Limited open information sharing and mobility promotes sustainability of jaguar tourism in Pantanal wetland, Brazil.

Wildlife tourism plays a crucial role in biodiversity conservation. However, long-term sustainability is difficult to achieve. In this paper, we use property theory to produce a mathematical model that aims to better support stakeholders from the wildlife tourism industry to better guarantee a balance between sightings probability, tourists' overall experience and operators' sharing behaviour. We illustrate our model with the case study of Porto Jofre in the Pantanal wetland, Brazil. We show that while dealing with low sighting probability, tourist operators must share information about species' locations, leading to a system of open access regarding mobility and information. However, when sightings become common, sharing must be restricted to a bounded group avoiding overcrowding, a system of limited open access. Finally, when the sighting probability is high, no sharing is needed to achieve maximum overall experience. Our case study in Porto Jofre, Pantanal, Brazil, clearly shows these shifts in terms of governance strategies. We show that by looking at sighting probability it is possible to predict the best optimal social strategy that will guarantee long-term sustainability of the wildlife tourism initiatives. We also show the need for external support on adaptation in cases where current strategies do not match the predicted ones.

Spatial distribution patterns and factors influencing rural tourism destinations: An empirical study of China's agritainment resorts.

Agritainment is one of the essential aspects of rural tourism and plays an important role in the economic transformation and revitalization of rural areas. Taking 9200 agritainment resorts in China as a research object, this paper systematically uses geospatial analysis methods to analyze their spatial distribution patterns and influencing mechanisms. The results indicate: (1) All types of agritainment have a condensed distribution in space and are oriented in the northeast-southwest direction, with a central axis generally located in the Beijing-Zhengzhou-Wuhan line. (2) The distribution of agritainment is uneven across different spatial scales, and there are high-density clusters in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Sichuan-Chongqing region as the core, and sub-high-density distribution areas in the Shaanxi-Gansu-Ningxia border, the southern coastal region, and the Xiangan-Jiang-Hubei border, manifesting prominent spatial distribution characteristics of large agglomeration and low dispersion. (3) Agritainment has a significant positive spatial autocorrelation. The Matthew effect is highly significant in space. The distribution of cold hot spots in the agritainment space shows a distribution pattern of "hot in the south and cold in the north." (4) The spatial distribution of agritainment is influenced by human factors such as society, economy, and the tourism industry as well as natural factors such as terrain, water systems, and climate. The intensity of influence of first-level human factors on the spatial distribution of agritainment ranks as follows: tourism industry factors (0.69) > social factors (0.37) > economic factors (0.30). The natural distribution of agritainment tends to be in humid plain and hilly areas with an altitude below 1000 m and annual precipitation above 800 mm. Agritainment is mainly distributed in the subtropical monsoon climate area adjacent to rivers. The research findings offer valuable insights for optimizing the spatial distribution pattern of agritainment in China, promoting the high-quality development of agritainment, and the sustainable development of rural tourism.

Socio-demographic analysis of destination selection factors for Himalayan Hill destinations.

Background: The towering peaks of the Himalayas lie in troves of captivating hill destinations, especially in India. Each destination aims to provide tourists with unique experiences and breath-taking landscapes. Understanding the tapestry of factors that weave the allure of these destinations and draw visitors from diverse backgrounds remains intriguing. Method: This study delves into the socio-demographic tapestry of Himalayan hill destination selection, unraveling the complex interplay of demographic characteristics, social influences, and individual motivations that shape tourists' choices. Results: This study aims to answer why different tourists have different travel choices and what factors are the drivers behind such choices. The results show that destination selection factors are similar irrespective of respondents' socio-demographic variabilities; however, for a few factors, the results are reversed. Conclusion: The study has implications for policymakers and the limitations of the research discussed at the end.

Spatial distribution of the sport fishing in the state of Amazonas, northern Brazil.

