Transferability of sustainable urban mobility measures

Research in Transportation Economics 22 (2008) 146–156

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Research in Transportation Economics journal homepage: www.elsevier.com/locate/retrec

Transferability of sustainable urban mobility measures Rosario Maca´rio a, *, Carlos Filipe Marques b a b

CESUR – Instituto Superior Te´cnico, Technical University of Lisbon, Av Rovisco Pais, 1049-001 Lisbon, Portugal ˜o e Sistemas, S.A., Av da Republica, n. 35, 6th Floor – 1050-182 Lisbon, Portugal TIS.PT – Transportes Inovaça

a b s t r a c t Keywords: Transferability Urban mobility Best practices

This paper describes an approach developed to identify common elements of city performance that have transferability potential across a number of cities. The findings provide a wealth of information sourced from 200 measures in 19 European cities. A transferability framework is proposed, that uses ideas from traditional top-down approaches using city clustering to infer the transferability of measures, as well as elements of a bottom-up approach, based on the concept of ‘‘measure enabling context’’. Systems’ thinking diagramming was used to depict relationships between measures, drivers and barriers, portraying the feedbacks at work and the cause–effect relationships, to establish appealing preconditions for transferability. Ó 2008 Elsevier Ltd. All rights reserved.

1. Introduction This paper provides a synthesis of previous studies, mainly unpublished, to develop guidelines to assess conditions of transferability of measures between cities,1 and to discuss how the selected guidelines were used in the CIVITAS I, (METEOR, 2004) cities project. The EC CIVITAS Initiative, which stands for CIty-VITAlity-Sustainability, is designe to assist European cities to achieve a more sustainable, clean and energy efficient urban transport system, by implementing and evaluating an integrated set of technology and policy based measures. CIVITAS I started in early 2002 (within the 5th Framework Research Programme); CIVITAS II, (METEOR, 2006) currently underway, started in early 2005 (within the 6th Framework Research Programme). Measures undertaken in the 36 European cities involved in both programs are estimated in more than V300 m, partially funded by the EU with V100 m. The fundamental assumption of the research is that transferability of a measure from a particular city (origin city) to another particular city (target city) is only predictable with a detailed understanding of its enabling context, since any macro guiding indicators such as size city, population density, urban sprawl, or even combinations of these will inevitably fail to reflect the complexity involved. In practical terms, this means that any new city wishing to adopt measures of the same kind as those adopted e.g. in CIVITAS, should be able to assess first whether specific measures adopted elsewhere are actually effective in their particular setting, looking comprehensively at the ‘‘preconditions for implementation’’. * Corresponding author. E-mail addresses: [email protected] (R. Maca´rio), [email protected] (C.F. Marques). 1 This work was done by the authors in the METEOR project (5th RTD) for the European Commission. 0739-8859/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.retrec.2008.05.026

A transferability algorithm was developed using a stepwise process piloted and sanctioned by the participating cities. Eleven broad clusters of measure were used to define the evaluation process:           

Transport information and management, Multimodal interchanges, Mobility management, Cycling, Car sharing and car pooling, Zones with controlled access, Clean vehicles and fuels, Public transport, Goods distribution and logistic services, Parking management, and Road urban pricing

This paper maps the contexts associated with each measure, highlighting the role of the standardized barriers and drivers identified in the scope of the process evaluation and the high level objectives (HLOs) served by each cluster. The importance of understanding the context of such dependencies is at the heart of the issue of ‘‘transferability’’, noting that the replication of measures and clusters of measures in a target city can only succeed if the favouring context is correctly understood. 2. State-of-the-art in research on transferability A review of past research (namely European Commission research projects like LEDA, TRANSPLUS, CUPID, MARETOPE) identified the following key guiding principles: A – Transferability will depend to some extent on compatibility of institutional context. This implies attention to the individual policy

