Optimizing risk mitigation in maritime supply chains through strategic supplier relationship management

Authors

  • Celine Vaandrager Delft University of Technology

DOI:

https://doi.org/10.59490/jscms.2024.7478

Keywords:

Risk mitigation, supply chain resilience, supplier relationship management, supplier segmentation, multi-criteria decision-making (MCDM), Best-Worst Method (BWM)

Abstract

Modern supply chains face escalating vulnerabilities, especially in the maritime industry. Traditional lean supply chain management lacks flexibility and risk mitigation measures, encouraging the proposal of agile-focused SCM. The success of companies is intricately tied to supplier performance, highlighting the pivotal role of procurement in risk mitigation through supplier relationship management (SRM) strategies. This emphasizes the role of procurement in risk mitigation since they manage suppliers using supplier relationship management (SRM) strategies. To properly apply SRM strategies, suppliers are segmented. The standard segmentation method is the Purchasing Portfolio Matrix (PPM). The downfall of this matrix is the focus on power relations, which misses a softer relationship side of SRM. The Supplier Potential Matrix (SPM) includes relationship dynamics but overlooks supply risk. A new matrix for segmentation is proposed, the Integrated Supplier Matrix (ISM), which combines and integrates the PPM and SPM. A case study in a maritime company assesses risks using the Best-Worst Method (BWM), revealing significant procurement risks such as product uniqueness, regulatory compliance, and external factors. The ISM then establishes relationships between supplier willingness, capabilities, risks, and profit impact. The findings emphasize the critical role of communication and trust in managing trade-offs within supplier relationship management (SRM).

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Published

2024-07-30

How to Cite

Vaandrager, C. (2024). Optimizing risk mitigation in maritime supply chains through strategic supplier relationship management. Journal of Supply Chain Management Science, 5(1-2), 48–65. https://doi.org/10.59490/jscms.2024.7478