The issue of policy changes to support teacher professional development is an important factor shaping the career trajectory, efficacy, and ultimately the success of Junior Reserve Officer Training Corps (JROTC) instructors and the performance of the secondary students they serve and whose lives they affect. Although a rich body of research associated with policies regarding teacher preparation and professional development exists, a more closely related area of research focused specifically on the policies regarding preparation and professional development of JROTC instructors is limited. This lack of research presents a unique opportunity to explore the experiences of JROTC instructors and their perspectives on policies affecting teacher preparation and professional development. This qualitative exploratory single-case study can help to advance understanding of the complexities and nuances of teacher preparation and professional development policies supporting the JROTC instructors serving in high schools across the United States and overseas. One-on-one interviews with 14 JROTC personnel who had completed required teacher preparation requirements and professional development initiatives were conducted. Data analysis revealed 11 themes. Recommendations for improving policies concerning JROTC instructor preparation and professional development, including placing greater emphasis on the unique requirements, as well as suggestions for future research, are provided.

This research was conducted using a survey research method to investigate the influence of Artificial Intelligence (AI) on Nigerian students' academic performances in tertiary institutions. Nigerian tertiary institutions have an estimated population of about 2.5 million students across the universities, polytechnics, monotechnics, and colleges of education. A sample size of 509 was used. The researchers adopted an online questionnaire (Google Form) to administer questions to respondents across Nigeria to elicit responses from the respondents bordering on their awareness and the use of AI and its attendant impacts on their academic performance. Five research objectives were raised for the proper investigation of this study. From the findings of the study, the researchers found that the majority of Nigerian students use AI and that AI has positive impacts on the educational performance of Nigerian students. It was also found that Nigerian students have training on the use of AI for educational purposes and that they are more familiar with Snapchat AI and ChatGPT. Conclusively, AI is useful to students in the sense that it enhances their knowledge of their courses, improves their learning and speaking skills, and helps them to have a quick understanding of their course by way of simplifying technical aspects of their courses. The researchers therefore recommend as follows: Nigerian tertiary institutions should formally train students as well as teachers on the use of AI for academic purposes so that they can understand the ethical implications of the use of AI. Using AI for writing could be interpreted to mean examination malpractice, and this should not be condoned in the educational sector; however, at the moment, a small number of students used AI for examinations. Albeit, the appropriate use of AI should be fully integrated into Nigerian tertiary institutions' curricula.

The financial services industry is experiencing a swift adoption of artificial intelligence (AI) and machine learning for a variety of applications. These technologies can be employed by both public and private sector entities to ensure adherence to regulatory requirements, monitor activities, evaluate data accuracy, and identify instances of fraudulent behavior. The utilization of artificial intelligence (AI) and machine learning (ML) has the potential to provide novel and unforeseen manifestations of interconnectivity within financial markets and institutions. This can be represented by the adoption of previously disparate data sources by diverse institutions. The researchers employed convenience sampling as the sampling method. The form was filled out over the period spanning from July 2023 to February 2024, and it was designed to be both anonymous and accessible through online and offline platforms. To assess the reliability and validity of the measurement scales and evaluate the structural model, we employed Partial Least Squares (PLS) for model validation. Specifically, we have used the software package Smart-PLS 3 with a bootstrapping of 5000 samples to estimate the significance of the parameters. The results indicate a positive and direct connection between artificial intelligence (AI) and either financial services or financial institutions. On the contrary, machine learning (ML) exhibits a strong and positive association among financial services and financial institutions. Similarly, there exists a positive and direct connection between AI and investors, as well as between ML and investors.

Green Human Resource Management (HRM) is considered an emerging field of management that evaluates and ensures green performance and outcomes in organizations. In today’s dynamic business environment, work-life balance has become one of the key issues faced by many employees all over the world. Maintaining work-life balance is an issue increasingly recognized as of strategic importance to the organization and significance to employees. In doing so, the present study introduced independent and dependent variables to explain the underlying mechanisms of green HRM and work-life balance and its impact on employee performance. A total of 90 employees of the calibration services company have completed a set of questionnaires through Google Forms to provide data for the analysis. This study is using census method as one of the best probability sampling techniques to be used it’s a systematic method that collects and records the data about the members of the population and is suitable when the case-intensive study is required or the area is limited. This study has adopted the quantitative method in this research as the method allows the researcher to focus on the research. The data were analyzed through SPSS which facilitates descriptive statistics, correlation, and multiple regressions. Multiple regression analysis was used to test the hypotheses in this research. The findings showed that green HRM and work-life balance were the significant variables influencing employee performance in the study. In addition, the significance of the study included providing new knowledge from the theoretical perspective, obtaining a better understanding of the importance of green HRM and work-life balance from the perspective of employee performance, and contributing to the efforts made by the government to improve the probability of green culture in organizational and balancing professional life and family life employment of employees through policies from the perspective of the government. Lastly, recommendations for employers, employees, government, and future research are made to improve employee performance.

Purpose: This research aims to explore the phenomenon of job-hopping in the engineering sector in Penang, Malaysia, focusing on how factors like positive work culture, compensation and benefits, and job satisfaction influence an engineer’s propensity to frequently change jobs. Design/methodology/approach: The study adopted a cross-sectional survey design, targeting 200 engineers in Penang. It was grounded in Herzberg’s Motivation-Hygiene Theory. Data collection was conducted using online questionnaires, which were adaptations of instruments used in previous research. Statistical analysis, including Pearson correlation and multiple linear regression, was performed using SPSS software. Findings: The Pearson correlation analysis revealed significant negative relationships between positive work culture, compensation and benefits, job satisfaction, and the tendency to job-hop. However, in the regression analysis, only job satisfaction emerged as a significant predictor of job-hopping behavior. This finding suggests that while factors like work culture and compensation/benefits contribute to the overall work environment, they do not primarily drive job mobility among engineers in this region. The study indicates that job satisfaction plays a more crucial role in influencing engineers’ decisions to change jobs frequently. Conclusion: The study enriches the field of organizational psychology by applying Herzberg’s theory to understand job-hopping behavior in the engineering sector. For organizations in Penang, the findings highlight the importance of enhancing job satisfaction as a strategy for reducing job-hopping and retaining talent. This insight is valuable for both academic research and practical application in the industry, emphasizing the critical role of job satisfaction in curbing job-hopping tendencies within the engineering field.

In today's changing world of work, Strategic Human Resource Management (SHRM)) still focuses on making workers more productive. This study systematically examines the mediating function of incentives both monetary and non-monetary between antecedent characteristics (e.g., leadership, organizational culture) and employee productivity using a systematic literature review (SLR) of papers published from 2010 to 2024. The review adheres to PRISMA principles and integrates 18 peer-reviewed studies chosen through a stringent screening and quality evaluation process from Scopus and Google Scholar. The results show that the success of incentives depends a lot on things like the ideals of the business, the style of leadership, and the demographics of the workforce. Thematic analysis, informed by the Ability-Motivation-Opportunity (AMO) theory and Strategic Human Resource Management (SHRM) frameworks, delineates four principal processes by which incentives affect productivity: goal alignment, perceived equity, motivational pathways, and cultural congruence. The research emphasizes the necessity of customizing incentive systems to specific organizational contexts and offers practical guidance for HR professionals. Recognizing limitations and publishing bias, suggestions for future incentive system design are presented.