A goal-based weighting for composite indicators constructed through Ordered Weighted Averaging (OWA) operator

Matheus Pereira Liborio, Petr Iakovlevitch Ekel, Sandro Laudares,Carlos Augusto Paiva da Silva Martins

METHODSX(2024)

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摘要
The Ordered Weighted Averaging (OWA) operator is a multicriteria method that has conquered space among researchers in the composite indicators field. Typically, OWA operator weights are defined by the decision maker. This type of weighting is highly criticized, as decision-makers are susceptible to errors and bias in judgment. Some methods have been used to define OWA operator weights objectively. However, none of them is concerned about the quality of the composite indicator. This paper introduces a method that defines the weights of the OWA operator based on two quality parameters of the composite indicator: the ability to capture the concept of the multidimensional phenomenon and the informational loss. The method can be implemented in Microsoft Excel Solver and has a high degree of flexibility and applicability in problems of a multidimensional nature and a high degree of appropriation by researchers and practitioners in the area. center dot Defines weights that maximize the ability of the composite indicator to capture the concept of the multidimensional phenomenon. center dot Considers restrictions to limit the informational loss of the composite indicator or emphasize positive or negative aspects of the multidimensional phenomenon. center dot Offers flexibility in setting the objective and constraints of the optimization algorithm.
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关键词
Multicriteria methods,Operation research,Multidimensional problems,Data-driven weighting scheme,Informational loss,Optimization algorithms
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