Affiliation:
1. College of Economics and Management, Shanghai Ocean University, Shanghai, China
Abstract
With the acceleration of technological change and globalization, companies face increasing environmental uncertainty and complexity. The COVID-19 pandemic has severely damaged the global supply chain and aggravated the operational risks of supply chains. Industry and academia have conducted studies on the construction of resilient and integrated supply chains, and to date a bulk of empirical literature has already been accumulated. A notable feature of existing literature is the heterogeneity in the characterization of the relationship between supply chain resilience, supply chain integration, and supply chain performance. In this study meta-analysis and structural equation modeling (MASEM) methods are integrated to construct a theoretical framework of supply chain resilience, supply chain integration, and supply chain performance. 45 empirical studies (73 effect size data, 2092 samples) are selected from 10,623 papers published over the years 2013 to 2021 to explore the transmission mechanisms, the role of mediator variable, and boundary conditions of the relationship between supply chain resilience and supply chain performance. The results show that supply chain resilience can promote supply chain performance. Moreover, supply chain integration (supplier integration, internal integration, and customer integration) plays a partial mediating role for the impact of supply chain resilience on supply chain performance. Situations and measurement factors such as industry type, national culture (power distance), sampling area, and logistics performance have a certain impact on the relationship, and the usage of different indicators may lead to marked differences in conclusions regarding the relationship. By extracting the conclusions of existing empirical studies, this study proposes new insights into the mechanism of action of supply chain resilience, supply chain integration, and supply chain performance and provides specific suggestions for future supply chain management.
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
Cited by
1 articles.
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