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Through a case study of the Po Klaong Girai temple in Vietnam, this paper explores how indigenous community perceive tourism benefit sharing (TBS) associated with their cultural tourism at sacred living-heritage sites and how this TBS enhances the equality and inclusion for indigenous community in the context of tourism in Vietnam.

This study employed ethnographic fieldwork and semi-structured interviews with 35 indigenous Cham priests directly associated with managing and preserving the Po Klaong Girai temple.

This research found that Cham community perceive inequality and exclusivity on tourism benefit sharing at this religious site. While Cham Ahier priests face economic barriers in providing these services to the community, annual tourism revenue is allocated to local government budgets. Such economic pressure forces the priests to seek alternative economic avenues to support their families at the expense of their traditional commitments to communal, cultural and religious activities, significantly impacting sustainable heritage conservation. This has led to strained relations between the local community and local authorities.

This research provides evidence to improve living heritage management practices by proposing tourism development policies for equality and inclusion among stakeholders, especially minorities and disadvantaged groups. This can be an experiential and necessary lesson for “dealing” with sustainable heritage management in heritage living sites in other ethnic minority areas in Vietnam and globally.

The findings from this study address the knowledge gap on equitable revenue sharing in heritage tourism, where financial benefits from the commodification of minority cultures should be used to support local communities and the custodians of indigenous heritage.

This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in geographic areas and the application of ecotourism elements that are integrated with big data innovation through artificial intelligence technology.

Data analysis is performed through dynamic system modeling. Simulations are carried out in three models: First, existing simulation models. Second, Scenario 1 is carried out by utilizing a causal loop through innovation of big data-based artificial intelligence technology to ecotourism elements. Third, Scenario 2 is carried out by utilizing a causal loop through big data-based artificial intelligence technology on aspects of ecotourism elements and destination competitiveness.

This study provides empirical insight into the competitiveness performance of destinations and the performance of implementing ecotourism elements if integrated with big data innovations that will be able to massively demonstrate the growth of sustainable tourism performance.

This study does not use a primary database, but uses secondary data from official sources that can be accessed by the public.

The paper includes implications for the development of intelligent technology based on big data and also requires policy innovation.

Sustainable tourism development.

This study finds the expansion of new theory competitiveness of ecotourism destinations.

This paper analyses the impact of the COVID-19 pandemic on Myanmar’s tourism industry, identifying challenges and innovations, and predicting future trends to foster a resilient and sustainable sector.

The study uses a comprehensive analysis of tourism trends, government and private sector responses and changes in tourist behaviour, employing data, case studies and policy reviews.

The pandemic significantly disrupted Myanmar’s tourism, causing economic losses and shifts towards sustainable, outdoor and cultural experiences. Effective strategies by the government and private sector are aiding recovery and suggesting a more diverse and resilient future.

The research is limited by the availability of data during the pandemic, highlighting the need for ongoing strategy adaptation.

The study recommends digitalization, health protocols, domestic tourism focus and sustainable practices for a robust post-pandemic industry.

The study emphasizes the pandemic’s social impact on tourism-dependent communities and the need for inclusive, sustainable tourism practices.

Itprovides unique insights into COVID-19’s multifaceted impact on Myanmar’s tourism, offering valuable information for future sector strategies.

Whether a human body has a healthy carrying capacity is calculated by body mass index (BMI). The BMI is found by dividing body weight in kilograms by the square of body length. If the person's body weight is more than the heaviness that the body can carry healthily, it is called obesity. Destinations have a specific area, just like a human body. Therefore, any destination whose carrying capacity is exceeded can be called an “obese destination”. This study's primary purpose is to reveal the importance of destination carrying capacity through the concept of obesity.

Content analysis, one of the qualitative research methods, was employed, and graffiti reflecting the feelings of the local people toward tourists were used as data. Graffiti was considered as a social carrying capacity indicator to identify obese destination symptoms. Fifty graffiti obtained from search engines about destinations with obesity problems were analyzed.

The study's findings reveal that anti-tourist graffiti indicates obese destination symptoms. Furthermore, when the content analysis of graffiti is examined, it is seen that the obese destination's local people have intense anger toward tourists. This is a clear manifestation of the destination's health deterioration.

This study, in which the concept of obese destination is used for the first time, suggests that destinations' health may worsen just like people. If destinations with over-tourism are called obese, a more expansive awareness will be created about the destinations' problems. The study suggests that nonecolabel can be used as a mandatory diet tool for obese destinations. Anti-tourist graffiti has been addressed as an obese destination symptom.

