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Analysing workforce development challenges in the Industry 4.0

Author

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  • Yesim Deniz Ozkan-Ozen
  • Yigit Kazancoglu

Abstract

Purpose - The aim of this paper is to identify and analyse workforce development challenges in the digital age by first, presenting these challenges and relationship between them, and then proposing a structural model that categorizes these challenges and proposes suggestions for managers to improve human resources practices and firm performance. Design/methodology/approach - Fuzzy total interpretive structural modelling (TISM) is used as the methodology, which gives an interpretive structural model by presenting direct and transitive relationship between workforce development challenges and categorizes them under autonomous, dependent, independent and linkage groups. Findings - In total, 13 different workforce development challenges are presented in this study. Results showed that lack of IT/digital skills has a critical role in workforce development in terms of affecting other challenges. Dependent group includes requirements for longer learning time and specialized training, lack of analytical thinking and dealing with complexity, and lack of interdisciplinary thinking and acting. On the other hand, lack of ability in decentralized decision-making and shortage of workforce with adequate skillset within the labour market have more macro-impacts on others. Most of the challenges located in the linkage group, which means that most of the challenges are interrelated with each other. Originality/value - Originality of this paper is presenting a systematic structure for workforce development in Industry 4.0 that considers challenges systematically.

Suggested Citation

  • Yesim Deniz Ozkan-Ozen & Yigit Kazancoglu, 2021. "Analysing workforce development challenges in the Industry 4.0," International Journal of Manpower, Emerald Group Publishing Limited, vol. 43(2), pages 310-333, May.
    • Handle: RePEc:eme:ijmpps:ijm-03-2021-0167
    DOI: 10.1108/IJM-03-2021-0167
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    Citations

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    Cited by:

    1. Wen-Chin Chen & An-Xuan Ngo & Hui-Pin Chang, 2024. "Enhancing Decision-Making Processes in the Complex Landscape of the Taiwanese Electronics Manufacturing Industry through a Fuzzy MCDM Approach," Mathematics, MDPI, vol. 12(13), pages 1-29, July.
    2. Virmani, Naveen & Sharma, Shikha & Kumar, Anil & Luthra, Sunil, 2023. "Adoption of industry 4.0 evidence in emerging economy: Behavioral reasoning theory perspective," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

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