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Approach for application-specific selection of risk assessment methods

In: Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg International Conference of Logistics (HICL), Vol. 31

Author

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  • Nikelowski, Lukas
  • Voss, Rika

Abstract

Purpose: The field of risk assessment contains many methods for evaluating risks. For companies who face the need of dealing with risks, the large number of methods might be confusing and overwhelming. This paper helps to introduce companies to the existing methods and its different requirements as well to support the application-specific selection of a risk assessment method. Methodology: A systematic literature review regarding existing risk assessment methods is executed using the following identification terms: 1. 'risk assessment' AND (method OR technique OR instrument OR tool OR process) AND 'supply chain' 2. 'risk analysis' AND (method OR technique OR instrument OR tool OR process) AND 'supply chain'. Used databases are EBSCOhost, Scopus, and Web of Science. Findings: 194 sources containing relevant content on the methods of risk assessment are identified. 138 sources are published as journal articles and 56 sources as conference contributions. The main result is a classification and an application-specific selection procedure for risk assessment methods. Originality: This publication enables a comprehensive comparison and evaluation of existing risk assessment methods. It further supports the decision-making by presenting an overview and a selection procedure for choosing an application-specific method.

Suggested Citation

  • Nikelowski, Lukas & Voss, Rika, 2021. "Approach for application-specific selection of risk assessment methods," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Ringle, Christian M. & Blecker, Thorsten (ed.), Adapting to the Future: How Digitalization Shapes Sustainable Logistics and Resilient Supply Chain Management. Proceedings of the Hamburg Internationa, volume 31, pages 853-877, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
  • Handle: RePEc:zbw:hiclch:249640
    DOI: 10.15480/882.3980
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    References listed on IDEAS

    as
    1. ManMohan S. Sodhi & Christopher S. Tang, 2012. "Supply Chain Risk Management," International Series in Operations Research & Management Science, in: Managing Supply Chain Risk, edition 127, chapter 0, pages 3-11, Springer.
    2. Anna Corinna Cagliano & Alberto De Marco & Sabrina Grimaldi & Carlo Rafele, 2012. "An integrated approach to supply chain risk analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 15(7), pages 817-840, August.
    3. Bimal Nepal & Om Prakash Yadav, 2015. "Bayesian belief network-based framework for sourcing risk analysis during supplier selection," International Journal of Production Research, Taylor & Francis Journals, vol. 53(20), pages 6114-6135, October.
    4. Tang, Christopher S. & Davarzani, Hoda & Sarkis, Joseph, 2015. "Quantitative models for managing supply chain risks: A reviewAuthor-Name: Fahimnia, Behnam," European Journal of Operational Research, Elsevier, vol. 247(1), pages 1-15.
    5. Djalma Araújo Rangel & Taiane Kamel de Oliveira & Maria Silene Alexandre Leite, 2015. "Supply chain risk classification: discussion and proposal," International Journal of Production Research, Taylor & Francis Journals, vol. 53(22), pages 6868-6887, November.
    6. Venkatesh, V.G. & Rathi, Snehal & Patwa, Sriyans, 2015. "Analysis on supply chain risks in Indian apparel retail chains and proposal of risk prioritization model using Interpretive structural modeling," Journal of Retailing and Consumer Services, Elsevier, vol. 26(C), pages 153-167.
    7. Eva Maria Falkner & Martin R.W. Hiebl, 2015. "Risk management in SMEs: a systematic review of available evidence," Journal of Risk Finance, Emerald Group Publishing, vol. 16(2), pages 122-144, March.
    8. William Ho & Tian Zheng & Hakan Yildiz & Srinivas Talluri, 2015. "Supply chain risk management: a literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 5031-5069, August.
    9. Dong, Qingxing & Cooper, Orrin, 2016. "An orders-of-magnitude AHP supply chain risk assessment framework," International Journal of Production Economics, Elsevier, vol. 182(C), pages 144-156.
    10. Thi Huong Tran & Mario Dobrovnik & Sebastian Kummer, 2018. "Supply chain risk assessment: a content analysis-based literature review," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 31(4), pages 562-591.
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