An integrated model of supply chain resilience and its impact on supply chain performance under disruption
Purpose: This study aims to explore the relationships among the five components of supply chain (SC) resilience (SCRES): visibility, velocity, flexibility, robustness and collaboration and their impacts on the SC performance under disruption (SCPUD). Design/methodology/approach: Five SCRES components are identified from the literature review and data are collected using an web survey from 113 manufacturing companies in Taiwan. The data are analyzed by structured equation modeling with the partial least square solution. Two-stage least-squares (2SLS) regression was used to test the potential endogeneity of SC collaboration (SCC). Findings: The results reveal that SCC is an exogenous driver of SCRES; it directly affects visibility, velocity, flexibility, robustness and SCPUD. Furthermore, SC flexibility is the only component of SC agility that directly affects SCPUD; it is influenced directly by SC velocity and indirectly by SC visibility through SC velocity. SC visibility is a vital agility component that positively influences SC velocity and SC robustness. Research limitations/implications: The data in this study are cross-sectional and the sample size of 113 is relatively small. The relationship between SC robustness and SCPUD needs a longer observation period to reveal. The logistic issue in the shortage of carriers caused by the pandemic has been overlooked. Practical implications: A firm should enhance its collaboration and flexibility in the SC as they both are the critical antecedents of SC performance (SCP) during the disruption period. Originality/value: This study integrates visibility, velocity, flexibility, robustness and collaboration into a complete framework of SCRES. The dependent variable, SCPUD, measures SC performance (SCP) under the disruption caused by the COVID-19 pandemic. It is the first study to investigate the associations of the six constructs in a research model.
Year of publication: |
2021
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Authors: | Juan, Shih-Jung ; Li, Eldon Y. ; Hung, Wei-Hsi |
Published in: |
The International Journal of Logistics Management. - Emerald, ISSN 0957-4093, ZDB-ID 2069452-0. - Vol. 33.2021, 1 (04.08.), p. 339-364
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Publisher: |
Emerald |
Saved in:
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