The objective of this study was to spatialize sport fishing operations and assess the frequency of the use of the fishing areas in the state of Amazonas by combining the Geographic Information System (GIS) approach and information available in the documents sent to the Instituto de Proteção Ambiental do Amazonas (IPAAM). Information on sport fishing tourism operations was gathered from the IPAAM database and fishing licenses (FLs). Data analysis was conducted utilizing descriptive analysis, and the spatialization of the locations was performed using Q-GIS software. From 2002 to August 2021, 163 requests for FLs were made. There was a decrease in the amount of first time FL requests, with a peak in 2018 and 2019, N=17 and N=18, respectively. The activity is conducted in 24 municipalities, with Barcelos (31.36%) and Presidente Figueiredo (17.75%) being the most popular. At the sub-basin level, sport fishing is notably present in the Negro, Amazonas, Aripuanã, Madeira, Purus and Solimões River basins. Overall, 26.38% of operations take place in conservation areas, specifically in sustainable development reserves (SDRs). Barcelos recorded the largest number of rivers used, with 15 rivers. These results can support future proposals for the sustainable management of fisheries through the zoning of fishing areas in the state of Amazonas.

Exploring tourists' preferences and willingness to pay for national park recreation improvements based on regret and utility comparison.

Research on the improvement of national park recreation policies has attracted much attention to discrete choice experiments to obtain tourists' preferences and willingness to pay. However, individual choice behavior is extremely complex, and the single Random Utility Maximization (RUM) model ignores anticipated regret and is insufficient to explain individuals' actual choice behavior. To investigate whether regret influences tourists' choices regarding the improvement of national park recreation attributes, this study introduces the Random Regret Minimization (RRM) model and explores the performance of polynomial logit models and hybrid latent class models in analyzing discrete choice models based on utility and regret. By constructing a hybrid utility-regret model, we examine how tourists trade off between attributes such as vegetation coverage, water clarity, amount of litter, and level of crowding in national park recreation. Results indicate that the RRM model has better goodness-of-fit and predictive ability than the RUM model, indicating that regret is a significant choice paradigm, and the hybrid model better explains respondents' choices. Specifically, 62.5% of tourists' choices are driven by regret, and regret-driven respondents are more inclined to increase vegetation coverage and improve water clarity, while utility-driven respondents are more inclined to reduce litter and crowding. This study not only provides a reference for managers to develop more optimal recreation improvement strategies but also offers theoretical insights for national park recreation improvement policies.

Developing an evaluation model for urban tourism competitiveness: combining community construction and community service to foster sustainable development of cities.

Introduction: This study aims to develop a comprehensive evaluation model for urban tourism competitiveness in China. Given China's transition into a mature tourist destination, there is a pressing need for a framework that can assess the effectiveness of its urban tourism strategies. The model presented in this study is designed to provide a holistic understanding of the factors influencing urban tourism competitiveness in the Chinese context. Methods: The methodology employed in this study combines both qualitative and quantitative approaches. A modified version of Porter's Diamond Model serves as the primary framework, augmented by the IMD World Competitiveness Center: International Institute for Management Development (IMD) framework to incorporate social governance and environmental dimensions. To derive comprehensive scores for sustainable development, a linear weighted evaluation method was used, incorporating the coefficient of variation entropy weight method. This approach allows for a quantitative assessment of urban tourism competitiveness from 2008 to 2019. Results: The key findings of the study reveal significant challenges within the current urban tourism landscape in China. These challenges include homogeneous competition, a lack of strategic management, and insufficient service quality. Furthermore, the study identifies the need for greater emphasis on sustainable tourism development, balancing economic benefits with the preservation of cultural and natural assets. Discussion: Based on the findings, the study proposes several solutions to address the identified challenges. These solutions include creating boutique inland tourism routes, developing unique urban tourism brands, and enhancing regional cooperation and management practices. Additionally, the study emphasizes the importance of integrating community development and services into the evaluation model to foster sustainable tourism development. The proposed solutions offer actionable insights for policymakers and planners seeking to improve the competitiveness and sustainability of urban tourism in China.

