freight transit traffic within transport modelling. the case of...

FREIGHT TRANSIT TRAFFIC WITHIN TRANSPORT MODELLING. THE CASE OF BELGIUM.

Tom Pauwels

University of Antwerp Department of Transport and Regional Economics

FIRST VERSION – PLEASE DO NOT QUOTE

1. INTRODUCTION. RESEARCH MOTIVATION This paper gives a summary of a PhD-research in progress. The main topics that have been studied will be highlighted and some provisional conclusions are shown. For full details we refer to Pauwels (2006). The research starts from the empirical observation that road freight transit traffic in Belgium is an important (political) issue. Freight transit traffic in a country is defined as freight flows being moved on the national infrastructure without loading or unloading of the goods on this infrastructure. Traffic flows can be divided into 4 categories: inland transport, import, export and transit. Inland transport is in this research characterized by the loading and unloading of the goods in Belgium. If the place of loading (unloading) is outside Belgium and the place of unloading (loading) is inside Belgium, this is defined as import (export). It is always possible to make a distinction between Belgian vehicles (registered in Belgium) and non-Belgian vehicles (not registered in Belgium). The same definitions apply to inland navigation and rail transport. It is clear that the total inland transport, the total import, the total export and the transit traffic carried out by Belgian trucks has an (in)direct importance for the Belgian economy. Transit traffic carried out by non-Belgian trucks shows no direct economic importance to Belgium. Moreover, those transit flows cause external costs. Foreign trucks are also responsible for hindering other road users (marginal congestion cost). Belgian road infrastructure is damaged (marginal infrastructure costs). Marginal environmental costs and accident costs will also occur. The main research question is: what does the research of modelling mode choice in freight transport (hinterland transportation: road, rail and inland navigation) offers in order to formulate statements and recommendations for freight transit traffic in Belgium. Freight transit traffic in Belgium has been estimated, based on the available information. Freight transit traffic in Belgium has been quantified in absolute

©Association for European Transport and contributors 2006

values and in relative values. Absolute values are characterized by tonnage and/or tonkilometres. Relative values are marked by the number of transit traffic relative to import, export, inland transport, transport by inland navigation, transport by rail,… Chapter 2 gives the main figures and findings about this quantification. The literature about freight mode choice (including freight models) is analyzed starting from the research question: can the conclusions and instruments of mode choice literature and freight models be used to analyze the transit traffic? An overview of this research and some conclusions are shown in chapter 3. Based on the findings of the literature analysis, a freight model has been selected and used that can give insight about the relations between mobility, economy, mode choice and transit traffic. Before deriving policy conclusions based on simulations of the model, a sensitivity analysis of the model is being carried out. In chapter 4, the methodology of this procedure is outlined and conclusions towards other freight models are included. In a final chapter 5 some main, provisional conclusions are gathered in order to derive (among others) policy conclusions about freight transit traffic within transport modelling. 2. QUANTIFICATION OF FREIGHT TRANSIT TRAFFIC IN BELGIUM Based on public available statistics, an overview has been made of the relative importance of freight transit traffic in Belgium (in other words: on the Belgian infrastructure). A division has been made between road transport (2.1.), inland navigation (2.2.) and rail transport (2.3.). In part 2.4, a comparison between the modes is made. Figures are reported about inland transport, import, export and transit. 2.1. Transit Belgium. Road Transport On the basis of the figures in table 2.1. one can see that the importance of road transit traffic in total road traffic (based on tonkilometres) varies between 4.75% (in 2000) and 12.23% (in 1990). The most recent figure shows a relative importance of 11.82% (in 2004). In tonnages (table 2.2.) the highest reported transit figure relates to the year 2004, namely 8.90%. In absolute volume a growth is reported of 932% between 1970 and 2004. On the basis of tonkilometre, we notice a growth of 675%. 1

