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The infrastructural development of the Greater Bay Area in China has experienced rapid growth in recent years. Given the national plans, local governments have to upgrade their urban habitat, convenience, leisure and recreation. Particularly, municipal governments have built lengthy bike lanes for multiple purposes such as commuting, exercise, leisure and tourism. Users' preferences have become more diversified. Within the GBA region, several bike lanes exceed 100 km and thus many rest stations are available along the route. Nevertheless, prior bike travelling studies in Asia Pacific countries have focused on the whole trip experience and bike lanes' safety design focusing in rural areas. There exists a paucity of information about users' preference of amenities for a relatively long-haul bike journey for leisure and tourism purpose in a metropolitan setting. To fill the gap, research with mixed methods using interviews with two groups of insightful persons and a survey of 342 potential users were undertaken to gather their perspectives on the 30 value-added amenities of rest stations for biking travelling. At last, the implications of findings on related policy planning were discussed inclusive the proposed establishment of a commission comprising boarder representativeness of stakeholders and the prioritized facilities in the planning for optimization of bike path for tourism and leisure. • Prior bike travelling studies in Asia Pacific countries have focused on the whole trip experience and bike lanes' safety design focusing in rural areas. There exists a paucity of information about users' preference of amenities for a relatively long-haul bike journey for leisure and tourism purpose in a metropolitan setting. • Two-phrase research design using interviews with two groups of insightful persons and a survey of 342 potential users were undertaken to gather their perspectives on the 30 value-added amenities of rest stations for biking travelling. • Implications of findings on related policy planning were discussed inclusive the proposed establishment of a commission comprising boarder representativeness of stakeholders and the prioritized facilities in the planning for optimization of bike path for tourism and leisure. [ABSTRACT FROM AUTHOR]

Information systems offer major contributions to the establishment of accessible tourism conditions. However, these solutions need to be correctly developed, which often implicates approaches based on user-centered methodologies. To improve information flow within the accessible tourism market, an accessible tourism information system was prototyped. The development of this solution, named access@tour by action, involved a rigorous testing process, to evaluate the acceptability and mainly the difficulties of interaction with specific needs. Thus, the objective of this study is to explore the results obtained from usability testing of the prototype, involving people with special needs, social organizations, and caregivers. The results showed that some improvements were needed namely in the registration process, evaluation of tourism offers, and on the layout of information. Notwithstanding, the overall perception of ease of interaction, and accessibility was good. This user feedback will be used to obtain the final version of the platform. [ABSTRACT FROM AUTHOR]

For over a decade, mobile applications are frequently used to make people's daily lives more accessible in all areas, such as commerce, tourism, education, medical care, and others. For implementing these applications, several frameworks exist that can accomplish this task, such as Google's Flutter, Microsoft's Xamarin, Facebook's React Native, Apple's Swift UI, Ionic, Django..etc. However, choosing the best framework to develop an application is not a simple enough decision for developers. This paper presents a detailed analysis of the four most widely used frameworks for implementing mobile applications: React Native, Swift UI, Flutter, and Xamarin. Furthermore, this study also aims to assist developers in choosing the most suitable framework by proposing an application that can recommend the best framework according to the needs entered by answering the questions, which are generally related to the relevant criteria resulting from the analysis of these frameworks. [ABSTRACT FROM AUTHOR]

Tourism is a very important sector and has a major influence on development and national income. Moreover, Indonesia has thousands of tourist destinations that are very beautiful and interesting to visit, both for Indonesians and foreigners. It's just that, there are still many local tours, such as tourist villages, which are still not well known by most people. In fact, there are many cultures, customs, places of recreation, or characteristics of an area that need to be seen and introduced to outsiders, even to Indonesians themselves. Therefore, this study aims to explain the problems that occur in the field of tourism, as well as provide solutions in the form of tourism applications that aim to help promote local Indonesian tourism, as well as make it easy for travel enthusiasts to organize their travel plans. The process of making this travel application is also carried out through various research and interviews with potential users and IT people in order to produce an attractive and effective application. This study uses the design thinking method. Researchers collected data sources from literature studies and surveys through questionnaires, where the results of the data obtained from the questionnaires were numerical or quantitative. The aim is to determine the level of public interest in tourism, as well as determine the level of potential users of this tourism application. That way, the goals of this application will be achieved and effective in helping solve tourism problems. [ABSTRACT FROM AUTHOR]

A prominent monument in DKI Jakarta is the Monument Nasional (abbreviated as Monas). This moniker serves as both a symbol for the city of Jakarta and a representation of the people of Jakarta and Indonesia. Apart from being a monument, Monas also has a history of the Indonesian nation. In this study, 3D models are designed to display visualizations of Monas and surroundings in 3D form with the aim of helping tourists who want to visit Monas in preparing and increasing their understanding of the tourism in Monas. This study was conducted with the help of CityEngine software that created the 3D models of Monas implemented and displayed on a website with a web scene format. Using image-based 3D modelling, the main geomatics techniques is photogrammetry, it allows for new methods to create virtual 3D. To do this, various components including route visualizations must collaborate. To do this work we have a framework that leverages the technology and data sources already available to reduce the time and work required for prospective 3D applications. With the existence of a Monas 3D visualization that can be accessed through web browser, it expected that it will make tourists not complicated to obtain various tourism information and increase the tourism in Jakarta. [ABSTRACT FROM AUTHOR]

[Display omitted] • This study applied the algorithm for adaptive tourism recommendation on applications. • Tourists can make decisions under local business standards and current information. • Gamification was use in offline and online activities to promote goal achievement. • Gamification-based activities promoted sustainable development in the tourism industry. This research aims to develop community tourism in emerging cities by applying the gamification approach to improve the standard of products and services in tourism for offline and online operations. The mobile and web application development concentrates on promoting and advertising tourist attractions, accommodations, restaurants, hotels, and standardized local businesses. The established application also displays the recommended travel routes applied with the adaptive tourism recommendation algorithm for suggesting high-quality travel routes. This algorithm was developed based on the data collected by tourists, tourist attraction staff, and local entrepreneurs altogether. The selected local entrepreneurs, which met the application standards, were demonstrated by the pin reward icons shown in Google Maps. The pin reward icons representing the standardized businesses provide valuable information to tourists when they make decisions. The result shows that the sensitivity was 98.63%, and the accuracy was 97.06% of the recommended location for the tourists, entrepreneurs, and tourism development agencies while using the applications. Ultimately, this will directly benefit the emerging cities if the public sector encourages mobile application utilization training and practices. [ABSTRACT FROM AUTHOR]

The traditional rural tourism industry has some problems, such as incomplete tourism information, unable to share all data, serious data loss, and the decline of tourism service quality. In recent years, with the support of big data and e-commerce technology, many villages have vigorously developed tourism e-commerce, which has brought huge economic benefits to rural residents and improved their living environment to a certain extent. This paper briefly expounds the concept and characteristics of big data, analyzes the needs of rural tourism e-commerce on the basis of being familiar with big data related technologies, develops a rural tourism e-commerce system (hereinafter referred to as RTES), and explains the design of the system in detail from the system architecture design, database design and system function structure design. The application of the system shows that the tourism e-commerce designed and developed in this paper is guaranteed in practicality and security, and reflects professionalism and comprehensiveness in service. It can not only recommend and book the best tourist routes for customers, but also provide support for managers and facilitate management. [ABSTRACT FROM AUTHOR]