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instruments concerned, accounting on how a policy instrument may fit with the context of the receptor city, while the identification of comparable cities may assist assessment of potential transferability. There may still be a need to transplant a policy with part of its institutional context, i.e. transfer not only a policy instrument, but some of the relationships between institutions and territories may have to be replicated in the new location. B – Different kinds of transferability may be recognised in terms of transfer of policy instruments between territories. Different components of transferability have been identified: 1. Scale of application of a policy (e.g. local measure or nationwide measure). 2. Degree of transfer (e.g. within a city, between cities, between countries, etc.). 3. Horizontal translation of a policy, where a policy is transferred from one institution/territory to another, without changing the scale of application. 4. ‘Vertical’ transfer, or ‘scaling up’ or ‘scaling down’ a policy (e.g. from local application to a nation-wide policy, or vice versa). C – Different phases or stages in the transfer process have been identified. These are: 1. Demonstration phase – best practice identified in originator city. 2. Test phase – includes policy case (factors of success) and risk analysis (barrier analysis). 3. Implementation – application to the receptor city; transfer concluded. D – Different kinds of process that assist transferability have been identified. Experience can be gathered through a range of mechanisms for seeking information. In addition to published data sources, networks, co-operative projects, skills exchanges, and various NGOs all provide access to new ideas. E – Transferability may be indirect through osmosis. In nearly all case studies analyzed where a policy had been transferred to a city (e.g. TRANSPLUS), there were a large number of influences through various informal channels and sources of direct or indirect contact, e.g. site visits may have been made, and information gathered by telephone, Internet or specific dissemination programs. Rather than the norm being a direct superimposition from one city to another, there often is a general osmosis effect where cities learn from each other and ideas filter through either from cities in the same country or from a city in another country. As take-up of a measure becomes established, it becomes more widely accepted, and eventually evolves into a part of the norm. This process of osmosis can be seen in the context of the introduction of development control systems, parking policies, pedestrianisation schemes and other practices which are now common-place. F – Acceptability is crucial. Transferability of measures which are perceived to support personal mobility, is more likely to be adopted without opposition compared with transferability of measures which are perceived to be restrictive. In general, evidences suggest that transferability of measures cannot actually be predicted from an objective analysis of certain key characteristics of origin and target cities. All evidence seems to stress the view that key transport practitioners at the city level are in the best position to screen measures, on the basis of their local knowledge of the local setting. Such practitioners need, however, to be provided with information about possible measures and be supported by a structured form of decision model algorithm. Indeed, a direct consequence of the review of literature undertaken is that, more than trying to find a universal solution for transferability based on a quantitative analysis, it is much more relevant to

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develop a methodological process for transferability. Moreover, the harmonisation of such process would have the advantage of endowing decision makers and practitioners with a common and structured approach, facilitating wide-scale engagement in innovative initiatives regarding sustainable mobility at the urban level. 3. Setting up a methodological framework for transferability The successful implementation of a transportation measure or of a package of measures at a given city should provide grounds for potential transfer to other cities, if the right conditions are met. The idea has been to identify the conditions under which a specific measure or package of measures can be applied with a comparable degree of success elsewhere. To undertake a transferability process between the CIVITAS cities and other cities, required the design and adoption of a general framework. However, this also implies the identification of the limits to the application and the definition of the conditions for successful transferability. The starting hypothesis is that if a measure or package of measures has been successfully implemented within a given geographical, demographic, socio-economic, cultural, technologic, institutional and organisational setting, then comparable results in terms of the degree of attainment of the measure or package of measures objectives can be achieved in areas characterized by a similar setting. For the above hypothesis to be operational, it becomes necessary to account for the preconditions for transferability. For instance, the definition of a successful implementation of a measure or a package of measures is of great importance, in order to qualify it as a candidate initiative to be transferred elsewhere. The definition of success will naturally depend on the objectives set. The following are examples of objectives set for a given measure, with the indication of a target, hence, of a success criteria that must be measurable:  5% Reduction in the number of high polluting vehicles on the network will be achieved by setting up of city centre clean zone.  Adoption of flexible parking policies and environmentally linked parking charges has a target of reducing the fuel consumption of the fleet using the parking facilities by 5% over and above normal improvements. It is desirable that the success dimension of each measure be translated into a predefined quantitative scale, for developing statistically meaningful relationships with city indicators. Benchmarks may offer a further source of information for quantifying the objectives associated with measures and enable the effectiveness and efficiency of the actions in question to be compared. Such data should be used with caution, however, and are no substitute for the types of indicators generated by a monitoring system. It has been recognised in previous studies (LEDA, 2000) that no significant predictions can be made as to whether measures may be transferred, if this is done simply by comparing the cities where the measures have already been implemented (the origin cities) with the cities which would like to implement the measures (the target cities). Transferability depends – to a large extent – on the characteristics of measures themselves in relation to the target city. This means that often there is no alternative to running a full process of checking transferability. Following the experience in undertaking a simulated transferability exercise in the LEDA project, a recommended approach for city authorities to follow when considering the transferability of measures was suggested:

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 The city authority determines which issue(s) or problem(s) need to be addressed.  A database of measures, such as the database developed in LEDA (1999), ELTIS or from CIVITAS, may be used to identify those measures which address the issue(s) or problem(s) identified.  The appropriate measure(s) is/are then selected looking at which key actors from within the city authority and from relevant outside agencies are involved in the selection process. These key actors should include both staff and elected members of the relevant departments of the city authority. This might include the planning, engineering, finance, legal and traffic departments; the key actors also include the following outside agencies: the police, public transport operators, chamber of commerce, regional authority, environmental groups, cycling groups, motoring organisations, road haulage associations, suppliers of public utilities (electricity, gas, telecommunications, water), trades unions and employer organisations.

between territorial transfers between jurisdictions at the same level (horizontal translation of a policy), vertical transfer between institutions at different levels (‘scaling up’ or ‘scaling down’ a policy), and transplanting of institutions and instruments. 3.1.2. How to do it? Examples indicate that a number of phases/stages must be followed in the transfer process: 1. A ‘‘demonstration phase’’ where best practice is identified in the originator city; 2. A ‘‘transferability phase’’ where the compatibility of the best practice in the receptor city is appraised; 3. An ‘‘assessment phase’’ where specific barriers amenable to change and factors of success are identified in the receptor city; and 4. Finally, an ‘‘implementation phase’’ where the good practice is implemented in the receptor city. 3.2. The transferability framework in 10 steps

Five core aspects of each measure, with the equivalent or matching characteristics of their own city and the likely actors involved in introducing the measure are appropriate for analysis:     

city objectives, legal framework, political framework, public acceptability, and enforcement issues.