In Pauwels (2006), other figures are also reported in detail, such as transit in tonne, tonkilometre, loaded and empty trips per reporting country. It is shown that


in 2004 Dutch trucks (trucks registered in the Netherlands) are the main transit category in Belgium (30.69% of the total reported transit volume). Table 2.1. Belgium. Overview road freight transport in tonkilometre (x 1000000; period 1970-2004) 1970 1980 1990 2000 2001 2002 2003 2004In absolute values

Inland 9194 10315 12616 23539 24681 24491 23038 23200Import 1419 2354 5031 11236 10906 10906 10998 11824Export 1419 2354 5031 13583 13190 13190 13025 13346Transit 837 1715 3160 2409 2611 2611 4086 6485 Total 12869 16738 25838 50767 51198 51198 51147 54855 In % Inland 71.44 61.63 48.83 46.37 47.03 47.84 45.04 42.29Import 11.03 14.06 19.47 22.13 21.18 21.30 21.50 21.56Export 11.03 14.06 19.47 26.76 26.51 25.76 25.47 24.33Transit 6.50 10.25 12.23 4.75 5.29 5.10 7.99 11.82 Total 100 100 100 100 100 100 100 100Source: own calculations based on FOD Economie – Algemene Directie Statistiek and Ministerie van Verkeer en Infrastructuur. Table 2.2. Belgium. Overview road freight transport in tonne (x 1000; period 1970-2004) 1970 1980 1990 2000 2001 2002 2003 2004In absolute values

Inland 298763 310711 276870 320494 297596 306290 299199 274580Import 16499 25989 52624 74905 74092 72710 73317 78828Export 16499 25989 52624 90556 92740 87936 86836 88977Transit 4187 8574 16505 16057 18521 17406 27237 43236 Total 335948 371263 398623 502012 482949 484342 486589 485621 In % Inland 88.93 83.69 69.46 63.84 61.62 63.24 61.49 56.54Import 4.91 7.00 13.20 14.92 15.34 15.01 15.07 16.23Export 4.91 7.00 13.20 18.04 19.20 18.16 17.85 18.32Transit 1.25 2.31 4.14 3.20 3.83 3.59 5.60 8.90 Total 100 100 100 100 100 100 100 100Source: own calculations based on FOD Economie – Algemene Directie Statistiek and Ministerie van Verkeer en Infrastructuur.


2.2. Transit Belgium. Inland Navigation In tables 2.3. and 2.4. it is shown that 6.58% of the total tonkilometres by inland navigation and 2.81% of the total tonnes by inland navigation is categorized as transit traffic executed by inland navigation. A slight fall of the figures over the years is shown. 2

Table 2.3. Belgium. Overview freight inland navigation in tonkilometre (x 1000000; period 1970-2004) 1970 1980 1990 2000 2001 2002 2003 2004In absolute values

Inland 2702 1570 1699 2391 2557 2779 2832 3057Import 2095 2193 2085 2955 3127 3284 3330 3317Export 1382 1550 1247 1471 1510 1555 1566 1528Transit 556 540 416 496 538 532 573 557 Total 6735 5853 5447 7313 7732 8150 8301 8459 In % Inland 40.12 26.82 31.19 32.70 33.07 34.10 34.12 36.14Import 31.11 37.47 38.28 40.41 40.44 40.29 40.12 39.21Export 20.52 26.48 22.89 20.11 19.53 19.08 18.87 18.06Transit 8.26 9.23 7.64 6.78 6.96 6.53 6.90 6.58 Total 100 100 100 100 100 100 100 100Source: own calculations based on FOD Economie – Algemene Directie Statistiek and Ministerie van Verkeer en Infrastructuur. Table 2.4. Belgium. Overview freight inland navigation in tonne (x 1000; period 1970-2004) 1970 1980 1990 2000 2001 2002 2003 2004In absolute values

