长三角集装箱码头效率时空演化及其影响因素

doi:10.11821/dlyj020190737

地理研究 ›› 2020, Vol. 39 ›› Issue (8): 1782-1793.doi: 10.11821/dlyj020190737

长三角集装箱码头效率时空演化及其影响因素

叶士琳¹^,²^,³(), 蒋自然⁴(), 祁新华²

1.福建师范大学湿润亚热带生态地理过程教育部重点实验室,福州 350007
2.福建师范大学地理科学学院,福州 350007
3.中国科学院地理科学与资源研究所/区域可持续发展分析与模拟重点实验室,北京 100101
4.浙江师范大学经济与管理学院,金华 321004

收稿日期:2019-08-26 修回日期:2020-05-17 出版日期:2020-08-20 发布日期:2020-10-20
通讯作者: 蒋自然
作者简介:叶士琳（1991-）,男,福建宁德人,博士,讲师,主要研究方向为区域发展与交通地理。E-mail: yeshilin1991@fjnu.edu.cn
基金资助:
国家自然科学基金项目(41901138);国家自然科学基金项目(41801111);教育部人文社会科学研究青年基金项目(19YJCZH225);浙江省自然科学基金项目(LY18D010004)

Spatio-temporal characteristics and influencing factors of container terminals efficiency in the Yangtze River Delta

YE Shilin¹^,²^,³(), JIANG Ziran⁴(), QI Xinhua²

1. Key Laboratory for Humid Subtropical Eco-geographical Processes of the Ministry of Education, Fujian Normal University, Fuzhou 350007, China
2. School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China
3. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
4. School of Economics and Management, Zhejiang Normal University, Jinhua 321004, Zhejiang, China

Received:2019-08-26 Revised:2020-05-17 Online:2020-08-20 Published:2020-10-20
Contact: JIANG Ziran

摘要/Abstract

摘要：

集装箱码头效率对区域经济发展具有重要影响。采用超效率SBM模型对2008—2017年长三角地区15家集装箱码头效率进行测度,分析其时空演化特征及关键影响因素。结果表明：长三角集装箱码头效率总体水平不高,但整体保持增长态势;纯技术效率的提高是推动集装箱码头效率增长的主要动力;长三角集装箱码头效率空间格局发生显著调整,表现出明显的阶段性特征,且近年来其空间差异向均衡化方向发展;沿海集装箱码头与沿江集装箱码头效率演化态势差异明显,前者总体表现更好;人力资源、集疏运条件和港口功能对集装箱码头效率具有显著的正向作用,股权结构与腹地经济等相关指标未通过模型检验,作用并不显著。

关键词: 码头效率, 超效率SBM模型, Tobit模型, 时空格局, 长三角地区

Abstract:

With the continuous development of the global port and shipping market, inter-port competition is increasingly manifesting as competition at the terminal level. The efficiency of container terminals will significantly affect the efficiency and competitiveness of the whole port supply chain, and then have an important impact on regional economic development. It has grown up to be a challenging task for many countries to measure and understand the efficiency characteristics of container terminals scientifically, especially for developing countries and emerging market countries. Therefore, research on container terminal efficiency has received more and more attention in recent years, but there are the research results based on the geographical perspective. In this paper, 15 main container terminals in the Yangtze River Delta region are chosen as the research object, and their efficiency between 2008 and 2017 is measured by using the super-efficiency SBM model, and then the spatial-temporal evolution characteristics are analyzed. On this basis, the Tobit model is utilized to analyze the key factors affecting the efficiency of container terminals. The result shows that: (1) the overall level of comprehensive technical efficiency of the Yangtze River Delta container terminal is not high, the highest efficiency value is only 0.581, but the overall growth trend remains unchanged. During the study period, the average scale efficiency value of container terminals showed a slowly decreasing trend year by year, while the average pure technical efficiency value maintained a steady growth trend. The gap between them is narrowing year by year. Besides, the principal driving force for the slow growth of comprehensive technical efficiency comes from the improvement of pure technical efficiency. (2) From 2008 to 2017, the change trends of container terminal efficiency in the study region were different, which jointly promote the significant adjustment of the spatial pattern of container terminals efficiency. During the study period, the coefficient of variation of the comprehensive technical efficiency of the delta container terminal fluctuated between 0.159 and 0.318, and the spatial pattern evolution of container terminals efficiency has obvious phase characteristics. Since 2013, this spatial difference has developed towards equalization. At the same time, there are noticeable differences in efficiency evolution between the coastal and the riverside container terminals, and the former performs better. (3) Depending on the regression analysis results of influencing factors, human resources, port collection and distribution conditions, and port functions have a significant positive effect on container terminal efficiency. Also, the relevant indicators of ownership structure and hinterland economy have not passed the model test, and their impact is not significant.