Accurately estimating daily tourism volumes is crucial for optimizing operational strategies and enhancing visitor experiences at tourist destinations. In this study, we leverage historical tourism volume data, search engine data, and online review data (including textual review contents) to forecast daily tourism demand. We develop a deep learning framework that includes a feature selection module to select search engine indices, a word embedding module to transform review texts into numerical predictors, and an extreme learning machine (ELM) enhanced with the whale optimization algorithm (WOA) for predictive modeling. Based on different word embedding techniques, we investigated two specific forecasting methods: one based on term frequency-inverse document frequency (TF-IDF) and Transformer, and the other based on the standard pre-trained bidirectional encoder representations from Transformers (BERT). These two methods enhance predictive accuracy while ensuring fast training and inference speeds, making it suitable for the high-frequency daily tourism forecasting task. Experimental results demonstrate that the two methods significantly outperform traditional approaches that rely solely on numerical data sources, achieving lower prediction errors and faster inference speeds compared to established benchmark methods, highlighting their potential to contribute to advancements in tourism prediction methodologies. [ABSTRACT FROM AUTHOR]

• Develop a research framework examining drivers of in-person tour intentions (ITI). • Propose a hybrid statistics and machine learning approach for the testing. • The results reveal that user engagement raise attitude toward VR(ATT). • Product-possessing innovativeness positively moderates the ATT and ITI. • Information-possessing innovativeness negatively moderates the ATT and ITI. Owing to recent uncertainty in the service sector, new attractive ways, such as virtual reality, have been adopted by online sites to provide products and services to individual users in the tourism context. Based on human–computer interaction user engagement and the domain segmentation innovativeness theory, we develop and test a theoretical framework to examine the impact of key user engagement drivers on in-person tour intentions as behavioral responses using the partial least squares structural equation model and a neural network with activation function analysis as the new two-stage approach. According to a survey sample of visitors' responses as the case, the results demonstrate that a) user engagement, including aesthetic appeal, focused attention, perceived usability, and reward experience, improves attitudes toward virtual reality; b) product-possessing innovativeness positively moderates the relationships between attitude toward virtual reality and in-person tour intentions; c) information-possessing innovativeness negatively moderates the relationships between the attitude toward virtual reality and in-person tour intentions; d) focused attention and reward experience show both linear high performance and nonlinear importance; and e) activation function analysis could further improve the accuracy of prediction. [ABSTRACT FROM AUTHOR]

The present study looks at the patterns of behavior by disputant and non-disputant parties in the South China Sea dispute over the 2010–2022 period in a bid to identify trends and policy implications. The method involves building an original dataset of events spanning five categories in the South China Sea—namely administrative, economic, diplomatic, military, and non-military/maritime. The data, which tracks a total of 1099 events between January 2010 and December 2022, shows that the growing combativeness seen in the area is due to two factors: (i) disputants and non-disputants continue to take unilateral actions, including strengthening their naval and maritime enforcement agencies at an uneven rate; and (ii) existing maritime partnership initiatives and joint exercises have largely taken place in the form of competing factions and fallen short of agreeable outcomes. More importantly, the research illustrates the multifaceted nature of analyzing actions in unsettled territorial and maritime disputes because political actors would deploy not just military actions but also a host of non-military tools, such as legal submissions, tourism development, administrative rezoning and renaming, infrastructure upgrade, fishing moratorium, and deployment of civilian forces to stake claims over disputed territories. Considering the continuous military expansion and diverse territorialization activities, the prospect of a regional maritime order is not only uncertain but also unlikely to improve soon. [ABSTRACT FROM AUTHOR]

Systems that rely on dyadic data, which relate entities of two types together, have become ubiquitously used in fields such as media services, tourism business, e-commerce, and others. However, these systems have had a tendency to be black-box systems, despite their objective of influencing people's decisions. There is a lack of research on providing personalised explanations to the outputs of systems that make use of such data, that is, integrating the idea of Explainable Artificial Intelligence into the field of dyadic data. Moreover, the existing approaches rely heavily on Deep Learning models for their training, reducing their overall sustainability. In this work, we propose a computationally efficient model which provides personalisation by generating explanations based on user-created images. In the context of a particular dyadic data system, the restaurant review platform TripAdvisor, we predict, for any (user, restaurant) pair, the review of the restaurant that is most adequate to present it to the user, based on their personal preferences. This model exploits the usage of efficient Matrix Factorisation techniques combined with feature-rich embeddings of the pre-trained Image Classification models, developing a method capable of providing transparency to dyadic data systems while reducing as much as 80% the carbon emissions of training compared to alternative approaches. [ABSTRACT FROM AUTHOR]

This paper briefly describes the overall concept of "TRAVEL TYCOON GREECE" (TTGR), a novel business simulation game which aims to simulate realistically a complete tourism experience. The latest image processing and computer graphics technologies were utilized to create accurate 3D backgrounds with different levels of detail, which were incorporated in the game engine and serve as a realistic and accurate terrain allowing the user to navigate in selected historical and touristic areas of Greece. A series of real-world scenarios representing multiple components of the tourism section were designed primarily for entertainment and marketing purposes. In order to motivate users to participate in the game or remain active, an incorporated ticketing platform allows users to win offers such as touristic products and services. [ABSTRACT FROM AUTHOR]

The tourism industry has particularly evolved in the era of social media, and due to the huge amount of data available on the web, tourism forums have become spaces for exchanging information about many topics concerning a country's tourism and hospitality, which has helped to establish a bank of knowledge that might encourage artificial intelligence researchers to follow some research tracks that could lead to interesting insights for decision makers in the sphere of tourism. This paper is an application of artificial intelligence within the tourism industry in the context of Morocco, whereby we carried out natural language processing transformers to classify entities (i.e., Named Entity Recognition) in text that was collected from the Moroccan forum in TripAdvisor. [ABSTRACT FROM AUTHOR]

The hotel uses modern information technology to establish a customer data group, which contains information about the customer's information on space configuration, color design, etc., and uses scientific operation methods to accelerate the rapid, transformation and upgrading of the hotel. The rapid development of information technology represented by the big intelligent mobile cloud has a lot of functions, can meet the needs of different customers and diversified characteristics at the same time, and provides a complete, stable and accurate information integration platform for hotel system management. The main research directions of DASH include client adaptive algorithm design, multi-client fairness and resource utilization issues, client improvement under multiple servers, and server load balancing. The development and application of scientific and technological information has broken through the development path of the hotel management system, providing new development space and opportunities for the improvement of the hotel management system, but at the same time it will also face more new challenges. Therefore, this article focuses on the characteristics of the tourism accommodation management system under the big data environment, and analyzes the development of the hotel management system under the network environment. The purpose is to provide some reference and reference significance. [ABSTRACT FROM AUTHOR]

This paper proposes a method that allows the clustering and identification of similarities between users of a digital tourism platform, through the extraction of the sentiments expressed by them in the reviews or comments registered and the subsequent automatic clustering of the users, according to the polarity of sentiments subjectively expressed in their posts. This research fills a gap in the text mining literature for the development, improvement and/or reorientation of services and products in the field of tourism, providing a method to explore the needs and desires of the client based on their digital footprint drawn from posts and reviews about the service or product in question. The sentiment analysis is detailed, comprehending language detection and some specific language syntax treatment, with a subsequent explanation of the clustering algorithm used. The developed algorithm was tested in the user's segmentation and sentiment analysis of their publications on a digital tourism platform. The results obtained demonstrate the efficiency of the solution, which presents a high accuracy in the classification of publications in four different languages and in the user's segmentation process. [ABSTRACT FROM AUTHOR]