Inland 31237 21471 21188 25472 27411 30472 31120 35748Import 35638 39451 46886 53635 59520 59440 60781 66794Export 20272 28944 28739 38124 37532 41196 41526 41078Transit 4418 3775 3163 3712 4097 4008 4330 4146 Total 91565 93641 99976 120943 128560 135116 137757 147766 In % Inland 34.11 22.93 21.19 21.06 21.32 22.55 22.59 24.19Import 38.92 42.13 46.90 44.35 46.30 43.99 44.12 45.20Export 22.14 30.91 28.75 31.52 29.19 30.49 30.14 27.80Transit 4.82 4.03 3.16 3.07 3.19 2.97 3.14 2.81 Total 100 100 100 100 100 100 100 100Source: own calculations based on FOD Economie – Algemene Directie Statistiek and Ministerie van Verkeer en Infrastructuur.


In Pauwels (2006), the transit figures are also reported in more detail: - per commodity group. As well based on tonnes as on tonkilometres the category “food products and animal feed” is the most important category; - transit in loaded and empty trips. In 2004 79.10% of transit trips is a loaded trip; - transit per owner of the vessel. Main category is transit performed by Dutch owners (38.05% of tonnes in transit by inland navigation is transported by a Dutch owner of the ship); - origin-destination information. Of all transit traffic by inland navigation, 31.11% is situated on the relation from The Netherlands to France. 2.3. Transit Belgium. Rail Transport On the basis of the figures in tables 2.5. and 2.6. one can conclude that 5.75% of the tonkilometres of rail freight transport and 4.65% of ton of rail freight transport is allocated to rail freight transit traffic in the year 2005. The figures of 2005 show a small increase in comparison with the figures of 2000-2004, but a decrease in comparison with 1990. 3

In Pauwels (2006), one can find more detailed figures of transit traffic by rail transport: - as well on basis of tonnes as on basis of tonkilometres, commodity group “products of metal industry” is the most important category in 2005; - origin-destination information. The relation from the Netherlands to France accounts for 23.14% of the freight transit traffic by rail transport. Table 2.5. Belgium. Overview rail freight transport in tonkilometre (x 1000000; period 1990-2005) 1990 2000 2001 2002 2003 2004 2005 In absolute values

Inland 2631 2031 1904 1922 1970 2113 2262 Import 1749 2032 1873 2065 2007 1945 2185 Export 3222 3179 3022 2949 3088 3317 3133 Transit 752 332 282 361 230 316 463 Total 8354 7574 7081 7297 7295 7691 8044 In % Inland 31.49 26.82 26.89 26.34 27.00 27.47 28.13 Import 20.94 26.83 26.45 28.30 27.51 25.29 27.17 Export 38.57 41.97 42.68 40.41 42.33 43.13 38.95 Transit 9.00 4.38 3.98 4.95 3.15 4.11 5.75 Total 100 100 100 100 100 100 100 Source: own calculations based on FOD Economie – Algemene Directie Statistiek, Ministerie van Verkeer en Infrastructuur and NMBS.


Table 2.6. Belgium. Overview rail freight transport in tonne (x 1000000; period 1990-2005) 1990 2000 2001 2002 2003 2004 2005 In absolute values

Inland 30227 23902 22788 22326 21432 23372 24180 Import 12164 14582 12851 13627 13284 12777 13716 Export 19964 20821 19736 19029 19632 20399 19680 Transit 4771 1974 1675 2216 1384 1906 2808 Total 67126 61279 57050 57198 55732 58454 60384 In % Inland 45.03 39.01 39.94 39.03 38.46 39.98 40.04 Import 18.12 23.80 22.53 23.82 23.84 21.86 22.71 Export 29.74 33.98 34.59 33.27 35.23 34.90 32.59 Transit 7.11 3.22 2.94 3.87 2.48 3.26 4.65 Total 100 100 100 100 100 100 100 Source: own calculations based on FOD Economie – Algemene Directie Statistiek and Ministerie van Verkeer en Infrastructuur and NMBS. 2.4. Transit Belgium. Comparison Road Transport, Inland Navigation and Rail Transport On the basis of the reported figures, one can calculate that the respective shares for road, inland navigation and rail transport are 88.14%, 7.57% and 4.29% of the transit traffic in 2004 (on the basis of tonkilometres). The relative shares on the basis of tonnes are 87.72%, 8.41% and 3.87% in 2004. 3. AGGREGATED MODELLING OF MODE CHOICE IN FREIGHT TRANSPORT In the PhD-research the relation has been analyzed between aggregated modelling of mode choice in freight transport and freight transit transport. First of all, a number of key concepts in (freight) modelling have been described: aggregated versus disaggregated modelling, revealed versus stated preferences, modal choice versus modal split, five step procedure, decision taker and hedonic features. The actual literature review is based on a number of (mainly academic) contributions, published between 1983 and 2006. Research before 1983 is summarized on the basis of existing review articles covering the period before 1983. The articles have been put in non-exclusive categories: - effect of a change of market circumstances on freight mode choice (e.g. liberalization process); - effect of the location decision of a firm on freight mode choice;


