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Latest bibliography of DEA with more than 10,000 articles
Mergoni, A. A. Emrouznejad, and K. De Witte (2025) Fifty years of Data Envelopment Analysis, European Journal of Operational Research, 326 (3): 389-412. https://doi.org/10.1016/j.ejor.2024.12.049.
CLICK HERE to download review of Fifty years of Data Envelopment Analysis
CLICK HERE to download bibliography (1978-2016)
CLICK HERE to download Supplement with list of over 10,000 articles
biblio
- Al-Shammari M (1999). “Optimization Modeling for Estimating and Enhancing Relative Efficiency with Application to Industrial Companies.” EJOR 115(3): 488-496.
- Al-Shammari M and A Salimi (1998). “Modeling the Operating Efficiency of Banks: A Nonparametric Methodology.” Logistics Information Management 11(1): 5-17.
- Althin R (1996). “A New, Transitive Productivity Index.” JPA 7(1): 19-28.
- Ali AI and LM Seiford (1993). “The Mathematical Programming Approach to Efficiency Analysis.” in Fried HO and SS Schmidt (eds.) the Measurement of Productive Efficiency: Techniques and Applications, Oxford U.K.: 120-159.
- Althin R (2001). “Measurement of Productivity Changes: Two Malmquist Index Approaches.” JPA 16(2): 107-128.
- Ali IA and LM Seiford (1990). “Translation Invariance in Data Envelopment Analysis.” Operations Research Letters 9(6): 403-405.
- Aly HY, R Grabowski, C Pasurka and N Rangan (1990). “Technical, Scale, and Allocative Efficiencies in U.S. Banking: An Empirical Investigation.” Review of Economics and Statistics 72(2): 211-218.
- Alirezaee MR (2005). “The Overall Assurance Interval for the Non-Archimedean Epsilon in DEA Models; a Partition Base Algorithm.” Appl Math Comput 164(3): 667-674.
- Ambrose P (1998). “A Comparison of Data Envelopment Analysis and Genetic Algorithm Techniques for Efficiency Analysis: Implications for Information Systems Research.? in Proceedings of Effective Utilization and Management of Emerging Information Technologies, IDEA Group Publishing: 382-389.
- Alirezaee MR, M Howland and C van de Panne (1998). “Sampling Size and Efficiency Bias in Data Envelopment Analysis.” J Applied Mathematics and Decision Sciences 2: 51-64.
