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PORT CONNECTIVITY AND SPATIAL-TEMPORAL DIFFERENCE OF ITS INFLUENCING FACTORS: THE CASE OF CHINA BOHAI RIM PORTS |
ZHANG Xin-fang, LV Jing |
College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China |
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Abstract In order to measure port connectivity and spatial-temporal difference of its influencing factors, a port comprehensive connectivity model is constructed from the aspect of port supply chain, taking into account three levels of port hinterland connectivity, domestic trade and foreign trade connectivity capacity, based on improved gravity model and location condition. The port connectivity in China Bohai Rim is research during 2002-2017, and its influencing factors are explored by adopting the spatial econometric model, including spatial error model, spatial lag model and Geographically Weighted Regression (GWR). The results show that: 1) There are great differences in hinterland connectivity, domestic trade, foreign trade and comprehensive connectivity of ports in Bohai Rim. Tianjin and Qingdao ports have the highest hinterland connectivity, Dandong and Weihai ports have the lowest, and Huanghua and Tangshan ports have the fastest growth of connectivity. 2) The pattern of port connectivity in Bohai Rim has the characteristics of "multi- core-edge" distribution, that is, the Beijing-Tianjin-Hebei region with Tianjin port as its core, the Shandong Peninsula with Qingdao port as its core and Liaoning Peninsula with Dalian port as its core. 3) There are some spatial correlation (or dependence), heterogeneity and spillover effects in the port connectivity in Bohai Rim, and the difference of connectivity among ports is gradually narrowing. Spatial econometric regression results show that all the factors have positive effect on connectivity, the logistics trade scale of has the most significant impact, and its connectivity distribution conforms to the Matthew effect.
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Received: 26 March 2019
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[1] |
Jiang L P, Jia Y, Zhang C, et al. Analysis of topology and routing strategy of container shipping network on "Maritime Silk Road"[J]. Sustainable Computing:Informatics and Systems, 2019,21(3):72-79.
|
[2] |
Beatriz T, Rubén H, Héctor R D. Container port competitiveness and connectivity:The Canary Islands main ports case[J]. Transport Policy, 2015,38:40-51.
|
[3] |
吴迪,王诺,于安琪,等."丝路"海运网络的脆弱性及风险控制研究[J].地理学报,2018,73(6):1133-1148.[Wu Di, Wang Nuo, Yu Anqi, et al. Vulnerability and risk management in the Maritime Silk Road container shipping network[J]. Acta Geographica Sinica, 2018,73(6):1133-1148.]
|
[4] |
吴迪,王诺,吴暖,等.主航道中断背景下集装箱海运网络的脆弱性及其对中国的影响[J].地理研究,2017,36(4):719-730.[Wu Di, Wang Nuo, Wu Nuan, et al. The impact of main channel interruption on vulnerability of container shipping network and China container shipping[J]. Geographical Research, 2017,36(4):719-730.]
|
[5] |
王诺,董玲玲,吴暖,等.蓄意攻击下全球集装箱海运网络脆弱性变化[J].地理学报,2016,71(2):293-303.[Wang Nuo, Dong Lingling, Wu Nuan, et al. The change of global container shipping network vulnerability under intentional attack[J]. Acta Geographica Sinica, 2016,71(2):293-303.]
|
[6] |
杨翠香,胡志华.中国与海上丝绸之路的连通性分析[J].上海大学学报(自然科学版),2018,24(3):1-9.[Yang Cuixiang, Hu Zhihua. Analysis of the connectivity between China and the Maritime Silk Road[J]. Journal of Shanghai University (Natural Science Edition), 2018,24(3):1-9.]
|
[7] |
严南南,陆珉,宗康.海上丝绸之路航线网络的连通性建模与仿真研究[J].华中师范大学学报(自然科学版),2017,51(5):655-662.[Yan Nannan, Lu Min, Zong Kang. Research on connectivity modeling and simulation for route network of Maritime Silk Road[J]. Journal of Central China Normal University (Natural Science Edition), 2017,51(5):655-662.]
|
[8] |
Jiang J L, Lee L H, Chew E P, et al. Port connectivity study:An analysis framework from a global container liner shipping network perspective[J]. Transportation Research Part E, 2015,73:47-64.
|
[9] |
Wang G W Y, Zeng Q C, Li K, et al. Port connectivity in a logistic network:The case of Bohai Bay, China[J]. Transportation Research Part E, 2016,95:341-354.
|
[10] |
Peter W de Langen, Kristina S. Intermodal connectivity as a port performance indicator[J]. Research in Transportation Business&Management, 2013,8(3):97-102.
