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This study aims investigate the effects of electronic human resource management (e-HRM) on communication pace and processing time reduction through the mediation of organizational agility. The study also investigates the moderating role of technological attitude (TA) on the relationship between e-HRM and organizational agility.

The data was collected from 331 information and communication technology (ICT) companies – one respondent from each company working in the Human Resource Management (HRM) department. The data was analyzed through the partial least square structural equational model (PLS-SEM) using WarpPLS7.0 software to test the study’s hypotheses.

We found that e-HRM has positive significant effects on communication pace and processing time reduction through the mediation of organizational agility. Furthermore, TA is found to be positively moderating the relationship between e-HRM and organizational agility.

The study adds significant value to the existing knowledge base on e-HRM by providing empirical insights about the role of e-HRM in optimizing the communication pace and processing time of today’s businesses.

The study also provides invaluable insights to practitioners to replace conventional HR systems with e-HRM to better perform HR functions by optimizing communication pace and processing time in the current fast-paced era.

E-HRM has become an issue of great significance in the contemporary corporate landscape to improve operational efficiency. Despite its widespread adoption in the corporate world, empirical evidence on e-HRM, particularly on its consequences, is still inconclusive.

Many studies have examined pre-diploma students' backgrounds and academic performance with results showing that some did not achieve the expected level of competence. This study aims to examine the relationship between students’ demographic characteristics and their academic achievement at the pre-diploma level using machine learning.

Secondary data analysis was used in this study, which involved collecting information about 1,052 pre-diploma students enrolled at Universiti Teknologi MARA (UiTM) Pahang Branch between 2017 and 2021. The research procedure was divided into two parts: data collecting and pre-processing, and building the machine learning algorithm, pre-training and testing.

Gender, family income, region and achievement in the national secondary school examination (Sijil Pelajaran Malaysia [SPM]) predict academic performance. Female students were 1.2 times more likely to succeed academically. Central region students performed better with a value of 1.26. M40-income students were more likely to excel with an odds ratio of 2.809. Students who excelled in SPM English and Mathematics had a better likelihood of succeeding in higher education.

This research was limited to pre-diploma students from UiTM Pahang Branch. For better generalizability of the results, future research should include pre-diploma students from other UiTM branches that offer this programme.

This study is expected to offer insights for policymakers, particularly, the Ministry of Higher Education, in developing a comprehensive policy to improve the tertiary education system by focusing on the fourth Sustainable Development Goal.

These pre-diploma students were found to originate mainly from low- or middle-income families; hence, the programme may help them acquire better jobs and improve their standard of living. Most students enrolling on the pre-diploma performed below excellent at the secondary school level and were therefore given the opportunity to continue studying at a higher level.

This predictive model contributes to guidelines on the minimum requirements for pre-diploma students to gain admission into higher education institutions by ensuring the efficient distribution of resources and equal access to higher education among all communities.

The Technical Education and Vocational Training Authority (TEVTA) plays a crucial role in the socioeconomic development of a country. Still, it is often stigmatized as a secondary choice in the Global South. This study explored the interrelationships and impacts of factors such as family, school, and society on the perception and reputation of TEVTA.

By employing quantitative methods, the analysis focused on how family, society, and school support influence these perceptions and reputations within TEVTA programs. Social Cognitive Theory is the theoretical underpinning of this study, in which 350 students from 13 TEVTA institutes participated by filling out questionnaires. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and IBM SPSS 28.

This study indicates that family and societal influences significantly shape students' perceptions, confirming their pivotal role in enhancing the reputation of these programs. School support also emerged as a critical factor, significantly impacting students' perceptions but not directly influencing the programs' reputation. The analysis underscores the importance of understanding the sociocultural context to develop effective strategies for the TEVTA sector in Pakistan. This clear understanding is essential for developing effective strategies to improve the reputation of TEVTA programs in this setting. Moreover, this research offers policy suggestions to make vocational education more attractive and accessible to diverse students, ultimately contributing to the country's socioeconomic development.

This study applied Social Cognitive Theory (SCT) to explore how individual thoughts, environmental influences (such as family, school, and society), and behaviors interact within the context of TEVTA programs. This approach fills gaps in current research and offers a clearer understanding of what affects TEVTA's perception and reputation.