Review Gold Open Access 2024

A Systematic Review of Industry 4.0 Technology on Workforce Employability and Skills: Driving Success Factors and Challenges in South Asia

Economies
Journal · Vol. 12 · Issue 2 · Art. 35
Abstract

The purpose of this study is to systematically analyze the impact of Industry 4.0 technologies on workforce employability and skills in the South Asian region. The study investigates the driving success factors, challenges, and needed skills by analyzing 48 peer-reviewed articles. The authors searched keywords on the Web of Science database for articles published between 2013 and 2022. The review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA 2020) and pareto principles. The analysis identifies nine critical success factors, such as artificial intelligence, digital skills, and big data analytics, that contribute to Industry 4.0’s productivity and efficiency. It also identifies six types of challenges, such as training and development, financial constraints, and regulatory issues that must be addressed to grab maximum potential. In addition, the research categorizes five different skills, including the technical, digital, and social skills that are essential for the evolving labor market. The proposed “Industry 4.0 SEI Framework” provides stakeholders with a comprehensive view of the dynamics of Industry 4.0, thereby facilitating policy and industry strategies. © 2024 by the authors.

Keywords

Author Keywords

Artificial intelligence labor market Industry 4.0 Digital Skills data analytics South Asia workforce employability

Index Keywords

Author Affiliations
Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, Godollo, Pest, Hungary, Department of Business Administration, Varendra University, Rajshahi, Bangladesh
Institute of Technology, Hungarian University of Agriculture and Life Sciences, Godollo, Pest, Hungary
College of Arts and Sciences, Western New England University, Springfield, MA, United States
Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, Godollo, Pest, Hungary, Institute of Agricultural and Food Economics, Hungarian University of Agriculture and Life Sciences, Godollo, Pest, Hungary
Funding & Acknowledgements
No funding information
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