Author(s)

YiTao Yin^1*, YiFei Liao², LeTong Ji³, ZiFan Wang²

Affiliation(s)

¹School of mathematics and statistics, Nanjing University of Information Science and Technology, Nanjing 210000, Jiangsu, China.

²School of Business, Nanjing University of Information Science and Technology, Nanjing 210000, Jiangsu, China.

³School of Computer Science, School of Cyber Security, Nanjing University of Information Science and Technology, Nanjing 210000, Jiangsu, China.

Corresponding Author

YiTao Yin

ABSTRACT

With the accelerated development of China's agricultural modernisation, the importance of cold chain logistics for agricultural products has become increasingly prominent. However, problems such as insufficient cold chain coverage and lack of pre-cooling links have led to high spoilage rates and high logistics costs for fresh agricultural products. Taking Jiangsu Province as an example, this study constructs a two-stage cold chain logistics and distribution centre site selection model that takes economic, environmental and social factors into account. In the first stage, this study selects 12 indicators in four dimensions, namely, economic development, traffic congestion, total logistics demand, and green and low-carbon level, and uses the entropy weight method to quantitatively assess the logistics level of 13 cities in Jiangsu Province. By calculating the logistics level score of each city, the spatial economic distance between cities is defined, and the K-means clustering algorithm is combined to divide Jiangsu Province into regions. The clustering results show that the clustering method based on spatial economic distance can more scientifically reflect the economic connection and logistics demand among cities, which provides an important basis for the subsequent site selection decision. In the second stage, the study uses the centre of gravity method to select the optimal distribution centre location within each clustering region. The centre of gravity method determines the optimal location of the distribution centre by calculating the weighted average location of each demand point within the region with the objective of minimising transport costs. Ultimately, by comparing the two methods based on spatial economic distance clustering and traditional geographic distance clustering, the results show that the clustering method based on spatial economic distance significantly reduces the transport cost. The total transport cost is reduced from $16,356.33 to $14,156.00, which is about 13.45%. This result not only verifies the validity and practicability of the constructed model, but also provides a scientific basis for the location of cold chain logistics distribution centre in Jiangsu Province, which helps to improve the operational efficiency and economic benefits of cold chain logistics.

KEYWORDS

Cold chain logistics; Site selection model; Entropy weight method; K-means clustering; Centre of gravity method

CITE THIS PAPER

YiTao Yin, YiFei Liao, LeTong Ji, ZiFan Wang. The location of cold chain logistics for agricultural products for the"first kilometre". Eurasia Journal of Science and Technology. 2025, 7(3): 60-66. DOI: https://doi.org/10.61784/ejst3093.

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