The aim of the research is to elucidate the features of the modern model of bioecomedicine and its components as a social determinant of sustainable societal development. The theoretical-methodological basis of the work was the complex use of scientific principles and a systematic approach, which determined the choice of research methods: general scientific and interdisciplinary. The concept generalized content is substantiated and the main lines of building the bioecomedicine model are characterized from the standpoint of information-structural modeling and sustainable development. Based on the structural-logical imperative, the object, subject, basic method and main concepts of this science sphere are characterized. The bioecomedicine principal idea as a social determinant of the sustainable development within a single information space is the unification of the knowledge information field of biology, ecology and medicine based on the use of the latest achievements in information technologies. It is proven that the algorithm for achieving the bioecomedicine global goal in the form of a set of principles reflects the essence of a systemic approach to solving the tasks of sustainable societal development by ensuring the system-environmental homeostasis of humans and the ecosystems that surround them.

This paper examines the relationship between renewable energy (RE) generation, economic factors, infrastructure, and governance quality in ASEAN countries. Based on the Fixed Effects regression model on panel data spanning the years 2002–2021, results demonstrate that domestic capital investment, foreign direct investment, governance effectiveness, and crude oil price exhibit an inverse yet significant relationship with RE generation. An increase in those factors will lead to a decline in RE generation. Meanwhile, economic growth and infrastructure have a positive relationship, which implies that these factors act as stimulants for RE generation in the region. Hence, it is advisable to prioritise policies that foster economic growth, including offering tax breaks specifically for RE projects. Additionally, it’s crucial to streamline governance processes to facilitate infrastructure conducive to RE generation, along with investing in RE infrastructure. This could be achieved by establishing one-stop centres for consolidating permitting processes, which would streamline the often-bureaucratic process. However, given the extensive time period covered, future research should examine the short-term relationship between the variables to address any potential temporal trends between the factors and RE generation.

This study investigates the impact of human resource management (HRM) practices on employee retention and job satisfaction within Malaysia’s IT industry. The research centered on middle-management executives from the top 10 IT companies in the Greater Klang Valley and Penang. Using a self-administered questionnaire, the study gathered data on demographic characteristics, HRM practices, and employee retention, with the questionnaire design drawing from established literature and validated measuring scales. The study employed the PLS 4.0 method for analyzing structural relationships and tested various hypotheses regarding HRM practices and employee retention. Key findings revealed that work-life balance did not significantly impact employee retention. Conversely, job security positively influenced employee retention. Notably, rewards, recognition, and training and development were found to be insignificant in predicting employee retention. Additionally, the study explored the mediating role of job satisfaction but found it did not mediate the relationship between work-life balance and employee retention nor between job security and employee retention. The research highlighted that HRM practices have diverse effects on employee retention in Malaysia’s IT sector. Acknowledging limitations like sample size and research design, the study suggests the need for further research to deepen understanding in this area.

This study aims to take Chinese higher vocational colleges professional group leaders as the research subjects to analyze the components of their key competencies, develop the competency model of professional group leaders (PGL), and analyze the main factors influencing the model. It provides a powerful help for improving the scientific level of the construction and management of the teaching staff in higher vocational colleges and filling the gap in the research on the quality and ability of Chinese professional group leaders. A mixed research method is deployed in this study. Data are collected with the help of a self-administrated questionnaire and a semi-structured interview based on grounded theory. Data analysis involves structural equation modeling using AMOS, complemented by qualitative coding in NVivo. It concludes that the competency development model of professional group leaders comprises two main dimensions: explicit competencies and implicit competencies. Explicit competencies include cross-border adaptability (CBA), resource integration ability (RIA), innovation and development practice ability (IDPA), management leadership ability (MLA), and interdisciplinary scientific research ability (ISRA). Implicit competencies include personality attitude (PA), and intrinsic motivation (IM). The study fills a significant gap in the literature by providing a detailed model of competency for professional group leaders in the context of higher vocational education, offering a practical framework for improving the training and management of teaching staff and promoting the development of professional groups effective in vocational colleges.

This study investigated the utilization of Artificial Intelligence (AI) in the Recruitment and Selection Process and its effect on the Efficiency of Human Resource Management (HRM) and on the Effectiveness of Organizational Development (OD) in Jordanian commercial banks. The research aimed to provide solutions to reduce the cost, time, and effort spent in the process of HRM and to increase OD Effectiveness. The research model was developed based on comprehensive review of existing literature on the subject. The population of this study comprised HR Managers and Employees across all commercial banks in Jordan, and a census method was employed to gather 177 responses. Data analysis was conducted using Amos and SPSS software packages. The findings show a statistically significant positive impact of AI adoption in the Recruitment and Selection Process on HR Efficiency, which in turn positively impacted OD Effectiveness. Additionally, the study indicated that the ease-of-use of AI technologies played a positive moderating role in the relationship between the Recruitment and Selection Process through AI and HR Efficiency. This study concludes that implementing AI tools in Recruitment is vital through improving HR Efficiency and Organization Effectiveness.