To better analyze the tourist experience of the Jinsha Site Museum, this study adopts a mixed research method, combined with questionnaire surveys, interviews, and online review data, to comprehensively analyze the tourist experience from three dimensions: cognition, emotion, and behavior. After statistical analysis of 223 questionnaire surveys and analysis of 530 online comments, it was found that tourists’ overall satisfaction with the Jinsha Site Museum reached 95.3%. In the feedback on interactive exhibitions, 63.8% of tourists hoped to add more interactive elements and technological applications. The above results indicate that the Jinsha Site Museum has been widely recognized by tourists in providing historical and cultural exhibitions and modern facility services. However, to meet the needs of more tourists, museums should consider innovating and upgrading in interactive exhibitions, adding technological interactive elements, and improving the usability and responsiveness of equipment.

The Public-Private Partnerships management model (PPP) in Portugal was initially applied to the highways sector. Recently, this model began to spread to the health sector for hospital management. The recent growth of patient’s knowledge and expectations regarding the quality of healthcare services is compelling service providers to pursue new ways of delivering this care to meet users’ expectations. One wonders if the increase in patient access to knowledge may indicate a growth in health literacy, particularly regarding PPP Hospitals. This study assesses the Portuguese population’s literacy level regarding the PPP Hospital model, using a quantitative research approach based on a survey of the Portuguese population served by PPP hospitals and a Public Hospital Management (PHM) model. It was found that the Portuguese population has a low literacy concerning the PPP model, which can cause feelings of injustice. It was found that PPP users tend to have a favourable opinion regarding private involvement since they are also more satisfied compared to PMH users. These results may impact political decision-making concerning the renewal of new contracts for private management of public services.

The Malaysian government’s heightened focus on Technical and Vocational Education and Training (TVET) reflects a strategic move towards economic and social development, particularly in addressing youth unemployment. Recognizing the potential of TVET to contribute to these goals, there is a specific emphasis on enhancing the marketability of women in the workforce from the current 62 percent to an ambitious 95 percent. However, a notable gender gap persists in entrepreneurial pursuits within the TVET sector in Malaysia, with female representation lagging. To bridge this gap, this study aims to construct a comprehensive framework that nurtures future-ready female TVETpreneur talent. This initiative aligns with the Malaysian Higher Education Blueprint, 2021–2025, i.e., fostering a diverse and innovative workforce. An extensive literature survey was conducted to identify the factors influencing female TVET students’ entrepreneurial intention. The literature revealed that social psychological and organizational approaches are commonly used to explore and analyze the relationship between the influence of female TVET students’ talents and behavior, their exposure to entrepreneurship, mentorship and support programs, role models in TVET, curriculum design, and access to resources. A comprehensive theoretical framework was developed based on these findings, which offers significant insights related to enhancing TVET opportunities for women and advancing Malaysia’s economic and social development goals in a sustainable way.

The efficiencies and performance of gas turbine cycles are highly dependent on parameters such as the turbine inlet temperature (TIT), compressor inlet temperature (T1), and pressure ratio (Rc). This study analyzed the effects of these parameters on the energy efficiency, exergy efficiency, and specific fuel consumption (SFC) of a simple gas turbine cycle. The analysis found that increasing the TIT leads to higher efficiencies and lower SFC, while increasing the To or Rc results in lower efficiencies and higher SFC. For a TIT of 1400 ℃, T1 of 20 ℃, and Rc of 8, the energy and exergy efficiencies were 32.75% and 30.9%, respectively, with an SFC of 187.9 g/kWh. However, for a TIT of 900 ℃, T1 of 30 ℃, and Rc of 30, the energy and exergy efficiencies dropped to 13.18% and 12.44%, respectively, while the SFC increased to 570.3 g/kWh. The results show that there are optimal combinations of TIT, To, and Rc that maximize performance for a given application. Designers must consider trade-offs between efficiency, emissions, cost, and other factors to optimize gas turbine cycles. Overall, this study provides data and insights to improve the design and operation of simple gas turbine cycles.

Indonesia’s tourism industry has emerged as a strategic sector, contributing to the country’s foreign exchange earnings. Given the prominence of this sector, there is significant potential for further development. Indeed, a mapping study to assess the dissemination of the trend and the potential for further issues to emerge would be highly beneficial. It is encouraging to note that academics have produced substantial literature on the subject, offering insights into its many facets. However, there is still a need for more in-depth analysis to understand the trends and issues currently facing the sector entirely. Consequently, this article examines the core themes in Indonesia’s tourism studies and maps the potential for future research on tourism issues and regulations. To this end, it employs a qualitative, four-year data set (2020–2023) and a SWOT analysis to identify critical aspects of Indonesian tourism issues. The data was collected in three forms: government reports, statistical data, and research articles (n = 252 samples) from the Scopus database. The results demonstrate that the predominant trend in Indonesia’s tourism industry is the widespread embrace of ecotourism at both the local and regional levels. Instead of identifying a limited number of leading destinations, the focus has shifted towards developing tourism villages and multi-stakeholder tourism. The primary concerns are the Indonesian tourism industry’s growth potential and sustainability. The development potential of Indonesian destinations based on SWOT objectives is a crucial aspect, and its score shows that Indonesia’s tourism sector is strategically positioned to take advantage of strengths and opportunities.

This study provides empirical data on the impact of generative AI in education, with special emphasis on sustainable development goals (SDGs). By conducting a thorough analysis of the relationship between generative AI technologies and educational outcomes, this research fills a critical gap in the literature. The insights offered are valuable for policymakers seeking to leverage new educational technologies to support sustainable development. Using Smart-PLS4, five hypotheses derived from the research questions were tested based on data collected from an E-Questionnaire distributed to academic faculty members and education managers. Of the 311 valid responses, the measurement model assessment confirmed the validity and reliability of the data, while the structural model assessment validated the hypotheses. The study’s findings reveal that New Approaches to Learning Outcome Assessment (NALOA) significantly contribute to achieving SDGs, with a path coefficient of 0.477 (p < 0.001). Similarly, the Use of Generative AI Technologies (UGAIT) has a notable positive impact on SDGs, with a value of 0.221 (p < 0.001). A Paradigm Shift in Education and Educational Process Organization (PSEPQ) also demonstrates a significant, though smaller, effect on SDGs with a coefficient of 0.142 (p = 0.008). However, the Opportunities and Risks of Generative AI in Education (ORGIE) study did not find statistically significant evidence of an impact on SDGs (p = 0.390). These findings highlight the potential opportunities and challenges of using generative AI technologies in education and underscore their key role in advancing sustainable development goals. The study also offers a strategic roadmap for educational institutions, particularly in Oman to harness AI technology in support of sustainable development objectives.