Despite the fact that city tourism has become increasingly attractive, still the planning authorities undervalue it when developing city infrastructures, especially when extending Wi-Fi covering or other mobile location services. In this paper, we are discussing some problems that occur in existing solutions for mobile applications for city tourism. We check a hypothesis if sharing a real-time location of city visitors may be beneficial for choosing urban attractions. Further, we examine a new type of tourism application that is based on gamification models and location-sharing tools. [ABSTRACT FROM AUTHOR]

Multi-modal fusion techniques show promising results and great potential in the tourism application area. Over the past decade, various multi-modal-based fusion methods have been employed in many sub-domains of tourism, including point-of-interest (POI) recommendations, tourism demand forecasting, and travel route planning. However, the lack of architectural descriptions and consistent terminologies makes it difficult compared to other solutions. This survey provides a comprehensive analysis of current methods of multi-modal fusion and explores the diverse fusion strategies, including the early, late, hybrid, and hierarchical fusion methods. This survey provides the details of multi-modal fusion fundamentals, analyzes the benchmark dataset, and includes statistical information on these datasets. In addition, this survey discussed the particulars of federated learning-based methods and the current problems of tourism applications and suggested a solution to those problems. This survey aims to thoroughly analyze fusion-based strategies in the tourism application area to offer a valuable reference for researchers, stakeholders, and practitioners. [Display omitted] • Explored multi-modal fusion in tourism and its significance. • Presented insights and statistics of tourism datasets. • Analyzed multi-modal feature fusion and deep learning models. • Discussed the fusion method in Federated Learning, including challenges, and future directions. [ABSTRACT FROM AUTHOR]

This study underscores the crucial role of small-scale fisheries (SSF) in promoting sustainable fishing practices within the Mediterranean context, emphasizing the necessity to align fisheries commerce with local seafood consumption. SSF in the Mediterranean, particularly in the Balearic Islands, are vital for local communities, contributing significantly to fish catches, while being deeply intertwined with cultural heritage and traditional values. However, these fisheries face several threats, including resource depletion, management strategies favouring fleet reduction, and increase of seafood imports. Our research investigates the relationships between the local fishing sector and resident population, exploring perspectives on sustainability. We examine SSF activities and perceptions through face-to-face questionnaires in nine fishing ports and assess seafood consumption habits through phone questionnaires. The study reveals an aging fishing sector rooted in family traditions that face administrative hurdles in implementing strategies such as fish tourism and direct sales, but seeks to enhance local product consumption. Despite the traditional relevance of fish in the Mediterranean diet, our findings also show low consumption of fresh and local seafood due to consumer's limited knowledge on local species and related cooking methods and perceived high costs. However, the cultural importance of these products remains undiminished. To reinforce the cultural heritage of SSF and improve the future perspectives of the sector, we advocated for a multi-pronged approach, including raising consumers' awareness about local species, controlling local prices, and promoting certified products through a reduction in the administrative burden and by promoting the active involvement of SSF. [ABSTRACT FROM AUTHOR]

Agritourism is an important supplementary activity in agricultural regions, attracting numerous visitors in search of new experiences and providing alternative incomes to those in rural areas. Whilst tourism literature has progressed in defining and characterising agritourism, there continues to be limited knowledge concerning what contributes directly and indirectly to enhancing and deepening the agritourism experience, particularly the role of visitor-provider interaction and the emotional connection to place. In this paper, we address this gap by exploring agritourism in Western Australia, drawing on a survey of providers and ten semi-structured interviews. We find that agritourism was comprised of four key experiential dimensions (location, authenticity, interaction, and learning) differentiated by six contextual factors which are either endogenous or exogenous to the provider. Our findings show how the agritourism experience can be curated, contributing to the establishment of a better understanding of how providers can improve visitor experience and the attraction of rural areas. The research offers a framework for understanding the role of location as a cross-cutting experiential dimension to better inform policymakers, regional development agencies and agritourism providers in developing agritourism 'products' that may increase visitor numbers and sales, improve regional development outcomes, and enhance rural understandings. • Agritourism is an increasingly important for rural economies. • There is limited understanding on how agritourism relates to unique local and regional contexts. • Agritourism experiential dimensions (location, authenticity, interaction, and learning) are framed by six provider factors. • Highlights location as a cross-cutting ad important dimension in improving regional development. [ABSTRACT FROM AUTHOR]

Due to its significant advantages for downstream applications, such as recommender systems, In the context of travel and tourism, user reviews on TripAdvisor have an impact on other travellers' judgments regarding a variety of travel-related issues, including the choice of a vacation spot, lodging, and places to visit. In graded user reviews, the model must specifically forecast the user's review score after receiving the textual review. The purpose of this article is to present a predictive outline for aspect-based extraction and classification that can estimate the users' optimal travel destination. This impression helps travellers in a variety of ways, such as by recommending better locations that also include expensive destinations. The underlying classification algorithm's processing time is significantly impacted by more dimensions. The term "curse of dimensionality" is often used in statistics and machine learning to describe these issues. By projecting the high-dimensional input data into the low-dimensional subspace while roughly maintaining the distance between the data points with a higher probability, the Random Projection (RP) ensemble classifier decreases the complexity of multivariate data. Extract the crucial information from the reviews, then use Glove word vector representation to categorise the relevant emotions. Further, the article proposed Multinomial Logistic Regression (MNLR) with a Fuzzy Domain Ontology (FDO) algorithm for aspect-based sentiment analysis. More intricate aspects than just the products themselves impact how satisfied people are with tourist destinations. The most important factor in evaluating how convenient a tourist route will be is typically the weather. The combined form of predicted sentiment score, start ratings and environment factor has to be calculated to predict the travel destination based on the measurement of personalized search results. The simulation was processed in Python software. The presented work has utilized some performance measures to evaluate the classification model such as F1-score, Recall, Precision, Mean Absolute Error (MAE), Mean Squared Error (MSE), Cohen Score and Matthew Score. The accuracy with GloVe word vector representation was 90% and after the GloVe representation, the classification model accuracy was about 94%. The proposed strategy outperforms in terms of classification accuracy, according to simulated results and analyses of real-world data. [ABSTRACT FROM AUTHOR]

• Pandemics and natural disasters expose uneven patterns of vulnerability. • COVID-19 impacted small-scale fisheries livelihoods, income and food security. • Social inequities and power relations surround fisheries resources access and aid contribute to vulnerability. • Recovery efforts must target those most vulnerable and marginalised. The global COVID-19 pandemic has exposed the shortcomings of our health, social, and economic systems. While responding to the health crisis, governments are scrambling to understand and address the knock-on economic effects from market disruptions, and respond to other major disturbances (e.g. natural disasters). We conducted 61 key informant interviews with Indo-Fijian small-scale fisheries (SSF) actors (i.e. fishers, boat owners (that may or may not fish), crew members, and traders) in May 2020, two months after Fiji got its first case of COVID-19 and a month after Cyclone Harold hit the country. We examined how these SSF groups whose access to resources depends on their ability to navigate existing social relations of power, have lived through, experienced, and responded to the two stresses. We found the main impact of COVID-19 on SSF actors was the reduction in sales of fish (73.8 % of respondents) likely a result of reduction in local consumption and/or the loss of tourism markets. Loss of purchasing power meant almost a fifth of Indo-Fijian SSF actors interviewed (comprising 44.4 % of crew members, 16.4 % fishers, 11.5 % boat owners, 8.3 % traders) were unable to obtain sufficient food to meet their families' daily needs. Many of these SSF actors do not have access to social security or similar safety nets leaving them vulnerable to the current crisis as well as to other shocks and changes. Furthermore, social inequities and power relations surrounding access to fisheries resources and government aid contributed to their vulnerability to economic stresses from COVID-19 and a severe cyclone. An understanding of early impacts of COVID-19 on SSF through an intersectional lens can assist decision-makers to quickly mobilise assistance to help people who are most vulnerable, and avoid widening inequities among social groups. [ABSTRACT FROM AUTHOR]

