Volume I: This report is part of the ‘Policy’ Work Package of the DaCoTA project (www.dacotaproject.eu). The ‘Policy’ Work Package is designed to fill in the gap in knowledge on road safety policy making processes, their institutional framework and the data, methods and technical tools needed to base policy formulation and adoption on scientifically-established evidence. This document provides the results of a detailed analysis of a survey conducted with a large panel of stakeholders. The aim was to assess what they considered to be priorities and necessities in terms of scientific data, information, and tools to conduct their road safety activities. The aim is to improve our knowledge of the items that should be included in the ERSO website or that are included in the website already but deserve being highlighted somewhat. Concrete recommendations are eventually made that should contribute to the ERSO’s usefulness for a wide variety of road safety actors. The present report builds on a model that has been previously defined in the same Work Package to formally describe the Road Safety Management process, and to couple it with scientific input. This model conceives road safety management as involving 4 key tasks: (1) Fact Finding; (2) Programme Development; (3) Preparing Implementation; (4) Monitoring and evaluation. For each type of task, scientific support may prove necessary, either in terms of data, tools for the treatment of these data, training tools, or other decision-support tools (see Muhlrad, Gitelman, & Buttler, 2011 for a detailed description of the road safety management model used). The Road Safety Management model has first served as basis for the interview of a panel of road safety experts (see Muhlrad &, Dupont, 2010 for a complete report of the interview analysis). Their answers served as basis to design a questionnaire which was meant to be submitted to a wider array of stakeholders involved in road safety. This questionnaire contained questions concerning the background of the stakeholders and, structured around the 4 road safety management tasks listed above, a list of possible data, information, and tools that could be used as input for the different tasks. The stakeholders answering the questionnaire were asked to rate each of these items’ level of priority for the type of road safety activities that they were performing along with its availability. In total, 512 stakeholders returned the questionnaire. A first description of the results can be found in Machata, Barnes, & Jahi, 2011 . The present deliverable contains the results of a further in-depth analysis of the stakeholders’ answers to that survey. In a first step, common dimensions underlying the priority and availability ratings of the tools listed in the questionnaire have been identified. Then, in a second step, these dimensions were used to identify “groups” (clusters) among the stakeholders. Finally, it was investigated whether the groups formed on the basis of the underlying priority-availability dimensions were associated with variation in the background characteristics of the stakeholders (country, type of organisation they were working for, type of road safety activities in which they were involved). Each of these analysis steps was performed in 2 different ways: Firstly, treating the priority and availability ratings separately, and secondly, by recoding the priority and availability ratings so as to recombine them into a common scale (the higher the score on this new scale, the more the item is considered to be a priority and to be unavailable). For this reason, the second type of data treatment is referred to as the “needs analysis”. The results revealed that meaningful dimensions can be identified that summarize the priority-availability ratings of the items included in the questionnaire in an efficient way. This was the case both when the priority and availability ratings were treated separately or recombined into a “needs” scale. Although the content of the dimensions identified varies somewhat depending on the type of data treatment, most of them display important similarities in content. Other dimensions, on the other hand, emerge more specifically when analysing the availability ratings or the combined “needs” scale. These dimensions furthermore ease the grouping of the stakeholders on the basis of their priority and availability ratings of the more than 50 items originally listed in the questionnaire. Working exclusively on the priority ratings, 4 different clusters were identified: ? Cluster 1 representing the stakeholders with “low priority for everything”; ? Cluster 2 representing the stakeholders considering that data and models are specifically important, ? Cluster 3 includes stakeholders that tend to assign “high priority for everything, but especially implementation”, ? Cluster 4 corresponds to stakeholders assigning high priority to in-depth data mostly The investigation of the relation between the different clusters the stakeholders are assigned to and their background characteristics reveals no clear relation with the type of country they originate from. They are however more clearly related to the type of organisation the stakeholders work for, e.g. stakeholders from the industry appear to be over-represented in the 4th cluster, while those from associations and interest groups tend to be over-represented in the third one and stakeholders working in national or regional administrations tend to be over-represented in cluster 2. On the basis of availability ratings, 3 clusters were identified: ? The first one groups stakeholders who basically declare that information on costs and benefits of measures are available, but that models are not. ? Cluster 2 corresponds