TAG Unit 3.1.4: Freight Modelling

June 2003

1 Freight Modelling
1.1 Introduction

2 References

3 Document Provenance

1 Freight Modelling

1.1 Introduction

1.1.1 The following factors distinguish freight transport from passenger transport. On the demand side:

• freight (other than livestock) is entirely passive, and the arrangements for loading and unloading are therefore critical; in many cases, these involve specialised infrastructure and/or equipment;
• most freight requires packing, often in several stages (e.g. packets in boxes on pallets in a container); the type of packing used is related both to its handling during transport and to the requirements of the shipper and recipient, including their arrangements for storage;
• many freight vehicles, especially railway wagons and bulk-carrying trucks or trailers, are specialised units for the carriage of a particular type of goods;
• the 'unit of decision' (which for passenger travel is ultimately the person- or group-journey, though influenced by other decisions such as car ownership and season ticket purchase) for freight can vary from the despatch of a single parcel to a contract running for several years and involving hundreds of thousands of tonnes of goods; and
• the characteristics of the journey itself are of very little importance to some consignments of freight (e.g. non-urgent shipments of bulk materials) but more critical than for passengers in other cases (e.g. the requirements of temperature-sensitive or very-high-value goods).

1.1.2 On the supply side:

• prices are much less well known than in passenger transport - the majority of transactions (except for small volume users of public services such as post and parcel delivery) are commercially confidential;
• it can be difficult to define the supply of freight transport services without going into a lot of detail about the characteristics of available terminals, especially on the railway network - and these are not fixed, since the cost of changing the characteristics may be modest compared with the overall transport costs involved; supply characteristics such as frequency and capacity are undefined until a potential shipper makes an enquiry; and
• since the movement of freight itself is nearly always one-way, the economics of freight haulage are considerably complicated by the scope for back-hauling, i.e. the possibility that the truck or wagon can carry a revenue-earning load on the return journey rather than running empty.

1.1.3 Some of these factors have analogies in passenger transport which can be taken into account in some forms of passenger transport modelling - for example, group size (and the resulting sharing of car costs) can be taken into account more readily in disaggregate choice modelling than in aggregate approaches. Others have no equivalent at all.

1.1.4 The main implications of these factors are that:

• the classification of freight is highly complex, and many of the obvious classifications (e.g. bulk, containerised, other) are reflections of transport decisions rather than independent dimensions; and
• the generalised cost of the individual trip or tour (which in passenger modelling is - rightly or wrongly - the main variable through which supply is described in choice modelling) will in many cases be less important than the arrangements for packaging and handling, which often though not always represent medium-term decisions comparable with, but much more complex than, the household car-ownership decision.

1.1.5 These in turn mean that the kind of choice model proposed elsewhere in this document for passenger modelling is less obviously applicable to freight mode choice. This does not mean that it cannot or should not be done; the conclusion of the National Transport Policy Model Feasibility Study (MVA et al, 1997) was that a choice model similar to the passenger choice model should be applied (that Study also listed a number of previous projects and the ways in which they had classified freight; some of these involved building such choice models). Disaggregate models would seem to offer considerable advantages, in that they can take account of a wide range of characteristics (such as the characteristics of the consignor and consignee, whether the shipment is regular, occasional or one-off, and the characteristics of the shipment itself) without having to process large numbers of very sparse matrices. However, it would seem highly desirable that more should be done to develop methods for modelling the medium- to long-term decisions about investment in (or leasing of) particular types of equipment, infrastructure and freight handling methods.

1.1.6 In terms of the origin-destination pattern of freight, the choice would seem to be between:

• simple factoring of observed base-year matrices;
• adjusting matrices by growth factors based on changes in planning data;
• a simple spatial interaction model; or
• a spatial input-output model.

1.1.7 Factoring methods would assume that the supply of transport had no impact on the volume or origin-destination pattern of freight within the modelled area. A simple spatial interaction model, with origins and destinations being factored up in proportion to appropriate planning data, would hypothesise some response to transport cost, with flows tending to increase where costs were reduced. A spatial input-output model would go further and would relate the patterns of trade to the interactions between different industries.

1.1.8 Spatial input-output models can be applied either:

• as the dominant component of interaction-location models (see Appendix B) in which case the location of industry is determined by the pattern of interactions; or
• as a less critical component of location-interaction models, in which case the location of industry is directly influenced by a wider set of factors.

1.1.9 Three points should however be noted about spatial input-output models:

• they may, in their most sophisticated forms, predict how sectors will substitute one input for another in response to changes in cost (whether transport cost or others), but they cannot in themselves predict technical innovation or the way that this will affect the linkages between sectors;
• the input-output modelling itself almost inevitably works in units of value (e.g. £X worth of goods and services sold from sector m in region i to consumers and businesses in region j); the conversion of trade by value into physical units of freight (and associated passenger movement) is a critical but relatively under-researched topic; and
• these models are dependent on input-output tables produced as part of the national accounts to specify the relationships between different sectors; they do not automatically predict growth in freight demand associated with increased intra-firm movements or with the use of third-party logistics contractors (who store and distribute goods, rather than just moving them), since these are not fully reflected in the set of transactions upon which the accounts are based.

1.1.10 For individual urban areas and small corridors, the factoring methods are probably the only ones directly applicable, since too large a proportion of freight movements will have one or both ends well outside the area that is likely to be modelled. (There will in such studies be a need to consider the impact of policies which affect the movement of freight within the urban area, such as lorry restrictions or time-specific bans; for many such policies, the transport effect follows automatically from the policy (e.g. deliveries must be made outside the hours when trucks are banned) and the main concern should be the impact on the businesses whose access is affected, and hence on the economic viability of the area.) The interaction and input-output models are likely to be applicable if the modelled area represents at least most of a region, and best applicable for studies which need to model more than one region.

2 References

MVA, David Simmonds Consultancy, ITS University of Leeds (1997). National Transport Model Feasibility Study - Project 1: Policy Model. Report to the Department of the Environment, Transport and the Regions.

3 Document Provenance

This Transport Analysis Guidance (TAG) Unit is based on Appendix C of Guidance on the Methodology for Multi-Modal Studies Volume 2 (DETR, 2000).

Technical queries and comments on this TAG Unit should be referred to:

Integrated Transport Economic Appraisal (ITEA) Division
Department for Transport
Zone 3/08 Great Minster House
76 Marsham Street
London
SW1P 4DR
itea@dft.gsi.gov.uk
Tel 020 7944 6176
Fax 020 7944 2198