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Journal of Transport Geography 19 (2011) 11631172
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Journal of Transport Geography
journal homepage: www.elsevier .com/ locate / j t rangeo
A strategic network choice model for global container flows: specification,estimation and application
Lrnt Tavasszy a,, Michiel Minderhoud b,1, Jean-Franois Perrin c,2, Theo Notteboom d,3a Delft University of Technology, Faculty of Technology, Policy and Management, Jaffalaan 5, 2628 BX Delft, The Netherlandsb TNO Mobility and Logistics, P.O. Box 49, 2600 AA Delft, The Netherlandsc Ile de Frances Roads Direction, Traffic Management and Technologies Service, 79 C, Avenue du Marchal de Lattre de Tassigny, 94 002 Crteil, Franced ITMMA, University of Antwerp, Keizerstraat 64, 2000 Antwerp, Belgium
a r t i c l e i n f o
Keywords:Intermodal transportFreightContainersGlobal networksPort choice
0966-6923/$ - see front matter 2011 Elsevier Ltd. Adoi:10.1016/j.jtrangeo.2011.05.005
Corresponding author. Tel.: +31 152782679; fax:E-mail addresses: email@example.com (L. Tava
tno.nl (M. Minderhoud), jean-francois.perrin@de(J.-F. Perrin), firstname.lastname@example.org (T. Notteboom
1 Tel.: +31 152696815; fax: +31 152696854.2 Tel.: +33 141787300; fax: +33 142071651.3 Tel.: +32 3 265 51 49; fax: +32 3 265 51 50.
a b s t r a c t
Container flows have been booming for decades. Expectations for the 21st century are less certain due tochanges in climate and energy policy, increasing congestion and increased mobility of production factors.This paper presents a strategic model for the movement of containers on a global scale in order to analysepossible shifts in future container transport demand and the impacts of transport policies thereon. Themodel predicts yearly container flows over the worlds shipping routes and passing through 437 con-tainer ports around the world, based on trade information to and from all countries, taking into accountmore than 800 maritime container liner services. The model includes import, export and transhipmentflows of containers at ports, as well as hinterland flows. The model was calibrated against observed dataand is able to reproduce port throughput statistics rather accurately. The paper also introduces a scenarioanalysis to understand the impact of future, uncertain developments in container flows on port through-put. The scenarios include the effects of slow steaming, an increase in land based shipping costs and anincreased use of large scale infrastructures such as the Trans-Siberian rail line and the opening of Arcticshipping routes. These scenarios provide an indication of the uncertainty on the expected port through-puts, with a particular focus on the port of Rotterdam in the Netherlands.
2011 Elsevier Ltd. All rights reserved.
International trade has increased rapidly during recent decades(see Fig. 1). Between 1948 and 1992, world trade grew from 57.5billion USD to 3600 billion USD. Since the beginning of the1960s, the share of containerized cargo in the worlds total dry car-go movements has increased significantly. The major growth polesfor maritime transshipment shifted to Asia (Borrone, 2005) andcontributed to a recent surge in cargo throughput in all Europeanports (Ruijgrok and Tavasszy, 2008) which lasted till the start ofthe economic crisis in late 2008. Worldwide, the growth in con-tainerisation has been facilitated by the opening up of the terminaloperating industry through processes of port commercialization,corporatization and privatization (Notteboom and Winkelmans,2001) and by massive terminal capacity extensions all over theworld.
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+31 152696854.sszy), Michiel.email@example.com).
