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Preventing mental strain for logistics workers: Guideline development

In: Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 29

Author

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  • Schwarz, Patrick
  • Klumpp, Matthias

Abstract

Purpose: The purpose of this paper is to discuss and analyze the introduction of a guideline, which aims to help prevent mental strain for logistics workers in an increasingly digitalized work environment. The guideline originates from the findings of computer science experimental rooms (IR) and expert workshops, which were analyzed in three German companies and are part of the INQA-project DIAMANT as well as from literature findings. Methodology: Mental strain and stress are identified from interviews and questionnaires in three experimental rooms as well as from literature review (and discussions with the logistics workforce of the German companies). The identified factors are then translated into a guideline with recommendations for reaching and maintaining a healthy digitalized work environment in logistics. Findings: The guideline "Case Studies Digitalization" shows the (interim) results of the three experimental rooms of the INQA-project DIAMANT. This paper offers insights regarding certain elements of the guideline and how the different recommendations were created. Originality: The paper provides interesting insights into the development process of a guideline that focuses on requirements for healthy digitalized work in logistics. Along with these requirements, the challenges today's logistics workforce faces in a quickly changing work environment are exposed.

Suggested Citation

  • Schwarz, Patrick & Klumpp, Matthias, 2020. "Preventing mental strain for logistics workers: Guideline development," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), Data Science and Innovation in Supply Chain Management: How Data Transforms the Value Chain. Proceedings of the Hamburg International Conference of Lo, volume 29, pages 737-761, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    • Handle: RePEc:zbw:hiclch:228938
    DOI: 10.15480/882.3133
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    References listed on IDEAS

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    1. Grosse, E. H. & Calzavara, M. & Glock, C. H. & Sgarbossa, F., 2017. "Incorporating human factors into decision support models for production and logistics: current state of research," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 88433, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
    3. Elisabeth Nöhammer & Stefan Stichlberger, 2019. "Digitalization, innovative work behavior and extended availability," Journal of Business Economics, Springer, vol. 89(8), pages 1191-1214, December.
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