The article presents the results of the analysis of the elements of business models of spa tourism enterprises in the context of the principles of sustainable development in tourism business. In the process of defining individual rules for tourist enterprises, an approach based on sustainable tourism criteria and an attempt to adjust them to individual conditions resulting from the specifics of the tourist business activity being carried out was proposed. The characteristics of the individual components of business models were based on the results of interviews conducted in 17 tourism enterprises. The CANVAS scheme was used to examine the structure of the business model. It was found that the business models of spa tourism enterprises not only fail to conform to the principles of sustainable development, but are also not used as managerial tools. Their knowledge among managers is very poor. The analysis was supplemented with additional roles played by Polish sanatoriums in preventing the SARS-Cov2 virus pandemic. The research also revealed an example of cooperation between several spa companies, in the framework of coopetition and exchange of knowledge and services, which can be considered as the initiation of cooperation based on open innovation. [ABSTRACT FROM AUTHOR]

This paper explores the impact of the living heritage approach for sustainable tourism & economics in Mount Lebanon. The proposed living heritage model is separated into three fundamental actions: firstly, the identification of important historical places and buildings that are reused to serve conservation and tourism development, as well as the participation of the core community in determining this. Secondly, the development of a tourism strategy and development plans, in which the local community must also participate. Thirdly, the development of maintenance and control programs, which must be supervised by the local community through its partnership with the Ministry and those responsible for conservation operations. Moreover, the hypothesis is to find a way to implement the living heritage in a local rural context. It also tackles different ways of implementing the living heritage approach based on international case studies (Albergo Diffuso, in Italy and the Meteora, in Greece), to inform sustainable economic and tourism development in the local rural context of Mount Lebanon. The methodological study will take into consideration two analyses: a theoretical (literature reviews and main definitions) and a practical (comparative analysis and case studies). In conclusion, several strategies can be taken into account in order to attain a successful living heritage of sustainable economics and tourism in Mount Lebanon. In fact, such a goal will be achieved through the partnership among private, public, and local sectors that can create a strong historical-touristic-economic bond. [ABSTRACT FROM AUTHOR]

• Survey of vehicle-based tourists conducted in 2018 in Norway. • Route features, trip and socioeconomic characteristics were observed. • Tourist route choice estimated using a path size correction logit model. • Travel time, road width, and road scenery were significant. • Sightseeing places, outdoor activities, and facilities were significant. The tourism industry is rapidly growing, and the massification of certain areas is jeopardising the environment. Certain roads in protected areas or near tourist attractions are experiencing an increase in traffic volumes, leading to higher pollution and noise levels and greater discomfort in the travel experience. To recommend measures intended to ensure a sustainable tourism industry without compromising the environment, it is necessary to obtain further knowledge regarding tourists' travel behaviour as it may differ from that of other travellers, i.e., tourists might choose a route based on variables other than time and cost, such as landscape or tourist attractions. Using Geiranger Fjord in Norway as a case study, tourist route choice preferences were observed and analysed. In total, 60 routes from 12 different origins were observed based on 408 responses collected through a tourist survey administered in the summer of 2018. These data were combined with information regarding road features and the locations of tourist attractions. A path size correction logit model was selected to estimate the significant variables in the choice of one route over other routes. The results showed that tourists selected their routes mainly based on the travel time, road scenery (water bodies and forests), sightseeing places among first-time visitors, and outdoor activities among those living outside of Norway. In addition, the tourists preferred local roads, and 'caravan' tourists were more attracted to roads with fewer facilities. The findings of this study show that tourists' route choice behaviour differs from that of other travellers. Policymakers should consider these differences to enhance transport systems. Further research should focus on incorporating these findings into a transport model to simulate tourists' travel patterns and quantify changes in traffic volumes due to different sustainable measures. [ABSTRACT FROM AUTHOR]

Differential has been extensively applied in solving many engineering matters. The development of tourism destination with multiple scenic spots is a long-term systematic project and the existing decision-making methods are actually not suitable for this process. Thus it is necessary to introduce new decision-making method to analyse the investment process of tourism destination project. Specifically, considering the irreversibility and extendibility of destination development, the present paper constructed a differential dynamic decision-making model for the long-term investment project based on the classical model of real option; B-S model, and analysed the key parameters affecting the modified model; the present price of the project (ω) and the volatility (δ). An example analysis and a case from Yinziyan scenic area were further analysed to test the operability of the proposed model. The proposed model contributes to dealing with uncertainties and enhancing the decision quality of investors in the investment of scenic spots. And the application of differential in tourism destination development contributes to the accuracy of decision-making. Therefore, this paper has both theoretical and practical significance. [ABSTRACT FROM AUTHOR]

The last four decades have witnessed profound social, demographic and economic change in Denham, the main town (a 'village' in European terms) in the Shark Bay region of Western Australia. Formerly highly isolated and dependent upon fishing and pastoralism, Denham today is a hub for nature-based tourism and nature conservation activities, and the site of residential developments catering largely to the distant urban population in the Western Australian capital, Perth. Shark Bay's World Heritage Area (WHA) status, proposed by the Australian government in the late 1980s and declared in 1991, became a popular symbol of these processes of socio-economic development and a focal point for conflict over the nature, scale and pace of local change. This paper examines WHA designation at Shark Bay, placing it within a broader context of Denham's transformation through the overlapping and interrelated processes of declining primary industries, improving transport networks, the growth of tourism and the expansion of nature conservation reserves and activities, and demographic change. It focusses on the reasons for the strength and persistence of negative perceptions towards WHA listing, and links a recent shift in community attitudes to demographic change and corresponding developments in the regional economy and local council membership. Denham, we suggest, presents a characteristically Australian case study of regional polarization against a backdrop of the shift from extractive primary industries towards tourism and nature conservation now characteristic of an increasingly large part of the nation's 'outback' communities. • Demographic and functional changes at Shark Bay related to a significant reduction in the village of Denham's level of isolation. • Community attitudes to World Heritage Area designation influenced by rural transformation or a 'post-productive transition'. • Shifting community attitudes to World Heritage Area status linked to recent demographic and socio-economic change. • Conceptions of scale in heritage should incorporate size, level and relation in order to explore the unique spatial politics that underpin opposition to World Heritage status. [ABSTRACT FROM AUTHOR]

