How did supply chain networks handle the COVID-19 pandemic? Empirical evidence from an automotive case study

INTERNATIONAL JOURNAL OF PHYSICAL DISTRIBUTION & LOGISTICS MANAGEMENT(2022)

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摘要
Purpose The coronavirus disease 2019 (COVID-19) pandemic unveiled resilience deficits in supply chains. Scholars and practitioners aim to identify supply chain resilience (SCRES) measures suitable for this unique disruption; however, empirical evidence on a pandemic's specific characteristics, resulting challenges, and suitable countermeasures is scarce. Design/methodology/approach A single-case study on an automotive supply chain network (ASCN), including eight nodes, was conducted. Based on current research and interviews with 35 experts, characteristic pandemic challenges for the ASCN were identified. Moreover, promising SCRES measures were determined along the most prominent SCRES levers. The findings lead to five central propositions and advance organizational information processing theory in the context of SCRES. Findings This study's results confirm unique pandemic characteristics along the supply chain disruption's duration, severity, propagation, and volatility. The resulting unprecedented challenges made the ASCN apply novel SCRES measures, particularly regarding collaboration and risk management culture. However, well-known visibility and flexibility strategies were also suitable. Overall, agility and collaboration measures showed the highest capacity to address characteristic pandemic challenges. A lack of preparedness impeded some measures' application, calling for enhanced proactive risk management following the pandemic. Originality/value This paper addresses several research calls by providing in-depth empirical evidence on hitherto conceptually researched pandemic characteristics, challenges, and suitable SCRES measures from a network perspective. The study uncovers the different perceptions of individual tiers, emphasizing the need to analyze supply chain disruptions from multiple angles.
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关键词
Supply chain resilience, COVID-19 pandemic, Automotive supply chain, Supply chain network, Case study, Organizational information processing theory
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