Weighting and aggregation of indicators for sustainability impact assessment in the SENSOR context
In response to the need for developing methods for evaluating multidimensional problems in sustainability assessment, the scientific literature provides many examples related to the theory and use of composite indicators. In the context of the SENSOR proj
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Maria Luisa Paracchini1, Cesare Pacini2, Silvia Calvo1 and Jürgen Vogt1 (1) Institute for Environment and Sustainability, Joint Research Centre (JRC), European Commission, Ispra, Italy (2) Department of Agronomy and Land Management (DISAT), University of Florence, Florence, Italy
Abstract In response to the need for developing methods for evaluating multidimensional problems in sustainability assessment, the scientific literature provides many examples related to the theory and use of composite indicators. In the context of the SENSOR project, dealing with the ex-ante assessment of environmental, social and economic impacts of European policies on multifunctional land use, new constraints and dimensions are added to the exercise. Examples are the need for consistency across European regions and across different scales of analysis; the use of qualitative and quantitative information; the possibility of aggregation to different administrative levels (sensitive areas, Member States, cluster regions, EU); and the correct balancing of the sustainability dimensions. As a basis for the development of a system of composite indicators, this paper presents a critical review of existing methods for the weighting and thematic aggregation of indicators, and considers the characteristics of selected approaches in relation to the needs of impact assessment in general and the SENSOR requirements in particular.
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Maria Luisa Paracchini et al.
Keywords composite indicators, weighting, aggregation, multi-criteria analysis, compensatory and non-compensatory analysis
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Introduction
Sustainability is a complex issue, and it is probably easier to describe it with a large number of indicators rather than trying to condense it into a few. Even though scientists might be more interested in uncondensed data that can be statistically analysed, policymakers and the public generally prefer condensed data related to policy objectives and free of redundancy (Pacini et al., 2003). This opens the challenge of defining a coherent and universal methodological framework for sustainability indicators, which satisfies the demand of data integration consonant with the needs of sustainable development, while at the same time reflecting the multiple dimensions inherent in the concept of sustainability. The difficulty at evaluating the environmental and socio-economic performance of so many indicators makes it necessary to reduce and combine them so as to make this information more accessible and easy to interpret (Kang, 2002). This is done by means of composite indicators which are the result of the combination of individual indicators into a single summarised index on the basis of an underlying model, so as to provide a multidimensional measure. Such a measure is useful for complex phenomena which otherwise could be hardly comparable (Tangian, 2006). Within the process of building composite indicators, the step of weighting and aggregation of indicators is crucial in all modelling frames where a large amount of information has to be condensed so
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