Multiple studies have provided evidence that the hospitality and tourism sector is experiencing a growing reliance on information and communication technology (ICT). Consequently, employees in this industry are facing an escalating expectation to stay connected and address work-related communication even outside their regular working hours. Little is known about how using ICTs during off-job can raise employee unfairness perceptions and job overload and how managers can control this. The primary focus of the current study is to examine the association between work-related ICT use after hours and employees' perceived injustice and the mediating role of work-role overload and the moderating role of psychological detachment in this relationship within the hospitality and tourism industry. By convenient sampling method, 400 employee responses were collected. The collected data were analyzed using structural equation modeling (SEM) with the "Partial least squares (PLS)" technique, employing SmartPLS-4 software. The empirical findings demonstrate a positive association between work-related ICT use after hours and employees' perceived injustice (EPI) and work role overload (WRO). Similarly, the mediating role of work-role overload and the moderating role of psychological detachment were supported. The study concludes by providing theoretical and practical implications and discusses how these findings can be applied within the tourism and hospitality industry. [ABSTRACT FROM AUTHOR]

The public interest doctrine has been deployed by successive state regimes in Indonesia to legitimise the forcible acquisition of land for the state and private interests since the colonial period. This article examines how the government of Indonesia during the Jokowi presidency, has redefined the meaning and scope of 'public interest' in the context of land governance in Indonesia, resulting in an escalation in social conflict and contestation over rights to use and access land. We employ a critical political economy approach to demonstrate how this redefinition of the 'public interest' has provided legitimacy for the national government's actions in forcibly acquiring land using a comparative case study of tourism development in East Nusa Tenggara and a dam construction project in Central Java in Indonesia. While the national government has argued that these 'development' projects benefit local communities, the empirical evidence challenges these claims. This article contributes to the land governance literature by examining the specific role of state institutions. In contrast to the liberal conception of the state as a neutral agent whose function is to balance diverse and conflicting interests over land in society to achieve common goals, the experience in Indonesia shows that the state is in fact the largest and most powerful procurer of land for capital investment in the country. Instead of benefiting the local communities, these state-sponsored development projects are more likely to serve the interests of politico-business elites. • Redefinition of the 'public interest' under the Jokowi presidency in Indonesia has seen an escalation in land conflicts. • A critical political economy lens shows how this redefinition has underpinned state legitimacy in forcibly acquiring land. • The Indonesian state is now the country's largest and most powerful procurer of land for capital investment. • State-sponsored development in the public interest today primarily serves the interests of politico-business elites. [ABSTRACT FROM AUTHOR]

This article examines the issues involved in publicly funded regional arts initiatives, through two contrasting examples of art works that creatively repurpose grain silos in rural Australia: the Silo Art Trail in north-west Victoria, and the silo art practices of the small town of Natimuk in the same region. Via desktop analysis supported by observation and interviews, we consider these initiatives in the context of a turn to arts-led regeneration and creative place-making in rural and regional development approaches and the role of public cultural policy within this. With the majority of public funding for cultural and creative projects in regional communities coming from urban-based governments in Australia (eg federal and state governments), decisions tend to be informed by urban-centric frameworks. Public cultural funding programmes often expect to develop projects that create jobs and generate market demand for creative products that will ensure creative enterprises are economically sustainable. This overlooks broader economic impacts and non-economic values that arts activities bring to rural and regional places, resulting in a misalignment between funding intention and outcomes. A lack of equity inherent in the relationship between urban-generated cultural funding approaches and regional priorities suggests a need for a rethink, to better understand and develop policies for creative practice in the regions that are driven by and responsive to regional priorities and capacities. • Rural arts development offers to redress declining local benefits of agriculture. • Strategies for rural arts regeneration are determined by urban-centric policy. • Large-scale public art on disused rural infrastructure attracts tourism. • Rural public art outcomes are greater when grounded in local community objectives. • Economic success from public art is greater when informed by local conditions. [ABSTRACT FROM AUTHOR]

Abstract Applying Search Engine Optimization (SEO) tools such as TrafficEstimate and Twitter Search, Google Trends, Alexa, SimilarWeb, SEMRUSH, SEO Analyzer, and Moz-Open Site Explorer; this research comparatively evaluates tourism websites of the government of India and of five Indian states. The criteria for selecting state websites are the number of Foreign Tourists Arrival (FTA). Using each SEO tool, individual rank is given first and then the mode of ranks is taken to give the final ranking to six tourism websites. Though there is literature available on evaluating Indian government (central or state) run tourism websites, there is no research available on comparing and ranking state government tourism websites in the Indian context, using Search Engine Optimization tools presented in this research. The result shows that the government of India's website www.tourism.gov.in ranks fourth. Tourism websites of three states i.e. Delhi, Maharashtra, and Tamil Nadu ranks first, second, and third respectively. Highlights • There is no prior study on applying Search Engine Optimization (SEO) tools to evaluate and compare tourism websites. • Government Tourism department's websites are informative but not as popular as privately run tourism websites such as www.tripadvisor.com • Out of six tourism websites evaluated, Delhi tourism website ranks first on selected SEO parameters. • West Bengal state tourism website ranks sixth while the Government of India's tourism website ranks fourth. [ABSTRACT FROM AUTHOR]

In recent years, there has been a significant increase in the utilization of Tourism Recommendation Systems (TRS) to enhance tourist satisfaction. However, planning a trip can be a daunting and time-consuming process, leading to concerns for travelers. This paper focuses on developing a highly personalized TRS that considers the complexities and limitations of tour itinerary planning. To achieve this, we propose an extension of the constrained orienteering problem that selects the most suitable attractions based on various constraints, such as maximum tour duration, mandatory visits, and start and end locations. In addition, we introduce the use of tier constraints to limit the time spent on similar attractions. In this study, we also propose a novel personalization approach that considers the individual preferences of tourists and generates personalized ratings for points of interest. Next, we focus on developing a new greedy genetic algorithm to address the NP-hard problem of finding optimal or near-optimal solutions. To assess the performance of the developed algorithm, we conducted a sensitivity analysis of the input parameters. Using different user profiles, we demonstrated its effectiveness on a real-world London city dataset. Moreover, we conducted a comparative experimental analysis of the algorithm with four baseline algorithms, and the results were statistically analyzed using non-parametric tests such as Wilcoxon and Friedman. Our algorithm achieved the best-known solutions for 100% of the instances tested, demonstrating its efficiency for large-scale problems with 200-300 points of interest. Furthermore, our TRS provides highly personalized tourist trips, making it a valuable tool for tourists. The new greedy genetic algorithm and unique personalization approach are significant features of the new GlobeTrott tourist recommendation system, which is accessible on popular mobile operating systems and through the website at https://www.globetrott.com/. [ABSTRACT FROM AUTHOR]

Identifying client needs to provide optimal services is crucial in tourist destination management. The events held in tourist destinations may help to meet those needs and thus contribute to tourist satisfaction. As with product management, the creation of hierarchical catalogs to classify those events can aid event management. The events that can be found on the internet are listed in dispersed, heterogeneous sources, which makes direct classification a difficult, time-consuming task. The main aim of this work is to create a novel process for automatically classifying an eclectic variety of tourist events using a hierarchical taxonomy, which can be applied to support tourist destination management. Leveraging data science methods such as CRISP-DM, supervised machine learning, and natural language processing techniques, the automatic classification process proposed here allows the creation of a normalized catalog across very different geographical regions. Therefore, we can build catalogs with consistent filters, allowing users to find events regardless of the event categories assigned at source, if any. This is very valuable for companies that offer this kind of information across multiple regions, such as airlines, travel agencies or hotel chains. Ultimately, this tool has the potential to revolutionize the way companies and end users interact with tourist events information. [Display omitted] • Computational techniques are used to classify tourism destination events. • A Large Language Model (BERT) is used to get vectorial representations of events. • A method to automatically classify events is proposed to easy the adoption of standards. • There is great scope for extending this methodology to other applications. [ABSTRACT FROM AUTHOR]