The current economic crisis has initiated mounting uncertaintyabout future growth, signaling increasing risks of over- and under-investment in container terminal capacity. Over the long term,transport costs are expected to increase due to rising oil prices, in-creased congestion in and around ports and economic centers andpublic policies aimed at internalizing the external costs related totransport. These cost changes are likely to have a negative impacton trade flows and might encourage a concentration of flows onhigh-density container routes. At the same time the economies ofthe Asian and African continents, together with the Central andEastern European countries are expected to attract an increasingshare of world trade. For port and hinterland infrastructure, uncer-tainties in future flows not only originate from unknowns in thetotal volume that is traded worldwide but also from spatial shiftsin transport chains and between ports within the same containerport system. These spatial shifts may occur as hinterlands change,but also depend on the availability, user price and quality of theport and hinterland infrastructures. For example, the rail landbridge between China and Europe, the enlargement of the PanamaCanal and the development of European freight corridors are ex-pected to have an influence on the spatial patterns of global freightflows. Finally, production systems and logistics services becomemore sophisticated, thereby contributing to increasingly complexhttp://dx.doi.org/10.1016/j.jtrangeo.2011.05.005mailto:firstname.lastname@example.org:Michiel.minderhoud@ tno.nlmailto:Michiel.minderhoud@ tno.nlmailto:email@example.com mailto:firstname.lastname@example.org://dx.doi.org/10.1016/j.jtrangeo.2011.05.005http://www.sciencedirect.com/science/journal/09666923http://www.elsevier.com/locate/jtrangeo
Seaborne Trade (billions of tons of goods loaded) - left axis
Exports of Goods (trillions of current USD) - left axis
World Port Throughput (in million TEU) - right axis
Fig. 1. Comparison of the evolution of container port throughput, seaborne trade and world exports. Source: own compilation based on Containerisation International andUnited Nations, Review of Maritime Transport.
1164 L. Tavasszy et al. / Journal of Transport Geography 19 (2011) 11631172
logistics networks that are spatially re-organized at a worldwidescale (Tavasszy et al., 2003; Notteboom and Rodrigue, 2008). Tobetter cope with these uncertainties, a model-based analysis isneeded to inform policy makers about future freight flows underdifferent scenarios.
The objective of this paper, therefore, is to develop a worldwidefreight model that analyzes freight transport chains over long dis-tances, chains that span large parts of the world where routingalternatives may lead over different continents. The challenge isto test whether this simplified model can be made consistent bothwith basic principles of shipper and carrier behavior, confirmed byin-depth research on the one hand, and with publically availabledata on worldwide freight trade and transport on the other. Withthese capabilities, a worldwide container model is a basis foranswering strategic policy questions, such as the impact of in-creased transport costs or the impact of new sea or land routesbecoming available.
In the next three sections of the paper we describe the mathe-matical formulation of the model and the data used to build themodel (Section 2), the estimation approach and results (Section3) and some applications on policy questions at the global level(Section 4). We conclude the paper in Section 5 with a brief sum-mary of the results and some recommendations for furtherresearch.
2. Model specification and data
2.1. A brief literature review on port selection and cargo routingthrough ports
Academic literature on port choice identifies a multitude of ser-vice-related and cost factors that influence the decisions made byshipping lines and shippers. These factors relate primarily to portinfrastructure, the accessibility over land and via the sea, the geo-graphical location vis--vis the immediate and extended hinter-land and the main shipping lanes (centrality and intermediacy),port efficiency, port connectivity, reliability, capacity, frequencyand costs of inland transport services, quality and costs of auxiliaryservices (such as pilotage, towage, customs, etc.), efficiency and
costs of port management and administration (e.g. port dues),the availability, quality and costs of logistic value-added activities(e.g. warehousing) and the availability, quality and costs of portcommunity systems, see e.g. Murphy et al. (1992), Murphy andDaley (1994), Malchow and Kanafani (2001), Tiwari et al. (2003),Nir et al. (2003), Song and Yeo (2004), Lirn et al. (2004) and Guyand Urli (2006).
Most quantitative research on port selection (see e.g. Tongzon,2009; De Langen, 2007; Malchow and Kanafani, 2004) uses disaggre-gate behavioral analysis, which limits the geographical scope ofapplication of models, due to the high costs of data acquisition in-volved. Aggregate models could in principle be applied at a global le-vel, if the specification of the model is such that data needs do notbecome prohibitive. Transportation literature presents a limitednumber of aggregate models for the routing of seaborne freight(Tang et al., 2008; Giannopoulos et al., 2007; Leachman, 2006; Aver-sa et al., 2005; Frmont, 2005; Veldman and Buckman, 2003). Noneof these, however, have been shown to be operable or vali