Editorial

Innovation and integration in urban transport policy

1. Introduction

This is the second Special Issue on urban transport based on

the work of the Special Interest Group on Urban Transport

(SIG-10) of the World Conference on Transport Research

Society. The first, published in 2003, presented selected papers

from the inaugural conference (May et al., 2003). In it, we

noted the objectives of the SIG:

† to increase our understanding of the performance of

transport policy instruments;

† to determine the principles of policy integration;

† to develop good practice in the monitoring and appraisal of

policy instruments;

† to identify good practice in the design, implementation and

operation of policy instruments; and

† to develop interactive information tools to aid the under-

standing of urban transport policy for students, practitioners

and decision-makers.

We also highlighted a number of research challenges which

were illustrated by that set of papers. There was still, we

argued, too little evidence on the performance of innovative

policy instruments and, by inference, on the process of

innovation. Partly as a result, predictive models and forecasting

tools were inadequate in their ability to represent the impacts of

the full range of policy instruments. There was limited

understanding of the principles for successfully combining

such policy instruments into an integrated strategy. Appraisal

methods, performance indicators and targets were less well

able to reflect the contribution of many of the newer policy

instruments. Finally, there was too little evidence on good

practice in implementation.

This Special Issue includes selected papers taken primarily

from the conference sessions organised by SIG-10 at the 10th

World Conference on Transport Research held in Istanbul in

July 2004. Between them they address the majority of these

research themes, and thus offer an advance in our under-

standing of urban transport policy. They focus on three areas:

innovation, particularly in public transport; tools for

predicting the performance of policy instruments; and policy

integration.

0967-070X/$ - see front matter q 2006 Elsevier Ltd. All rights reserved.

doi:10.1016/j.tranpol.2005.12.001

2. Innovation

The development and understanding of innovative policy

instruments is a crucial aspect of our further understanding of

urban transport policy. Ongkittikul and Geerlings report on the

effects of regulatory change in Britain and The Netherlands on

innovation in their public transport industries. Their study

examined a period of fairly radical change in the public transport

industry in Britain through the introduction of deregulation and

compared that to amoremoderate periodof change in the industry

in The Netherlands which involved decentralisation of powers to

provincial authorities and the gradual introduction of competitive

tendering for concessions.The authors postulate thatmore radical

reform within the industry is a prompt for more innovative

development, not only to service operation, but also to the

development of innovation in infrastructure and vehicles.

However, such innovation will in the main be stimulated by

commercial rather than public policy objectives.

3. Performance

For many policy instruments, it is their impact on demand

for travel which principally determines their contribution to

overall policy objectives. Much of the evidence for such

demand impacts comes from empirical studies, and policy

makers are heavily reliant on the relatively rare situations in

which those implementing a policy have seen fit to evaluate its

performance. Paulley et al. report the results of a meta-study,

which has brought together such evidence for a range of public

transport policies. The full report, published in 2004, was

planned to update the seminal work of Webster and Bly (1980),

who had first brought together international evidence on the

impact of fares and service policies on demand.

The study found clear and reasonably consistent evidence

on elasticities with respect to fares, service levels and income.

More importantly, as a departure from the earlier study, it

showed that long run elasticities are typically higher than short

run ones, reflecting users’ ability to adjust their travel patterns

over time. In many cases these long run elasticities imply that

the impact of a given public transport policy intervention is

much greater than had been suggested by the earlier report.

Conversely, the study concluded that there was still too little

evidence on many of the softer attributes of public transport

provision, such as reliability, the waiting environment,

interchange facilities, personal security and awareness cam-

paigns. These are precisely the types of policy instrument on

Transport Policy 13 (2006) 281–282

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Editorial / Transport Policy 13 (2006) 281–282282

which innovation is focusing, but that innovation does not yet

appear to have brought with it the empirical evidence to

improve our understanding. Indeed, the private sector will

rarely see that it is in its commercial interest to publicise

evidence on the effectiveness of its innovative measures.

While elasticities can be used directly to estimate the likely

effect of a change to a given bus or rail service, it can be much

more difficult to predict the effects of changes in services which

are part of a wider transport network, given the ability of users

to change the modes, routes and timing of their journeys. In

these more complex environments, predictive models are often

used to assess the likely performance of a given strategy. While

such models have a history of over 40 years of development,

many city authorities remain suspicious of them, or lack

confidence in their use.

Shepherd et al. report the findings of a review of the use of

models for local transport planning in the UK. They find that

around a third of UK local authorities do not use predictive

models in preparing their Local Transport Plans, and that a

further third only use single mode models, even though the

focus of their Plans is on multi-modal solutions. Barriers to the

use of such models include their complexity, their cost, their

failure to reflect the performance of many policy instruments,

and the lack of specialist modelling skills. Shepherd et al.

advocate a hierarchical approach, with greater emphasis on

simpler strategic models to develop the overall strategy, and

more detailed models to support the design of individual

elements of the strategy.

4. Integration

Integrated transport strategies have long been promoted as a

more realistic and effective approach to solving urban transport

problems than individual measures. The difficulty from a

research perspective is understanding how different packages

of instruments interact, if they are simply additive in effect, or

if some degree of synergy or added benefits is achieved and

whether in certain combinations they are more successful at

overcoming barriers to change. The paper by May et al.

explores the synergy question through assessment of a number

of model based case studies. The results show little evidence of

synergy in the performance of the groups of instruments

against objectives, but some evidence of synergy in responses

within the transport system.

As May et al. demonstrate, the evidence on the

performance of integrated transport strategies is limited,

and wholly dependent on the results of studies using multi-

modal models. The final paper by Zhang et al. presents the

results of one of the most comprehensive of such studies, in

which a simple strategic model of the kind envisaged by

Shepherd et al. is used in conjunction with an optimisation

routine to determine the most suitable combinations of a set

of policy instruments. The results demonstrate the import-

ance of changes in public transport fares and service levels

and of charges for car use in improving the performance of

the transport system. All three of these can be varied in

scale by area and time of day, and the system performance

is critically dependent on setting these policy variables at

the correct level.

In particular, in the UK context studied, the results

indicated that fares should be reduced and service levels

increased, with charges on car use providing a means of

financing these changes. Zhang et al. stress the importance

of providing cities with direct control over all of these

policy variables, but note that the deregulated environment

in most UK cities does not permit this, and thus limits the

ability to achieve public policy objectives. This brings us

full circle to the thesis of Ongkittikul and Geerlings: the

private sector may be more capable of innovation than city

authorities, but it is less likely to be willing to innovate in

ways which are not compatible with its commercial

objectives.

References

May, A.D., Jopson, A., Mathews, B., 2003. Research challenges in urban

transport policy. Transport Policy 10 (3), 157–164.

Webster, F.V., Bly, P.H., (Eds.), 1980. The demand for public transport. Report

of an International Collaborative Study, Transport and Road Research

Laboratory, Crowthorne, Berkshire.

A.D. May

M.R. Tight*

Institute for Transport Studies, University of Leeds, 36-40

University Road, Leeds LS2 9JT, UK

E-mail address: mtight@its.leeds.ac.uk

Available online 3 February 2006

* Corresponding author. Tel.: C44 113 343 5350; fax: C44 113 233 5334.