Promoting sustainable development in rural areas through industrial transformation has emerged as a global consensus. The rural complex, characterized by its integration of industrial elements, serves as an advantageous target for China's rural transformation and development. However, the lack of accurate assessment and identification of industrial resource potential has impeded the progress and growth of rural complexes. Therefore, there is a pressing need for an evaluation framework that includes screening and identification functionalities to effectively guide the industrial transformation of rural complexes. Commencing with a precise definition of rural complexes and an explanation of relevant policies, this study combines qualitative theoretical constructs with quantitative multi-criteria decision-making models. Additionally, the study incorporates the gravity model to measure the impact of urban radiation on rural areas. The resulting framework for evaluating industrial resource potential consists of "3 + 7" Modules. Subsequently, utilizing Changsha as a case study, the effectiveness of the evaluation framework is verified across 804 administrative villages. The findings classify these villages into three regions, revealing a circular distribution pattern characterized by decay from the urban center towards the periphery, except for education. Moreover, all modules demonstrate significant spatial autocorrelation. Infrastructure and the ecological environment exert a substantial influence on other industries, while notable synergies exist among the Internet, culture, tourism, and science & technology innovation. Finally, based on the findings, five development suggestions are proposed, focusing on spatial integration and construction mechanisms. The study strengthens the theoretical understanding of rural complexes, provide a practical decision-making tool for project approval processes and the diagnosis of rural industries, and enhance the strategic investment approach toward rural revitalization. • A new evaluation framework for rural complex based on industrial resource potential. • The staged and modular evaluation criteria under internal and external influences. • The gravity model was used to determine the degree of the economic impact of a central city. • Some industrial resources showed a positive correlation and a circle-like distribution. • The resource potential of 804 villages in Changsha was calculated and then analyzed. [ABSTRACT FROM AUTHOR]

Affected by the COVID-19 epidemic, vacation tourism presents a new trend of short-term and short-range, and the traditional multi-day light luxury entertainment vacation has gradually transformed into micro-vacation. Micro-vacation tourism is a new tourism type. This paper complements the "cognition-emotion-overall" three-dimensional model of tourist destination image perception, and considers tourists' feelings in the early, middle and late stages of tourism into the overall framework of micro-vacation tourism destination perception, aiming to clarify the relationship between the image perception of micro-vacation destination and tourists' experience intention, and find out the decisive factors that affect tourists' travel intention through the perception of tourism destination image. Taking the tourism market of Lihuayu eco-tourism resort as the research object, this paper analyzes the micro-tourism market and construct a research model with the cognitive image, emotional image and overall image of the micro-vacation destination as intermediary variables. The findings: the influence of image perception and experience intention of micro-tourism destination is complex and multidimensional. The five dimensions of micro-vacation tourism motivation, micro-vacation tourism preference, cognitive image of micro-vacation tourism destination, emotional image of micro-vacation tourism destination and overall image of micro-vacation tourism destination all have direct or indirect influence on consumers' intention to experience micro-vacation. The micro-vacation market is dominated by weekend short-distance self-help travel. The micro-vacation tourists attach importance to the quality of leisure experience and tend to obtain tourism information from new media platforms. [ABSTRACT FROM AUTHOR]

Understanding tourist mobility patterns of demographic subgroups is vital to tourism planning and management. However, existing empirical studies used various indicators and methods to depict tourist mobility but reached conflicting conclusions across different regions. Existing studies mostly analyzed mobility patterns from a single aspect of mobility indicator, time, and space, which leads to a limited understanding of tourist heterogeneity. Therefore, we proposed a multidimensional framework that combined three aspects and then conducted an empirical study to explore tourist mobility differences. Based on one-month mobile phone data from Chongqing, we identified the differences in mobility indicators, temporal patterns, and spatial patterns among demographic subgroups, which exist in gender, age, and location of origin. The analysis results indicate that older tourists have the highest enthusiasm for tourism, while middle-aged tourists have the lowest. Female tourists have an earlier start time and longer duration of traveling. The spatial structure of neighboring tourists is centered around the railway station, while non-neighboring is the airport. By revealing the different tourism preferences of subgroups, our findings can provide references for tourism planning and travel service provision in rapidly developing tourist cities. • We present a multidimensional framework to understand tourist mobility patterns. • Tourist mobility patterns are compared across different demographic subgroups from indicator, time and space aspects. • We provide some new insights into mobility patterns in terms of gender, age, and location of origin. • We discuss how the obtained insights can help the stakeholders. [ABSTRACT FROM AUTHOR]

Past research in marketing has shown metacognitive ease affects product evaluation, yet little is known about whether it also affects the persuasiveness of travel texts. Through three experiments, the authors show metacognitive ease induced by font (italic or non-italic style, typeface, and color grey or black) affects people's perceptions of a tour, while tourism motivation determines the direction of the effect. Results indicate that when a proposed tour offers relaxation/rest, easy-to-read (vs. difficult-to-read) font increases preference for the tour (i.e., willingness to pay); but when a tour offers adventure/excitement, difficult-to-read (vs. easy-to-read) font increases preference for it. The samples sizes ranged from 138 to 205 Chinese student/adult respondents. [ABSTRACT FROM AUTHOR]

The overall purpose of this study is to explore the relationship between emotion tendency and e-WOM publishing during four phases of tourists' travel experience, from the multiplatform perspective, which has not been much studied in the field of tourism management. We firstly carried out a sentiment analysis of reviews on two platforms, the results indicated that there is a ∖ distinct emotion polarity. Then we measured 260 Chinese respondents' emotion tendency in four scenes using mDES and investigated their selection of different platforms to publish e-WOM. The statistical analysis and correlation analysis revealed that tourists with positive affect tend to share their experiences on social media while those with negative affect prefer integrated tourism websites. The results also revealed that the positive emotions are more frequent than negative emotions in a journey and the emotions of males and females are quite different. Finally, we give some management suggestions to different platforms. [ABSTRACT FROM AUTHOR]

The effect of online reviews on resulting decisions attracted the interests of merchants and researchers in different fields. According to existing studies, the decisions of tourists are highly likely modified after browsing online reviews from other travelers on a tourism website. The manner in which online reviews on tourism websites are utilized to select hotels and support tourists is a noteworthy research problem. Online reviews of a hotel are provided by various tourists with respect to different criteria; thus, each tourist is regarded as a decision-maker. In this instance, the problem of hotel selection is based on online reviews in a tourism website and is expressed as a multi-criteria decision-making problem. In this study, a mathematical model was designed to select appropriate hotels on websites. First, a new comparison method for linguistic distribution assessments was proposed based on linguistic scale functions. Second, a novel distance measurement between linguistic distribution assessments with different numbers of linguistic terms was defined with an adjustable parameter. Third, a model for calculating weights and a mathematical model were constructed according to the idea of prioritized aggregation operator and distance measurement. Finally, a case study of TripAdvisor.com was conducted to select suitable hotels using online reviews of hotels. Data analysis was completed to prove the viability of the designed model. [ABSTRACT FROM AUTHOR]