to stakeholders declaring that models are available, but that data and definitions are needed. ? Finally, stakeholders in Cluster 3 request information about the costs and benefits of measures. Again, the investigation of background characteristics reveals little association with the countries the stakeholders work in, but a stronger relationship with the type of organisation they work for. Stakeholders from both research institutes and national/regional organisations tend to be over represented in the first cluster, but under-represented in the third one, while stakeholders from associations and interest groups tend to be over-represented in the second cluster. Finally, when working with the combined “needs” scale, 6 clusters are identified: ? Cluster 1 “needs for most items, especially accident and infrastructure analysis”; ? Cluster 2 “moderate needs for all”, ? Cluster 3 “High needs for models, moderate needs in other, implementation unimportant”, ? Cluster 4 “No needs for models, moderate needs in implementation” ? Cluster 5 “Low importance of implementation and models, moderate needs in crash causation” ? Cluster 6 “High needs for implementation but no use of accident and infrastructure analyses The stakeholders in the first cluster only rarely state that data and tools are of “high importance” for their professional activities, do not seem to use databases (national and international) much, and tend to declare more that they are “very satisfied” with the data and resources currently available. This cluster does not clearly relate to any particular type of organization, of road safety activity, or of country. The stakeholders in Cluster 2 generally consider data and tools to be important in their daily road safety activities, report making substantial use of databases (international and national). Stakeholders involved in sensitization activities tend to be better represented in this cluster and generally consider scientific input to be relatively important for their professional activities, without showing a marked preference for any particular type of information. Stakeholders involved in research and working for road safety organizations tend to be over-represented in Cluster 3. This cluster is the one with the highest proportion of respondents declaring that tools are very important for their road safety activities and tending to assign very high priority to statistical models. Cluster 4 is also characterized by a substantial proportion of stakeholders involved in research activities. They stress — although to a moderate extent — the needs for information about the implementation of measures, the safety impacts of measures and on accident analysis with regard to road infrastructure. Cluster 5 contains the highest proportion of policy makers, along with a higher proportion of respondents from the industry. These stakeholders generally tended to consider all data and information types as less important (especially information related to the implementation of measures and statistical models), but they stressed more the importance of accident causation information and information on the safety impacts of measures. Finally, the stakeholders in Cluster 6 did not report using databases much. This cluster is, along with Cluster 5, the one containing the highest share of policy makers. Clearly “sensitization” is a dominant activity among these respondents. They insisted on the importance of information related to the implementation of measures and, on the other hand, on the lesser importance of accident and infrastructure analysis. The report ends on a discussion of the implications that the analyses’ results have for the ERSO. On the basis of an overview of the dimensions identified on the basis of the stakeholders ratings, concrete recommendations are made for the future development of ERSO, in terms of project results whose accessibility and visibility should be ensured on the website (EU-funded, national projects or other international research initiatives), but also in terms of data collection. / Volume II: The main objective of the DaCoTA project with respect to road safety management systems was to investigate the road safety management framework in European countries in order to help promote “good practice” and optimize management processes. Within this context, the road safety management investigation model proposed by Muhlrad et al. (2011) is based on several “good practice” criteria, defined by an exhaustive literature review, aiming to address the need for optimized road safety management systems, leading to better road safety performance, in a changing environment. In this research, road safety management systems have been thoroughly investigated in 14 European countries in 2010, by means of interviews with both governmental representatives and independent experts in each country who filled in an extensive DaCoTA questionnaire on the degree to which the various road safety management systems meet the “good practice” criteria. The questions related to five main areas of Road Safety Management: ? Institutional organisation, coordination and stakeholders’ involvement ? Policy formulation and adoption ? Policy implementation and funding ? Monitoring and evaluation ? Scientific support and information, capacity building A shorter version of the DaCoTA questionnaire has also been prepared in collaboration with the European Transport Safety Council (ETSC). This questionnaire includes 11 key questions similar to those of the original DaCoTA questionnaire and was dispatched to the PIN panel of the ETSC, i.e. the 30 high level national experts from ETSC network of member organisations. The combined use of the two questionnaires allowed on the one hand the coverage of