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Sustainable Human–Machine Collaborations in Digital Transformation Technologies Adoption: A Comparative Case Study of Japan and Germany

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  • Young Won Park

    (Graduate School of Humanities and Social Sciences, Saitama University, 255 Shimo-Okubo, Sakura-ku, Saitama 3388570, Japan)

  • Junjiro Shintaku

    (Graduate School of Economics, The University of Tokyo, 3-34-3 Hongo, Bunkyo-ku, Tokyo 1130033, Japan)

Abstract

The Digital Transformation (DX) megatrend is fundamentally disrupting and changing the nature of work, business, and industry at a rapid pace. Although the notion of DX has garnered much research interest from practitioners, scholarship on this topic is somehow lagging behind, possibly because of the lack of theoretical frameworks on DX. Recently, most Japanese firms have begun to use diverse digital technologies to sustain their competitive advantages. However, the return of investment on digital technologies has not been as high as expected for some firms. Furthermore, as the visions of Industry 5.0 describe sustainable, resilient, and human-centered future factories that will require smart and resilient capabilities both from next-generation manufacturing systems and human operators, it is necessary to design resilient human–machine collaborations within factories. To this end, this paper presents a research model between DX technologies and scientific problem-solving in terms of deduction, induction, and abduction inference structures as an approach to resilient human–machine collaborations. The purpose of this research is to analyze the difference in the utilization pattern of the digital technology of American, German, and Japanese firms based on three types of decision-making methods. Next, we apply this framework in a comparative case study of two Japanese firms and one German firm, where we find that there is a difference in DX technologies utilization among the Japanese and German firms. We assert that the utilization of IoT technology in the United States and Germany is pursuing IoT with the aim of autonomous control, whereas Japanese firms prioritize robot–human collaboration. Finally, we discuss how our findings contribute to the burgeoning field of resilient human–machine collaborations by showing the distinct roles of deduction, induction, and abduction inference structures. Furthermore, our research contributes to international comparative studies to identify the difference in national IT utilization. Lessons and implications are discussed.

Suggested Citation

  • Young Won Park & Junjiro Shintaku, 2022. "Sustainable Human–Machine Collaborations in Digital Transformation Technologies Adoption: A Comparative Case Study of Japan and Germany," Sustainability, MDPI, vol. 14(17), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:17:p:10583-:d:897286
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    References listed on IDEAS

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