Norwegian port connectivity and its policy implications

被引:42
作者
Jia, Haiying [1 ]
Lampe, Ove Daae [2 ]
Solteszova, Veronika [2 ]
Strandenes, Siri P. [3 ]
机构
[1] Norwegian Sch Econ, NHH, Ctr Appl Res SNF, Helleveien 30, N-5045 Bergen, Norway
[2] Christian Michelsen Res AS, Bergen, Norway
[3] Norwegian Sch Econ, Dept Econ, Bergen, Norway
关键词
Port connectivity; AIS; big data; short sea shipping; port planning; CHOICE;
D O I
10.1080/03088839.2017.1366080
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The importance of a seaport depends on how well it is connected in a transportation network. A port's connectivity is therefore one of the key issues in determining its competitiveness and developments in regions and countries. We construct a port connectivity index for major Norwegian ports based on a unique dataset derived from the automated identification system (AIS) for multiple vessel types over a 7-year period. Port connectivity is evaluated empirically by the number of unique vessel visits, vessel sizes, and cargo sizes. The research has implications for port authorities and policy makers in the areas of port planning, infrastructure investment, short sea shipping promotion, and environmental policies. The contributions of this research are twofold. First, the methodology linking the AIS vessel-tracking system with port connectivity is a pioneering empirical application of maritime big data. Second, the port connectivity index is constructed for multiple vessel types and regional port groups, which is an improvement from the current literature where conceptual measures are constructed based on hypothetical and usually too simple optimization rules. The methodology can be easily expanded to other regions in the world.
引用
收藏
页码:956 / 966
页数:11
相关论文
共 36 条
  • [1] Acciaro M., 2013, POSITION PAPER OECD
  • [2] Are AIS-based trade volume estimates reliable? The case of crude oil exports
    Adland, Roar
    Jia, Haiying
    Strandenes, Siri P.
    [J]. MARITIME POLICY & MANAGEMENT, 2017, 44 (05) : 657 - 665
  • [3] Bird J., 1988, MARITIME POLICY MANA, V15, P35
  • [4] The potential for the clustering of the maritime transport sector in the Greater Dublin Region
    Brett, Valerie
    Roe, Michael
    [J]. MARITIME POLICY & MANAGEMENT, 2010, 37 (01) : 1 - 16
  • [5] Buhaug O., 2009, 2 IMO GHG STUDY
  • [6] Button K.J., 1993, TRANSPORT EC, V2nd
  • [7] Casaca A.C. P., 2007, Maritime Economics and Logistics, V9, P302, DOI [10.1057/palgrave.mel.9100184, DOI 10.1057/PALGRAVE.MEL.9100184]
  • [8] Charlier J.J., 1994, MARIT POLICY MANAG, V21, P237
  • [9] Identifying influential attributes in freight route/mode choice decisions: a content analysis
    Cullinane, K
    Toy, N
    [J]. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2000, 36 (01) : 41 - 53
  • [10] Mathematically calculating the transit time of cargo through a liner shipping network with various trans-shipment policies
    Du, Yuquan
    Meng, Qiang
    Wang, Shuaian
    [J]. MARITIME POLICY & MANAGEMENT, 2017, 44 (02) : 248 - 270