basic road safety management elements for all European countries (DaCoTA/ETSC-PIN questionnaire), and on the other hand the full in-depth analysis for a subset of European countries (DaCoTA questionnaire). The data was analyzed in two ways: ? Qualitative analysis: making a thorough analysis and cross-checking of the questionnaire responses and related comments of both the governmental representatives and the independent experts, in order to draw a reliable and accurate picture or “profile” for each country, and allowing in-depth country comparisons for selected key items. ? Quantitative analysis: using statistical methods to identify patterns, correlations and rankings of countries, as regards both the road safety management characteristics, and the relationship between road safety management and road safety performance. The two types of analyses had therefore different yet complementary objectives, and their combination allowed for full exploitation of the wealth of data gathered by the DaCoTA team. More specifically, the present research contributes the following analyses and results: ? Road safety management country profiles: road safety management systems in the 14 European countries are analysed and compared to a reference “good practice” system, meeting all the criteria defined in DaCoTA, on the basis of the extensive DaCoTA questionnaire. Road safety management structures and outputs are described according to the policy-making cycle (agenda setting, policy formulation, adoption, implementation and evaluation) and set against the background of a typical hierarchical national government organization. ? Country comparisons: country comparisons are carried out for all 30 European countries for specific issues within each area of road safety management, in order to understand how the different countries in Europe handle their road safety management systems and whether the model developed under DaCoTA can serve as a useful tool for comparing different national solutions. For this analysis, apart from the DaCoTA questionnaire, the DaCoTA/ETSC-PIN data, as well as additional data sources from the literature, were also exploited. ? Clustering of countries on the basis of road safety management components: statistical clustering techniques are used to group and rank the 14 European countries on the basis of their level of availability of the various road safety management “good practice” elements, separately for each one of the five areas of the DaCoTA questionnaire. A final global ranking of countries in terms of their road safety management system as a whole is also presented. ? Statistical models linking road safety management with road safety performance: regression models were develop in order to test whether road safety management is associated with road safety performance, within the framework of the SUNflower methodology for road safety management systems. Different road safety outcomes (fatalities, reduction in fatalities, Safety Performance Indicators - the intermediate outcomes) were tested against road safety management indicators and other background variables. The results of the DaCoTA analyses on road safety management systems suggest that, although a number of “good practice” elements can be established as regards road safety management structures, processes and outputs, it is not possible to identify one single “good practice” model at national level. Best performing countries are not always ranked best in terms of road safety management components. On the other hand, the proposed “good practice” criteria seem to work as regards the worst performing countries. One clear finding is that similar performance in road safety management can be achieved by means of differing structures and implementation processes. Similarly, similar road safety performance in terms of final outcomes (i.e. fatalities) may be the “result” of substantially different road safety management systems. Despite the differences in European road safety management systems, there have been several elements that emerged as more critical “good practice” criteria, such as the presence of a strong lead agency, the efficiency of the implementation — monitoring — evaluation part of the policy making cycle, the embedding of programmes in sustainable and results-focused structures and processes, and the distribution and coordination of responsibilities between federal, regional and local levels. Especially the implementation, funding, monitoring and evaluation elements showed the lowest level of availability in the European countries and appear to be the most problematic sections of the road safety management systems. When examining the relation between road safety performance and road safety management in the different countries, there appeared to be little or no effect of road safety management features on safety performance, and background indicators (GDP, level of motorisation) were dominant over road safety management effects. However, road safety management was found to be (weakly) associated with safety performance indicators (SPIs), reflecting the operational level of road safety in each country — these are considered “intermediate” outcomes, affecting in turn the “final” outcomes, i.e. road safety casualties. The weak relationship between road safety management and road safety performance is attributed to the fact that the European countries do not exhibit big differences in road safety performance, and no big differences in road safety management overall - a minimum acceptable level exists in both cases. Another factor that should be taken into account is the time of observation. In some countries, road safety management components may be so recent that they hadn’t yet had the time to