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Review of Industry 4.0 in the Light of Sociotechnical System Theory and Competence-Based View: A Future Research Agenda for the Evolute Approach

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Advances in Human Factors, Business Management and Society (AHFE 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 783))

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Abstract

This paper reviews the concept of Industry 4.0 related challenges and basic requirements for successful implementation of it. It proposed that sociotechnical system theory (STS) and competence-based view (CBV) are best approaches towards implementation of industry 4.0 in the organizations. STS theory leads to such systems, which are more acceptable to end users and deliver better value. While competence-based view prepares those users to interact efficiently with new systems. To support competence-based view for industry 4.0 we argue that competence models of the Evolute approach need to be revised and updated, as well as, there is need for new competence models for emerging new job profiles. The combination of these three approaches will result into successful implementation of new industry 4.0 systems in the organizations.

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Authors and Affiliations

  1. School of Technology and Innovations, University of Vaasa, 65101, Vaasa, Finland

    Faisal Imran & Jussi Kantola

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  1. Faisal Imran
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  2. Jussi Kantola
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Correspondence to Faisal Imran .

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Editors and Affiliations

  1. School of Technology and Innovations, University of Vaasa, Vaasa, Finland

    Jussi Ilari Kantola

  2. Institute of Maritime Operations, University College of Southeast Norway, Borre, Norway

    Salman Nazir

  3. Hungarian-Netherlands School of Educational Management, University of Szeged, Szeged, Hungary

    Tibor Barath

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Imran, F., Kantola, J. (2019). Review of Industry 4.0 in the Light of Sociotechnical System Theory and Competence-Based View: A Future Research Agenda for the Evolute Approach. In: Kantola, J.I., Nazir, S., Barath, T. (eds) Advances in Human Factors, Business Management and Society. AHFE 2018. Advances in Intelligent Systems and Computing, vol 783. Springer, Cham. https://doi.org/10.1007/978-3-319-94709-9_12

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  • DOI: https://doi.org/10.1007/978-3-319-94709-9_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94708-2

  • Online ISBN: 978-3-319-94709-9

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