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The coordinated development of regional logistics and the economy is crucial for regional economic progress and for reducing regional development disparities. This study applies regional coordinated development theory and coupling theory, utilizing the Coupling Coordination Degree Model (CCDM) to analyze data from 31 provinces and cities in China in 2021, with the analysis results serving as the outcome variable. Additionally, we use data from four dimensions: infrastructure investment (II), technological innovation (TI), industrial structure (IS), and human capital (HC), as the conditional variables, conducting a multi-factor configurational analysis using fsQCA. Three paths with high coupling coordination and one path with non-high coupling coordination are identified, and the reasons for each path are analyzed. The results indicate that: 1) there are significant regional disparities in China regarding economic development, logistics development, and the degree of their coupling and coordination, with the eastern regions exhibiting higher levels and the western regions and other remote areas exhibiting lower levels. 2) The three paths with high coupling coordination are: "Infrastructure Investment-Technological Innovation", "Technological Innovation-Industrial Structure-Human Capital", and "Infrastructure Investment-Fundamental Innovation-Industrial Structure". These three types facilitate the well-coordinated progress of regional logistics and the economy. The article concludes by highlighting policy suggestions that underscore the significance of fortifying the bond between the logistics industry and the economy, alongside earnest efforts to enhance regional logistics standards. This will foster a mutually reinforcing and co-developing situation, further promoting coordinated development among regions, achieving high-quality regional development, and reducing the imbalances in logistics and economic development among different regions.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10833549 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0297441 | PLOS |
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Departmento de Química Inorgánica, Universidad de Valencia, C/Dr. Moliner 50, 46100 Burjasot, Valencia, Spain.
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School of Mathematics and Computer Science, Gannan Normal University, Ganzhou, 341000, China.
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State Key Laboratory of Agricultural Products Safety, Ningbo University, Ningbo, Zhejiang 315211, China.
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