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The relationship between supply chain integration and sustainability performance: a meta-analysis.

Authors :
Wang, Qinru
Chen, Lujie
Jia, Fu
Luo, Yujia
Zhang, Zhiwei
Source :
International Journal of Logistics: Research & Applications; Aug2024, Vol. 27 Issue 8, p1388-1409, 22p
Publication Year :
2024

Abstract

Supply chain integration (SCI) has been considered an antecedent of sustainability performance (SP) by some studies; however, empirical findings on the nexus between SCI and SP in the existing literature are inconsistent. The study aims to provide an extensive literature review on the SCI–SP relationship. We propose a conceptual research framework to investigate the SCI–SP relationship with consideration of the effects of contextual moderators. A meta-analysis is adopted to analyse the sample of 60 selected empirical papers focusing on this relationship. The results provide evidence of a positive relationship between SCI and SP, which is affected by the two types of moderating variables: operationalisation of SP construct and control variables (industry sector, economic development, and the country's logistics capabilities). We find that SCI has the greatest impact on economic SP and the lowest impact on social SP. The SCI–SP relationship is more robust in the service industry than in the manufacturing industry. When a country's logistics capabilities increase, SCI's influence on SP becomes weaker. The results of this study are drawn from extant empirical research, and thus the validity and reliability of these findings rely on the validity and reliability of the original studies. This study is the first meta-analysis to examine the vital relationship between SCI and SP and adopted a country's logistics capabilities as a moderator. The results offer managerial insights regarding integration dimensions that positively affect various measures of SP. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13675567
Volume :
27
Issue :
8
Database :
Complementary Index
Journal :
International Journal of Logistics: Research & Applications
Publication Type :
Academic Journal
Accession number :
178714219
Full Text :
https://doi.org/10.1080/13675567.2022.2144812