All information available on successful actual or simulated transfer to other cities should be searched, taking into account the context of the relevant similarities or differences between their city and the other city or cities. In particular, the issues of political and public acceptability must be investigated in some depth, as these are the key to the successful implementation of measures. Once a choice of measure is established there is a need to pay particular emphasis to consultation. The most significant barriers to transfer a measure relate to political frameworks and public acceptance, underlining the vital importance of obtaining political and public support. Consultation processes are often built into the legal and regulatory framework governing the introduction of measures in many countries. However, consultation processes also have a cultural dimension and therefore it is not possible to present a standard process for all to follow. 3.1. Transferability principles The transfer of experience in CIVITAS should involve all the policy makers and practitioners in the cities considered that have the power to take decisions affecting a given policy context in a multi-governance decision making exercise. The multi-governance perspective is required, in particular, when addressing measures which have a wide ‘footprint’ or area of impact, as well as strong local impacts. The following elements emerged from TRANSPLUS research on transferability and may be of use to support the multi-governance decision making on a large scale and for a wide range of policy issues. 3.1.1. What does it imply? Transferability does not imply simply the attention to individual technical or operational features of instruments, but how a policy instrument may fit with the context of the receptor city. There may be the need to transfer not only the policy instrument but also some of the relations between institutions and territories. TRANSPLUS research identified different kinds of transferability that distinguish

The transferability process departs from the assumption that practices under analysis are those best suiting the target city conditions. Therefore, a diagnosis of the situation in the target city is required, followed by a pre-selection of the possible measures addressing the problems identified. Should this be clear, it will then be possible to initiate a transferability process to obtain a deeper understanding of the steps involved, and the hypothesis and feasibility of the process to become operational. The next 10 suggested steps, envisage providing a logical framework for the transferability process: STEP 1 Diagnostic of the problems. STEP 2 Characterisation of the city. STEP 3 Analysis of the city context and implications of problems identified. STEP 4 Look around for similar contexts. STEP 5 Selecting examples of source urban contexts. STEP 6 Identify measures with potential for transferring. STEP 7 Packaging and dimensioning the measures for transferring. STEP 8 Ex-ante assessment of measures to transfer. STEP 9 Identify need for adjustment. STEP 10 Implement measures and steer results.

3.2.1. STEP 1 – diagnostic of the problems A target city is the city where the replication of actions undertaken elsewhere is intended to take place. However, we may consider that, originally, target cities do not have such self-consciousness. Therefore, several steps are required before this concept starts taking shape. A first step is to develop a structured analysis of the own situation and assess the need to take actions, which is normally identified through the deviation from objectives. At that stage, we will then be ready to engage in a source/target city analysis in view of transferring and adapting practices adopted elsewhere. To do this requires a number of preconditions framing the approach, such as having a clearly defined number of guiding objectives, without which the ability to undertake an effective improvement process will be lost. Hence, should a city have a clear definition of its strategic orientations, it will be possible to frame and identify specific key areas contributing to or against attaining those objectives. 3.2.2. STEP 2 – characterisation of the city A detailed identification of the characteristics of the city environment and urban structure is required in the transferability

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process, at for example, the geographic, structural, demographic, architectural, cultural levels. This should allow a first screening of the setting in which the city operates, helping to frame the range of problems within specific urban contexts. It will be important later to check whether candidate measures that were successful elsewhere in mitigating similar problems did share similar contexts. As no single measure can be said to be uniquely related to a specific type of city context, reasonable latitude for discussion should be permitted. Given the overall objective to transfer conclusions from the demonstration cities to other European cities, the variables chosen to make this characterisation are expected to fit within a set of common parameters. One must focus on this point in order to identify and discuss those variables. Two major variables can be identified as a first step: Physical variables and Institutional variables. Background literature review allows identification of some further preliminary conditions to pre-ensure comparability and subsequent transferability, namely the identification of demographic, geographic and transport system-related factors. This means the definition of the physical and socio-economic context of an urban area such as population density, area of city, number of households, number of cars, length of major road network, average income, and influence over surrounding areas. 3.2.3. STEP 3 – analysis of the city context and implications of problems identified Based on the previous steps, it will be necessary to set up a city profile based on a set of variables describing the main characteristics of specific context and the results of the diagnostic steps. This will be a key step in the clustering approach, with other ‘‘source contexts’’ sharing similar conditions. This will be a preliminary step before looking for compatible situations within the selected cluster, allowing case-by-case city comparisons. At this stage, the city context is clear, based on the characterisation in Section 3.2.2. The obstacles or problems that play a role in challenging achieving the strategic goals set were identified in Section 3.2.1. By themselves, these two initial steps set the foundations of the transferability process. It will be necessary to clarify what are the actual circumstances that must be given more focus. Major areas of intervention that may help sorting out problems and promote convergence towards HLOs adopted start taking shape here. Examples of such areas in the urban context are:  Significant reduction in transport-related emissions;  Significant reduction in congestion; and  Uptake of clean transport vehicles. A quantification of the real impact of the obstacles/problems identified in the 1st STEP may be useful, as not all problems have similar influence across the range of HLOs. Ranking of major obstacles as identified in STEP 1 will further help creating a list of priorities, in view of the best possible efficiency of the resources applied in any future mitigating measures. The net result of STEP 3 will then be: 1. A detailed characterisation of the high level objectives considered; 2. Selection and ranking of the related problems identified; and 3. Preliminary political decision on which HLOs and PROBLEMS should remain the focus of the discussion.

