Monitoring multidimensional phenomena with a multicriteria composite performance interval approach

Abstract

In the last two decades, the construction of composite indicators to measure and compare multidimensional phenomena in a broad spectrum of domains has increased considerably. Different methodological approaches are used to summarise huge datasets of information in a single figure. This paper proposes a new approach that consists in computing a multicriteria composite performance interval based on different aggregation rules. The suggested approach provides an additional layer of information as the performance interval displays a lower bound from a non-compensability perspective, and an upper bound allowing for full-compensability. The outstanding features of this proposal are: 1) a distance-based multicriteria technique is taken as the baseline to construct the multicriteria performance interval; 2) the aggregation of distances/separation measures is made using particular cases of Minkowski Lp metric; 3) the span of the multicriteria performance interval can be considered as a sign of the dimensions or indicators balance.

Normalization methods for spatio‐temporal analysis of environmental performance: Revisiting the Min–Max method

“…Over the past years, composite indicators' construction for measuring and comparing multidimensional phenomena across a wide spectrum of domains has increased considerably (García–Bernabeu & Hilario–Caballero 2021; Kuc‐Czarnecka, Lo Piano, & Saltelli, 2020; Greco et al, 2019). Environmental performance is one of the topics which is dealt with the most in the literature as it is associated, for example, with specific ecological indicators.…”