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.

This study explores the critical role of the retail sector in the global economy and the importance of working capital management within retail businesses. Recognizing retail’s influence beyond just income generation, the research examines its impact on economic stability, job creation, and national GDP, and how it links industries such as manufacturing and logistics. Employing a blended-methods approach, the study integrates quantitative analysis using AMOS software with qualitative insights from interviews with financial managers and retail experts. Key focus areas include cash flow management, market demand, and supplier relationship management in the context of working capital management. Findings highlight the necessity of effective working capital management in maintaining financial stability, optimizing shareholder wealth, and ensuring long-term business viability in the retail sector. Strategies for enhancing profitability, such as improving supplier relationships and adapting to market demands, are identified. This research contributes to understanding the economic impact of the retail sector and the intricacies of working capital management. It offers insights for policymakers, retail managers, and academics, emphasizing the need for supportive retail industry measures and effective financial management practices. The study fills a gap in literature and sets a foundation for future research in this critical area of economic studies and retail management.

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.

The research aims to explore the role of Electronic Human Resources Management on employee performance through employee engagement. The present research’s population included all Jordanian Service and Public Administration Commission employees. The data was collection through a questionnaire that was administered for the study Population. 262 questionnaires collected from employees working in Service and Public Administration Commission in Jordan valid for statistics. The analysis of the data was undertaken through the use of SEM (structural equation modelling). The results showed that E-HRM has a direct impact on employee performance and employee engagement. Consequently, the indication from the results was that a significant role in mediation within the effect that E-HRM had upon employee performance been played by employee engagement. The conclusion reached was that transformation of the public sector through implementation of technological HRM methods fosters employee engagement, with that being a key driver for the alignment of employee behaviors for the achievement of high levels of employee performance.

The study investigates the impact of artificial intelligence (AI)-powered chatbots on brand dynamics within the banking sector, focusing on the interrelationships between AI implementation and key brand dimensions, including awareness, equity, image, and loyalty. Using structural equation modeling (SEM) analysis on data collected from 520 banking customers, the study tests eight hypotheses to explore the direct and indirect effects of AI-driven interactions on brand development. The findings reveal that AI chatbots significantly enhance brand awareness in banking services, demonstrating moderate positive effects on both brand equity and brand image. Notably, while brand awareness exerts a strong influence on brand image, it does not have a significant direct effect on brand loyalty. Instead, the study shows that brand loyalty is primarily developed through the mediating effects of brand equity and image, with brand image exerting a particularly strong influence on brand equity. For banking practitioners, these insights suggest a need to integrate AI chatbots within a comprehensive brand strategy that merges technological innovation with traditional relationship-building approaches. Limitations of the study and potential directions for future research are also discussed, providing avenues for further exploration of AI’s role in brand management.