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Article

RANKING EFFICIENT AND INEFFICIENT DECISION MAKING UNITS IN DATA ENVELOPMENT ANALYSIS

1 / 4 / 245-256 Pages

Author(s)

Rita Markovits-Somogyi - Budapest University of Technology and Economics, Department of Transport Economics, Bertalan L. u. 2, H-1111 Budapest, Hungary -


Abstract

Data envelopment analysis is a non-parametric linear programming method capable of the efficiency evaluation of decision making units (e.g. public transport companies). It is very often used in the transport sector for the efficiency assessment of airports, ports, railways and public transport companies. However, the original DEA method does not differentiate the efficient firms and thus, does not create full ranking. To overcome this problem, several methods have been developed with the aim of enlarging the distinguishing power of DEA. The present article aims to review these methods with a special emphasis on the ones elaborated in the last decade.


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Keywords:
data envelopment analysis; full ranking; different techniques;


Acknowledgements:

This work is connected to the scientific program of the “Development of qualityoriented and harmonized R+D+I strategy and functional model at BME” project. This project is supported by the New Széchenyi Plan Project ID: TÁMOP-4.2.1/B-09/1/KMR-2010-0002). This work is also related to the scientific content of the project “Modeling and multi-objective optimization based control of road traffic flow considering social and economical aspects” supported by program CNK 78168 of OTKA.


References:

Adler, N.; Berechman, J. 2001. Measuring Airport Quality from The Airlines’ Viewpoint: an Application of Data Envelopment Analysis, Transport Policy 8(3): 171-181.

 

Adler, N., Friedman, L., and Sinuany-Stern, Z. (2002). Review of ranking methods in the data envelopment analysis context. European Journal of Operations Research, 140: 249 - 265.

 

Alirezaee, M. R.; Afsharian, M. 2007. A Complete Ranking of DMUs Using Restrictions in DEA Models, Applied Mathematics and Computation 189(2): 1550-1559.

 

Andersen, A.; Petersen, C. N. 1993. A Procedure for Ranking Efficient Units in DEA, Management Science 39(10): 1261-1264.

 

Banker, R. D.; Das, S.; Datar, S. M. 1989. Analysis of Cost Variances for Management Control in Hospitals, Research in Governmental and Nonprofit Accounting 5: 268-91.

 

Banker, R. D.; Gifford, J. L. 1988. A Relative Efficiency Model for The Evaluation of Public Health Nurse Productivity. Pittsburgh: School of Urban and Public Affairs, Carnegie Mellon University.

 

Banker, R. D.; Morey, R. 1986. Efficiency Analysis for Exogenously Fixed Inputs and Outputs, Operations Research 34(4): 513–521.

 

Bardhan, I.; Bowlin, W. F.; Cooper, W. W.; Sueyoshi, T. 1996. Models and Measures for Efficiency Dominance in Data Envelopment Analysis. Part I: Additive Models and MED Measures, Journal of the Operations Research Society of Japan 39(3): 322–332.

 

Bazargan, M.; Vasigh, B. 2003. Size Versus Efficiency: A Case Study of US Commercial Airports, Journal of Air Transport Management 9(3): 187-193.

 

Charnes, A.; Cooper, W. W.; Rhodes, E. 1978.. Measuring The Efficiency of Decision Making Units, European Journal of Operational Research 3(4): 339-354.

 

Charnes, A.; Cooper, W. W.; Huang, Z. M.; Sun, D. B. 1990. Polyhedral Cone-Ratio DEA Models with an Illustrative Application to Large Commercial Banks, Journal of Econometrics 46(1-2): 73-91.

 

Chen, J. X.; Deng, M. 2011. A Cross-Dependence Based Ranking System for Efficient and Inefficient Units in DEA, Expert Systems with Applications, article in press, doi: 10.1016/j.eswa.2011.01.165.

 

Chen, Y. 2004. Ranking Efficient Units in DEA, Omega The International Journal of Management Science 32(2): 213- 219.

 

Chen, Y.; Sherman, H. D. 2004. The Benefits of Non-Radial vs. Radial Super-Efficiency DEA: an application to burden-sharing amongst NATO member nations, Socio-Economic Planning Sciences 38(4): 307-320.

 

Cooper, W. W.; Seiford, L. M.; Zhu, J. 2004. Handbook on Data Envelopment Analysis, International Series in Operations Research & Management Science 71: 593 p.

 

Doyle, J. R.; Green, R. 1994. Efficiency and Cross-Efficiency in Data Envelopment Analysis: Derivatives, Meanings and Uses, Journal of the Operational Research Society 45(5): 567-578.

 

Du, J.; Liang, L.; Zhu, J. 2010. A Slacks-Based Measure of Super-Efficiency in Data Envelopment Analysis: A Comment, European Journal of Operational Research 204(3): 694-697.

 

Friedman, L.; Sinuany-Stern, Z. 1997. Scaling Units via the Canonical Correlation Analysis and The Data Envelopment Analysis, European Journal of Operational Research 100(3): 629-637.