This study aims to determine the effects of lodging infrastructure development (LID) on Cordillera Administrative Region’s (CAR) environmental quality and natural resource management and its implication to globally responsible leadership. Specifically, this study sought to determine the contribution of LID to environmental deterioration and natural resource degradation in the CAR. As a result, a mathematical model is developed, which supports sustainability practices to maintain the environmental quality and natural resource management in CAR, Philippines.

This study used a descriptive research design using a mixed-methods approach. Self-structured interview and survey were used to gather the data. The population of this study involved three groups. There were 6.28% (34) experts in the field for the qualitative data, 70.24% (380) respondents for the quantitative data and 23.47% (127) from the lodging establishments. 120 respondents from the Department of Tourism – CAR (DOT-CAR) accredited hotels. Nonparametric and nonlinear regression analysis was used to process the data.

The effects of LID on the environmental quality and natural resource management in CAR as measured through carbon emission from liquefied petroleum gas (LPG), electricity and water consumption in the occupied guest rooms revealed a direct correlation between the LID. Findings conclude that the increase in tourist arrival is a trigger factor in the increase in LID in the CAR. The increase in LID implies a rise in carbon emission in the lodging infrastructure. Any increase in tourist arrivals increases lodging room occupancy; the increased lodging room occupancy contributes to carbon emissions. Thus, tourism trends contribute to the deterioration of the environmental quality and degradation of the natural resources in the CAR. A log-log model shows the percentage change in the average growth of tourist arrival and the percentage increase in carbon emissions. Establishments should observe standard room capacity to maintain the carbon emission of occupied lodging rooms at a minimum. Responsible leadership is a factor in the implementation of policy on standard room capacity.

The result of the study has some implications for the lodging businesses, the local government unit (LGU), the Department of Tourism (DOT) and the Department of Environment and Natural Resources (DENR) in the CAR. The study highlights the contribution of the lodging establishments to CO₂ emission, which can degrade the quality of the environment, and the implication of responsible leadership in managing natural resources in the CAR. The direct inverse relationship between energy use and CO₂ emission in hotels indicates that increased energy consumption leads to environmental degradation (Ahmad et al., 2018). Therefore, responsible leadership among policymakers in the lodging and government sectors – LGU, DOT and DENR – should abound in the CAR. Benchmarking on the model embarked from this study can help in designing and/or enhancing the policy on room capacity standardization, considering the total area with its maximum capacity to keep the carbon emission at a lower rate. Furthermore, as a responsible leader in the community, one should create programs that regulate the number of tourists visiting the place to decrease the number of overnight stays. Besides, having the political will to implement reduced room occupancy throughout the lodging establishments in CAR can help reduce the carbon emissions from the lodging businesses. After all, one of the aims of the International Environment Protection Organization is to reduce CO₂ emissions in the tourism industry. Hence, responsible leadership in environmental quality preservation and sustainable natural resource management must help prevent and avoid greenhouse gas (GHG) emissions.

Most studies about carbon emission in the environment tackle about carbon dioxide emitted by transportation and factories. This study adds to the insights on the existing information about the carbon emission in the environment from the lodging establishments through the use of LPG, electricity and water consumption in the occupied guest rooms. The findings of the study open an avenue for globally responsible leadership in sustaining environmental quality and preservation of natural resources by revisiting and amending the policies on the number of room occupancy, guidelines and standardization, considering the total lodging area with its maximum capacity to keep the carbon emission at a minimum, thus contributing to the lowering of GHG emissions from the lodging industry.

This article analyzes research on digital transformation in the tourism sector, providing insights into leading work, authors, journals, trends and future research opportunities. However, limited in-depth research exists on this topic, and the existing studies lack an understanding of its development, scope and relevant areas.

The study utilized the Scopus database to identify 61 articles on digital transformation in the tourism sector. The research employed VOSviewer software to analyze publication and citation structure, incorporating bibliometric variables like co-authorship, co-citation network, keywords co-occurrence network and bibliographic coupling.

The study yielded valuable insights from top-cited articles, revealing their contributions to digital transformation in tourism research. It also highlighted publication trends and the impact of authors, journals and studies and conducted co-occurrence, co-authorship and bibliographic analyses to identify key trends and issues in the tourism sector. The study calls for further examination of the digital revolution in tourism research and outlines future opportunities for researchers in this area.

