A Novel Approach for Efficiency Measurement in AHP with Mixed Criteria and Its Comparison with DEA
الموضوعات : International Journal of Data Envelopment AnalysisFarzad Rezai Balf 1 , Fatemeh Zarabi 2
1 - Department of Mathematics, Islamic Azad University, Qaemshahr, Iran
2 - Department of Mathematics, Sari Branch, Islamic Azad University, Sari, Iran.
الکلمات المفتاحية: Analytic Hierarchy Process, Data Envelopment Analysis, Multi-Criteria Decision-Making, Efficiency Analysis.,
ملخص المقالة :
Multi-Criteria Decision-Making (MCDM) problems often involve a combination of qualitative and quantitative criteria for evaluating alternatives. A major challenge in such problems is employing a methodology that can simultaneously and effectively process both types of criteria. While Data Envelopment Analysis (DEA) is a well-established method for efficiency evaluation in quantitative-based problems, its inherent limitations in handling qualitative criteria reduce its applicability in more complex decision scenarios. In this study, we introduce a novel efficiency measurement approach using the Analytic Hierarchy Process (AHP) and establish a mathematical comparison with the CCR-DEA model. The proposed method integrates pairwise comparisons and weight derivations for qualitative and quantitative criteria, enabling efficiency analysis without requiring the conversion of qualitative data into numerical values. The findings demonstrate that AHP not only provides a meaningful efficiency assessment in the presence of mixed criteria but also exhibits structural similarities to DEA under specific conditions. This highlights the potential of AHP as a complementary tool for MCDM problems where both qualitative and quantitative factors play a crucial role.
Andersen, P., Petersen, N.C., 1993. A procedure for ranking efficient units in data envelopment analysis. Management Science 39, 1261-1264.
Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429-444.
Cheng, E.W.L., Li, H., 2005. Analytic Hierarchy Process: An approach to determine measure for business performance. Measuring Business Excellence 9, 12-22.
Coelli, T.J., Rao, D.S.P., Battese, G.E. 2005. An Interduction to Efficiency and Productivity Analysis (2nd ed.) Springer.
Fare, R., Grosskopf, S., Lindgern, B. 2009. A Review on the 40Years of Existence of Data Envelopment Analysis. Journal of Productivity Analysis, 31 (1), 1-27.
Govindan, K., Rajendran, S., Srkis, J., Murugesan, P., 2015. Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production 98, 66-83.
Ishizaka, A., Labib, A., 2011. Review of the main developments in the analytic hierarchy process. Expert Systems with Applications 38, 14336-14345.
Jablonsky, J., 2016. Efficiency analysis in multi-period systems: an application to performance evaluation in the Czech higher education. Central European Journal of Operations Research 24, 283-296.
Rossetti, M.D., Kloeber, C.W., Gopal, A.R. 2017. The Green New Deal : Scope, Scale, and Implications. American Action Fourm.
Saaty, T.L., 1980. The Analytic Hierarchy Process, New York: McGraw Hill. International, Translated to Russian, Portuguese, and Chinese, Revised editions, Paperback (1996, 2000), Pittsburgh: RWS Publications.
Saaty, T.L., 2008. Decision making with the analytic hierarchy process. International Journal of Services Sciences 1, 83-98.
Vaidya, O.S., Kumar, S., 2006. Analytic hierarchy process: An overview of applications. European Journal of Operational Research 169, 1-29.
Wang, J.J., Jing, Y.Y., Zhang, C.F., Zhao, J.H., 2009. Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Review 13, 2263-2278.