3.2.4. STEP 4 – look around for similar contexts The concept of similarity is fundamental comparison of situations, taking ‘‘inter-object similarity’’ as a measure of correspondence or resemblance between contexts. To some extent, the so-called Similar

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Cases (either in their current condition or sometime back in the past) will have to share the general setting characterising in the Target City. Seeking out similar cases will therefore imply identifying groups with similar characteristics, calling for an existing stock of situations against the situation set in STEP 3. It is important here to assess similarity of the context itself, rather than limiting the scope to e.g. geographical or sizing conditions. It is important to note that we are discussing ‘‘Conditions of Comparability’’, rather than ‘‘clustering the cities’’. These steps requires specific data collection to clarify whether application conditions are met, including the collection of specific elements such as indicators expressing the physical (geographical) structure, elements in relation to transport usage, demographic elements, social and economic background, technological advancement, institutional background of a city. The EC research project SESAME 194 (1999) has adopted a database used to survey a sample of 40 European cities. The data gathered relates to the following domains: ‘‘land-use’’, ‘‘socio-economy’’, ‘‘transport supply’’, ‘‘travel demand’’, ‘‘impact indicators’’, ‘‘local policy’’ and ‘‘cultural indicators’’. 3.2.5. STEP 5 – selecting examples of source urban contexts Having selected similar contexts as a starting point for transferability, we are entering the stage where it becomes possible to focus on the practices adopted in those contexts, based on the likelihood that the rationale adopted in sorting out problems is to some extent adaptable. A definition on what is considered as a successful implementation of a measure or a package of measures is required, in order to qualify it as a candidate initiative to be transferred elsewhere. The definition of success will naturally depends on the objectives set. But even when objective elements for decision indicate that feasibility is positive, there is still place to further examine whether the operational environment is favourable to the implementation of a given measure. This requires a number of qualitative analyses, which should include the transportation system, to check the viability of the proposed measure in the given setting. Some of the most important indicators, needed to obtain basic insight in the functioning of urban systems are the ‘‘core indicators’’. Core indicators are indicators, which can be used to make comparisons between similar programmes or measures. In some cases, they may be aggregated to a higher level. However, the diversity of practices and definitions suggest that different indicators can be categorised as ‘‘core’’ by different user groups depending upon the objectives being pursued. 3.2.6. STEP 6 – identify measures with potential for transfer Even if a measure is proven to be applicable in a given setting (environment), it is not guaranteed that transferability will be successful, unless further operational viability analysis returns positive. Is the operational viability a sufficient condition for transferability or it is required further evaluation of the measure in terms of its costeffectiveness in the new setting (environment) where it is supposed to be transferred? Finally, is it sufficient to identify a measure as cost-effective for the new setting (environment) where it is supposed to be transferred, or the community acceptance of the measure should also be considered, before the measure is actually transferred? The answers to the questions provide the framework for characterising a candidate measure or package of measures as transferable between similar settings (environments). Explore existing conditions regarding the following vectors:  Physical,  Organisational, and  Functional.

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The pre-selection of candidate measures to be implemented elsewhere could then follow a procedure, as follows:

 What is expected to happen at that time if they are implemented.

1. Set the group of relevant source urban contexts identified in previous steps. 2. Select from all measures adopted in the source urban contexts, those which have reached success thresholds, according to the homogeneous criteria that should have been adopted. 3. Subject the resulting list to peer review. 4. Build a list of candidate measures, including specific remarks on crucial conditions of applicability identified in the peer review, as well as other pertinent comments.

In terms of the conditions of implementation of the measures, ex-ante evaluation relies on micro-indicators. For example, in the case of a fiscal measure on motor fuel, the micro-indicators might show the percentage of tax in the gasoline price at the end of the implementation with and without the measure, the change in this percentage over the time resulting from the measure, and the change in this percentage.

