The tourism sector is exponentially expanding across the globe. Despite different forms of tourism, community-based tourism has evolved with new dimensions of development. Assessing the sustainable development of the sector is a top priority in order to adopt the new forms. Therefore, in this study, the association between community-based tourism and its sustainable development was measured under the lens of collaborative theory and social exchange perspective. Non-probabilistic judgmental sampling techniques were applied, and 201 respondents were assessed. Data analysis was conducted using structural equation modeling (SEM). The study grounded with residents’ perspectives and attested that community-based tourism directly enhanced residents’ economic conditions with a better environment, and the relationship between residents and tourists enhanced the tourism industry’s sustainable development. Stakeholders like government and local administrations play a significant role in exploring community-based tourism. This outcome of the research will be a substantial resource for local administrations, governments, researchers, policymakers and practitioners.

The rising trend of tourists selecting agrotourism as a tourist destination has become an intriguing study issue. Seremban is a well-known tourist attraction that is popular among visitors. As a result, Seremban has been selected as the study site. However, river pollution may have an influence on Seremban’s natural environment and agrotourism potential. Furthermore, inadequate infrastructure, such as unauthorized parking, exacerbated the inhabitants’ problems. A growing number of young people leave Seremban to pursue employment or further education in other cities, with no desire to work as farmers. The labor scarcity has also made it difficult for farmers to grow their farms. Consequently, the study aims to examine how factors such as the natural environment, tourist infrastructure, perceived social advantages, and perceived barriers influence the attitudes of Seremban residents towards agrotourism, with a focus on its potential for driving economic growth. This study adopts quantitative research methods, employing descriptive and causal research designs. Primary data collection is conducted through questionnaires, supplemented by secondary data. Non-probability quota sampling is utilized due to the absence of a specific sampling frame, with a sample size of 385 respondents determined using G*Power software. Constructs are developed based on previous research, and the questionnaire comprises Likert-scale items to gauge attitudes and perceptions. A pilot study assesses the instrument’s reliability. Data analysis is performed using SPSS software, encompassing multiple linear regression and Pearson correlation analyses in addition to descriptive statistics. The findings provide valuable insights into the factors driving residents’ perceptions of agrotourism in Seremban, emphasizing the importance of the natural environment, tourism infrastructure, perceived social benefits, and perceived barriers in shaping attitudes. Additionally, the study highlights the resilience of residents’ positive attitudes toward agrotourism, despite potential challenges and barriers identified. Overall, these results offer implications for policymakers and stakeholders involved in tourism development in the region.

After the pandemic (COVID-19), there is a dire need to gain a competitive advantage for tourism organizations which can be accomplished by implementing new technologies to facilitate sustainable healthier services. Given that, the study aims to shed light on the importance of digital leadership to improve sustainable business performance considering the parallel mediation of digital technology and digital technology support in the tourism sector of Pakistan. The sample population consists of technology-based tourism organizations in Pakistan. Cochran’s formula was chosen for sampling, in which 37 organizations with 792 employees were selected for data through a random sampling technique. The collected data were analyzed through structural equation modeling, and findings reveal that digital leadership positively influences sustainable business performance. Furthermore, the mediating role of technological leadership support and digital technologies partially mediates the association between digital leadership and sustainable performance.

This study discusses prospects and challenges facing start-up entrepreneurs in language and culture-related tourist attractions in Lombok, Indonesia. Data were collected by observing the operations of tourism entrepreneurs and interviewing the owners, workers, clients, and authorities in the industry. The data were analyzed using a mixed method where tourism sales over one year of business experience were quantitatively analyzed and where prime causes leading to profits and losses were qualitatively explicated. The findings identify six prospective opportunities and five challenges in sustainably establishing language and culture-related tourist attractions as core entrepreneurial businesses. This study enriches our understanding of what micro and small entrepreneurs experience at the early stages of business start-ups and how they respond to uncertainties facing them. The study also provides readers with an understanding of the prospects and the challenges facing small tourist-related entrepreneurs in operations at early start-up stages and serves as a reminder to small businesses about the potential challenges in their business operations. The article also recommends viable management plans to refer to as contingency strategies for probable future challenges. Furthermore, this study attempts to fill a gap in the literature on start-up entrepreneurship in language and culture-related tourist attractions.

This study aims at predicting the interrelationship between among Chat GPT with its six dimensions, tourist’s satisfaction and Chat GPT usage intention as perceived by tourist, and as well as to examine the moderating effect of traditional tour operator services on the relationships between all the variables. Data were collected from 624 tourists. The study hypotheses were tested and the direct and indirect effects between variables were examined using the PLS-SEM. The SEM results showed that Chat GPT’s six dimensions have a positive and significant direct impact on tourist’s satisfaction, and emphasis the moderating role of Traditional Tour Operator Services “TTOS” on the relationship between GPT’s six dimensions and “TS”, and on the relationship between ‘TS” and Chat GPT usage intention. These findings yield valuable insights for everyone interested in the use of IT in the tourism industry, and provide effective strategies for optimizing the use of technological applications by traditional tour operators.