Topological structure and COVID-19 related risk propagation in TFT-LCD supply networks

Yue, Xiongping; Mu, Dong; Wang, Chao; Ren, Huanyu; Ghadimi, Pezhman

doi:10.1080/00207543.2022.2027039

Cited by 21 publications

(7 citation statements)

References 89 publications

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“…The COVID-19 pandemic has unveiled a new and understudied area of SC resilience, i.e., analysis of SC operations and performance under long-lasting disruptions of exogenous dynamics [ 8 , 29 , 38 , 84 , 100 ]. In particular, SC decision-makers were frequently lacking a guidance on how to react to the pandemic.…”

Section: Introductionmentioning

confidence: 99%

Adapting supply chain operations in anticipation of and during the COVID-19 pandemic

Rozhkov

Ivanov

Blackhurst

et al. 2022

Omega

127

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Section: Introductionmentioning

confidence: 99%

Adapting supply chain operations in anticipation of and during the COVID-19 pandemic

Rozhkov

Ivanov

Blackhurst

et al. 2022

Omega

127

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“…and (Chervenkova & Ivanov, 2023) studied intertwining strategies for automotive industry repurposing for production of healthcare product through intertwining of commercial and healthcare supply chains. Yue et al, (2023) used network simulation to identify hidden risky sources in TFT-LCD supply networks, considering risk propagation. Their approach allows the detection of hidden risky interfirm cooperation.…”

Section: Circular-intertwined Supply Networkmentioning

confidence: 99%

Design of resilient and viable sourcing strategies in intertwined circular supply networks

Echefaj,

Charkaoui,

Cherrafi

et al. 2024

Ann Oper Res

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This study examines the effects of intertwining and circularity on the design of resilient and viable sourcing and recovery strategies in supply chains. We first construct a case study where the supply chains of three industries (i.e., automotive, healthcare, and electronics) frame an intertwined supply network (ISN). Through a discrete-event simulation model developed in anyLogistix, we examine the impact of disruptions in supply and demand on the performance of individual supply chains and the ISN as a whole. We test the performance of several sourcing strategies and their combinations. A special focus is directed toward shared reverse flows. The results show that disruption impact and recovery processes in the Circular ISN do not always follow conventional patterns known from the resilience of individual supply chains due to intertwining and circularity effects. We offer some managerial recommendations for the design of resilient sourcing strategies in the ISN context that are triangulated around collaborative sourcing practices, coordinated production planning, shared reverse flows, and visibility in inventory management.

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“…Huo et al [49], Gomez et al [57], and Hosseini and Ivanov [58] modeled an SCN as a multilayer network rather than a single-layer network. Yue et al [59] considered the existence of weights for the edges in a network with different degrees of business transactions between node enterprises. Zhao et al [53], Li and Zobel [15]; Wang, Zhou, and Jin [24]; and Kim, Chen, and Linderman [43] studied the influence of the degree of initial infection nodes, the average degree size, and the network type.…”

Section: Supply Chain Network Risk Propagationmentioning

confidence: 99%

Research on Supply Chain Network Resilience: Considering Risk Propagation and Node Type

Xue,

Li,

et al. 2024

Applied Sciences

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The aim of this study is to investigate the impact of network characteristics on supply chain network resilience (SCNR) when risk propagation occurs in supply chain networks (SCNs). The network characteristics we study here (e.g., clustering coefficient, scalar index, node type, etc.) are exceptionally important for real-life SCNs, but are not sufficiently considered in the previous research on SCNR. To this end, we first construct an SCN model with adjustable parameters for multiple network characteristics. Second, this SCN model is combined with a susceptible–infectious–susceptible model to construct an SCN risk propagation model. Third, we propose using the average (i.e., a novel SCNR metric considering node type) of the sizes of the maximum connected subgraphs (which contain all node types) over a period of time after risk propagation reaches a steady state. Fourth, the parameters of the SCN model are adjusted to generate SCNs with different network characteristics, and then the resilience of these SCNs is addressed accordingly. The simulation results mainly show the following: the larger the scalar index of an SCN is, the higher its resilience; the larger the clustering coefficient of an SCN is, the smaller its resilience; and the more uniform the distribution of node types is in an SCN, the higher its resilience. Our research work will help optimize SCNs’ structure, which has important implications for society and practice.

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Topological structure and COVID-19 related risk propagation in TFT-LCD supply networks

Cited by 21 publications

References 89 publications

Adapting supply chain operations in anticipation of and during the COVID-19 pandemic

Adapting supply chain operations in anticipation of and during the COVID-19 pandemic

Design of resilient and viable sourcing strategies in intertwined circular supply networks

Research on Supply Chain Network Resilience: Considering Risk Propagation and Node Type

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