供应链
有可能
风险分析(工程)
风险管理
供应链风险管理
适应性
供应链管理
鉴定(生物学)
计算机科学
分析
匹配(统计)
信息技术
业务
实证研究
大数据
机制(生物学)
服务管理
产业组织
过程管理
信息安全
Nexus(标准)
外包
预测分析
公司治理
功率(物理)
标识
DOI:10.1108/scm-06-2025-0582
摘要
Purpose This study aims to examine how computing enhances firms’ supply chain risk management capability by addressing its role as a critical element of digital infrastructure. It explores both the magnitude and mechanisms through which computing power strengthens firms’ ability to anticipate, mitigate, and respond to supply chain disruptions, thereby improving operational security and adaptability in volatile environments. Design/methodology/approach This study uses a firm-level panel dataset of Chinese listed companies. A fixed-effects model is applied, along with instrumental variable estimation and propensity score matching to address endogeneity. Mechanism and heterogeneity analyses are conducted to reveal the pathways of influence and contextual conditions shaping the effectiveness of computing power. Findings Empirical results demonstrate that computing power significantly enhances firms’ supply chain risk management capability. Mechanism analyses reveal three distinct channels: predictive analytics that improve risk sensing, strategic agility that enables adaptive response, and logistics optimization that supports efficient reconfiguration. Heterogeneity analyses further indicate that these effects are more pronounced in firms with stronger internal resilience, those operating in regions with more advanced digital infrastructure, and manufacturing sectors. Originality/value This study positions computing power as a critical enabler of supply chain risk management by embedding it within the dynamic capabilities framework, emphasizing its role in risk sensing, strategic response, and logistics reconfiguration. It advances the resource-based view in the digital era by conceptualizing computing infrastructure as a foundational resource. By developing novel firm-level measures and employing a causal identification strategy in an emerging market context, the study offers empirical insights into how digital capacity translates into adaptive supply chain capabilities.
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