To enhance the comprehensiveness of data collection, it is recommended that researchers consider including publications from databases such as WOS (Web of Science), Dimensions and PubMed in addition to the Scopus database. This broader inclusion of sources can provide different network structures and valuable insights from the field of digital transformation in the tourism sector.

The research provides substantial value to the study of digital transformation in tourism by focusing on bibliometric data from the Scopus database for the period from 2017 to 2022. By analyzing this data, it identifies significant trends in digital transformation within tourism research. Additionally, the study uncovers new areas of digitization in the tourism sector, further enhancing its value and relevance.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

This study examines experiences and enjoyment of national parks in the context of Tanzania.

A cross-sectional design with quantitative and qualitative methods is applied. The study area is Nyerere National Park in Tanzania. Data collected from fully completed structured questionnaires by 360 domestic tourists are subjected to descriptive statistics and Partial Least Square Structural Equation Modeling analysis. Content analysis is used to analyze qualitative data.

The findings have revealed that there is a significant relationship between direct experiences and enjoyment of southern national parks among domestic tourists.

The suggestion is for future studies to explore a longitudinal approach to determine the patterns of domestic tourists in reference to experiences and enjoyment of national parks so as to improve domestic tourism.

The practical implication is for the government, private sector and tourism stakeholders to improve infrastructure and conduct regular surveys and tour guide training.

This study examines experiences and enjoyment of national parks in the context of Tanzania and, specifically analyzes the relationship between direct experiences and enjoyment of southern national parks among domestic tourists in Tanzania guided by types of tourists’ theory.

The purpose of this paper is to have a deeper understanding of the nonlinear relationship between the impact of climate change on tourism development. Current studies on the effects of climate change on tourism development primarily rely on linear correlation assumptions.

Based on the New Institutional Economics theory, the institutional setting inherently motivates and ensures the growth of the tourism industry. For a precise evaluation of the nonlinear consequences of climate change on tourism, this paper concentrates on Chinese cities between 2011 and 2021, methodically analyzing the influence of climate change on tourism.

The study findings suggest that there is an “inverse U”-shaped nonlinear relationship between climate change and tourism development, initially strengthening and subsequently weakening. Based on these findings, the research further delves into how institutional contexts shape the nonlinear association between climate change and tourism growth. It was found that in a higher institutional backdrop, the “inverse U” curve tends to flatten and surpass the curve adjusted for a lesser institutional context. Upon deeper mechanism analysis, it was observed that cities with more advanced marketization, improved industrial restructuring and enhanced educational growth exhibit a more evident “inverse U”-shaped nonlinear connection between climate change and tourism evolution.

First, previous studies on climate change and tourism development largely rely on questionnaire data (Hu et al., 2022). In contrast to these studies, this paper uses dynamic panel data, which to some extent overcomes the subjectivity and difficulty of causality identification in questionnaire data, making our research conclusions more accurate and reliable. Second, this study breaks through the linear relationship hypothesis of previous literature regarding climate change and tourism development. By evaluating the nonlinear relationship of climate change to tourism development from the institutional pressure perspective, it more intricately delineates their interplay mechanism, expanding and supplementing the research literature on the relationship mechanism between climate change and tourism development. Thirdly, the conclusions of this study are beneficial for policymakers to better understand and assess the scope of climate change impacts. It also aids relevant departments in clarifying the direction of institutional environment optimization to elevate the level of tourism development when faced with adverse impacts brought about by climate change.

This research investigates Airbnb’s financial implications in emerging economies and their potential to influence stock market profitability.

Employing a multifaceted approach, the study combines parametric and nonparametric tests, robustness checks, and regression analysis to assess the impact of Airbnb’s announcements on emerging economy stock markets.

Airbnb’s announcements affect emerging economies' stock markets with a distinct pattern of cumulative abnormal returns (CAR): negative before the announcement and positive afterward. Informed investors strategically leverage this opportunity through short selling before the announcement and acquiring positions following it. Regression analysis validates these trends, revealing that stock index returns and inbound tourism affect CAR before announcements, while GDP growth influences CAR afterward. Announcements pertaining to emerging economies exert a more pronounced impact on stock indices compared to city-specific announcements, with COVID-19 period announcements demonstrating greater significance in abnormal returns than non-COVID-19 period announcements.

This study advances existing literature through a comprehensive range of statistical tests, differentiation between emerging countries and cities, introduction of five macroeconomic variables, and reliance on credible primary Airbnb data. It highlights the potential for investors to leverage Airbnb announcements in emerging markets for stock market profits, emphasizing the need for adaptive investment strategies considering broader macroeconomic factors.