Hotel selection on tourism websites has been a prevailing trend in traveling in recent years, and selecting a suitable hotel is a high-risk decision for millions of tourists because of the intrinsic imperceptibility of the provided products. Decision support models for hotel selection have drawn the interest of numerous scholars. The problem is that some existing models cannot address substantial amounts of online information, and they neglect the influence of interrelationships among different criteria on tourists’ decisions. To cover these defects, an applicable hotel decision support model is developed for tourists utilizing online reviews on TripAdvisor.com. Considering a great deal of review information associated with hotels posted by numerous tourists on TripAdvisor.com, probabilistic linguistic term sets (PLTSs) are introduced to summarize this information statistically. Processing qualitative concepts requires effective support of reliable tools; then, a cloud model can be employed to deal with probabilistic linguistic information. First, PLTSs are converted, and a novel concept of probabilistic linguistic integrated cloud (PLIC) is proposed. Moreover, the essential algorithms and distance measure of PLICs are defined. Two information fusion tools are subsequently presented based on Heronian mean operator. Then, the hotel decision support model is established. Finally, a hotel selection problem on TripAdvisor.com is provided to demonstrate the model. Its stability and validity are further verified by a sensitivity analysis and comparison with other extant methods. [ABSTRACT FROM AUTHOR]

Nowadays, the medical tourism industry encourages many healthcare practitioners to provide high-quality and low-cost medical services for patients worldwide. The development of operations research models and algorithms is one important instrument for improving the medical tourism industry based on the economic, political, social, and cultural aspects. In this paper, a medical tourism trip design problem is developed where patients travel from their city of residence to a destination city that may be in another country to receive high-quality and low-cost medical care. The most important part of this problem is to visit a number of tourist cities for each patient individually in the destination. In addition to the total cost, the patients prefer to increase the attractiveness of trips by referring to the quality of medical services and the attractiveness of visiting tourist cities. As far as we know in the area of medical tourist studies, no study has considered the minimization of total cost and maximization of the attractiveness of trips, simultaneously using utility function. The proposed multi-objective optimization model assigns the patients from the origin country to the hospitals in the destination country while making their routing and scheduling decisions to visit the tourist cities. The proposed model is limited by patients' interests and time restrictions while allocating patients to the hospital and orienteering the patients toward visiting tourist attractions. As a complex optimization problem, another significant novelty of this paper is the proposal of a local search-based non-dominated sorting genetic algorithm (LSNSGA-II) for solving the proposed multi-objective optimization model. The proposed algorithm is compared with the original non-dominated sorting genetic algorithm (NSGA-II) and epsilon constraint (EC) method based on different multi-objective criteria. Finally, one main finding from our analyses is finding a trade-off between the total cost and attractiveness of trips as a challenging decision while proposing high-quality solutions in a reasonable time (i.e., less than one hour). • A new multi-objective medical tourism trip design problem is developed. • Proposed model minimizes the total cost while maximizing the attractivity of trips. • A utility function is used to compute variable staying time for visiting tourist places. • An efficient local search-based non-dominated sorting genetic algorithm is introduced. [ABSTRACT FROM AUTHOR]

The task of organizing ecosystem accounting and integrating the value of ecosystems and ecosystem services into the management process has been set in Russia. The municipal level is the key one in the system of ecological spatial planning. However, the analysis of the official documents on spatial planning in Russia revealed that ecosystem services are still to be integrated into them. This paper aims to develop guidelines for the formation and implementation of integrated plans for the development of rural areas in the aspect of ecosystem development. The suggested methods of ES evaluation and monetization are based on the use of open statistical data and available digital land cover maps. This way, ecosystem services were calculated in biophysical indicators by converting the area of different types of ecosystems into the demanded and supplied volumes of ecosystem services. The described approaches were approbated on four municipal districts in different federal subjects of Russia (Kiznerskiy district in the Udmurt Republic; Elizovskiy district in Kamchatskiy krai; Maikopskiy district in the Adygeya Republic; and Bobrovskiy district in Voronezh oblast). It reveals that carbon regulation makes up the major part of a total ecosystem services value in the studied districts, thus making regulating services constitute the largest share of the total supplied ecosystem services volume. Recreational and other cultural ecosystem services do not make up a considerable part of the total ES value in any district. These evaluations, on the one hand, form an incomplete and exaggerated idea of ecosystems' value as a source of natural resources; and on the other, detract their regulating and cultural services, which are also extremely significant for the sustainable development on different spatial levels. • Open data bases for Russian municipalities lack geospatial, statistical and monitoring materials, which are essential for accurate assessment of ES at the regional level. • Regulating services perform the largest and most valuable volume of ES in the districts, but their assessment is the most problematic one. • Districts with particularly valuable ecosystems have the most intense tourism development, straining the ecological potential. • The assessment of ES at the regional level in Russia requires an individual time-consuming approach that is hard to complete for all 1600 municipal districts 1 1 Statistical data for municipal districts of other federal subjects is available by adding the district's number at the end of the presented link at www.gks.ru: 30 – Kamchatskiy; 20 – Voronezhskaya; 79 – Maikopskiy; 94 – Udmurtskaya. [ABSTRACT FROM AUTHOR]

Recreation and ecotourism opportunities are significant and complex Cultural Ecosystem Services, including various ecological and socio-economic aspects. Therefore, an integrated approach is needed to address these service complexities to help inform recreation and tourism planning and management. This study aims to develop an integrated model to map and assess Recreation Opportunity Ecosystem Services (ROES) in the north of Iran involving various ecosystem attributes and indicators. The methodological framework followed in this study allowed us to identify the spatial distribution pattern of recreation ES supply and demand in the study area. Particularly, this study explored the spatial mismatches between the capacity of ecosystems to provide recreational services and societal needs by applying a supply-demand ratio indicator. To predict the future pattern of recreation ES provision in the study area, two scenarios were performed. The results showed that the areas with the highest ROES provision account for only a small share of the study area where there is a high ecosystem potential to fulfill human demand for recreation ES. The results of the mismatch analysis revealed that urban and rural areas showed a shortfall in supply, whereas the areas with a high degree of naturalness exhibited an excess supply than demand. The hot spot analysis performed for two current and future scenarios showed that the areas of recreation ES hot spots considerably decreased due to population growth and land use change in the study area over a 30-year period. Our findings can provide insights for decision-making and spatial planning to maintain recreation ES and the benefits delivered to users. • Mapping and analyzing recreation ES supply and demand at a regional scale. • Identifying spatial distribution pattern of Recreation Opportunity Ecosystem Services (ROES) across the study area. • Mismatch analysis to identify relationship between recreation supply and demand. • Hot spot and cold spot analysis to generate clustered zones for inform tourism planning and management in the territory. • Providing insights for land use planning and decision-making. [ABSTRACT FROM AUTHOR]