3.2.7. STEP 7 – packaging and dimensioning the measures for transferring Stemming from the research in TRANSPLUS, strategic issues related to the design of the package of measures will have implications on its effectiveness. Therefore, the analysis of transferability should consider not only individual measures considered as eligible, but also the relationships between measures that may enhance their impact. The effect of combining measures enhancing the individual success of each measure represents one of the major challenges when defining optimum packaging. The suggested procedure is to assess the most promising relationships in order to set up the packages of measures. This should account not only for operational aspects but also for policy and acceptability related issues. For instance, how important would it be for the success of the measure ‘‘Set up of city centre clean zone’’ to have measures such as ‘‘Time based entrance/road pricing policies’’ or ‘‘Adoption of flexible parking policies and environmentally linked parking charges’’? However, the success of transferring a given measure or package of measures, will also depend on the dimension of the implementation. Which scale will best fit the target city in relation to the origin city will depend on the nature of the measure itself. Therefore, it will be important to recognise that there are groups of measures that may be more affected by scaling than others, before even entering such analysis, which may otherwise be worthless or at least non-critical. 3.2.8. STEP 8 – ex-ante assessment of measures to transfer Target cities need to have identified the goals that the selected measures are expected to meet. These should be set out with considerable coherence, the main objective being to develop an exante evaluation plan that will permit an assessment of the extent to which the implemented measures achieve the high level objectives. The following issues should therefore be pre-assessed:  Relevance: to what extent is the adoption of selected measures relevant in relation to the evolving needs and priorities at the local/National/EU level?  Efficiency: how were the resources (inputs) turned into outputs or results?  Effectiveness: how far has the transferability process contributed to achieving its specific and global objectives?  Utility: will the process have an impact on the target groups or populations in relation to their needs?  Sustainability: to what extent can the changes (or benefits) be expected to last after the measures have been completed? The basic principle of ex-ante evaluation is to compare two future situations:  What would happen, at a future target year to be defined, if the measure is not implemented.

3.2.9. STEP 9 – identify need for adjustment In order to assess whether adjustments are needed, it is desirable to review the conditions for transferability. To this end, published data sources, networks, co-operative projects, skills exchanges, and various NGOs can provide additional valuable inputs. As transferability will depend to some extent on compatibility of institutional context, there may be a need to transplant a policy with part of its institutional context, i.e. transfer not only a measure but some of the relationships between institutions and territories may have to be replicated as well. 3.2.10. STEP 10 – implement measures and steer results A minimum amount of information is necessary to allow proper monitoring of the implementation strategy. Global objectives and specific targets should be stated and quantified along with any expected results (City Evaluation Report). A detailed description of measures together with a quantification of the associated operational objectives should be contained in the programme drawn up at city level, as foreseen in the Inception Reports. Establishing operational monitoring arrangements covers the following areas: 1. The definition of the data to be collected in order to provide the necessary information on outputs, results, impacts, and corresponding indicators. 2. The methods used to quantify the data or estimates generated by e.g. surveys must be specified (sample, panel data, databases, monitoring mechanisms, etc.) as well as authorities or bodies responsible for their collection. 3. The definition of data to be provided to the monitoring activities and the frequency and timing of their transmission. 4. The definition of operational links with the evaluation activities (ex-ante, mid-term, and ex post). 5. The definition of programme-specific indicators for use to allocate the performance at mid-term, if possible. The preparatory work for setting up a monitoring system must also serve to detect the gaps that the information systems contain. This may require relying on technical assistance and outside experts to fill gaps and deficiencies, improve the general implementation conditions, and make monitoring more effective. 3.3. Setting up the transferability algorithm in 10 STEPS Fig. 1 illustrates the methodological framework proposed to undertake processes of transferability of measures within CIVITAS. The proposed framework identifies the sequence and the interrelationships between the various questions that should be addressed in order to assess the potential for success of such an operation. The major assumption of the proposed methodology is that transferability is expressed through the applicability, optimum packaging, and community acceptance of the candidate measures. The application of the proposed framework further requires its operationalization through the provision of implementation guidelines. Fig. 2 illustrates the 10 STEPS transferability algorithm.

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STEP 1 - Diagnostic of the Problems

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STEP 2 - Characterisation of the City

STEP 3 - Analysis of the city context and implications of problems identified

STEP 4 - Look Around for Similar Contexts

STEP 5 - Selecting Examples of Origin Urban Contexts

STEP 6 - Identify measures with potential for transferring

STEP 7 – Packaging & Dimensioning the Measures for Transferring

STEP 8 – Ex-ante Assessment of Measures to Transfer

STEP 9 - Identify Need for Adjustment

Need to Adjust?

Yes

No

STEP 10 - Implement Measures and Steer Results Fig. 1. Transferability algorithm.

4. Application to CIVITAS initiative

TRANSFERABILITY FRAMEWORK STEP 1 - Diagnostic of the Problems STEP 2 - Characterisation of the City STEP 3 - Analysis of the city context and implications of problems identified STEP 4 - Look Around for Similar Contexts STEP 5 - Selecting Examples of Source Urban Contexts STEP 6 - Identify measures with potential for transferring STEP 7 - Packaging and Dimensioning the Measures for Transferring STEP 8 - Ex-ante Assessment of Measures to Transfer STEP 9 - Identify Need for Adjustment STEP 10 - Implement Measures and Steer Results

EVALUATION TEMPLATES

EVALUATION REPORTS

REVIEW OF KEY “TRF” ELEMENTS

TRANSFERABILITY SUPPORT TOOL SYSTEMATIZATION OF RESULTS

“PURPOSE reORIENTATION” OF MEASURES

Fig. 2. Methodological approach in CIVITAS.

