• Is the environmental performance of the transport sector improving?
• Are we getting better at managing transport demand and improving the modal split?
• Are spatial and transport planning becoming better coordinated so as to match transport demand to the needs of access?
• Are we optimizing the use of existing transport infrastructure capacity and moving toward a better-balanced intermodal transport system?
• Are we moving toward a fairer and more efficient pricing system, which ensures that external costs are internalized?
• How rapidly are improved technologies being implemented, and how efficiently are vehicles being used?
• How effectively are environmental management and monitoring tools being used to support policy and decision making?
indicator construction in the third step and unravel the data requirements before data collection in the fourth step.
Once produced, we must interpret the indicators, explaining why they are developing as they are and linking them back to the story and policy questions. This must be done in connection with other information using relevant literature, more detailed studies, and comparisons with other available data and indicators. The various factors steering the development of an indicator should be distinguished as much as possible (e.g., natural processes, changes in the size and structure of the economy or society, and changes deliberately brought about by environmental policies). Specific regional phenomena influencing the indicator should be highlighted, such as strong economic growth or differences in welfare.
The last step consists of making conclusions about the whole set of indicators, communicating them to the network of people making or influencing decisions, and preparing an improved indicator set for the next round of reporting.
Using common processes and frameworks for developing indicators will not necessarily result in a common set of indicators. Common processes, frameworks, and typologies are guides for the identification and development of indicators. They support a scientific, systematized approach, help enforce consistency with existing knowledge, and help provide balance in outcomes, including highlighting gaps. Each indicator-building process may require different indicators, but within a certain scope (and at different scales) the frameworks and typologies can be more universal. New frameworks may be needed or existing ones extended as the extent and purpose of the indicators vary, such as between environment and health issues (e.g., DPSIR and DPSEEA).
Consistency of indicators is important within a certain field for practical reasons, including data availability, coordination, and efficiency of data collection and processing. Consistent indicators can also be more effective and reliable communication tools because over time they become familiar and long-term trends can be built up. For all of these reasons, consistency and reliability favor a small core set of indicators, because the fewer the indicators, the more recognizable and manageable they are. However, a small core set does not have the flexibility of a larger indicator set for covering a full cause-and-effect framework. Also, there is a risk that as issues evolve and their scientific understanding improves, a small indicator set will stagnate unless regularly reviewed, updated, or expanded. To understand and manage this tension between stability and flexibility of indicator sets and to develop the necessary trade-offs, suitable processes must be established and run with the appropriate stakeholders. It is here that the common processes, frameworks, and typologies presented in this chapter are useful for enforcing consistent approaches and ensuring that the indicator development and selection process falls within scientific understanding and acceptable norms.
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