deploy their full potential; or they may have been around for such a long time that their impact has already gradually faded away. Moreover, the evolution of road safety management may be associated with the evolution of road safety performance, but no data was available to examine this temporal dimension. Another finding concerns the differences observed between expert’s and government’s responses, the latter tending to be more positive, especially as regards the role of the parliament, the availability of programmes, the resources and funds allocation, the reporting procedures, the information of citizens etc. It was concluded that expert responses may reflect an independent and more objective view and that future analysis might better use experts’ opinion as a prime source. On the basis of the results of the present research, the following key messages and recommendations can be outlined: ? Recommendations at national and local level 8 Develop objective knowledge of RSM within countries 8 Decentralisation with care 8 Establishment of an Independent Lead Agency 8 Inter-sectoral and vertical coordination 8 Continuous stakeholders consultation 8 Vision and strategy is crucial for creating a road safety culture, but implementation is the critical step towards road safety improvement 8 Strengthen the link from policy formulation to policy adoption 8 Regular monitoring and evaluation 8 Resources and funding 8 Knowledge-based policies 8 Capacity building & training 8 Handle road safety management in times of recession ? Recommendations at European level 8 Adopting the safe systems approach 8 Exploiting the synergies of road safety and environmental policies 8 Adoption of serious injury reduction targets 8 Focusing on the essentials, leaving the details to the individual countries 8 Strengthening the role of ERSO 8 Publication of a Road Safety Management Good Practice Manual 8 Building on the existing framework and improving where necessary 8 Political will and commitment from all stakeholders. / Volume II: The main objective of the DaCoTA project with respect to road safety management systems was to investigate the road safety management framework in European countries in order to help promote “good practice” and optimize management processes. Within this context, the road safety management investigation model proposed by Muhlrad et al. (2011) is based on several “good practice” criteria, defined by an exhaustive literature review, aiming to address the need for optimized road safety management systems, leading to better road safety performance, in a changing environment. In this research, road safety management systems have been thoroughly investigated in 14 European countries in 2010, by means of interviews with both governmental representatives and independent experts in each country who filled in an extensive DaCoTA questionnaire on the degree to which the various road safety management systems meet the “good practice” criteria. The questions related to five main areas of Road Safety Management: ? Institutional organisation, coordination and stakeholders’ involvement ? Policy formulation and adoption ? Policy implementation and funding ? Monitoring and evaluation ? Scientific support and information, capacity building A shorter version of the DaCoTA questionnaire has also been prepared in collaboration with the European Transport Safety Council (ETSC). This questionnaire includes 11 key questions similar to those of the original DaCoTA questionnaire and was dispatched to the PIN panel of the ETSC, i.e. the 30 high level national experts from ETSC network of member organisations. The combined use of the two questionnaires allowed on the one hand the coverage of basic road safety management elements for all European countries (DaCoTA/ETSC-PIN questionnaire), and on the other hand the full in-depth analysis for a subset of European countries (DaCoTA questionnaire). The data was analyzed in two ways: ? Qualitative analysis: making a thorough analysis and cross-checking of the questionnaire responses and related comments of both the governmental representatives and the independent experts, in order to draw a reliable and accurate picture or “profile” for each country, and allowing in-depth country comparisons for selected key items. ? Quantitative analysis: using statistical methods to identify patterns, correlations and rankings of countries, as regards both the road safety management characteristics, and the relationship between road safety management and road safety performance. The two types of analyses had therefore different yet complementary objectives, and their combination allowed for full exploitation of the wealth of data gathered by the DaCoTA team. More specifically, the present research contributes the following analyses and results: ? Road safety management country profiles: road safety management systems in the 14 European countries are analysed and compared to a reference “good practice” system, meeting all the criteria defined in DaCoTA, on the basis of the extensive DaCoTA questionnaire. Road safety management structures and outputs are described according to the policy-making cycle (agenda setting, policy formulation, adoption, implementation and evaluation) and set against the background of a typical hierarchical national government organization. ? Country comparisons: country comparisons are carried out for all 30 European countries for specific issues within each area of road safety management, in order to understand how the different countries in Europe handle their road safety management systems and whether the model developed under DaCoTA can serve as a useful tool for comparing different national solutions. For this analysis, apart from the DaCoTA