The approach outlined in the previous sections provides a useful framework within which to identify causal structures as a first step in defining a sustainable urban transport system’s boundaries, before constructing a formal simulation model to provide grounded support to policy making and transferability. Individual Causal Loop Diagrams (or mind maps) were set up to link impact and process evaluation of CIVITAS with the characterisation of the context within a cluster and the respective high level objectives. Through such causal diagramming it is possible to illustrate associations and impacts common to all observed cities studied in the CIVITAS project, that can assist in guiding policy instruments to achieving the high level objectives (HLOs) of specific cities. For each cluster in CIVITAS a set of Core Measures targeted at the high level objectives of the Cluster were defined, combined with their Support Measures which resulted in identifying measures that worked towards the support and success of other measures, aiding the objective of transferability. 4.1. Recommendations on packaging for successful transferability Measures were generally related to the most obvious things to do to promote sustainable mobility. These sort of measures can

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gather large consensus by themselves, with the power to create their own momentum. But even in such cases, it might be possible that their full potential is not achieved, prejudicing their effectiveness, unless enhancing combinations of measures are considered. This is the basic notion of packaging explored herein, as CIVITAS revealed significant evidence for a systematized approach to packaging, depicting key relationships within and across clusters. Both perspectives are considered below. 4.1.1. Packaging across policy clusters Clusters of measures complement and enhance the effectiveness of others often beyond what any superficial analysis would indicate. They form what can be called a ‘‘package’’ of clusters acting together towards a certain objective. The key associations between broad objectives and the relevance of the clusters of policy measures adopted in the cities observed are depicted below. The need for packaging Across Policy Clusters stems from the notion that there are interactions and feedback relationships between measures, both across and within policy fields/clusters. For the transferability analysis, it is most relevant to check the interrelationships across the clusters considered. The following sections illustrate the associations of clusters found to be relevant for the key aims of the CIVITAS initiative, with an indication about the relevance of each cluster in the scope of such combination, assessed using a blue shaded scale, from stronger (darker) to weaker (lighter). A – Promotion of clean urban transport. The following objectives are directly related to the general purpose of promoting clean urban transport:  HLO14 decrease local emission and improve quality of life in city centers.  HLO3 reduce traffic emissions and energy consumption.  HLO5 increase the efficiency of the transport system.  HLO8 increase clean vehicles market share in private and public fleets.  HLO9 establish business cases and accelerate take-up of clean vehicles solutions.  HLO11 increase competitiveness and reliability of local production of alternative fuels.  HLO12 foster competitive procurement of clean vehicles. Table 1 identifies the requirements in terms of putting together the policy fields that contribute to such purpose. The importance of combining them is complemented by an indication about the relevance of each cluster in this association, estimated from the collection of references provided in the city reports. In order to successfully transfer such measures it should be given priority to adopt measures such as ‘‘Clean Vehicles’’. Indeed, the natural prevalence of measures regarding ‘‘Clean Vehicles’’ themselves, seems fair if we consider that the overall purpose of the package is simply unachievable without actual promotion of new technologies. On the other hand, ‘‘Car Sharing and Car Pooling’’ appear somewhat surprisingly as a policy measures that has a relatively high importance in this context, which may be explained if we consider the experimental phase in which the adoption of clean vehicles exists, and the role of these sort of measures in promoting increased market share for hybrids, for example, in the urban context. Although the importance of each policy field in the package should be carefully analyzed on a case-by-case basis, it seems reasonable to assume that all the measures with a relevance equal and above two should, in all cases, be strongly considered in such package. B – Promoting better conditions for public transportation. The following objectives are directly related to the objective of promoting better conditions for public transportation, including increased modal share.

Table 1 Packaging of policy fields to promote clean urban transport

POLICY FIELD

RELATIVE RELEVANCE IN THE PACKAGE

• Clean Vehicles and Fuels • Car Sharing and Car Pooling • Cycling • Zones with Controlled Access • Public Transport • Parking Management • Mobility Management • Goods Distribution and Logistic Services • Road Pricing

 HLO2 reduce congestion.  HLO7 increase the attractiveness of public transport, induce modal shift and PT share.  HLO13 reduce journey times. Table 2 identifies the requirements in terms of putting together the policy fields aimed at contributing to such an objective. The importance of combining them is complemented by an indication about the relevance of each cluster in this association, estimated according to the collection of references from the city reports. It may be concluded that there is a reasonable balance among the policy fields in terms of their relative importance in the package, with the caveat that measures in combination should be carefully analyzed on a case-by-case basis in order to promote a successful transfer of best practice. C – Long term planning of the transport and land-use system. The following objectives are directly related to the objective of promoting long term planning of the transport and land-use system:  HLO1 improve the longer-term planning process and information provision.  HLO6 promote better integrated planning between transport and land use.  HLO4 protect city centre.  HLO10 decrease parking pressure. Table 3 identifies the requirements for policy fields that contribute to this objective. The importance of combining them is complemented by an indication about the relevance of each cluster in this association, estimated according to the references from the city reports.

