies was organized into three tiers. The system provides information, including place names, images, descriptive text, and an audio option for users to listen to the information, supporting tourists with disabilities. Employing advanced AI algorithms alongside NLP, developed systems capable of generating predictive analytics, personalized recommendations, and conducting real-time, multilingual communication with tourists. This system was implemented and evaluated in Suphan Buri and Ayutthaya, UNESCO World Heritage sites in Thailand, with 416 users participating. The results showed that system satisfaction was influenced by (1) the tourism experience, (2) tourism planning and during-trip factors (attention, interest, and usage), and (3) emotion. The relative Chi-square (χ2/df) of 1.154 indicated that the model was suitable. The Comparative Fit Index (CFI) was 0.990, the Goodness-of-Fit Index (GFI) was 0.965, and the model based on the research hypothesis was consistent with the empirical data. This paper contributions significant advancements in the field of smart tourism by demonstrating the integration of Gen AI, NLP, and the IoT and offering practical solutions and theoretical insights that enhance accessibility, personalization, and environmental sustainability in tourism.

Research on the Innovation of Tourism Management Curriculum in the Context of Smart Tourism

Research on the Innovation of Tourism Management Curriculum in the Context of Smart Tourism