Sports tourism downturn: The impact of COVID-19 on Chinese tourism among urban and rural residents under epidemic.

BACKGROUND: China's sports tourism has seen significant growth since the 2008 Olympics, only to be challenged by the coronavirus disease 2019 pandemic. This study aims to assess the impact of the pandemic on China's tourism and sports tourism, which are highly interrelated. METHOD: Data and materials from 2019 to mid-2023 were systematically collected and analyzed, focusing on seasonal tourism reports published on official local networks in China. RESULTS: The study reveals a prepandemic annual tourism consumption of 6.63 trillion CNY, a 52.1% decline during the pandemic, and a postpandemic rebound exceeding pre-coronavirus disease levels. CONCLUSION: The pandemic's impact was profound, yet the resilience of China's tourism sector is evident, with a focus on the recovery's implications for sustainable growth. Despite the pandemic's disruption, China's tourism and sports tourism sectors have demonstrated resilience and potential for continued growth, warranting ongoing attention.

Smartphone region-wise image indoor localization using deep learning for indoor tourist attraction.

Smart indoor tourist attractions, such as smart museums and aquariums, require a significant investment in indoor localization devices. The use of Global Positioning Systems on smartphones is unsuitable for scenarios where dense materials such as concrete and metal blocks weaken GPS signals, which is most often the case in indoor tourist attractions. With the help of deep learning, indoor localization can be done region by region using smartphone images. This approach requires no investment in infrastructure and reduces the cost and time needed to turn museums and aquariums into smart museums or smart aquariums. In this paper, we propose using deep learning algorithms to classify locations based on smartphone camera images for indoor tourist attractions. We evaluate our proposal in a real-world scenario in Brazil. We extensively collect images from ten different smartphones to classify biome-themed fish tanks in the Pantanal Biopark, creating a new dataset of 3654 images. We tested seven state-of-the-art neural networks, three of them based on transformers. On average, we achieved a precision of about 90% and a recall and f-score of about 89%. The results show that the proposal is suitable for most indoor tourist attractions.

Using geotagged facial expressions to visualize and characterize different demographic groups' emotion in theme parks.

Tourism is an emotional sphere, and researchers focus on emotions to optimize tourism experiences. Tourism studies on emotions mostly ignore differences in emotions across demographic tourist groups by gender and age, thus limiting the understanding of emotions to the explicit characteristics of tourists' emotions. On the basis of geotagged facial expressions on social media platforms, this study aims to visualize the emotions of groups in scenic spots and then reveal the variations between groups' emotions within theme parks. By employing a facial recognition algorithm, an emotion distribution graph was proposed to represent groups' emotions in detail. Some analytical methods were combined to characterize of the emotion distribution of each group. Through a comprehensive comparison, the results suggest that there are unique characteristics of emotion distribution for each group and considerable variations between them. This study helps researchers achieve a deeper understanding of tourists' emotional differences and enhances the theorization of emotions. This research also highlights the advantages and significant practical implications of our method framework.

Sensitivity analysis and global stability of epidemic between Thais and tourists for Covid -19.

This study employs a mathematical model to analyze and forecast the severe outbreak of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), focusing on the socio-economic ramifications within the Thai population and among foreign tourists. Specifically, the model examines the impact of the disease on various population groups, including susceptible (S), exposed (E), infected (I), quarantined (Q), and recovered (R) individuals among tourists visiting the country. The stability theory of differential equations is utilized to validate the mathematical model. This involves assessing the stability of both the disease-free equilibrium and the endemic equilibrium using the basic reproduction number. Emphasis is placed on local stability, the positivity of solutions, and the invariant regions of solutions. Additionally, a sensitivity analysis of the model is conducted. The computation of the basic reproduction number (R0) reveals that the disease-free equilibrium is locally asymptotically stable when R0 is less than 1, whereas the endemic equilibrium is locally asymptotically stable when R0 exceeds 1. Notably, both equilibriums are globally asymptotically stable under the same conditions. Through numerical simulations, the study concludes that the outcome of COVID-19 is most sensitive to reductions in transmission rates. Furthermore, the sensitivity of the model to all parameters is thoroughly considered, informing strategies for disease control through various intervention measures.

