中国城际专线物流网络空间格局

doi:10.11821/dlxb202004011

地理学报 ›› 2020, Vol. 75 ›› Issue (4): 820-832.doi: 10.11821/dlxb202004011

中国城际专线物流网络空间格局

任梦瑶^1,², 肖作鹏^1,³(), 王缉宪⁴

1. 哈尔滨工业大学（深圳）,深圳 518055
2. 香港理工大学,香港 999077
3. 深圳市城市规划与决策仿真重点实验室,深圳 518055
4. 香港城市大学,香港 999077

收稿日期:2018-08-27 修回日期:2019-12-02 出版日期:2020-04-25 发布日期:2020-06-25
通讯作者: 肖作鹏
作者简介:任梦瑶(1991-), 女, 河北张家口人, 博士生, 主要从事城市交通与土地利用方面的研究。E-mail: mengyao_ren@hotmail.com
基金资助:
国家自然科学基金重大项目(71390335);国家自然科学基金项目(41801151);广东省自然科学基金项目(2018A030310691)

Spatial pattern of intercity less-than-truckload logistics networks in China

REN Mengyao^1,², XIAO Zuopeng^1,³(), James J. WANG⁴

1. Harbin Institute of Technology, Shenzhen 518055, Guangdong, China
2. The Hong Kong Polytechnic University, HKSAR 999077, China
3. Shenzhen Key Laboratory of Urban Planning and Decision Making, Shenzhen 518055, Guangdong, China
4. City University of Hong Kong, HKSAR 999077, China

Received:2018-08-27 Revised:2019-12-02 Online:2020-04-25 Published:2020-06-25
Contact: XIAO Zuopeng
Supported by:
Major Program of National Natural Science Foundation of China(71390335);National Natural Science Foundation of China(41801151);Natural Science Foundation of Guangdong Province, China(2018A030310691)

摘要/Abstract

摘要：

物流是地域间社会经济联系的重要要素,城市间的物流联系是理解区域生产消费联系和城市空间体系的重要视角。但是由于数据与方法等层面的不足,较少有研究能够有效地揭示全国城市间的物流网络格局。近年来随着互联网与数据科学的发展应用,第四方物流平台的出现及其对各类物流资源和数据的整合为物流研究提供了新的数据源和基础平台。本文采集了中国规模最大的电子商务平台旗下第四方物流平台上的物流专线交易数据,采用社会网络分析方法,以地级市为空间单元汇总计算到发各城市的物流订单,测算各城市的专线物流联系强度以及网络中心性,旨在揭示中国城际专线物流的联系格局,透视各城市在全国专线物流网络中的职能差异。研究发现：① 中国城际专线物流联系强度的空间分布与区域间社会经济发展格局基本一致,以“京津冀—长三角—珠三角”为核心,呈现出由沿海向内陆地区梯度递减的趋势;② 中国城际专线物流具有明显的跨区流动特征,1200 km距离范围内的专线物流活动最为活跃;③ 依照全国专线物流网络中的职能特征,可将各城市划分为全国物流首位城市、全国物流中心城市、全国物流节点城市、区域物流节点城市和地区物流节点城市5类。上述研究结论期望从专线物流联系的视角为国家与各区域及城市制定空间规划及专项规划提供支撑。

关键词: 城际物流联系, 专线物流, 社会网络分析, 空间格局, 职能分类

Abstract:

Freight logistics is one of the most important socioeconomic connection elements between regions. The intercity logistics connection is an important perspective to understand regional production-consumption relationship and urban spatial structure. However, due to the lack of data and methods, few studies can effectively reveal the intercity logistics network pattern at the nation level. With the development and application of Internet and data science, the logistics resources and data integrated by the fourth party logistics platform provide new data source and research foundation for logistics studies. Drawing online less-than-truckload logistics transaction data for 3 months from November 2017 to January 2018, from the largest 4th party logistics (4PL) platform in China, this research aims to explore the intercity logistics connection pattern and urban logistics function differences. The outbound and inbound transaction numbers were calculated first for each prefecture-level city. With the approach of social network analysis (SNA), the logistics connection intensity and corresponding centrality were then computed and visualized for each city in the network. The research results show that: (1) the intercity logistics landscape roughly coincides with interregional socio-economic development. Taking three metropolises (i.e., Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta) as core triangle corridors, the national logistics connection pattern decreases from coastal area to inland areas. (2) Logistics activities are characterized by significant cross-regional flow. Active are intercity logistics shipment activities within the threshold of 1200 km distance. (3) According to the less-than-truckload logistics (LTL) network pattern, cities in China could be further divided into five categories, namely the national primary logistics city, national logistics center cities, national logistics node cities, regional logistics center cities and local logistics cities. These conclusions are expected to, from the perspective of intercity logistics connections, support national, provincial and city governments to make spatial planning and logistics planning.

Key words: intercity logistics connection, less-than-truckload logistics, social network analysis, spatial pattern, functional classification

任梦瑶, 肖作鹏, 王缉宪. 中国城际专线物流网络空间格局[J]. 地理学报, 2020, 75(4): 820-832.

REN Mengyao, XIAO Zuopeng, James J. WANG. Spatial pattern of intercity less-than-truckload logistics networks in China[J]. Acta Geographica Sinica, 2020, 75(4): 820-832.

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类别		城市
I 全国物流首位城市		上海^**(1个)
Ⅱ 全国物流中心城市	Ⅱ-1输出型	深圳^、宁波^(港口型物流中心城市2个)
		苏州^*、东莞^、佛山^*(制造型物流中心城市3个)
		广州^、杭州^(枢纽型物流中心城市2个)
	Ⅱ-2输入型	北京^、天津^、成都^、重庆^、武汉^**(5个)
Ⅲ 全国物流节点城市		沧州、无锡^、绍兴、温州^、泰州、金华^、台州、青岛^、常州、泉州^、南通^、嘉兴、郑州^、汕头、阳江、中山、新乡、厦门^、廊坊、南京^、西安^*(21个)
Ⅳ 区域物流节点城市		衡水、惠州、洛阳^、潮州、邢台、湖州、潍坊^、江门、烟台^、揭阳、保定^、镇江、盐城、扬州、济南^*、徐州^、石家庄^、福州^、合肥^、沈阳^、长沙^、大连^、昆明^、哈尔滨^、长春^**(25个)
V 地区物流节点城市		南宁^、贵阳^、唐山^、南昌^、邯郸^、太原^、海口^、兰州^、乌鲁木齐^、呼和浩特^、西宁^、银川^、拉萨^……(186个)

中国城际专线物流网络空间格局

Spatial pattern of intercity less-than-truckload logistics networks in China

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