The COVID-19 pandemic in 2019 heralded a downturn in the Thai economy, particularly in the tourism and hospitality sectors which rely heavily on international tourists. To decrease the dependence of international tourists, this research outlined three objectives as 1) explore and classify the high-end domestic tourism market among 77 provinces in Thailand, 2) study the potential and readiness of tourism resources and tourism products to cater to the demand of high-end domestic tourists, and 3) suggest tourism management approaches for domestic high-end tourists after the crisis. Both quantitative and qualitative research methodologies were applied to achieve the research objectives. Income was used to identify and segment high-end domestic tourists living in 77 provinces in Thailand, while a verified questionnaire collected data from 1200 respondents nationwide. Forty-one experts from different tourism-related agencies at local and regional levels were targeted using purposive sampling techniques, and semi-structured interviews were conducted to acquire qualitative data. High-end domestic tourists, classified by monthly income, were segmented into Silver (50,000–70,000 THB), Gold (70,001–90,000 THB), Diamond (91,001–110,000 THB), and Platinum groups (Over 110,001 THB). These high-end domestic tourists shared both similarities and differences in tourism needs, preferences, and behaviors. Sixteen provinces in six domestic regions demonstrated the potential and readiness of tourism resources and products to satisfy the needs, preferences, and behaviors of high-end domestic tourists.

The purpose of this study is to address the issue of low local participation in ecotourism management in Indonesia, specifically at the Malela Waterfall ecotourism site in Cicadas Village, Rongga District, West Bandung Regency, West Java, Indonesia. The research method is action research, which includes observation data gathering, in-depth interviews, and Focus Group Discussions. The findings of the study show that by carrying out the process of developing social infrastructure, namely development that prioritizes strengthening human resources in carrying out social service functions in ecotourism activities such as skill training of residents in the field of ecotourism, massive ecotourism outreach, and strengthening social communities—Non-Governmental Organizations (NGOs) and youth organizations as ecotourism actors. This type of development serves to raise awareness and participation among local inhabitants in Malela Waterfall ecotourism in West Bandung Regency. This promotes harmony and mutually beneficial partnerships among all Malela Waterfall ecotourism stakeholders. Furthermore, increasing community participation benefits the well-being of residents in the tourist region.

Financial literacy is an essential life skill today and plays a crucial role in business success. This study examined the relationship between college students’ financial literacy, financial management behavior, and entrepreneurial opportunity recognition. A survey was conducted among college students in the Busan and Gyeongnam regions, and a total of 272 responses were analyzed using SPSS 28.0. The results showed that financial literacy partially positively affects financial management behavior. Furthermore, financial management behavior positively influences entrepreneurial opportunity recognition. Financial management behavior partially mediates the relationship between financial literacy and entrepreneurial opportunity recognition. Improving the financial literacy of college students during adolescence serves as a motivation for entrepreneurship and significantly impacts their exploration and practice of various income activities to achieve their expected future living standards. The study’s findings indicate that for potential entrepreneurs, recognizing and promoting entrepreneurship as a source of innovation and growth requires incorporating financial literacy and desirable financial management behavior education into university curricula.

Despite many investigations concerning antecedents of organizational commitment in the workplace, very few studies so far have analyzed the direct or indirect impact of HR change leadership role on organizational commitment via HR attribution. Therefore, given the reciprocal principle of social exchange theory, attribution theory and signal theory, this study formulated hypotheses and a model to test the relationships between included variables by employing the mixed-method approach. In-depth interviews were initially conducted to develop questionnaires to collect quantitative data. Employing PLS-SEM to analyze the data collected from 1058 employees working in 24 sustainable enterprises in Vietnam, the findings show that the degree of adopting HR change leadership role was positive, directly affecting organizational commitment. Also, both well-being and performance HR attribution play partially mediated roles in the relationship. The findings suggest that the organizational commitment depends on not only how the degree of adopting HR change leadership role is executed, but also how employees perceive and interpret the underlying management intent of these practices. In a sustainable context, adopting HR change leadership role plays a critical role in shaping employees’ interpretations of sustainable HR practices and their subsequent attributions. Besides, employees’ belief on why are sustainable HRM practices implemented has an influence on the organizational commitment that in turn contributes to the overall sustainable performance.

This study aims to advance understanding of the factors affecting Generation Z employee commitment in the workplace of the information and technology (IT) companies in Vietnam. A survey of 450 Generation Z employees in IT companies shows that company remuneration, reward and welfare, work environment, colleagues, direct manager, promotion, job characteristics, green initiatives are positively related to Generation Z organizational commitment. More specifically, work environment and direct manager have the highest effect on Generation Z employee commitment to organization while promotion and colleagues have the lowest effect on Generation Z employee commitment to organization. Research results also revealed that green initiatives of the organization have significant effect on Generation Z employee commitment in companies. This finding suggests that including green initiatives in corporate strategy is a valuable approach for improving Generation Z employee commitment to organization. We discuss the implications for theory, practice, limitations, and directions for future research.

Surveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.