Spatial distribution characteristics and influencing factors of tourism resources based on point of interest data.

The agglomeration and dispersion of tourist attractions in space greatly affect the development of regional tourism resources and the consumption choice of tourism market. At present, the research on the spatial distribution characteristics of tourist attractions and their influencing factors mainly adopts induction and investigation, and there is a lack of effective statistical models for the research on the spatial distribution of tourist attractions and their influencing factors in some historical and cultural ancient cities. This paper uses Internet technology to obtain the spatial distribution data of tourist attractions in Shaoxing city, and uses mean nearest neighbor analysis, nuclear density analysis, imbalance index analysis, standard deviation ellipse and other spatial statistical analysis techniques and geographical detector methods to study the spatial distribution characteristics and influencing factors of tourist attractions in Shaoxing City. This paper studied the distribution characteristics of tourist attractions in Shaoxing city, such as spatial aggregation, distribution equilibrium and spatial orientation, and applied geographical detector to study the influencing factors of the spatial distribution of scenic spots. It was concluded that the spatial distribution pattern of scenic spots was affected by various factors such as natural environment, social environment and economic environment. The explanatory power of two-factor interaction is obviously stronger than that of single factor. The research results provide scientific basis for the planning, layout and development of tourist attractions in Shaoxing and its similar cities, and then promote the high-quality development of tourism in Shaoxing and its similar historical and cultural ancient cities.

Impact of tourism on metal concentrations in Phorcus sauciatus due to the COVID-19 pandemic period in Canary Islands (CE Atlantic, Spain).

The pandemic (COVID-19) had diverse effects on marine pollution. Throughout the lockdown periods, temporary enhancements in water quality and biodiversity were observed due to reduced human activity and constraints on travel and maritime transportation. The marine snail, Phorcus sauciatus, served as an indicator for marine pollution, and samples were collected in Tenerife, Canary Islands, during various months in 2020. The findings indicated that metal concentrations in Phorcus sauciatus were higher in February but declined in July and December as a result of reduced tourist activity during the pandemic. This underscores the significance of promoting sustainable tourism in the Canary Islands to mitigate high metal concentrations in the marine environment. The COVID-19 pandemic had a positive impact on reducing metal concentrations in marine pollution, underscoring the importance of adopting sustainable tourism practices to protect marine ecosystems.

Exploring the influence of historical storytelling on cultural heritage tourists' revisit intention: A case study of the Mogao Grottoes in Dunhuang.

The revisit intention of tourists has long been a focal point of academic inquiry. However, there is still insufficient research on the antecedents of revisit intention from the perspectives of historical storytelling, destination image and perceived value. Taking the Mogao Grottoes in Dunhuang, a UNESCO World Heritage Site, as a case study, this paper, based on stimulus-organism-response (SOR) theory, examines the impact of historical storytelling on the destination image, perceived value, and revisit intention. Additionally, it further explores the mediating role of destination image and perceived value, as well as the moderating effect of place attachment in this chain. The research findings indicate that: (1) Historical storytelling significantly enhances tourists' perception of the tourism experience and revisit intention; (2) The study supports the mediating effect of destination image and perceived value; (3) Place attachment has a significant positive moderating effect between historical storytelling and revisit intention. Effective historical storytelling can significantly enhance destination image and perceived value, improve tourists' participation and satisfaction in tourism, stimulate revisit intention, and promote the sustainable development of tourist destinations. These findings enrich the research content of cultural heritage tourism, providing valuable suggestions for improving the management level of cultural heritage tourism attractions and increasing visitors' revisit intention.

