Du J, Wang J, Liang J, Liang R. Research on the impact of smart logistics on the the manufacturing industry chain resilience.
Sci Rep 2025;
15:9052. [PMID:
40090946 PMCID:
PMC11911421 DOI:
10.1038/s41598-025-93806-8]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2024] [Accepted: 03/10/2025] [Indexed: 03/19/2025] Open
Abstract
The development history of smart logistics and smart manufacturing in China demonstrates a high degree of synergy. This study aims to analyze the impact, mechanisms, and heterogeneous performance of smart logistics on the manufacturing industry chain resilience. The analysis is based on panel data collected from 30 provinces in China, covering the period from 2012 to 2023. The empirical findings suggest a significant positive impact of smart logistics on the manufacturing industry chain resilience, and the research findings are relatively robust. This impact can be primarily attributed to the reduction of transaction costs and improvements in logistics efficiency. In a comparison of the impact relationships between the three different economic regions of the East, Center and West, it was found that the Eastern region had a stronger facilitating effect, the Central region had a less pronounced facilitating effect, and the Western region had a weaker facilitating effect relative to the Eastern region. Moreover, Intelligent logistics has a greater role in promoting the resistance and renewal of the manufacturing industry chain, and a relatively weaker role in promoting the recovery of the manufacturing industry chain. Futhermore, threshold test shows that, in terms of long-term dynamics, there is a threshold effect of smart logistics development on the enhancement of manufacturing industry chain toughness; at the same time, higher level of advanced industrial structure and innovation environment, smart logistics is conducive to the enhancement of manufacturing industry chain toughness level.
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