Modelling the competitiveness of the ports along the Maritime Silk Road with big data

doi:10.1016/j.tra.2018.10.041

	Modelling the competitiveness of the ports along the Maritime Silk Road with big data
	Peng, Peng 1,2; Yang, Yu 2,3; Lu, Feng 1,2,4,5; Cheng, Shifen 1,2; Mou, Naixia 6; Yang, Ren 6
刊名	TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
	2018-12-01
卷号	118 页码:852-867
关键词	Port competitiveness Maritime Silk Road Evaluation model Entropy-AHP method Vessel trajectory Maritime transport network
ISSN号	0965-8564
DOI	10.1016/j.tra.2018.10.041
通讯作者	Yang, Yu(yangyu@igsnrr.ac.cn) ; Lu, Feng(luf@lreis.ac.cn)
英文摘要	China's 21st Century Maritime Silk Road trade initiative includes investment in international port infrastructure. Comprehensive analysis of port competitiveness is of great significance for effectively guiding the flow of such resources. Conventional models mainly consider statistical indices for port operation, while neglecting the real operational status of these ports and their position in the changing global maritime transport network. To fill this gap in existing research, we designed a comprehensive evaluation CCPE model measuring port competitiveness by 18 factors related to conditions, capacity, potential, and efficiency using big data related to the geographical environment, cargo vessels trajectories, port infrastructure, and regional socioeconomics. This model was then used to evaluate the competitiveness of 99 ports in 51 countries along the Maritime Silk Road, with several important results. First, a port's status in the global maritime transport network was the most influential of all competitiveness indices. Second, competitive ports were mainly concentrated in the Mediterranean, the Suez Canal, and the Hormuz Strait, with Singapore, Marsaxlokk, and Algeciras ranking as the top three. The least competitive ports were mainly concentrated in East Africa, with Rangoon, Berbera, Lamu, Songkhla, Mtwara, and Sittwe ranking lowest. Third, port competitiveness was clearly polarized in that the most competitive ports stood far above all others due to significant gaps in their network status index.
资助项目	Key Project of the Chinese Academy of Sciences[ZDRW-ZS-2016-6-3] ; Natural Science Foundation of China[41871118] ; Strategic Priority Research Program of the CAS[XDA20040400] ; Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences[2016RC202]
WOS关键词	CONTAINER-PORT ; BALANCED THEORY ; CHOICE ; EFFICIENCY ; CONNECTIVITY ; PERSPECTIVE
WOS研究方向	Business & Economics ; Transportation
语种	英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD
WOS记录号	WOS:000452941000057
资助机构	Key Project of the Chinese Academy of Sciences ; Natural Science Foundation of China ; Strategic Priority Research Program of the CAS ; Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/51476]
专题	中国科学院地理科学与资源研究所
通讯作者	Yang, Yu; Lu, Feng
作者单位	1.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Fujian Collaborat Innovat Ctr Big Data Applicat G, Fuzhou 350003, Fujian, Peoples R China 5.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Jiangsu, Peoples R China 6.Shandong Univ Sci & Technol, Coll Geomat, Qingdao 266590, Peoples R China
推荐引用方式 GB/T 7714	Peng, Peng,Yang, Yu,Lu, Feng,et al. Modelling the competitiveness of the ports along the Maritime Silk Road with big data[J]. TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE,2018,118:852-867.
APA	Peng, Peng,Yang, Yu,Lu, Feng,Cheng, Shifen,Mou, Naixia,&Yang, Ren.(2018).Modelling the competitiveness of the ports along the Maritime Silk Road with big data.TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE,118,852-867.
MLA	Peng, Peng,et al."Modelling the competitiveness of the ports along the Maritime Silk Road with big data".TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE 118(2018):852-867.