Key words: terminal efficiency, super-SBM model, Tobit model, spatial-temporal patterns, the Yangtze River Delta

叶士琳, 蒋自然, 祁新华. 长三角集装箱码头效率时空演化及其影响因素[J]. 地理研究, 2020, 39(8): 1782-1793.

YE Shilin, JIANG Ziran, QI Xinhua. Spatio-temporal characteristics and influencing factors of container terminals efficiency in the Yangtze River Delta[J]. GEOGRAPHICAL RESEARCH, 2020, 39(8): 1782-1793.

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指标	产出	投入
指标	集装箱吞吐量(TEU)	码头长度(m)	桥吊数量(台)	轮胎吊数量(台)	在岗职工人数(人)
最大值	8900088	3000	60	140	1110
最小值	221045	300	3	4	252
均值	3008600.90	1345.27	15.54	43.21	596.61
标准差	2198505.84	717.95	9.960	28.43	222.24

集装箱码头	2008年	2009年	2010年	2011年	2012年	2013年	2014年	2015年	2016年	2017年
连云港新东方	0.584	0.561	0.683	0.829	0.878	1.150	0.794	1.048	1.003	0.792
南京龙潭	0.451	0.427	0.474	0.559	0.572	0.644	0.660	0.585	0.609	0.630
南通港	0.453	0.408	0.423	0.437	0.444	0.449	0.465	0.462	0.466	0.483
张家港永嘉	0.466	0.496	0.471	0.594	0.559	0.773	0.545	0.495	0.496	0.515
太仓国际	0.339	0.324	0.424	0.385	0.374	0.385	0.392	0.391	0.383	0.385
扬州远扬	0.442	0.434	0.491	0.461	0.390	0.385	0.397	0.411	0.376	0.387
上海浦东	0.647	0.519	0.549	0.540	0.502	0.518	0.543	0.562	0.571	0.594
上港振东	0.650	0.568	0.621	0.617	0.628	0.653	0.698	0.764	0.638	0.656
上海沪东	0.554	0.553	0.568	0.597	0.542	0.551	0.569	0.598	0.603	0.636
上海明东	0.582	0.569	0.624	0.535	0.356	0.476	0.514	0.548	0.569	0.624
上海盛东	0.437	0.372	0.451	0.429	0.580	0.582	0.616	0.621	0.630	0.685
上海冠东	0.291	0.356	0.459	0.584	0.625	0.627	0.655	0.658	0.666	0.717
宁波北仑	0.507	0.462	0.515	0.516	0.509	0.469	0.495	0.503	0.500	0.610
宁波北二	0.593	0.542	0.579	0.549	0.583	0.610	0.553	0.494	0.518	0.508
宁波大榭	0.319	0.335	0.398	0.422	0.446	0.449	0.500	0.515	0.460	0.492

变量	回归系数	标准误差	Z统计量	P值
X₁	0.385	0.090	4.268	0.000^***
X₂	0.015	0.064	0.240	0.810
X₃	0.030	0.080	0.379	0.705
X₄	0.091	0.050	1.811	0.070^*
X₅	-0.048	0.134	-0.359	0.720
X₆	-0.039	0.113	-0.342	0.733
X₇	0.187	0.063	2.972	0.003^***
c	-0.030	0.077	-0.383	0.701
对数似然值	89.165

长三角集装箱码头效率时空演化及其影响因素

Spatio-temporal characteristics and influencing factors of container terminals efficiency in the Yangtze River Delta

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