摘要
基于2005—2015年中国省级面板数据,运用TOPSIS模型测度省区物流业发展水平,并结合核密度估计、探索性数据等方法研究物流产业演化规律,最终构建GTWR模型考察物流产业发展的驱动因素及其时空异质性。研究表明:中国省域物流业发展差异性与相关性并存;物流产业多维驱动要素呈现出明显的时空非平稳性,不同时点、地区各驱动要素的波动方向和强度并不相同,不同驱动要素分别呈现出左偏、右偏、对称、多峰等分布态势;各要素均呈现出一定的东、中、西梯度分布格局;不同地区各驱动要素的时变形态也存在不同。
Based on the Chinese provincial panel data from 2005 to 2015, this study utilizes TOPSIS model to measure the development level of provincial logistics industry, and combines Kernel density estimation method and ESDA method to analyze the law of industrial evolution. Besides, the Geographical and Temporally Weighted Regression (GTWR) model is developed to explore the driving factors and spatial-temporal heterogeneity of the logistics industry. The results prove that spatial difference and spatial autocorrelation exist in the development of China′s provincial logistics industry. The multi-dimensionally influencing factors of the logistics industry obviously show temporal and spatial non-stationarity. Moreover, the direction and intensity of the driving factors differ from time points and regions. From the perspective of the overall distribution of coefficients, different driving elements show the left, right, symmetrical, multi-peak and other distribution trends. However, from the view of spatial difference of the coefficients, each element presents a certain gradient of east, middle and west pattern. Also, from the perspective of time series fluctuation of coefficients, the time-varying patterns of driving factors in different regions are different, mainly rising, falling and volatility.
作者
唐建荣
张鑫和
类延波
TANG JianRong;ZHANG XinHe;LEI YanBo(School of Business, Jiangnan University, Wuxi 214122)
出处
《财贸研究》
CSSCI
北大核心
2019年第1期1-19,共19页
Finance and Trade Research
基金
国家自然科学基金项目"小样本非等距灰色预测模型建模及其应用研究"(71301061)
江苏省研究生培养创新工程项目"基于可拓物元模型的我国物流产业成熟度评价"(SJZZ16_0213)
关键词
物流产业
驱动因素
GTWR模型
异质性
logistics industry
driving factors
geographical and temporally weighted regression
heterogeneity
