Forecasting and spatial distribution analysis of cold chain logistics demand for fresh agricultural products in China
China’s coastal and inland regions exhibit significant disparities in economic development, population density, and agricultural diversity, creating a critical need to understand their distinct cold chain logistics demands. This study employs the Grey Model (1,1) to forecast the demand for fresh agr...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | en |
| Published: |
Springer Nature
2025
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/50595/1/s10668-025-06969-9.pdf http://ir.unimas.my/id/eprint/50595/ https://link.springer.com/article/10.1007/s10668-025-06969-9 https://doi.org/10.1007/s10668-025-06969-9 |
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| Summary: | China’s coastal and inland regions exhibit significant disparities in economic development, population density, and agricultural diversity, creating a critical need to understand their distinct cold chain logistics demands. This study employs the Grey Model (1,1) to forecast the demand for fresh agricultural foods cold chain logistics in these regions from 2023 to 2027 and conducts a spatial distribution analysis. The results project that by 2027, the
total national demand will reach 1,571.14 million tons, with the inland region accounting for the larger share at 876.56 million tons compared to 694.58 million tons in the coastal
region. These findings indicate a persistent and growing regional imbalance in demand. The study concludes that such a detailed forecast is essential for refined decision-making
and provides valuable insights for policymakers and stakeholders to optimize resource allocation, enhance risk management, and promote the sustainable development of China’s agricultural supply chain. |
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