Reports:

Study of European best practice in the delivery of integrated transport: report on stage 1 - benchmarking

1. Introduction

STUDY AIMS AND OBJECTIVES

1.1 The Commission for Integrated Transport (CfIT) is an independent organisation that advises the UK Government on integrated transport issues. CfIT's remit, as set out in the Integrated Transport White Paper, includes "continuing and refreshing the transport policy debate; and identifying and disseminating best practice from home and abroad".

1.2 This study on European Best Practice in the Delivery of Integrated Transport aims to:

• Stage 1 - develop measures to compare UK performance against other EU countries and identify a number of areas across a selection of countries where performance on a range of measures is significantly better than the UK;
• Stage 2 - conduct detailed case studies to establish more clearly how these areas perform and the reasons they are better than the equivalent UK; and
• Stage 3 - assess transferability of the best practice identified and how it can be implemented in the UK, including the barriers that need to be overcome.

PURPOSE OF THIS REPORT

1.3 This report on Stage 1 compares UK performance against other EU countries using a selection of indicators at the national and local levels to assess relative progress in achieving the desired outcomes of integrated transport policies. These desired outcomes include:

• reducing the need to travel, particularly by private car, through closer integration of transport and land use planning and encouraging alternative modes;
• improving transport safety, particularly for children, and pedestrians and cyclists;
• reducing congestion on the roads without eroding economic competitiveness;
• reducing the environmental impact of transport in terms of human health, the local environment and the global environment; and
• creating a more inclusive society with improved access for all to goods, services, and employment.

1.4 Sensible comparison of outcomes requires benchmarking against various inputs or determinants of travel behaviour such as demographic and socio-economic characteristics, the supply of transport, and levels of investment in provision which can help to explain some of the differing levels of success in policy delivery. Where no clear indicators of policy outcomes exist, it has been necessary to define proxy measures such as modal shares, utilisation of the highway and household expenditure on transport. These outputs represent necessary conditions for achieving desired outcomes.

BENCHMARKING

1.5 In undertaking the benchmarking we have sought to group UK and overseas examples in an attempt to compare 'like with like' to narrow the number of external variables when considering transferability in Stage 3 and allow other UK local authorities to extend the benchmarking exercise to include the performance of their own city or town. The data limitations (see below) have constrained the number of classifications possible, however, we have drawn a distinction between:

• national performance;
• world cities;
• large cities/metropolitan areas (with population in excess of 1.3 million);
• medium cities (population between 0.3 and 1.3 million); and
• small cities and towns (populations of less than 0.3 million).

1.6 Statistics have been adjusted and ratios or relative values have been used to allow comparisons between different countries, and areas within those countries, and to overcome variations associated with differences in inputs. For example, where appropriate we have:

• adjusted GDP-related indicators for purchasing power parity (EU=100) to eliminate the differences in prices between countries^[1];
• adjusted accident statistics according to the OECD 30-standard^[2];
• used ratios of outputs/outcomes relative to determinants (such as car ownership per capita, vehicles per kilometre of road, etc); and
• considered percentage changes over time rather than absolute values.

LIMITATIONS OF AVAILABLE EUROPEAN DATA

1.7 In undertaking the work to date it is evident that benchmarking integrated transport is still in its infancy. Whilst several data sources have been obtained (including two prime European data sets; UITP Millennium Cities project and Citizens' Network Benchmarking Initiative) collectively these do not provide a basis for a comprehensive benchmarking exercise.

1.8 The significant limitations are best summarised using the headings listed as "user requirements" in ECMT's Transport Benchmarking Methodologies, Applications and Data Needs^[3].

Completeness

• No one data set has information covering the full range of desired outcomes, outputs and inputs. Different information has been sought from different surveys for different sets of regions, cities and towns.
• The bulk of the data available relates to large cities, though the ECMT Urban Travel Study (currently underway) will look at some of the smaller-sized cities and towns. There is currently little information relating to peri-urban, inter-urban and rural areas - largely because such areas have not been involved in previous European best practice studies.

Accuracy

• Definitions of indicators are inconsistent both between surveys and between different countries, regions, cities and towns responding to the same survey. Whilst some guidance was offered by the main surveys in order to encourage consistency, none have placed emphasis on validating responses. Where there were obvious discrepancies between data sets we have used judgement to choose those which we perceive to be the most accurate. Particular definitional and accuracy issues relate to methods for measuring travel volume, journey times, and differences in geographic areas (CBD, city, urban periphery, hinterland, etc).
• Establishing and enforcing consistency in data collection, collation, analysis and interpretation is in itself a major exercise and one that remains largely unaddressed. Those responsible for the main European benchmarking surveys to date appear to start to be giving increasing attention to these problems and it is likely in our view that any 'second generation' benchmarking of integrated transport will be preceded by further significant work on defining data requirements. So far there appears to have been a reluctance to focus on the technical aspects of benchmarking, given that the associated complexities could detract from establishing, albeit imperfectly, broad comparisons of performance for informing integrated transport policy.