- effect of the knowledge of a decision taker on freight mode choice; - aggregating of disaggregated figures; - results based on surveys; - market definition (only those freight flows have to be considered which can make a shift from mode); - studies about modelling the quality of service; - review of some freight transport models; - relevance of elasticities; - intermodal transport; - other studies. Based on the literature review, the following research question is covered: what does the literature of freight mode choice modelling (hinterland transportation: road, rail and inland navigation) offers in order to formulate statements and recommendations for freight transit traffic in Belgium. Hereby, we formulate some provisional conclusions. Quite a lot of elasticities have been reported in the literature. However, it makes no sense to search for universal results. This means that the elasticities have to be interpreted and used with care. Cultural (country specific) factors play also a role. Elasticities also change over time. The published results can only be used as an indication for solving the research question. It is reported that in Belgium 43236 t (x 1000) is categorized as road transit traffic. Starting from the assumption that this is long distance transport, we can calculate the possible shift when the total cost of road transport is 5% higher (elasticities based on Beuthe et al. (2001)). The transported tonnage via the road will diminish with 0.64% or 277 t (x 1000). Given an average load factor of 14 t, this corresponds with 19765 trucks. Inland navigation will increase by 1.03% or 43 t (x 1000) and rail transport by 2.10% or 59 t (x 1000). This means that 175 t (x 1000) will disappear and 102 t (x 1000) will shift. Some nuances and considerations should be made on previous calculations. We show that the calculation of 19765 trucks should be seen as an upper limit. In the example above, one starts with the assumption of a raise of the total cost of road transport with 5%. This refers to the total route cost and including transshipment costs. If one chooses to raise the transport cost on the Belgian road infrastructure, the effect on the total cost will be considerably lower (given the fact of long distance transport). If political authorities want to reach more sustainable transit flows, a pricing policy on European level is necessary. A raise of the cost of transit flows cannot be a measure on its own. All road transport has to be treated in the same way (as well inland transport, import and export; as well Belgian vehicles as non-Belgian vehicles).


Previous analysis also starts from the assumption that all transit flows can be considered for the application of the elasticities. However, a part of the 43236 t (x 1000) cannot be considered to make a shift from road to inland navigation or rail transport (given the type of goods, given the lack of supply of inland navigation and rail). This is referred to as the market definition. Reported elasticities always start from the exisiting situation (e.g. existing market circumstances, existing locations of the firms). This means that elasticities should be used in their own, specific context. Second, elasticities are only valid within a limited range (within ranges of price changes). The expansion of the European Union induces more transit flows in Belgium with non-Belgian trucks. Changes of the market circumstances leads to a change in the characteristics of the transit flows. The literature review reveals that most research institutes base their research on decision takers located in the same country as the researchers. When analyzing the transit flows it would be more appropriate to study those decision takers in other countries. Literature review also shows that modelling the quality of service (when using a specific mode) has received more attention in the last years. In the past, the variable time was used as a proxy for quality. Nowadays, attempts have been made to quantify also reliability, flexibility, frequency,… However, it seems that there are no unambiguous conclusions (which factor is the most important?; relation to cost?). However, one can start from the assumption that the demand for quality as such is more important than the demand for a transport mode. This means that a government should focus on the quality features of rail transport and inland navigation. Action on European level will be necessary, in the view of transit transport. Some freight models take into account transit traffic. The model MOBILEC is one of the examples and has been applied to Belgium, the Netherlands and Luxembourg simultaneously. For road transport, a variable has been constructed to calculate the transit traffic in regions under study (Belgium: “arrondissementen”; Netherlands: “coropgebieden”). This will be discussed in more detail in the next section. 4. EMPIRICAL ANALYSIS A transport model has been selected that takes into account the PhD-research topics: freight mode choice and freight transit traffic in Belgium. A transport model is defined as a set of equations making it possible to simulate future evolutions of transport. A model has been chosen that takes into account the


