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Hidden Supply Chain Risk and Incoterms ® : Analysis and Mitigation Strategies

Author

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  • Jonathan Davis

    (GMSC Department, Marilyn Davies College of Business, The University of Houston Downtown, Houston, TX 77002, USA)

  • John Vogt

    (GMSC Department, Marilyn Davies College of Business, The University of Houston Downtown, Houston, TX 77002, USA)

Abstract

Among the many sources of financial and operational risk in supply chains are the Incoterms ® , which are terms of trade used to decide who does what in a cargo movement, when risk passes from seller to buyer and who pays for which part of the movement. Wrong Incoterms ® create unexpected costs or risks, at best, and inoperable contracts at worst, with all the challenges implied. This paper analyzes risk in supply chain management (SCM) through the lens of the responsibilities and costs imposed by Incoterms ® . The authors also conducted a survey of 100 supply chain decision makers on supply chain contracts creation and Incoterms ® knowledge in the population. Failure mode and effect analysis (FMEA) of Incoterms ® reveals many scenarios that pose financial, operational, and even legal risk to firms. Results suggest Incoterms ® rules are poorly understood by supply chain practitioners in general, are often chosen by personnel who are not aware of the implications of their choices, and are therefore frequently chosen incorrectly or non-strategically, thereby increasing cost and risk. This paper discusses the implications of the analysis and survey results on supply chain performance as well as mitigation strategies for practitioners in strategically using Incoterms ® to remove cost, risk, and delay from supply chain transactions.

Suggested Citation

  • Jonathan Davis & John Vogt, 2021. "Hidden Supply Chain Risk and Incoterms ® : Analysis and Mitigation Strategies," JRFM, MDPI, vol. 14(12), pages 1-16, December.
  • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:12:p:619-:d:706412
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    References listed on IDEAS

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    1. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    2. Lo, Huai-Wei & Liou, James J.H. & Huang, Chun-Nen & Chuang, Yen-Ching, 2019. "A novel failure mode and effect analysis model for machine tool risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 173-183.
    3. Liu, Hu-Chen & You, Jian-Xin & Duan, Chun-Yan, 2019. "An integrated approach for failure mode and effect analysis under interval-valued intuitionistic fuzzy environment," International Journal of Production Economics, Elsevier, vol. 207(C), pages 163-172.
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