Journal of Transport Geography - ?· Intermodal transport Freight Containers ... bridge between China…

Download Journal of Transport Geography - ?· Intermodal transport Freight Containers ... bridge between China…

Post on 01-Nov-2018




0 download

Embed Size (px)


<ul><li><p>Journal of Transport Geography 19 (2011) 11631172</p><p>Contents lists available at ScienceDirect</p><p>Journal of Transport Geography</p><p>journal homepage: www.elsevier .com/ locate / j t rangeo</p><p>A strategic network choice model for global container flows: specification,estimation and application</p><p>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</p><p>a r t i c l e i n f o</p><p>Keywords:Intermodal transportFreightContainersGlobal networksPort choice</p><p>0966-6923/$ - see front matter 2011 Elsevier Ltd. Adoi:10.1016/j.jtrangeo.2011.05.005</p><p> Corresponding author. Tel.: +31 152782679; fax:E-mail addresses: (L. Tava</p><p> (M. Minderhoud), jean-francois.perrin@de(J.-F. Perrin), (T. Notteboom</p><p>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.</p><p>a b s t r a c t</p><p>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.</p><p> 2011 Elsevier Ltd. All rights reserved.</p><p>1. Introduction</p><p>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.</p><p>ll rights reserved.</p><p>+31 152696854.sszy),</p><p>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 complex</p> tno.nlmailto:Michiel.minderhoud@</li><li><p>0</p><p>50</p><p>100</p><p>150</p><p>200</p><p>250</p><p>300</p><p>350</p><p>400</p><p>450</p><p>500</p><p>550</p><p>600</p><p>0</p><p>2</p><p>4</p><p>6</p><p>8</p><p>10</p><p>12</p><p>14</p><p>16</p><p>18</p><p>20</p><p>22</p><p>24</p><p>1955</p><p>1957</p><p>1959</p><p>1961</p><p>1963</p><p>1965</p><p>1967</p><p>1969</p><p>1971</p><p>1973</p><p>1975</p><p>1977</p><p>1979</p><p>1981</p><p>1983</p><p>1985</p><p>1987</p><p>1989</p><p>1991</p><p>1993</p><p>1995</p><p>1997</p><p>1999</p><p>2001</p><p>2003</p><p>2005</p><p>2007</p><p>Seaborne Trade (billions of tons of goods loaded) - left axis</p><p>Exports of Goods (trillions of current USD) - left axis</p><p>World Port Throughput (in million TEU) - right axis </p><p>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.</p><p>1164 L. Tavasszy et al. / Journal of Transport Geography 19 (2011) 11631172</p><p>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.</p><p>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.</p><p>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.</p><p>2. Model specification and data</p><p>2.1. A brief literature review on port selection and cargo routingthrough ports</p><p>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</p><p>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).</p><p>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 valid at a globalscale and suffer from additional shortcomings, such as:</p><p> A lack of route assignment using actual container liner servicenetworks as offered by international seaborne carriers: modelsusing a link and node based network do not allow service linesto be distinguished and assume that link performance is inde-pendent of the membership of such a link of service lines. An absence of elements describing aggregate choice behavior</p><p>of shippers and preferences related to the generalized costsof freight and the value of time of goods. Here, again, modelssuffer from one or more shortcomings. Routing models aredeterministic (applying all-or-nothing techniques) withoutaccounting for heterogeneity in choices, do not include thevalue of time going beyond time as a factor cost (see Blauwensand Van de Voorde, 1988) or are not estimated to replicateobserved flows. A problematic model specification is one where port attractive-</p><p>ness depends directly on port throughput (and vice versa). Thisis the case in the Veldman model (Veldman and Buckman,2003), where port attractiveness is found to be a significant fac-tor in explaining port choice, and later regressed against trans-shipment volume, the reasoning in the model becomes circular.</p></li><li><p>L. Tavasszy et al. / Journal of Transport Geography 19 (2011) 11631172 1165</p><p> Assuming stochastic independence between alternative routes,implicitly, by using the basic multinomial logit approach to dis-crete choice modeling. Due to this assumption of independencebetween routes, choices will be heavily biased towards groupsof routes that overlap, unless the choice model is adapted foruse in a network situation. All specifications cited above, includ-ing the disaggregate logit based models, suffer from thisproblem.</p><p>The limitations of our model for the purpose of strategic fore-casting of worldwide container flows are twofold. Firstly, we as-sume that congestion does not significantly affect the routing offreight flows. Short-term congestion can be caused by cycles/sea-sonality in the traffic volumes or temporary situations such asstrikes or bad weather conditions. Structural congestion is causedby a chronic underinvestment in ports and terminals. High portcongestion levels enhance terminal developments in the affectedports. If such developments are impeded by environmental andland availability issues, congestion can lead to the emergence ofnew container terminal facilities in the vicinity of established butcongested load centers as described in challenge of the peripheryphase in port system development (see also (Hayuth, 1981; Slackand Wang, 2002; Notteboom, 2005 and Frmont and Sopp,2007). In some cases, new ports emerge far away from existing(congested) ports in combination with the development of newcorridors to serve the hinterland market (e.g. Prince Rupert in Can-ada as a new gateway port on the West Coast of North America faraway from existing gateways). However, given that many portscapacity extensions are above the mean growth scenarios, partlyas a result of the economic crisis of 2008/2009, we simplify ourmodel by assuming that congestion levels are too small to signifi-cantly affect medium term forecasts on the routing of goodsthrough port systems. For long-term scenarios (e.g. 2040) conges-tion is expected to influence the use of shipping routes and wewould recommend extension of the model. Such an extensionwould require a major modeling effort, as aggregated congestionfunctions for port complexes are not available and would need tobe developed anew. Challenges in this process include data acqui-sition and data aggregation; their detailed treatment is beyond thescope of our paper. The degree to which congestion affects flows inthe base year will implicitly be included in the model, as the esti-mated parameters include a representation of the shadow price ofcongestion, as experienced in the base year. We recommend thatfuture expected congestion levels are entered into the model exog-enously by increasing the transshipment times, according to cur-rent practice in other aggregate models.</p><p>Secondly, our model is limited to routing issues and does not in-clude impacts on trade itself. Again, for medium-term forecasts webelieve this is not problematic. For long-term forecasts, especiallyif we want to look at major shifts in overall transport costs (e.g.resulting in a doubling of trade costs), integration with a globaltrade model would be desirable.</p><p>In the remainder of this section we describe the choice model indetail, in particular the choice criteria used, the behavioralassumptions behind the model and its mathematical specification.</p><p>2.2. Choice criteria and choice function</p><p>The choice of shipping route for unitised goods is a complexprocess involving many attributes of different actors and services.Port selection factors typically relate to the geographical locationof origins and destinations of freight, the costs of transport (inlandand overseas), the forwarding organizations preferences (e.g. mer-chant or carrier haulage), the logistics characteristics of the goods(e.g. perishability, sensitivity and unit value), the available facilitiesand services (e.g. ports and inland infrastructure) and the decision</p><p>agents characteristics and strategies (forwarders, shippers or ship-ping lines).</p><p>Academic literature on port selection factors is abundant (seeearlier section and Magala and Sammons (2008) for a recent liter-ature review). Our intention is not so much to study these factors,but rather to apply the exis...</p></li></ul>


View more >