The weights generated by the common weights approach provide a common criterion for ranking the decision-making units (DMUs) in data envelopment analysis (DEA). Existing common weights models in DEA are either very complicated or unable to produce a full ranking for DMUs. This paper proposes a new compromise solution model to seek a common set of weights for full ranking for DMUs. The maximum inefficiency scores calculated from the standard DEA model are regarded as the anti-ideal solution for the DMUs to avoid. A common set of weights that produces the vector of inefficiency scores for the DMUs furthest to the anti-ideal solution is sought. The discrimination power of the new model is tested using two numerical examples and its potential application for fully ranking DMUs is illustrated.
Abbasi, M., Ghomashi, A., & Shahghobadi, S. (2022). Finding common weights in DEA using a compromise solution approach. International Journal of Data Envelopment Analysis, 10(2), 63-72. doi: 10.30495/ijdea.2022.68441.1165
MLA
Masomeh Abbasi; Abbas Ghomashi; Saeed Shahghobadi. "Finding common weights in DEA using a compromise solution approach". International Journal of Data Envelopment Analysis, 10, 2, 2022, 63-72. doi: 10.30495/ijdea.2022.68441.1165
HARVARD
Abbasi, M., Ghomashi, A., Shahghobadi, S. (2022). 'Finding common weights in DEA using a compromise solution approach', International Journal of Data Envelopment Analysis, 10(2), pp. 63-72. doi: 10.30495/ijdea.2022.68441.1165
VANCOUVER
Abbasi, M., Ghomashi, A., Shahghobadi, S. Finding common weights in DEA using a compromise solution approach. International Journal of Data Envelopment Analysis, 2022; 10(2): 63-72. doi: 10.30495/ijdea.2022.68441.1165
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