The patronage of religious tourism seen from its motivations that predict satisfaction and loyalty: The Virgin of Chaguaya in Bolivia.

This study focused on pilgrimages as part of religious tourism and aimed to achieve the following objectives: identify the main motivational factors of religious tourism focused on pilgrimages; analyze the motivational dimensions that predict satisfaction in religious tourism focused on pilgrimages; analyze the motivational dimensions that predict loyalty in religious tourism focused on pilgrimages. The study was conducted during the pilgrimage to the Virgin of Chaguaya in Bolivia. The sample consisted of 384 tourists who were surveyed on-site. The statistical techniques used included factor analysis and multiple regression. The results revealed four motivational dimensions: Tourism and Escape, Religious Experience, Belief Experience, and Shopping. Additionally, specific motivations that influence the satisfaction and loyalty of attendees at religious events such as pilgrimages have been identified, among them the "Religious Experience" and the "Belief Experience" motivational dimensions. The findings will contribute to planning and management guidelines for religious event administrators and provide information to academic literature.

Understanding the impact of tourist behavior change on travel agencies in developing countries: Strategies for enhancing the tourist experience.

The study investigates the impact of tourist behavior change on travel agencies in developing countries, with a focus on strategies for enhancing the tourist experience. The research aims to identify the main factors influencing tourist purchasing behavior and understand their relationship with the customer experience. Data were collected from 368 experienced tourists in Ho Chi Minh City and Hanoi, Vietnam, using a combination of convenience and random sampling. Partial Least Squares Structural Equation modeling (PLS-SEM) is employed to analyze the research model. The findings confirm that product quality, product price, brand image, and marketing strategy significantly influence tourist purchasing behavior. Importantly, the results highlight the indirect effect of these factors on purchasing behavior, mediated through customer experience. It suggests that enhancing the customer experience is a crucial aspect of influencing tourist purchasing decisions. Based on these findings, industry managers and travel agents in developing countries should prioritize enhancing customer experience and building a strong brand through personalized services, digital integration, and active social media engagement. Implementing dynamic pricing strategies and targeted marketing campaigns that address safety concerns and highlight local experiences are crucial for competitiveness and attracting travelers post-crisis. Future research should explore the long-term effects of these strategies on travel agency performance and adapt the model to specific regional contexts. By adopting these multifaceted approaches, travel agencies in developing countries can enhance their competitiveness and better navigate the changing tourist behavior in the post-crisis era.

Identifying the determinants of tourism receipts of Thailand and relevant determinant-determinant interactions.

The study examined the determinants that affect tourism receipts in Thailand. To this end, quarterly data from eight main provinces of Thailand from the period 2015-2019 were used and constituted a repeated measures design. Accordingly, a generalized linear mixed model was applied for developing two different random intercept models by treating 1) province, and 2) a combination of province and calendar quarter as cluster-specific effects. It was found that determinants that increased tourism receipts were the number of visitors, the average cost per day, the length of stay of visitors, the presence of low-cost airlines, and a relatively low offence rate. Moreover, an increase in the number of visitors in the fourth quarter produced a higher amount of additional receipts as compared to a similar increase in the first quarter. Specifically, for Thailand attracting high-spending tourists and extending tourist visas for more than 30 days is recommended. Beyond Thailand, uncovering interaction effects as described above may help tourism agencies to focus their limited resources on the determinants that matter.

Research on risk assessment of cruise tourism supply chain based on catastrophe theory.

The past COVID-19 outbreak caused a huge impact on China's cruise industry. Now that China's cruise industry is about to recover, how to assess the risks faced by the cruise industry has become an important issue. On this basis, this paper constructs China's cruise tourism supply chain and supply chain risk assessment system based on the research contributions made by previous researchers, evaluates the risk indicators of China's cruise tourism supply chain based on the catastrophe theory, and derives the risk assessment results through the catastrophe progression method, which can be used as a reference for the safe operation of cruise lines in the future.