 

Guo, J.; Jia, L.; Qiu, L. 2006. Research on Supply Chain Performance Evaluation Based on DEA/AHP Model, in Proceedings of the 2006 IEEE Asia-Pacific Conference on Services Computing. (APSCC’06), 0-7695-2751-5/06.

 

Hibiki, N.; Sueyoshi, T. 1999. DEA Sensitivity Analysis by Changing a Reference Set: Regional Contribution to Japanese Industrial Development, Omega 27(2): 139-153.

 

Hirschhausen, C. V.; Cullmann, A. A. 2010. A Nonparametric Efficiency Analysis of German Public Transport Companies, Transportation Research Part E 46(3): 436-445.

 

Hougaard, J. L. 1999. Fuzzy Scores of Technical Efficiency, European Journal of Operational Research 115(3): 529-541.

 

Jahanshahloo, G. R.; Junior, H. V.; Lotfi, F. H.; Akbarian, D. 2007. A New DEA Ranking System Based on Changing the Reference Set, European Journal of Operational Research 181(1): 331-337.

 

Karsak, E. E. 1998. A Two-Phase Robot Selection Procedure, Production Planning and Control 9(7): 675-684.

 

Lee, H. S.; Chu, C. W.; Zhu, J. 2011. Super-Efficiency DEA in The Presence of Infeasibilty, European Journal of Operational Research, article in press, doi: 10.1016/j. ejor.2011.01.022.

 

Lotfi, F. H.; Jahanshahloo, G. R; Esmaeili, M. 2007. Sensitivity Analysis of Efficient Units in The Presence of Non-Discretionary Inputs, Applied Mathematics and Computation 190(2): 1185–1197.

 

Markovits-Somogyi, R. 2011a. Measuring Efficiency in Transport: The State of The Art of Applying Data Envelopment Analysis, Transport 26(1): 11-19.

 

Markovits-Somogyi, R. 2011b. Data Envelopment Analysis and its Key Variants Utilized in The Transport Sector, Periodica Polytechnica. Transportation Engineering, article in press.

 

Royendegh, B. D.; Erol, S. 2009. A DEA-ANP Hybrid Algorithm Approach to Evaluate a University’s Performance, International Journal of Basic & Applied Sciences 9(10): 115-129.

 

Seiford, L. M.; Zhu, J. 1999.. Infeasibility of Super-Efficiency Data Envelopment Analysis Models, Infor 37(2): 174-187.

 

Sexton, T. R.; Silkman, R. H.; Hogan, A. J. 1986. Data Envelopment Analysis: Critique and Extensions. in Measuring Efficiency: An Assessment of Data Envelopment Analysis. San Francisco: Jossey-Bass. 73-105.

 

Sinuany-Stern, Z.; Mehrez, A.; Barboy, A. 1994. Academic Departments Efficiency via Data Envelopment Analysis, Computers and Operations Research 21(5): 543-556.

 

Sinuany-Stern, Z.; Mehrez, A.; Hadad, Y. 2000. An AHP/DEA Methodology for Ranking Decision Making Units,International Transactions in Operational Research 7(2): 109-124.

 

Talluri, S.; Yoon, K. P. 2000.: A Cone-Ratio DEA Approach for AMT Justification, International Journal of Production Economics 66(2): 119-129.

 

Thompson, R. G.; Singleton, F. D.; Thrall, R. M.; Smith, B. A. 1986. Comparative Site Evaluations for Locating a High Energy Physics Laboratory in Texas, Interfaces 16(6): 35-49.

 

Tone, K. 2002. A Slacks-Based Measure of Super-Efficiency in Data Envelopment Analysis, European Journal of Operational Research 143(1): 32-41.

 

Torgersen, A. M.; Forsund, F. R.; Kittelsen, S. A. C. 1996. Slack-Adjusted Efficiency Measures and Ranking of Efficient Units, The Journal of Productivity Analysis 7(4): 379-398.

 

Troutt, M. D. 1995. A Maximum Decisional Efficiency Estimation Principle, Management Science 41(1): 76-82.

 

Wang, Y. M.; Luo, Y. 2011. Common Weights for Fully Ranking Decision Making Units by Regression Analysis, Expert Systems with Applications, article in press, doi: 10.1016/j.eswa.2011.01.004.

 

Wang, Y.-M., Luo, Y., & Liang, L. (2009a). Fuzzy data envelopment analysis based upon fuzzy arithmetic with an application to performance assessment of manufacturing enterprises. Expert Systems with Applications, 36(3): 5205–5211.

 

Wen, M.; Li, H. 2009. Fuzzy Data Envelopment Analysis (DEA): Model and Ranking Method, Journal of Computational and Applied Mathematics 223(2): 872-878.

 

Wu, Y. C. J.; Goh M. 2010. Container Port Efficiency in Emerging and More Advanced Countries, Transportation Research Part E 46(6): 1030-1042.

 

Zhang, H.; Li, X.; Liu, W. 2006. An AHP/DEA Methodology for 3PL Vendor Selection in 4PL, Lecture Notes in Computer Science 3865: 646-655.


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Related Keywords

EFFICIENCY MEASUREMENT OF DELIVERY POST OFFICES USING FUZZY DATA ENVELOPMENT ANALYSIS (POSSIBILITY APPROACH)