Continuity and Timeliness

• Rates of change in indicators requires comparison of time series data or at least data for two points in time. In many cases information is available for only one point (a snap shot) in time and where data is available for more than one point the precise date and hence rate of change is sometimes unclear.
• Different surveys provide data for different years as well as for different areas and hence it is not possible to control for exogeneous factors such as changes in global economic and political conditions.

Transparency

• Information on particular indicators may be affected by whether a respondent specifically wanted to keep that information concealed and, in fact, several participants in the ECMT study requested that some of their information be treated as confidential.

STRUCTURE OF THIS DOCUMENT

1.9 Following this introductory chapter, this report is divided into two parts; Part 1 contains national level comparisons, and Part 2 contains local level comparisons.

1.10 Within Part 1:

• Chapter 2 considers transport inputs by presenting comparisons of key determinants of integrated transport outputs and outcomes, such as demographic and socioeconomic indicators, supply of transport and investment levels.
• Chapters 3-6 cover outputs and outcomes covering the key policy themes of mobility and modal choice, road safety, congestion and environmental impact, and accessibility and social inclusion.

1.11 Within Part 2, cities have been classified as world cities, large cities/metropolitan areas, medium cities and small cities and towns (as shown in Table 1.1), as size will affect the overall demand for travel and this is likely to influence the provision and cost effectiveness of different forms of transport infrastructure and services.

Table 1.1 - Sample of Cities

World Cities	Large Cities/ Metropolitan Areas	Medium Cities	Small Cities & Towns
Athens	Copenhagen	Amsterdam, Neth's	Bath
Barcelona	Glasgow	Bristol	Brighton and Hove
Berlin	Manchester	Brussels, Belgium	Cambridge
London	Munich	Edinburgh	Graz, Austria
Madrid	Milan	Frankfurt, Germany	Jyväskylä, Finland
Paris (Ile de France)	Stockholm	Helsinki, Finland	Oulu, Finland
Rome	Vienna	Leeds	Portsmouth
		Marseille, France	Stoke on Trent
		Nantes, France	Terni, Italy
		Newcastle	Umea, Sweden
		Stuttgart, Germany	Weimar, Germany
			York

1.12 The locations of these cities and towns are shown in Figure 1.1 below.

Figure 1.1 - Locations of Cities & Towns

1.13 Each chapter covers a category of city and considers the key inputs and outputs/outcomes shown in Table 1.2 below.

Table 1.1 - Key Inputs, Outputs & Outcomes for Cities

Section	Indicator/Proxy Indicator
Key Local Determinants	Demographic and socio-economic characteristics Supply of roads and parking Supply of public transport Investment[1] Comparative costs of travel[1]
Mobility and Modal Choice	Transport intensity[1] Trip rates and journey lengths[1] Mode share
Road Safety	Fatality and injury risk [2]
Traffic Congestion and Environmental Outcomes	Highway utilisation[1] and speeds Bus speeds Emissions
Social Inclusion	Distance to Work[1] Subsidy to public transport[1] Concessionary Fares[1]

1: Data not available for Small Cities.
2: World and Large Cities only.

1.14 Data has been collected from a variety of sources, including Eurostat, UITP's Millennium Cities database, EU Citizens' Network, European Metropolitan Transport Authorities (EMTA), and via overseas facilitators who were sub-contracted to WS Atkins to assist in this study.

1.15 All indicators relate to the latest available year - usually 1998. In a small number of cases the latest available data for UK cities is the 1991 Census and this has been noted in tables and charts.

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1: Purchasing Power Parities show the ratio of prices in national currencies for the same good or service and allow international comparisons to be made. For example, if an identical train journey costs 15 francs in France and £2 in the UK, then the PPP is 15/2 or 7.5 francs to the £, so for every £ spend on train fares in the UK, 7.5 francs would be spent in France.
2: The internationally agreed definition of a road traffic fatality is any person who died within 30 days as a result of the accident. In practice, definitions vary from death at the scene or immediately afterwards (in Portugal), within 24 hours (Spain until 1993), within three days (Greece and Austria until 1991), within six days (France) and within seven days (Italy). Conversion factors exist to help overcome these differences and allow international comparisons.
3: Transport Benchmarking Methodologies, Applications and Data Needs, OECD/ECMT, August 2000.

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