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A Managerial Early Warning System at a Smart Factory: An Intuitive Decision‐making Perspective

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  • Tine Bertoncel
  • Ivan Erenda
  • Mirjana Pejić Bach
  • Vasja Roblek
  • Maja Meško

Abstract

Early warning systems are becoming increasingly important in high‐risk industries, because of their potential to detect all kinds of subtle threats and opportunities, that is, weak signals, in order to avoid strategic surprises. However, it is an under‐researched area within the context of smart factories. For the purpose of the study, semi‐structured group interviews were used to investigate how managers at a smart factory, a highly innovative global supplier in the automotive industry sense weak signals, perceive the role of intuition, smart systems and business model adjustments. The results of the study show that managers perceive early warning systems as highly important for timely response to development changes and that both smart systems and intuition play an essential role in detecting and responding to weak signals. Based on this study, we propose a managerial early warning system model with four stages, namely, identifying, screening, appraising and responding to weak signs, within the context of a smart factory. © 2018 John Wiley & Sons, Ltd.

Suggested Citation

  • Tine Bertoncel & Ivan Erenda & Mirjana Pejić Bach & Vasja Roblek & Maja Meško, 2018. "A Managerial Early Warning System at a Smart Factory: An Intuitive Decision‐making Perspective," Systems Research and Behavioral Science, Wiley Blackwell, vol. 35(4), pages 406-416, July.
    • Handle: RePEc:bla:srbeha:v:35:y:2018:i:4:p:406-416
    DOI: 10.1002/sres.2542
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    Cited by:

    1. Qiang Ma & Xueling Li & Peggy E. Chaudhry & Sohail S. Chaudhry, 2020. "Public relations and legitimacy: A study of new ventures on the corporate life cycle," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 699-710, July.
    2. Li Da Xu, 2020. "The contribution of systems science to Industry 4.0," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 618-631, July.
    3. Runping Guo & Xingqun Lv & Yuan Wang & Peggy E. Chaudhry & Sohail S. Chaudhry, 2020. "Decision‐making logics and high‐tech entrepreneurial opportunity identification: The mediating role of strategic knowledge integration," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 719-733, July.
    4. Chebbi, Hela & Yahiaoui, Dorra & Sellami, Mohamed & Papasolomou, Ioanna & Melanthiou, Yioula, 2020. "Focusing on internal stakeholders to enable the implementation of organizational change towards corporate entrepreneurship: A case study from France," Journal of Business Research, Elsevier, vol. 119(C), pages 209-217.
    5. Laubengaier, Désirée A. & Cagliano, Raffaella & Canterino, Filomena, 2022. "It Takes Two to Tango: Analyzing the Relationship between Technological and Administrative Process Innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    6. Yu Sun & Ling Li & Hui Shi & Dazhi Chong, 2020. "The transformation and upgrade of China's manufacturing industry in Industry 4.0 era," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 734-740, July.
    7. Kopalle, Praveen K. & Kuusela, Hannu & Lehmann, Donald R., 2023. "The role of intuition in CEO acquisition decisions," Journal of Business Research, Elsevier, vol. 167(C).
    8. Yongdang Chen & Zhiyou Han & Kunyu Cao & Xianrong Zheng & Xiaobo Xu, 2020. "Manufacturing upgrading in industry 4.0 era," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 766-771, July.
    9. Yongping Xie & Yixuan Yin & Wei Xue & Hui Shi & Dazhi Chong, 2020. "Intelligent supply chain performance measurement in Industry 4.0," Systems Research and Behavioral Science, Wiley Blackwell, vol. 37(4), pages 711-718, July.

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