The technology deployment in smart e-tourism brings high potential in terms of customer data, events, reservations, and others. It acts as an effective and personalized guide to aid travelers. There is an increasing variety of smart e-tourism apps with multiple categories and criteria, but in terms of decision making, this presents a multicriteria complex problem to determine the best app from a group of available options with high criteria subjectivity. Literature reviews have evaluated and modeled the existing smart e-tourism apps alternatives, but informational uncertainty remains. The fuzzy sets and Multi-Attribute Decision Analysis (MADA) were used to handle the subjectivity issue. However, this process includes levels of uncertainty, which affects the decisions made and still an open issues. Spherical fuzzy rough sets (SFRSs) environment are useful in this situation for resolving fuzziness and ambiguity. This paper proposed a decision modeling approach for smart E-Tourism data management applications based on SFRSs environment. For methodology: firstly, a decision matrix is adopted for 5 different categories of Smart E-tourism's system applications on the basis of the integrated 12 evaluation criteria. Secondly, a new formulation and development formulating a new extension of FWZIC, called a Spherical Fuzzy Rough-Weighted Zero-Inconsistency (SFR-WZIC), for weighting the smart key concept attributes involved in modeling smart e-tourism, whereas a new formulation and development for a new extension of FDOSM, called a Spherical Fuzzy Rough Decision by Opinion Score Method (SFR-DOSM), for modeling the applications of smart e-tourism per each e-tourism category; then, the new developments are integrated. The proposed methods were evaluated using systematic ranking and sensitivity analysis. • A homogeneous SFRS-MCDM framework for benchmarking smart e-tourism applications is developed. • A new formulation of FWZIC and FDOSM based on SFRS are presented. • Systematic ranking and sensitivity analysis assessments were presented to evaluate the robustness of the proposed work. [ABSTRACT FROM AUTHOR]

The development of road trips and car campsites depends on the construction of road infrastructure. The development of road trips and car campsites is described as follows: • Since 2016, high-speed rail travel and road travel have become the mainstream, and people's travel patterns have undergone significant changes. • China's self-drive tour industry is growing steadily. In 2016, the number of self-drive tour employees reached 2.64 billion, up 12.8% year on year, accounting for 59.5% of the total domestic tourism. • Due to the differences in economic development, transportation infrastructure and tourist attractions in different regions, the proportion of self-drive trips ranged from 49 percent to 65 percent. Road trips in Beijing remained the most popular form of road trips, accounting for 84.32 percent of the total. • In September 2016, six national ministries and commissions jointly issued the Notice on Accelerating the Construction of Self-driving RV Camp [1]. The implementation of the paid leave system, the improvement of road infrastructure, the regulation of scenic spots and the regulation of market behavior have all promoted the significant expansion of motor campsites, thus promoting the development of leisure tourism in China. The development of self-driving tourism and automobile campgrounds depends on the construction of road infrastructure. In this study, we utilized aeronautical reconnaissance coverage geographic information system (ArcGIS), spatial analysis technology and accessibility model to quantitatively examine the accessibility and spatial pattern of automobile campgrounds in Beijing. Our findings reveal that Beijing's automobile campgrounds exhibit a circular distribution pattern, with decreasing accessibility from the center to the periphery areas. The overall accessibility maintains high-level road directivity, with an average travel time to automobile campgrounds ranging from 0.028 to 3.37 h. Access to automobile campgrounds is higher in the central and southern-central regions compared to the northwest and southwest regions, highlighting a highly unbalanced spatial pattern of accessibility. Finally, we provide suggestions for optimizing the accessibility of automobile campgrounds in Beijing based on our research. [Display omitted] [ABSTRACT FROM AUTHOR]

By using a human-centric approach to online recommender systems, this research aims to estimate the language discrepancies of which travelers and destination marketers describe the travel experiences across 11 tourism destinations in USA. In order to address the research purpose, data has been collected from two different sources that reflect the views of travelers and service providers. Then, a set of text data mining methods (i.e., clustering analysis and Jaccard distance score) was applied to identify the language differences between travelers and CVB websites, according to the following categories: shopping, dining, nightlife/activities, and attractions. Some possible methodological extensions that can improve recommendation capabilities, and managerial implications of these findings are provided. [ABSTRACT FROM AUTHOR]

The impact of information and communications technology (ICT) in tourism (e-tourism) has altered the ways tourism services are accessed and consumed. Ubiquitous and highly innovative ICTs provide different channels for consumers to use tourism services; thus, studies on e-tourism are numerous and fragmented. Different factors account for how consumers embrace these channels. The purpose of this study is to review studies on consumers’ acceptance or adoption of e-tourism in order to group the studies, synthesize the theories, models and frameworks used and identify the antecedents influencing consumers’ e-tourism acceptance and usage. A total of 71 studies from 2005 to 2016 (inclusive) from both tourism-based and non-tourism-based journals were selected, synthesized, and included. Based on their contexts, similarity and relevance, the 71 studies were segregated into three distinct groups. This study found that research among the groups is uneven. Implications and research directions are suggested. [ABSTRACT FROM AUTHOR]

Tourism decisions are interdependent of one another. This study aims to explore the interrelations among three pertinent tourism choices, i.e., travel season, transport mode and length of stay, from a data-driven perspective. To achieve a joint model of three travel behavioural decisions, this paper adopts a Frank-type fully nested Archimedean copula function, which is capable of efficiently incorporating a logistic regression model, a multinomial logit model and a lognormal accelerated failure time model. Then, we empirically evaluate the proposed model framework using single-destination Sydney-based trip-level data collected in 2017–2018. Gumbel, Clayton and Frank copula results are compared. To illustrate its application, the modelling results are used to build a simulated COVID-19 pandemic scenario according to the social distancing restrictions within New South Wales, Australia, and a three-dimensional elasticity analysis for trip destinations is performed. The findings suggest the model provides nuanced insights into simulating tourist behaviours and transport policy appraisal aimed at tourism recovery or/and development. [ABSTRACT FROM AUTHOR]

The conservation and tourism development of World Heritage (WH) sites has always been a key and urgent scientific issue to be solved urgently by academia and industry all over the world. An increasing number of researchers and practitioners are paying attention to this issue. However, there is a lack of a comprehensive literature review on this topic. To fill this gap, this study conducts a systematic literature review (SLR) based on 179 related studies retrieved from the Web of Science (WoS) and Google Scholar (GS) databases. Focusing on the research question of the conservation and tourism development of World Natural Heritage (WNH) sites, we built an SLR framework to implement the review process. First, quantitative research was conducted to analyse the annual numbers, content and continents of the published literature. Second, we classified and summarized the main progress and achievements from theoretical research, technical methods, model construction, monitoring and evaluating, and application demonstration. Finally, in view of the current research situation of the conservation and tourism development of WNH sites, we proposed eight key scientific issues to be solved and several directions for future research. [ABSTRACT FROM AUTHOR]

• The impact of multi-criteria ratings on recommendation agents performance is investigated. • LDA for feature extraction and EM and SOM for data clustering are used. • Online customers' reviews from TripAdviosr are analysed. • Sparsity issue was alleviated by the clustering techniques. • The accuracy of CF recommender systems was improved by multi-criteria ratings. Recommender Systems (RSs) have played an important role in online retailing portals and customers' decision-making processes. Recommender systems that are based on the conventional Collaborative Filtering (CF) approach rely on single customers' ratings on retailing websites. Multi-criteria CF (MCCF) approaches that rely on multi-aspects of the products have provided more reliable and effective recommendations on retailing websites. However, these approaches should be improved in terms of accuracy by solving sparsity issues and incorporating criteria ratings. In addition, most of the recommendation agents that are based on MCCF cannot learn automatically from the features of the products to model customers' preferences and generate accurate recommendations on retailing websites. Besides, although previous studies have utilized single and multi-criteria ratings in recommendation agents of tourism websites, still, if there is a lack of ratings of items, most of these systems will fail to generate accurate recommendations to users. In this research, we develop a new recommendation agent based on a MCCF approach to effectively improve the performance of previous recommendation systems for tourism websites. The results demonstrated that the method can predict the most relevant products to users, particularly when the dataset is sparse. [ABSTRACT FROM AUTHOR]