Abstract
The growing importance of sustainable development as a policy objective has initiated a debate about those suitable frameworks and tools useful for policy makers when making a sustainable decision. Composite indicators (CIs) aggregate multidimensional issues into one index, thus providing comprehensive information. However, it is frequently argued that CIs are too subjective, as their results undesirably depend on the normalization method, a specific weighting scheme, and the aggregation method of subindicators. This article applies different combinations of normalization, weighting, and aggregation methods for the assessment of an industrial case study, with the aim of determining the best scheme for constructing CIs. The applied methodology gradually aggregates sustainable development indicators into sustainability sub-indices and, finally, to a composite sustainability index. The normalization methods included in this analysis are: minimum-maximum, distance to a reference, and the percentages of annual differences over consecutive years. Equal weightings, the 'benefit of the doubt' approach, and budget allocation process were used for determining the weights of individual indicators and sustainability sub-indices. The linear, geometric, and non-compensatory multi-criteria approaches (NCMCs) were used as aggregation methods. The NCMC is modified to fit the two-level aggregation, then to sub-indices, and finally to a composite sustainable index. Also, a penalty criterion is introduced into the evaluation process with the aim of motivating the company to move towards sustainable development. The results are analyzed by variance-based sensitivity analysis. According to the results the recommended scheme for CIs' construction is: distance to a reference- benefit of the doubt-linear aggregation. © US Government 2012.