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Spatial Network Analysis of Container Port Operations: The Case of Ship Turnaround Times

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Abstract

This research investigates the determinants of ship turnaround times at about 2,300 container ports between 1977 and 2016, based on nearly 3 million daily vessel movements. It adopts a multilevel approach combining territorial and network indicators to characterize ports, and proposes a new methodology calculating shipping delays. Main results reveal that port connectivity, Gross Domestic Product per capita, the number of vessel calls, and island location foster efficient port operations. Conversely, urban population, voyage delays at sea, maximum ship size, and upstream location increase turnaround time. While average turnaround time and inter-port sailing time have both regularly declined, operational and technological changes in the ports and maritime sector - especially after the 2007/8 global financial crisis - accelerated intra-port time and slowed down inter-port time. This relational and spatial approach also underlines the geographic differentiation of ship times nationally and regionally, as it is far from being randomly distributed on the globe. ... Yutani, H.

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Data Availability

The datasets generated during and/or analysed during the current study are not publicly available due to copyrights but are available from the corresponding author on reasonable request.

Notes

  1. The length of inter-port links is measured by the orthodromic (or “great-circle”, spherical) distance, namely the shortest distance between two connected ports at the surface of the Earth.

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Author information

Authors and Affiliations

  1. French National Centre for Scientific Research (CNRS), UMR 7235 EconomiX, Nanterre, France

    César Ducruet

  2. Kwansei Gakuin University, Nishinomiya, Japan

    Hidekazu Itoh

Authors
  1. César Ducruet
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  2. Hidekazu Itoh
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Correspondence to César Ducruet.

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Appendix 1 The results of influencing factors to ship turnaround time

Appendix 1 The results of influencing factors to ship turnaround time

Variables

a) ATT

b) ATT ratio

c) CVTT

pop ratio for yearly global average

0.024

***

0.023

***

-0.024

***

GDP per capita

-0.013

   

0.160

***

The share of trade value for GDP

0.106

***

0.126

***

0.021

***

Continental dummies

Africa

0.063

***

0.079

***

-0.020

***

East Asia

0.201

***

0.209

***

0.043

***

Latin America

0.039

***

0.044

***

0.008

 

North America

0.027

***

0.021

***

-0.009

*

Oceania

0.027

***

0.025

***

-0.040

***

West Asia

0.037

***

0.041

***

-0.033

***

Location dummies

island

-0.036

***

-0.038

***

0.056

***

upstream

0.064

***

0.073

***

-0.008

*

downstream

0.058

***

0.058

***

0.007

 

Total traffic (calls)

-0.086

***

-0.090

***

0.098

***

Vessel capacity (MAXDWT)

0.107

***

0.144

***

  

Degree centrality (K)

-0.209

***

-0.256

***

0.203

***

Betweenness centrality (BC)

0.084

***

0.101

***

-0.118

***

Inverse Clustering coefficient (invCC)

0.093

***

0.080

***

  

Link clustering coefficient (linkCC)

    

0.283

***

Average of shipping delay time

0.056

***

0.085

***

-0.014

***

Dispersion of shipping delay time

-0.077

***

-0.067

***

0.262

***

Adj. R2

0.105

0.140

0.678

  1. Parameters are standardized. “Europe” is baseline for continental dummy. “Coastal” is baseline for location dummy
  2. *10% significant
  3. **5% significant
  4. ***1% significant

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Ducruet, C., Itoh, H. Spatial Network Analysis of Container Port Operations: The Case of Ship Turnaround Times. Netw Spat Econ 22, 883–902 (2022). https://doi.org/10.1007/s11067-022-09570-z

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