Students from different cultures possess varying levels of skills in learning, remembering, and understanding concepts. Some terms and their explanations may seem easy for one group of students but difficult for another. Therefore, delivering educational content that aligns with student’s learning capabilities is a challenging task based on cultural orientations. This study addresses the learning challenges by developing a Thesaurus Glossary E-learning (TGE) framework method. This study introduces the TGE method which is a multi-language tool with visual associations that adapts to students’ capabilities. It also examines cultural differences and native languages, particularly aiding Arab Native to visualize appropriate terms (thesaurus) and their explanations (glossary) based on students’ learning capabilities. TGE learns from students’ term selection behavior and displays terms at a simple or advanced level that matches their learning ability. Additionally, TGE demonstrated its effectiveness as an e-learning tool, accessible to all students anytime and anywhere. The study analyzed 314 records related to student performance, out of which 114 students were surveyed to evaluate the effectiveness of the TGE method. This work presents TGE as a novel e-learning tool designed to enhance conceptual thinking within the context of modern educational practices during the digital transformation. TGE is based on artificial intelligence algorithms and associative rules that simulate the human brain, establishing logical connections between related key terms and sketching associations among diverse facets of a situation. An experiment was conducted at a private university in the Sultanate of Oman to assess the effectiveness of the proposed TGE tool. TGE was integrated with selected subjects in information systems and used by the students as a resource for e-learning methods and materials. The results show that 85% of students who used TGE improved their performance by 19%. We believe this work could establish a new smart e-learning teaching method and attract modern and digital universities to enhance student learning outcomes linked with conceptual thinking.

This research aims to investigate the impact of knowledge-based human resource management (KBHRM) practices on organizational performance through the mediating role of quality and quantity of knowledge worker productivity (QQKWP). The data were collected from 325 employees working in different private universities of Pakistan by using convenience and purposive sampling techniques. The quantitative research technique was used to perform analysis on WarpPLS software. The result revealed that only knowledge-based recruiting practices have a positive and significant direct effect on organizational performance. While knowledge-based performance appraisal practices, training and development practices and compensation practices all were insignificant in this regard. However, through mediator QQKWP, the knowledge-based recruiting practices (KBRP), knowledge-based training and development (KBTD), and knowledge-based compensation practices (KBCP) all were positively and significantly influencing organizational performance but only knowledge-based performance appraisal (KBPA) was insignificant in this mediating relationship. Lastly, the current study provides useful insights into the knowledge management (KM) literature in the context of private higher educational institutes of developing countries like Pakistan. The future studies should consider the impact of KBHRM practices on knowledge workers’ productivity and firms’ performances in the context of public universities.

Purpose: This research examines the intricate interplay between Business Intelligence (BI), Big Data Analytics (BDA), and Artificial Intelligence (AI) within the realm of Supply Chain Management (SCM). While the integration of these technologies has promised improved operational efficiency and decision-making capabilities, concerns about complexities and potential overreliance on technology persist. The study aims to provide insights into achieving a balance between data-driven insights and qualitative factors in SCM for sustained competitiveness. Design/methodology/approach: The research executed interviews with ten Arab Gulf-based consulting firms. These companies’ ability to successfully complete BI projects is well recognised. Findings: Through examining the interplay of human judgement and data-driven strategies, addressing integration challenges, and understanding the risks of excessive data reliance, the research enhances comprehension of the modern SCM landscape. It underscores BI’s foundational role, the necessity of balanced human input, and the significance of customer-centric strategies for lasting competitive advantage and relationships. Practical implications: The research provided information for organizations seeking to effectively navigate the complexities of integrating data-driven technologies in SCM. The research is a foundation for future studies to delve deeper into quantitative measurement methodologies and effective data security strategies in the SCM context. Originality: The research highlights the value of integrating BI, BDA, and AI in SCM for improved efficiency, cost reduction, and customer satisfaction, emphasising the need for a balanced approach that combines data-driven insights, human judgement, and customer-centric strategies to maintain competitiveness.

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.

Ukrainian Human Resource (HR) practices have multiple difficulties from economic changes combined with digital transformation and workforce instability brought on by the war in 2022. The study examines Ukrainian HR practices between 2015 and 2024, focusing on the digitalization of HR systems, talent development, staff engagement, and hiring strategies. It considers the effects of organizational size and industry type. The study combined interviews with 30 HR professionals and surveyed 150 organizations from different industry groups and sizes. Our data required both quantitative statistical tests and manual content breakdown with codes. Research has shown significant differences between Information Technology (IT) and farming firms, as 89% of IT businesses have integrated artificial intelligence (AI)-powered HR tools. In comparison, only 15% of agricultural companies have adopted them. Small and medium-sized enterprises (SMEs) showed less commitment to digital transformation and European Union (EU) requirements than large enterprises, which adopted these systems at rates of 75% and 88%, respectively. Western Ukraine first established mental health initiatives during the crisis, and Eastern Ukraine moved toward decentralized administration. Digitalization assistance for small businesses, along with EU and local human resources frameworks, should form the basis of our suggestions. This research calls for flexible people management methods to boost the Ukrainian workspace’s ability to recover from shocks.

Organizations are gradually focusing on creating a healthy workplace for their employees and becoming more people-centric. This occurs because a healthy workforce increases the work performance of the organisation and the personal development of its employees. This study aims to investigate the HR functions that impact employee motivation in the Malaysian banking sector. The three HR functions that were selected were training and development, rewards and recognition, and career management. The study utilised a cross-sectional design, and the research instruments were adapted from a number of past studies. A total of 350 respondents from the Malaysian banking industry were recruited. Using SPSS Version 26.0, the research hypotheses were examined. The results show that rewards and recognition are not significant predictors of employee motivation in the Malaysian banking industry; however, training and development and career management are significant predictors of employee motivation. These results will help the human resources department develop and improve its HR operations.