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Building composite indicators using multicriteria methods: a review

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Abstract

Composite indicators are increasingly recognised as a useful tool in policy analysis and public communication. They provide simple comparisons of units that can be used to illustrate the complexity of our dynamic environment in wide-ranging fields, such as competitiveness, governance, environment, press, development, peacefulness, tourism, economy, universities, etc. Their construction has been dealt with from several angles. Some authors claim that MCDM techniques are highly suitable in multidimensional frameworks when aggregating single indicators into a composite one, since this process involves making choices when combining criteria of different natures, and it requires a number of steps in which decisions must be made. In this paper, we conduct a literature review of papers published after 2002 in leading international journals indexed in a recognised database (JCR), in order to identify the different MCDM methods used for aggregating single indicators into composite ones. They have been classified in five categories: the elementary methods, the value and utility based methods, the outranking relation approach, the data envelopment analysis based methods and the distance functions based methods. In general, our review has shown a clear tendency towards an increasing number of papers that use MCDM methods to construct composite indicators since 2014.

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Notes

  1. The UTASTAR method is an improved version of the original UTA model and it was proposed by Siskos (1985).

  2. According to Gabus and Fontela (1973), the DEMATEL method is one of the tools used for multiple criteria decision making and it is able to transform qualitative issues into quantitative tasks for analysis.

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Acknowledgements

We acknowledge the support received from the Spanish Ministry of Economy and Competitiveness (Project ECO2016-76567-C4-4-R) and from the Regional Government of Andalucía (research group PAI-SEJ-417).

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El Gibari, S., Gómez, T. & Ruiz, F. Building composite indicators using multicriteria methods: a review. J Bus Econ 89, 1–24 (2019). https://doi.org/10.1007/s11573-018-0902-z

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