relation between economy and transport. Therefore, the model MOBILEC has been investigated. MOBILEC (MOBILity/Economy) is a dynamic and interregional model which quantifies the relationships between the economy, mobility, transport infrastructure and regional features. It contains freight and passenger transport by mode. The main characteristic of the model is the interaction between the economy and transport: the economy influences transport and transport influences the economy. The mathematical specification of the model, including the values of the coefficients, is described in Van de Vooren (2004). An application of this model has been constructed for Benelux (Belgium, The Netherlands and Luxembourg): MOBILEC-Benelux. 4 The model contains 7388 origin-destination relations. For Belgium there are 43 subregions (arrondissementen) and for the Netherlands 40 subregions (coropgebieden). Freight transport from and to Germany and France is also taken into account, given the fact that the evolution of the econonomy in those 2 countries is exogenously determined. In the PhD-research, five steps have been treated: - a description of the necessary input values of MOBILEC-Benelux (some values can be collected; other values have to be estimated); - a description of the computer program in order to run MOBILEC-Benelux (macro in Microsoft Excel); - a sensitivity analysis of the model (see here under); - an overview of guidelines that can be used to work optimally with the model; - confronting the sensitivity analysis with previous simulations and applications of the model. In the sensitivity analysis, a working domain of the model has been outlined in which it can be used. Three steps have been distinguished to carry out a sensitivity analysis. First of all, a zero-scenario has been constructed. This means that some formulas and evolutions have been neutralized. The effects of a change of exogenous variables can then be calculated (in other words, how sensitive is the output of the model for a variation of the exogenous variables). The following changes are examined: -20%, -5%, -1%, +1%, +5% and +20%. In a second step, the re-activation of some formulas has been studied. Third of all, the importance of the basic data set has been outlined (in other words: how sensitive is the output of the model when the model would be re-estimated on the basis of an adjusted dataset). Once the sensitivity analysis has been performed, adequate policy conclusions can be drawn. The following origin-destination relations have been studied in detail: - relation 1: region Antwerp (arrondissement) – region Antwerp (arrondissement); - relation 2: region Antwerp (arrondissement) – region Luik (arrondissement); - relation 3: region Groot Rijnmond (coropgebied) – France.


