Analysis of the Factors Affecting the Logistics Efficiency of Urban Farm Products in the Context of Low-carbon Economy
DOI:
https://doi.org/10.13052/spee1048-5236.4324Keywords:
Low-carbon economy, farm product, logistics efficiency, influencing factorsAbstract
The refrigeration equipment used to preserve the freshness of farm products in the farm logistics process generates carbon emissions, so the factors affecting the logistics efficiency need to be analyzed to make it sustainable in the context of low-carbon economy. This paper briefly introduced the calculation method of farm product logistics efficiency in the context of low-carbon economy and analyzed the farm product logistics industry in Jiangsu Province from 2011 to 2020. The results suggested that the input-output efficiency of the farm product logistics industry in Jiangsu was relatively high at the level of logistics technology in the context of low-carbon economy, but there was still room for improvement in the expansion scale; the economic level, industrial agglomeration, and industrial structure had a significant positive effect on the efficiency of farm product logistics, and the environmental constraints had a significant inhibitory effect on the efficiency of farm product logistics. Finally, several suggestions were put forward according to the analysis results.
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References
F. Merdivenci, M. B. Erturan, ‘LPIBased Two Stage Network DEAModel to Measure Logistics Efficiency: An Application on OECDCountries’, J. Busin. Res., 13(2):1187–1199, 2021.
H. H. Park, S. J. Cho, ‘An Analysis of the Effect of Logistics Efficiency on the Export of Korean Agricultural Products to New Southern Countries’, J. Korea Trade, 25(1):169–183, 2021.
S. T. Wang, M. H. Li, C. C. Lien, ‘Analysis of the Optimal Application of Blockchain-Based Smart Lockers in the Logistics Industry Based on FFD-SAGA and Grey Decision-Making’, Symmetry, 13(2):1–19, 2021.
H. Yu, Y. Dai, L. Zhao, ‘Evaluation and Study on influencing factors of agricultural products logistics efficiency based on DEA-Tobit model – from panel data from 2010 to 2019’, J. Phys. Conf. Ser., 1941(1):1–10, 2021.
Q. Zhang, J. Mai, Y. Li, ‘Three-stage DEA Model on the Low-carbon Logistics Efficiency in Ten Coastal Provinces of China’, J. Phys. Conf. Ser., 1910(1):1–6, 2021.
H. Yu, L. Zhao, M. Wu, ‘Study on the evaluation of agricultural product logistics efficiency in Jilin province’, J. Phys. Conf. Ser., 1629:1–8, 2020.
C. Yin, W. Gao, Z. Li, Z. Wu, Y. Wang, ‘Improved two-stage DEA model: an application to logistics efficiency evaluation enterprise in Xiamen, China’, Int. J. Innov. Comput. I., 15(2):535–549, 2019.
H. Liu, J. Tang, ‘The Research on Logistics Efficiency and Otherness on Primary Zone of Jilin Province’, IOP Conf. Ser. Mater. Sci. Eng., 677(5):1–8, 2019.
D. Wu, X. Wang, D. Xia, ‘Evaluation of freight logistics delayed efficiency in China’, IOP Conf. Ser. Earth Environ. Sci., 587:1–6, 2020.
J. Dai, ‘Evaluation Method of Logistics Transportation Efficiency of Port Enterprises Based on Game Model’, J. Coastal Res., 103(sp1): 609–613, 2020.
H. M. Amin, T. M. Shahwan, ‘Logistics management requirements and logistics performance efficiency: the role of logistics management practices – evidence from Egypt’, Int. J. Logist. Syst. Manag., 35(1):1–27, 2020.
Y. Song, G. Yeung, D. Zhu, L. Zhang, Y. Xu, L. Zhang, ‘Efficiency of logistics land use: The case of Yangtze River Economic Belt in China, 2000–2017’, J. Transp. Geogr., 88:1–12, 2020.
S. Nikolicic, M. Kilibarda, M. Maslaric, D. Mircetic, S. Bojic, ‘Reducing Food Waste in the Retail Supply Chains by Improving Efficiency of Logistics Operations’, Sustainability, 13(12):1–24, 2021.
Jiangsu Statistics Bureau. Jiangsu Statistical Yearbook (2010). China Statistical Publishing House, 2010.
M. Huang, J. Lian, ‘Comprehensive efficiency analysis of logistics industry based on machine learning and self-service data envelopment analysis model’, J. Intell. Fuzzy Syst., 40(9):1–12, 2020.