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机构地区:[1]中国矿业大学(北京)理学院,北京
出 处:《统计学与应用》2021年第2期345-353,共9页Statistical and Application
摘 要:本文利用2020年中国31个省级行政区邮政快递业收入及相关经济发展指标数据,借助空间统计分析的方法,分析了我国邮政快递业收入的空间关联性及影响因素。通过空间权重矩阵不同形式的比较,确定了基于地理邻接性的空间权重矩阵在本研究中的合理性;全局Moran指数表明我国各省份邮政快递业收入存在显著的空间聚集性;基于局部Moran散点图分析了离群点广东省和海南省的邮政快递业收入异常成因;LISA集聚图表明我国快递业低值集聚区域(冷点)主要集中在西北部,高值集聚区(热点)主要集中在东部、东南部沿海地区;通过不同局部自相关指数与实际情况的对比分析可知,对我国邮政快递业收入来说局部Moran指数相较其他两种指标分析结果更合理;对各省份邮政快递业收入与人均可支配收入进行了双变量自相关分析。最后结合实际情况,对长三角和珠三角的未来快递业发展给出了相关建议。This article mainly uses data on the income of the postal express industry and related economic development indicators of the provinces nationwide in 2020, and analyzes the spatial correlation and influence factors of the income of the postal express industry in the country by spatial statistical analysis methods. Compare different defining methods of spatial weights, confirming the rationality of spatial weight matrix based on geographic proximity in this research. Global Moran index indicates that there is a significant spatial correlation in the income of the postal express industry in all the provinces. Based on Moran scatter plot, the abnormal points of postal express industry income in Guangdong Province and Hainan Province and their causes are analyzed. The LISA cluster map shows that the low-value agglomeration areas (cold spots) are mainly concentrated in the northwest, and the high-value agglomeration areas (hot spots) are mainly concentrated in the eastern and southeast coastal areas. The comparison of the analysis results of different indexes and the reality shows that the Moran index is better than the other two indexes for analyzing the spatial correlation of postal express industry income. A bivariate autocorrelation analysis between the postal express industry income and average disposable income in various provinces is carried out. Considering the actual situation, Yangtze River Delta and the Pearl River Delta is compared and relevant suggestions for future development directions are given.
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