Fuzzy data envelopment analysis in composite indicator construction

Abstract

Data envelopment analysis (DEA) as a performance evaluation methodology has lately received considerable attention in the construction of composite indicators (CIs) due to its prominent advantages over other traditional methods. In this chapter, we present the extension of the basic DEA-based CI model by incorporating fuzzy ranking approach for modeling qualitative data. By interpreting the qualitative indicator data as fuzzy numerical values, a fuzzy DEA-based CI model is developed, and it is applied to construct a composite alcohol performance indicator for road safety evaluation of a set of European countries. Comparisons of the results with the ones from the imprecise DEA-based CI model show the effectiveness of the proposed model in capturing the uncertainties associated with human thinking, and further imply the reliability of using this approach for modeling both quantitative and qualitative data in the context of CI construction. © 2014 Springer-Verlag Berlin Heidelberg.