A common weight MCDA-DEA approach to construct composite indicators

A common weight multi criteria decision analysis (MCDA)-data envelopment analysis (DEA) approach is proposed to construct composite indicators (CIs). The proposed MCDA-DEA model enables the construction of CIs among all entities via a set of common weights. The model is capable to discriminate entities which receive CI score of 1, i.e., the efficient entities leading to determination of a single best entity. Common weights structure of the proposed model has more discriminating power when compared to those obtained by previous DEA-like models. In order to validate the proposed MCDA-DEA model, it is applied to two case studies taken from the literature to construct two well-known CIs, i.e., Sustainable Energy Index (SEI) and Human Development Index (HDI). Both the robustness and discriminating power of the proposed method are studied through these case studies and tested by Spearman's rank correlation coefficient. The results reveal several merits of the proposed method in constructing CIs.