摘要
新一代信息技术促使冷链智能化水平得以快速发展,精准把控智慧冷链发展水平是实现技术瓶颈重点突破与发展方向战略布局的前提基础与保障。基于此,本研究从供给能力、仓储能力、运输能力、经济效益、信息化水平等维度构建了中国智慧冷链发展评价指标体系,运用熵权法并结合优劣解距离法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS)对2017—2021年中国30个省市(不包含西藏、中国香港、中国澳门、中国台湾)的智慧冷链发展水平进行定量评价,通过探索性空间数据分析法(Exploratory Spatial Data Analys,ESDA)和地理加权回归(Geographically Weighted Regression,GWR)分析评价指标对不同省市的影响变化。研究结果表明,经济发展状况、配套设施建设与信息化水平对智慧冷链建设影响作用较大;东部沿海地区智慧冷链发展普遍较好,西南和西北地区发展缓慢,整体发展较为落后;评价指标具有显著时空异质性,影响程度随空间位置和时间发生变化。为提升中国智慧冷链整体发展水平,就加强配套设施建设、促进信息化转型升级提出相应发展对策。本研究可为实现中国智慧冷链全局性谋划、战略性布局、整体性推进等提供科学依据。
The new generation of information technology has led to the rapid development of the intelligent level of the cold chain,and the precise control of the development level of the smart cold chain is the prerequisite foundation and guarantee to achieve the key breakthrough of the technical bottleneck and the strategic layout of the development direction.Based on this,an evaluation index system for China's intelligent cold chain development from the dimensions of supply capacity,storage capacity,transportation capacity,economic efficiency and informationization level was conducted.The entropy weight method combined with the technique for order preference by similarity to ideal solution(TOPSIS)was used to quantitatively evaluate the development of intelligent cold chain in 30 Chinese provinces and cities(excluding Tibet,Hong Kong,China,Macao,China and Taiwan,China)from 2017 to 2021.The quantitative evaluation of the level of intelligent cold chain development was conducted.The impact of the evaluation indicators on different provinces and cities was analysed by exploratory spatial data analyses(ESDA)and geographically weighted regression(GWR).The results showed that indicators such as economic development status,construction of supporting facilities and informationization level had greater weight and played a more important role in influencing the construction of intelligent cold chain.The overall level of intelligent cold chain development in China is divided into four levels,with most cities at the third and fourth levels.Beijing and the eastern coastal provinces and cities generally have a better level of intelligent cold chain development,while the southwest and northwest regions are developing slowly.In terms of overall development,the overall development of China's intelligent cold chain is relatively backward,with insufficient inter-regional synergy.The global spatial autocorrelation analysis shows that the variability in the development of China's intelligent cold chain logistics is gradually becoming greater.Through the local spatial autocorrelation analysis,it can be seen that there is a positive spatial correlation between the provinces and cities in East China,and negative spatiality in North China and South China.After geographically weighted regression analysis,it can be seen that the evaluation indicators have significant spatial and temporal heterogeneity in 2017,with the degree of influence changing with spatial location and time,and the spatial and temporal heterogeneity of the evaluation indicators is not significant in 2021.In order to improve the overall development level of China's intelligent cold chain,corresponding development countermeasures are proposed to strengthen the construction of supporting facilities and promote the transformation and upgrading of information technology.This study can provide a scientific basis for the global planning,strategic layout and overall promotion of China's intelligent cold chain.
作者
杨霖
杨斌
任青山
杨信廷
韩佳伟
YANG Lin;YANG Bin;REN Qingshan;YANG Xinting;HAN Jiawei(Research Center of information Technology,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;National Engineering Laboratory for Agri-product Quality Traceability,Beijing 100097,China;Key Laboratory of Cold Chain Logistics Technology for Agro-product,Ministry of Agriculture and Rural Affairs,Beijing 100097,China;College of Information Science and Technology,Zhongkai Agricultural Engineering College,GuangZhou 510225,China)
出处
《智慧农业（中英文）》
CSCD
2023年第1期22-33,共12页
Smart Agriculture
基金
北京市农林科学院科技创新能力建设专项(KJCX20210408)
北京市农林科学院科研创新平台建设(PT2023-24)
国家重点研发计划课题(2022YFD2001804)。
关键词
智慧冷链
熵权法
TOPSIS
探索性空间分析
地理加权回归
评价指标体系
信息化水平
intelligent cold chain
entropy power method
TOPSIS
exploratory spatial data analysis
geographically weighted regression
evaluation indicator system
informationization level
