Multimodal transportation acts as an important support for efficient, resilient, and sustainable supply chains. Although, it is observed that financial barriers across supply chain stakeholders often slow the success of multimodal transportation systems. This study fits within the field of supply chain finance as a key method to support transportation integration and logistics coordination. The aim of the chapter is to identify and structurally analyze supply chain finance enablers that strengthen multimodal transportation integration. The study utilized an expert mining approach and an Interpretive Structural Modeling (ISM) methodology to figure a hierarchy of enablers. Furthermore, the study used MICMAC framework to assess dependence power and driving power of enablers. Results of the study has shown that enablers such as access to credit, risk-sharing mechanisms, digital financial platforms, and institutional support have a strong driving influence on multimodal outcomes. Whereas, linkage and dependent factors relate to operational coordination, working capital management, and service reliability in terms of financial inclusion across transport modes. The findings provide suggestions to policymakers, logistics planners, and financial institutions in order to design focused supply chain finance actions that can help to improve multimodal transportation.

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A Structural Investigation of Supply Chain Finance Enablers Supporting Multimodal Transportation Integration Using ISM and MICMAC

  • Kuldeep Singh

摘要

Multimodal transportation acts as an important support for efficient, resilient, and sustainable supply chains. Although, it is observed that financial barriers across supply chain stakeholders often slow the success of multimodal transportation systems. This study fits within the field of supply chain finance as a key method to support transportation integration and logistics coordination. The aim of the chapter is to identify and structurally analyze supply chain finance enablers that strengthen multimodal transportation integration. The study utilized an expert mining approach and an Interpretive Structural Modeling (ISM) methodology to figure a hierarchy of enablers. Furthermore, the study used MICMAC framework to assess dependence power and driving power of enablers. Results of the study has shown that enablers such as access to credit, risk-sharing mechanisms, digital financial platforms, and institutional support have a strong driving influence on multimodal outcomes. Whereas, linkage and dependent factors relate to operational coordination, working capital management, and service reliability in terms of financial inclusion across transport modes. The findings provide suggestions to policymakers, logistics planners, and financial institutions in order to design focused supply chain finance actions that can help to improve multimodal transportation.