Diagnosis of delivery vulnerability in a logistics system for logistics risk management

Pei‐Ju Wu · Pattra Chaipiyaphan

35 citations0/0 files storedThe International Journal of Logistics Management

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Supply Chain Resilience and Risk Management Big Data and Business Intelligence Logistics and Transportation Systems

Abstract

Purpose Delivery vulnerability is a critically important theme in logistics risk management. However, while logistics service providers often collect and retain massive amounts of logistics data, they seldom utilize such information to diagnose recurrent day-to-day logistics risks. Hence, the purpose of this paper is to investigate delivery vulnerabilities in a logistics system using its own accumulated data. Design/methodology/approach This study utilizes pragmatic business analytics to derive insights on logistics risk management from operations data in a logistics system. Additionally, normal accident theory informs the discussion of its management implications. Findings This study’s analytical results reveal that a tightly coupled logistics system can align with normal accident theory. Specifically, the vulnerabilities of such a system comprise not only multi-components but also interactive ones. Research limitations/implications The tailored business analytics comprise a research foundation for logistics risk management. Additionally, the important research implications of this study’s analytical results arrived at via such results’ integration with normal accident theory demonstrate the value of that theory to logistics risk management. Practical implications The trade-offs between logistics risk and logistics-system efficiency should be carefully evaluated. Moreover, improvements to such systems’ internal resilience can help to alleviate potential logistics vulnerabilities. Originality/value This pioneering analytical study scrutinizes the critical vulnerability issues of a logistics service provider and therefore represents a valuable contribution to the field of logistics risk management. Moreover, it provides a guide to retrieving valuable insights from existing stockpiles of delivery-vulnerability data.

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References

2014A Contingent Resource‐Based Perspective of Supply Chain Resilience and Robustness 2014A critical review on supply chain risk – Definition, measure and modeling 2015Structural drivers of upstream supply chain complexity and the frequency of supply chain disruptions 2017Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review 2018A review of supply chain risk management: definition, theory, and research agenda 2017Supply chain disruption propagation: a systemic risk and normal accident theory perspective 2018Resilience in agri-food supply chains: a critical analysis of the literature and synthesis of a novel framework 2011Global supply chain design considerations: Mitigating product safety and security risks

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