道路货物运价的空间统计分析及应用  

Spatial Statistical Analysis and Application of Road Freight Price

作　　者：张若梦[1] 赵南希 宿硕 ZHANG Ruomeng;ZHAO Nanxi;SU Shuo(Highway Science Research Institute of the Ministry of Transportation,Beijing 100088,China)

机构地区：[1]交通运输部公路科学研究院,北京100088

出　　处：《综合运输》2020年第12期120-124,共5页China Transportation Review

基　　金：中央级公益性科研院所基本科研项目:基于大数据的道路货运市场监测智能分析及辅助决策关键技术研究(2019-0087)。

摘　　要：本文采用2018年全国31个省会及直辖市(不含港澳台)的道路货物运价数据,构成运价矩阵,分别对综合运价、发送流、到达流计算全局Moran’s I统计量和局部Moran统计量,在建立带有空间滞后项的空间自相关模型,并与普通回归模型对比,最后对道路货运价格流的影响因素和空间效应进行探讨,为政府制定运价政策提供依据,为企业开展运价业务提供工具。This paper adopts the road freight price data of 31 provincial capitals and municipalities(excluding Hong Kong,Macao and Taiwan)in 2018 to form a freight price matrix,and calculates global Moran’s I statistics and local Moran’s statistics for freight price,transmission flow and arrival flow respectively.Then,a spatial autocorrelation model with spatial lag term is established and is compared with the general regression model.Finally the influencing factors and spatial effects of road freight price flow are discussed.This study provides the basis for the government to formulate freight rate policies,and provide the tool for enterprises to carry out freight rate business.

关 键 词：空间统计学 Moran’s I指数 空间自相关模型 道路货物运价 空间权重矩阵 

分 类 号：F540.4[经济管理—产业经济]