Table 2 Packaging of policy fields to promote better conditions for public transportation

POLICY FIELD • Zones with Controlled Access • Transport Information and Management • Road Pricing • Public Transport • Multimodal Interchange • Mobility Management • Parking Management • Goods Distribution and Logistic Services • Car Sharing and Car Pooling

RELATIVE RELEVANCE IN THE PACKAGE

´rio, C.F. Marques / Research in Transportation Economics 22 (2008) 146–156 R. Maca Table 3 Packaging of policy fields to promote long term planning of the transport and land use system

POLICY FIELD

RELATIVE RELEVANCE IN THE PACKAGE

• Transport Information and Management • Mobility Management • Zones with Controlled Access • Parking Management • Cycling • Car Sharing and Car Pooling

Again, it may be concluded that there is a reasonable balance among the policy fields regarding their relative importance in the package, allowing us to conclude that combinations of measures should be analyzed on a case-by-case basis in order to promote successful transfer of best practices. Successful long term planning seems to be strongly associated with initiatives aimed at developing new ‘‘Transport Information and Management Systems’’ as well as ‘‘Mobility Management Measures’’, which can be considered as crucial requirements when planning to transfer related best practices such as ‘‘Zones with Controlled/Restricted Access’’, ‘‘Parking Management’’, or ‘‘New Cycling and Walking Facilities and Services’’.

153

4.2. Packaging of specific measures within policy clusters Only a few measures have been implemented in cities which are not in any way grouped or packaged. Hence, we see that most of the measures have been developed coherently within each cluster, and most of the times the need for simultaneous implementations of the measures that are inside the cluster is rather straightforward and can be identified from mapping the relationships within each cluster. For each of the clusters considered we present sensible packaging indications, judging from the evidences taken from the city reports. Within each cluster we could find the Main Measures primarily targeted at the high level objectives of the Cluster, assisted by the complementary measures. Table 4 summarizes the findings. These findings suggest that there are measures that worked towards the support and success of others. The packaging within each cluster therefore results from the adoption of core measures with the complementary or supportive ones. However, this cannot ensure, by itself, that the full potential of effectiveness is seized, since the role of packaging across clusters will, in most cases, represent another important feature. 4.2.1. Transferability of measures The findings above suggest that clusters of measures can indeed be characterized by their ability to be successfully transferred to different cities. The most important drivers in a successful transferability process seem to be related, first of all to the replicability of its context, namely physical, cultural and institutional conditions. By mapping the context to the measures, hence the clusters, it has been possible to provide a detailed insight into:

Table 4 Packaging of specific measures per policy cluster Policy cluster

Packaging Main measures

Complementary measures

Transport information and management

Transport planning integrated with land-use Automatic vehicle detection/real-time passenger information On-street information High level service bus and tram routes Accessible road network (street) data

Information on the Internet Network management Centres for E-working, commerce and learning

Multimodal interchanges

PT integration through service extensions Quality improvement and integration of PT Park and ride Improve interchange facilities

Awareness raising Multimodal information for passengers

Mobility management

Mobility management actions on the field

Mobility centre

Cycling

New cycling and walking facilities and services

Information material/awareness campaigns

Car sharing/car pooling

Implementation of car pooling and car sharing services Establishment of park & pool areas Physical integration between car sharing schemes and PT

Information material/awareness campaigns Management of car pooling and car sharing services Establishment of HOV-lanes and/or use of bus lanes for HOVs Smart card systems between car sharing schemes and PT

Zones with controlled access

Set up of city centre clean zone Set up of clean corridors Residential traffic management

Information material/awareness campaigns

Clean vehicles and fuels

Introduction of clean road vehicles Introduction of zero emission trams

Information on the use of clean vehicles Renewable energy supply New service stations Analysis of previous biogas experience

Public transport

Introduce new PT services Services for special customer Improve PT security and safety

Groups integrated pricing systems

Goods distribution and logistic services

Innovative city logistics schemes

Info. & support services to Kerbside-doorstep delivery Creation of a material logistic centre Community delivery points

Parking management

Parking pricing

Innovative parking paying schemes

Road pricing

Implement road pricing

´rio, C.F. Marques / Research in Transportation Economics 22 (2008) 146–156 R. Maca

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Table 5 Transferability requirements (packaging across clusters)

(i) each policy cluster, and (ii) across policy clusters.

(iv) A list of high level objectives built from the objectives declared by the cities for each cluster detailed above.

This work was based on:

4.2.2. Transferability guidelines The approach to key interdependencies between context variables and successful measures suggests that the success of some individual measures within a certain policy cluster is sensitive to several different conditions. This makes any aggregated analysis on transferability likely to be insufficient for a city to assess its own situation. In that case, individual considerations per measure will be required. However, it is worth noticing that there are general notions to explore about the guidelines for transferability.