Several intuitionistic fuzzy hamy mean operators with complex interval values and their application in assessing the quality of tourism services.

In order to assess the quality of senior tourism services in vacation destinations, we examine complex interval valued intuitionistic Fuzzy Dombi Hamy Mean (CIVIFDHM) operators. These operators successfully manage imprecision and uncertainty in the preferences of senior tourists. However, the Hamy mean (HM) operator can identify the connections between various input data sets and produce excellent outcomes when combining and evaluating information. We illustrate their usefulness and efficacy through a case study, providing a strong instrument for improving service quality for senior citizens and promoting an inclusive and fulfilling travel experience. In this work, we develop the HM operator and Dombi operations with Complex interval valued intuitionistic fuzzy numbers (CIVIFNs). We recommend the CIVIFDHM operator, complex interval valued intuitionistic fuzzy weighted Dombi Hamy mean (CIVIFWDHM), complex interval valued intuitionistic fuzzy dual Dombi Hamy mean (CIVIFDDHM), and complex interval valued intuitionistic fuzzy weighted dual Dombi Hamy mean (CIVIFWDD) operators. Next, multiple attribute decision making (MADM) models are constructed with the help of CIVIFWDHM and CIVIFWDDHM operators. We provided an evaluation of an older tourism operator in a tourist area as an example to show the suggested models.

Perceived differences in coastal tourism image under tourist experience-IPA analysis based on UGC data of 12 coastal cities.

The destination image perceived by tourists is crucial to coastal tourism market positioning and marketing. This paper utilizes tourists' Internet-generated content from 2017-2021, adopts the jieba text analysis method to identify the cognitive, emotional, and overall image of coastal tourism, divides the constituent elements of the destination image into four main classes and 20 subclasses through the text clustering method, and explores the tourists' perception of the image of coastal tourism with the help of the IPA model. The study found that: 1) The commonality of the cognitive image of "ocean" in 12 coastal cities is outstanding, but the internal characteristics are obvious, tourists pay more attention to coastal tourism in Bohai Rim and southern coastal areas, and Shanghai, Ningbo and Hangzhou show strong correlation; 2) Tourists' emotional image of coastal tourism destinations is dominated by positive attitudes, with a high overlap of adjectives representing positive emotions, but with heat differences in different cities; 3) The overall image of coastal tourism can be divided into three circles, including "traditional core-characteristic structure-peripheral perception", and there are obvious differences in the characteristics of the social semantic network of each city; 4) Tourists are more satisfied with the components of coastal tourism image, but pay more attention to the construction of optimized coastal tourism environment. Based on this, in the process of coastal tourism development, it is necessary to focus on creating distinctive and diversified tourism values, focusing on tourists' experience needs, improving the construction of quality tourism facilities and services, and promoting the high-quality development of coastal tourism.

Achieving destination sustainability: How tourist-to-tourist interaction quality affects tourist loyalty?

Although tourist-to-tourist interaction (TTI) has been identified as an essential element in tourist experiences, the effect of TTI quality on tourist loyalty, and the mechanism underlying this effect is scarcely discussed in the literature. Based on the self-determination theory, this study aims to examine whether and how TTI quality influences tourist loyalty, representing a significant means to achieve destination sustainability. More specifically, this study tested a moderated mediation model in which basic psychological needs satisfaction mediated the relationship between TTI quality and tourist loyalty, while sociability moderated the link between TTI quality and basic psychological needs satisfaction. A survey research approach was used, and 746 complete, usable responses were collected in multiple cities in China. The results revealed that the direct impact of TTI quality on tourist loyalty is mediated by basic psychological needs satisfaction. Furthermore, sociability positively moderates the influence of TTI quality on tourist loyalty. This study extends the TTI literature by demonstrating the mechanism of basic psychological needs satisfaction and tourists' sociability in the relationship between TTI quality and tourist loyalty. Managerial suggestions are provided for industry practitioners to improve tourist relationship management and the sustainability of destinations.