questionnaire, the DaCoTA/ETSC-PIN data, as well as additional data sources from the literature, were also exploited. ? Clustering of countries on the basis of road safety management components: statistical clustering techniques are used to group and rank the 14 European countries on the basis of their level of availability of the various road safety management “good practice” elements, separately for each one of the five areas of the DaCoTA questionnaire. A final global ranking of countries in terms of their road safety management system as a whole is also presented. ? Statistical models linking road safety management with road safety performance: regression models were develop in order to test whether road safety management is associated with road safety performance, within the framework of the SUNflower methodology for road safety management systems. Different road safety outcomes (fatalities, reduction in fatalities, Safety Performance Indicators - the intermediate outcomes) were tested against road safety management indicators and other background variables. The results of the DaCoTA analyses on road safety management systems suggest that, although a number of “good practice” elements can be established as regards road safety management structures, processes and outputs, it is not possible to identify one single “good practice” model at national level. Best performing countries are not always ranked best in terms of road safety management components. On the other hand, the proposed “good practice” criteria seem to work as regards the worst performing countries. One clear finding is that similar performance in road safety management can be achieved by means of differing structures and implementation processes. Similarly, similar road safety performance in terms of final outcomes (i.e. fatalities) may be the “result” of substantially different road safety management systems. Despite the differences in European road safety management systems, there have been several elements that emerged as more critical “good practice” criteria, such as the presence of a strong lead agency, the efficiency of the implementation — monitoring — evaluation part of the policy making cycle, the embedding of programmes in sustainable and results-focused structures and processes, and the distribution and coordination of responsibilities between federal, regional and local levels. Especially the implementation, funding, monitoring and evaluation elements showed the lowest level of availability in the European countries and appear to be the most problematic sections of the road safety management systems. When examining the relation between road safety performance and road safety management in the different countries, there appeared to be little or no effect of road safety management features on safety performance, and background indicators (GDP, level of motorisation) were dominant over road safety management effects. However, road safety management was found to be (weakly) associated with safety performance indicators (SPIs), reflecting the operational level of road safety in each country — these are considered “intermediate” outcomes, affecting in turn the “final” outcomes, i.e. road safety casualties. The weak relationship between road safety management and road safety performance is attributed to the fact that the European countries do not exhibit big differences in road safety performance, and no big differences in road safety management overall - a minimum acceptable level exists in both cases. Another factor that should be taken into account is the time of observation. In some countries, road safety management components may be so recent that they hadn’t yet had the time to deploy their full potential; or they may have been around for such a long time that their impact has already gradually faded away. Moreover, the evolution of road safety management may be associated with the evolution of road safety performance, but no data was available to examine this temporal dimension. Another finding concerns the differences observed between expert’s and government’s responses, the latter tending to be more positive, especially as regards the role of the parliament, the availability of programmes, the resources and funds allocation, the reporting procedures, the information of citizens etc. It was concluded that expert responses may reflect an independent and more objective view and that future analysis might better use experts’ opinion as a prime source. On the basis of the results of the present research, the following key messages and recommendations can be outlined: ? Recommendations at national and local level * Develop objective knowledge of RSM within countries * Decentralisation with care * Establishment of an Independent Lead Agency * Inter-sectoral and vertical coordination * Continuous stakeholders consultation * Vision and strategy is crucial for creating a road safety culture, but implementation is the critical step towards road safety improvement * Strengthen the link from policy formulation to policy adoption * Regular monitoring and evaluation * Resources and funding * Knowledge-based policies * Capacity building & training * Handle road safety management in times of recession ? Recommendations at European level * Adopting the safe systems approach * Exploiting the synergies of road safety and environmental policies * Adoption of serious injury reduction targets * Focusing on the essentials, leaving the details to the individual countries * Strengthening the role of ERSO * Publication of a Road Safety Management Good Practice Manual * Building on the existing framework and improving where necessary * Political will and commitment from all stakeholders. (Author/publisher)
Samenvatting