The regions Antwerp and Groot Rijnmond have been selected because of the ports of Antwerp and Rotterdam. The relation Antwerp – Luik is interesting because of the trimodal characteristic: road, rail and inland navigation. The relation Groot Rijnmond – France has been analyzed as a proxy of the freight transit traffic in Belgium. For all details of the sensitivity analysis, we refer to Pauwels (2006). The analysis performed to conduct the sensitivity analysis should serve as an example for other freight models. Once a similar analysis has been applied to all existing models, it will be possible to make a selection of one or more models to carry out a specific simulation. It is important to deal in a correct way with the advantages and disadvantages of a model. 5. CONCLUSIONS: FREIGHT TRANSIT TRAFFIC WITHIN TRANSPORT MODELLING Two research areas have been combined in a PhD-research, of which this paper provides an overview of the activities and some first conclusions. First of all, an aggregated analysis of freight mode choice is shown. Secondly, the focus is also on the analysis of freight transit flows in Belgium. Transit flows are defined as freight flows being moved on the national infrastructure without loading or unloading of the goods on this infrastructure. In 2004, the reported relative importance of transit traffic in Belgium (relative to total transport and total transport is the sum of inland transport, import, export and transit) for road, inland navigation and rail is respectively 11.82%, 6.58% en 4.11% (based on tonkilometre). On the basis of tonnages those values are 8.90%, 2.81% and 3.26%. The modal split of the transit traffic is 88.14% for road, 7.57% for inland navigation and 4.29% for rail (based on tonkilometre). The values for the modal split are respectively 87.72%, 8.41% and 3.87% on the basis of tonnages. Trucks registered in the Netherlands are the main type of truck being used for freight transit traffic. The reviewed literature of freight mode choice has been put in several research areas, such as the effect of changes in market circumstances, the importance of the location of a company, the quality of service,… Several publications have warned for the possible misuse of elasticities. All elasticities in the literature should be considered as giving an indication of a trend. All elasticities should be seen from their own context. With respect to quality of service, it has been argued that the demand for quality in general is more important than the demand for a specific mode.


Transit traffic is in general categorized as long distance transport. The introduction of a two part tariff pricing system in Belgium for road transport, will have a small effect on the total cost of transport. The possible shift to rail or inland navigation will therefore be small. Action on European level will be necessary. A sensitivity analysis has been carried out to determine the ranges of the model (how should the model be used). It is important for a user of a freight model to know if such an analysis has been carried out, before using the results. The use of a black box has to be avoided: garbage in, garbage out. The sensitivity analysis in the PhD-research of the freight model Mobilec can be seen as an example and can be used as a benchmark method. Future research will focus on: - refining the existing data material about freight transit traffic; - setting up a procedure for carrying out a sensitivity analysis for other freight models; - estimation of the potential shift of tonnage that can be moved from road transport to inland navigation or rail transport in case of freight transit traffic; - calculation of external costs of freight transit traffic. 6. BIBLIOGRAPHY Beuthe, M., Jourquin, B., Geerts, J-F & Koul à Ndjang’ha (2001), Freight transportation demand elasticities: a geographic multimodal transportation network analysis, Transportation Research E, 37, 253-266. Blauwens, G., De Baere, P. & E. Van de Voorde (2006), Transport economics, 2nd edition, De Boeck, Antwerp. Pauwels, T. (2006), Geaggregeerde analyse van de vervoerswijzekeuze in het goederenvervoer, met bijzondere aandacht voor transitstromen in België, provisional version of a doctorate in order to obtain the degree of “Doctor in Applied Economics”, University of Antwerp, Antwerp. Van de Vooren, F.W.C.J. (2004), Modelling transport in interaction with the economy, Transportation Research Part E, 40 (5), 417-437. 7. ACKNOWLEDGEMENTS The author wishes to express his gratitude to Prof. Dr. G. Blauwens, Prof. Dr. H. Meersman, Prof. Dr. E. Van de Voorde and Dr. F. van de Vooren (University of Antwerp) for their suggestions.



Notes 1 In Pauwels (2006), some nuances of the figures of road transport have been reported. For example, the method of estimation of the transit figures has changed over the years. 2 In Pauwels (2006), some nuances of the figures of inland navigation have been reported. For example, from 1986 on the provisioning of sea vessels in the port of Zeebrugge is not included. 3 Only figures from 1990 on are reported. Figures before and after 1986 are not comparable because of different definitions of inland transport, import, export and transit. 4 MOBILEC-Benelux has been financed by Universiteit Antwerpen (Departement Transport en Ruimtelijke Economie), Rijkswaterstaat directie Zeeland, Rijkswaterstaat directie Noord-Brabant and Rijkswaterstaat directie Limburg.

freight transit traffic within transport modelling. the case of...

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