(i) The identification of barriers and drivers undertaken elsewhere in this report (including its assessment as low, medium, high influence). (ii) The CIVITAS measures themselves. (iii) The key concerns and crucial actions for success referred in all the city reports for all measures adopted.

Table 6 Sensitiveness to local context Policy cluster

Transport information and management Multimodal interchange Mobility management Cycling Car sharing and car pooling Zone with controlled access Clean vehicles and fuels Public transport Goods distribution and logistic services Parking management Road pricing

Other local conditions Mobility master plan/trip plan in place

Ability for effective enforcement

N/A

Positive

N/A

Positive

Positive

Positive

N/A

N/A

Positive

Positive

Positive

N/A

Positive N/A

Positive Positive

N/A Positive

N/A Positive

Positive Positive

Positive N/A

N/A

N/A

Positive

Positive

Positive

Positive

Positive

N/A

N/A

Positive

Positive

Negative

N/A

Positive

N/A

N/A N/A

Negative Negative

N/A N/A

Positive N/A

Positive Positive

N/A N/A

Negative N/A

N/A N/A

Positive Positive

N/A

N/A

N/A

Positive

Positive

Positive

Positive

Positive

Positive

Positive

Positive

N/A

Positive

Positive

Positive

Positive

N/A

N/A

City size

Urban sprawl

City hilliness

Public support/ acceptability

Previous successful experiences

Public transport network Quality

Density

Positive

N/A

N/A

N/A

Positive

Positive

Positive

Positive

N/A

Positive

N/A

N/A

N/A

N/A

N/A

Negative Positive

Negative Negative

Negative N/A

Positive

Negative

N/A

N/A – not available/applicable.

Table 7 Assessment of policy cluster’s transferability sensitiveness to other constraints Policy cluster

1

2

3

7

8

9

Politics and strategy opposition/ commitment

Politics and strategy conflict/ coalition

Planning Planning Planning Planning user technical economic policy conflict/ assessment synergy

4

5

6

Institutions administrative structures and practices

Institutions legislation and regulation

Information Technology Public Co-operation Co-operation Citizen funds participation and public partnership key and relations individuals and subsidy involvement

10

11

12

13

14

15

Exchange Cultural and life and style mutual learning

16

17 Problem pressure

Medium

High

High

–

Moderate High

–

High

Moderate –

High High

High –

High High

High

–

High

–

Low

High

High

Moderate

–

High

Low

Moderate

Moderate

Moderate

High

–

–

–

–

High

High

Moderate

–

High

–

–

High

–

–

–

–

–

Moderate High

–

High

–

–

–

Moderate

–

–

–

Moderate –

Low –

High High

High High

– –

– High

High –

– –

High –

High Moderate

– –

– – Moderate Low

High Low

– –

High

–

High

High

–

High

High

–

–

High

Moderate

–

–

–

Moderate

High

High

High

High

–

High

–

–

–

Moderate

High

High

–

–

–

High

Moderate High

High

High

High

–

High

High

–

Low

Moderate

Moderate

High

–

–

–

High

High

High

High

High

–

High

High

–

–

–

–

–

–

–

Moderate

High

High

–

High

High

–

–

Moderate

Moderate

–

Low

–

High

–

Moderate

–

High

–

–

–

High

High

–

–

–

–

High

High

High

High

–

High

–

´rio, C.F. Marques / Research in Transportation Economics 22 (2008) 146–156 R. Maca

Transport information and management Multimodal interchange Mobility management Cycling Car sharing and car pooling Zone with controlled access Clean vehicles and fuels Public transport Goods distribution and logistic services Parking management Road pricing

Drivers/barriers

155

156

´rio, C.F. Marques / Research in Transportation Economics 22 (2008) 146–156 R. Maca

Those general guidelines are presented below in Tables 5–7, building on the links found per each policy cluster. A Guidelines on packaging of policy clusters. B Guidelines on policy cluster’s transferability sensitiveness to local context. C Guidelines on policy cluster’s transferability sensitiveness.

management, clean vehicles and fuels, cycling, goods distribution and logistic services.  Low risk: those measures that can be implemented using existing powers and which are relatively easily enforceable, while perceived to provide clear benefits for the city or to the public. These measures include parking management, transport information and management, and public transport improvements.

5. Conclusions References A direct consequence of the research approach developed herein is a recommendation to collect and process the knowledge produced by initiatives such as CIVITAS in order to strengthen the consistency of the information available to undertake ex-ante assessments of transferability potential. The suite of measure identified in the clustering exercise in terms of transferability risk can be classified as follows:  High risk: those that absolutely require some form of support or have a perceived risk if imposed above and beyond what can be considered ‘normal’. Consequently these measures are assessed as requiring careful checking of the preconditions of implementation as well as an adequate supportive packaging. This group includes zones with controlled access, multimodal interchange, car sharing, car pooling and road pricing.  Moderate risk: those measures that can typically be undertaken under current common circumstances in most European cities, but still need careful attention in terms of adequate local conditions, and still require particular attention to supportive packaging. These measures include mobility

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