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A Delphi-based risk analysis — Identifying and assessing future challenges for supply chain security in a multi-stakeholder environment

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  • Markmann, Christoph
  • Darkow, Inga-Lena
  • von der Gracht, Heiko

Abstract

Identifying and assessing the potential impact and likelihood of future events, which might evolve into risks, are a prerequisite to identify future security challenges. In particular, risks associated with global supply chains are special since they involve a multitude of international stakeholders with different perspectives on security needs and measures. Therefore, it is essential to determine which techniques and instruments are best suited for risk assessment in complex and multi-organizational environments. The Delphi expert survey technique has proven to be a valuable instrument for long-term decision making support as well as foresight, and has a potential value for risk assessment. We contribute to this research strand and conduct a Delphi-based risk analysis. Our research concentrates on man-made risks in global supply chains which are particularly uncertain in terms of type, location, and affected supply chain partners and can therefore be classified as inherently “wicked” issues, i.e. issues that are multidimensional with often unpleasant outcomes. We illustrate that Delphi research makes a fivefold contribution to risk analysis by: (1) identifying and quantifying risks; (2) analyzing stakeholder perceptions and worldviews; (3) stimulating a global communication process; (4) identifying weak signals, outlier opinions, and wildcards; (5) and facilitating risk scenario development.

Suggested Citation

  • Markmann, Christoph & Darkow, Inga-Lena & von der Gracht, Heiko, 2013. "A Delphi-based risk analysis — Identifying and assessing future challenges for supply chain security in a multi-stakeholder environment," Technological Forecasting and Social Change, Elsevier, vol. 80(9), pages 1815-1833.
    • Handle: RePEc:eee:tefoso:v:80:y:2013:i:9:p:1815-1833
    DOI: 10.1016/j.techfore.2012.10.019
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    Citations

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    Cited by:

    1. Engelke, Henning & Mauksch, Stefanie & Darkow, Inga-Lena & von der Gracht, Heiko A., 2015. "Opportunities for social enterprise in Germany — Evidence from an expert survey," Technological Forecasting and Social Change, Elsevier, vol. 90(PB), pages 635-646.
    2. Crispim, José & Fernandes, Jorge & Rego, Nazaré, 2020. "Customized risk assessment in military shipbuilding," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    3. Aengenheyster, Stefan & Cuhls, Kerstin & Gerhold, Lars & Heiskanen-Schüttler, Maria & Huck, Jana & Muszynska, Monika, 2017. "Real-Time Delphi in practice — A comparative analysis of existing software-based tools," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 15-27.
    4. Andersen, Per Dannemand & Hansen, Meiken & Selin, Cynthia, 2021. "Stakeholder inclusion in scenario planning—A review of European projects," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    5. Jiang, Ruth & Kleer, Robin & Piller, Frank T., 2017. "Predicting the future of additive manufacturing: A Delphi study on economic and societal implications of 3D printing for 2030," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 84-97.
    6. Fleuchaus, Paul & Schüppler, Simon & Bloemendal, Martin & Guglielmetti, Luca & Opel, Oliver & Blum, Philipp, 2020. "Risk analysis of High-Temperature Aquifer Thermal Energy Storage (HT-ATES)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    7. Julia V. Ponomareva & Anna V. Sokolova, 2015. "The Identification of Weak Signals and Wild Cards in Foresight Methodology: Stages and Methods," HSE Working papers WP BRP 46/STI/2015, National Research University Higher School of Economics.
    8. Schlecht, Laura & Schneider, Sabrina & Buchwald, Arne, 2021. "The prospective value creation potential of Blockchain in business models: A delphi study," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    9. Guertler, Benjamin & Spinler, Stefan, 2015. "Supply risk interrelationships and the derivation of key supply risk indicators," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 224-236.
    10. Jażdżewska-Gutta, Magdalena, 2014. "Supply Chain Security Measures - The Business Perspective," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Blecker, Thorsten & Kersten, Wolfgang & Ringle, Christian M. (ed.), Innovative Methods in Logistics and Supply Chain Management: Current Issues and Emerging Practices. Proceedings of the Hamburg International Conferenc, volume 19, pages 225-248, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    11. Rajesh, R., 2017. "Technological capabilities and supply chain resilience of firms: A relational analysis using Total Interpretive Structural Modeling (TISM)," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 161-169.
    12. Rengarajan, Srinath & Moser, Roger & Narayanamurthy, Gopalakrishnan, 2021. "Strategy tools in dynamic environments – An expert-panel study," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    13. Dinwoodie, John & Landamore, Melanie & Rigot-Muller, Patrick, 2014. "Dry bulk shipping flows to 2050: Delphi perceptions of early career specialists," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 64-75.
    14. Geng, Liuna & Liu, Ting & Zhou, Kexin & Yang, Genmao, 2018. "Can power affect environmental risk attitude toward nuclear energy?," Energy Policy, Elsevier, vol. 113(C), pages 87-93.

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