|
[11] |
潘静静,王晓峰.复杂网络视角下的港口连通性建模及应用[J].深圳大学学报理工版,2017,34(5):544-550.[Pan Jingjing, Wang Xiaofeng. Port connectivity model based on complex network and its application[J]. Journal of Shenzhen University Science and Engineering, 2017,34(5):544-550.]
|
[12] |
Peng P, Jessie P H, Yang Y, et al. Global oil traffic network and diffusion of influence among ports using real time data[J]. Energy, 2019,172(1):333-342.
|
[13] |
Peng P, Cheng S F, Chen J H, et al. A fine-grained perspective on the robustness of global cargo ship transportation networks[J]. Journal of Geographical Sciences, 2018,28(7):881-899.
|
[14] |
Peng P, Yang Y, Cheng S F, et al. Hub-and-spoke structure:Characterizing the global crude oil transport network with mass vessel trajectories[J]. Energy, 2019,168(1):966-974.
|
[15] |
Peng P, Yang Y, Lu F, et al. Modelling the competitiveness of the ports along the Maritime Silk Road with big data[J]. Transportation Research Part A, 2018,118(C):852-867.
|
[16] |
杨忍,牟乃夏,彭澎,等."海上丝绸之路"沿线重要港口竞争力评价[J].地球信息科学学报,2018,20(5):623-631.[Yang Ren, Mou Naixia, Peng Peng, et al. Evaluation on competitiveness of important ports along 21st-Century Maritime Silk Road[J]. Journal of Geo-information Science, 2018,20(5):623-631.]
|
[17] |
牟乃夏,廖梦迪,张恒才,等."海上丝绸之路"沿线重要港口区位优势度评估[J].地球信息科学学报,2018,20(5):613-622.[Mou Naixia, Liao Mengdi, Zhang Hengcai, et al. Evaluation on location advantages of the ports along the Maritime Silk Road[J]. Journal of Geo-information Science, 2018,20(5):613-622.]
|
[18] |
石伟,苏奋振,周成虎,等.南沙岛礁及周边港口可达性评价模型研究[J].地理学报,2014,69(10):1510-1520.[Shi Wei, Su Fenzhen, Zhou Chenghu, et al. Research on accessibility model of Nansha Islands and surrounding seaports[J]. Acta Geographica Sinica, 2014, 69(10):1510-1520.]
|
[19] |
Thill J C, Lim H. Intermodal containerized shipping in foreign trade and regional accessibility advantages[J]. Journal of Transport Geography, 2010,18(4):530-547.
|
[20] |
韩增林,尚颜颜,郭建科,等.东北地区港口内陆空间可达性综合测度[J].地球科学进展,2017,32(5):502-512.[Han Zenglin, Shang Yanyan, Guo Jianke, et al. Comprehensive assessment of inland spatial accessibility of the Northeast seaports[J]. Advances in Earth Science, 2017,32(5):502-512.]
|
[21] |
吕靖,王爽.基于不确定理论的原油海运网络连通可靠性研究[J].运筹与管理,2018,27(5):85-94.[Lv Jing, Wang Shuang. Connectivity reliability of maritime transportation network for crude oil based on uncertainty theory[J]. Operations Research and Management Science, 2018,27(5):85-94.]
|
[22] |
王爽,吕靖,赖成寿.基于Vine Copula的原油海运网络中节点连通可靠性研究[J].交通运输系统工程与信息,2018,18(4):32-37.[Wang Shuang, Lv Jing, Lai Chengshou. Connectivity reliability of nodes in the maritime transportation network of crude oil based on vine copulas[J]. Journal of Transportation Systems Engineering and Information Technology, 2018,18(4):32-37.]
|
[23] |
Wang S, Yang D, Lu J. A connectivity reliability-cost approach for path selection in the maritime transportation of China's crude oil imports[J]. Maritime Policy&Management, 2018,45(5):567-584.
|
[24] |
Ferrari C, Parola F, Gattorna E. Measuring the quality of port hinterland accessibility:The Ligurian case[J]. Transport Policy, 2011,18(2):382-391.
|
[25] |
Chen S L, Jeevan J, Cahoon S. Malaysian container seaport-hinterland connectivity:Status, challenges and strategies[J]. The Asian Journal of Shipping and Logistics, 2016,32(3):127-137.
|
[26] |
Guo L Q, Yang Z Z. Evaluation of foreign trade transport accessibility for Mainland China[J]. Maritime Policy&Management, 2018, 45(1):34-52.
|
[27] |
Wei H R, Sheng Z H. Logistics connectivity considering import and export for Chinese inland regions in the 21st-Century Maritime Silk Road by dry ports[J]. Maritime Policy&Management, 2018,45(1):53-70.
|
|
|
|