Necessary Antecedents of Supply Chain Resilience: The Nonnegotiable Influence of Supply Chain Responsiveness and Collaboration

业务 供应链 弹性(材料科学) 产业组织 供应链管理 链条(单位) 供应链风险管理 营销 服务管理 天文 热力学 物理
作者
Ethan Nikookar,Imran Ali,Mark Stevenson,Sajjad Shokouhyar
出处
期刊:Journal of Supply Chain Management [Wiley]
卷期号:61 (4): 54-76 被引量:8
标识
DOI:10.1111/jscm.70000
摘要

ABSTRACT According to the social‐ecological systems view, a resilient supply chain possesses the ability to persist, adapt, and transform in the face of disruptions. Extant research has identified a range of antecedents that foster supply chain resilience but without distinguishing between those that are sufficient and those that are necessary. While altering sufficient antecedents might affect resilience, their absence does not preclude it because of the potential compensatory effects of other factors. Conversely, necessary antecedents are indispensable, as their absence prevents the realization of resilience, a scenario that cannot be rectified by modifying other antecedents. Grounded in dynamic capabilities theory, this research hypothesized that supply chain visibility, responsiveness, flexibility, and collaboration are necessary antecedents of supply chain resilience. To empirically test this, the research applied Necessary Condition Analysis (NCA) to survey data from 479 manufacturing firms in Australia. The results indicate that only supply chain responsiveness and collaboration are necessary antecedents. A bottleneck analysis was also undertaken to determine how much supply chain collaboration and responsiveness is needed to achieve different levels of supply chain resilience. The research proposes a two‐tiered maturity model—Tier 1 (necessary) capabilities versus Tier 2 (contributory) capabilities—for building supply chain resilience and extends dynamic capabilities theory by demonstrating that specific capabilities may be nonnegotiable for enhancing sensing, seizing, and resource‐reconfiguration capacities. The research provides managerial guidance for determining how limited organizational resources can be most efficiently deployed to handle disruptions.
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