级联中断:模块化和关联供应商预测的影响

IF 10.2 2区 管理学 Q1 MANAGEMENT
Jafar Namdar, Jennifer Blackhurst, Kang Zhao, Suyong Song
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引用次数: 0

摘要

供应中断可能从供应网络中的一个供应商开始,波及其他供应商和企业,即所谓的连锁中断。本研究分析了供应网络模块化对连锁中断的影响。模块化度量的是供应网络可划分为自足子网络的程度,对供应网络的复原力有不同的影响。高度模块化的供应网络由于模块之间缺乏桥梁(缺乏模块间连接),可防止级联中断在整个网络中蔓延。因此,在高度模块化的供应网络中,级联中断的规模(以受级联中断影响的供应商数量来衡量)往往小于模块化程度较低的供应网络中的级联中断规模。然而,模块内部的高度连通性(模块内部的过度连通性)是级联中断的温床。这意味着,模块化网络中的小规模中断可能会影响较少的供应商(即较小的级联规模),但以服务水平衡量,其严重程度会更高。最后,在 "关联供应商 "这一理论概念的基础上,本研究提出了一个新的预测模型,用于识别其中断会对焦点企业的运营产生重大影响的运营关联供应商。该模型的准确性在现实世界的全球供应网络中进行了实证测试,涉及 51 个国家和 111 个行业的 2598 家企业和供应商。该模型识别关联供应商的准确率高达 95%,使管理者和政策制定者能够积极主动地规划缓解策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Cascading disruptions: Impact of modularity and nexus supplier predictions

Cascading disruptions: Impact of modularity and nexus supplier predictions

Disruptions can start at one supplier in the supply network and ripple through, impacting other suppliers and firms, known as cascading disruptions. This research analyzes the effect of supply network modularity on cascading disruptions. Modularity measures the degree to which a supply network can be divided into self-contained sub-networks and has different effects on supply network resilience. A highly modular supply network prevents cascading disruptions from spreading through the whole network because of the lack of bridges between modules (lack of inter-module connectivity). Hence, the size of cascading disruptions—measured by the number of suppliers impacted by a cascading disruption—in highly modular supply networks tends to be smaller than the size of cascading disruptions in less modular supply networks. However, the high level of internal connectivity within a module (excessive intra-module connectivity) acts as an incubator for cascading disruptions. This means a small disruption in a modular network may impact fewer suppliers (i.e., smaller cascading size) but with higher severity measured by service level. Finally, building upon the theoretical concept of nexus suppliers, this research proposes a new predictive model to identify the operational nexus suppliers whose disruptions would considerably impact focal firms' operations. The model's accuracy is empirically tested on real-world global supply networks involving 2598 unique firms and suppliers across 51 countries and 111 industries. The model identifies nexus suppliers with 95% accuracy, allowing managers and policymakers to plan for mitigation strategies proactively.

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来源期刊
CiteScore
16.00
自引率
6.60%
发文量
18
期刊介绍: ournal of Supply Chain Management Mission: The mission of the Journal of Supply Chain Management (JSCM) is to be the premier choice among supply chain management scholars from various disciplines. It aims to attract high-quality, impactful behavioral research that focuses on theory building and employs rigorous empirical methodologies. Article Requirements: An article published in JSCM must make a significant contribution to supply chain management theory. This contribution can be achieved through either an inductive, theory-building process or a deductive, theory-testing approach. This contribution may manifest in various ways, such as falsification of conventional understanding, theory-building through conceptual development, inductive or qualitative research, initial empirical testing of a theory, theoretically-based meta-analysis, or constructive replication that clarifies the boundaries or range of a theory. Theoretical Contribution: Manuscripts should explicitly convey the theoretical contribution relative to the existing supply chain management literature, and when appropriate, to the literature outside of supply chain management (e.g., management theory, psychology, economics). Empirical Contribution: Manuscripts published in JSCM must also provide strong empirical contributions. While conceptual manuscripts are welcomed, they must significantly advance theory in the field of supply chain management and be firmly grounded in existing theory and relevant literature. For empirical manuscripts, authors must adequately assess validity, which is essential for empirical research, whether quantitative or qualitative.
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