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Review of Input Congestion Estimating Methods in DEA

Author

Listed:
  • Mohammad Khodabakhshi
  • Farhad Hosseinzadeh Lotfi
  • Kourosh Aryavash

Abstract

Congestion is an economic phenomenon in the production process where excessive amounts of the input cause a reduction of the output. The motivation of this paper is to investigate and compare the methods provided for estimating congestion in the DEA literature.

Suggested Citation

  • Mohammad Khodabakhshi & Farhad Hosseinzadeh Lotfi & Kourosh Aryavash, 2014. "Review of Input Congestion Estimating Methods in DEA," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnljam:v:2014:y:2014:i:1:n:963791
    DOI: 10.1155/2014/963791
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    References listed on IDEAS

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    1. Cooper, William W. & Seiford, Lawrence M. & Zhu, Joe, 2000. "A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 1-25, March.
    2. Noura, A.A. & Hosseinzadeh Lotfi, F. & Jahanshahloo, G.R. & Rashidi, S. Fanati & Parker, Barnett R., 2010. "A new method for measuring congestion in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 44(4), pages 240-246, December.
    3. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    4. Fare, Rolf & Svensson, Leif, 1980. "Congestion of Production Factors," Econometrica, Econometric Society, vol. 48(7), pages 1745-1753, November.
    5. Dervaux, Benoît & Kerstens, Kristiaan & Vanden Eeckaut, Philippe, 1998. "Radial and nonradial static efficiency decompositions: a focus on congestion measurement," Transportation Research Part B: Methodological, Elsevier, vol. 32(5), pages 299-312, June.
    6. A. T. Flegg & D. O. Allen, 2007. "Does Expansion Cause Congestion? The Case of the Older British Universities, 1994-2004," Education Economics, Taylor & Francis Journals, vol. 15(1), pages 75-102.
    7. Rolf Färe & Shawna Grosskopf, 2000. "Research Note. Decomposing Technical Efficiency with Care," Management Science, INFORMS, vol. 46(1), pages 167-168, January.
    8. Wei, Quanling & Yan, Hong, 2009. "Weak congestion in output additive data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 43(1), pages 40-54, March.
    9. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Weak and strong disposability vs. natural and managerial disposability in DEA environmental assessment: Comparison between Japanese electric power industry and manufacturing industries," Energy Economics, Elsevier, vol. 34(3), pages 686-699.
    10. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    11. Odeck, James, 2006. "Congestion, ownership, region of operation, and scale: Their impact on bus operator performance in Norway," Socio-Economic Planning Sciences, Elsevier, vol. 40(1), pages 52-69, March.
    12. Patricia Byrnes & Rolf Färe & Shawna Grosskopf & C. A. Knox Lovell, 1988. "The Effect of Unions on Productivity: U.S. Surface Mining of Coal," Management Science, INFORMS, vol. 34(9), pages 1037-1053, September.
    13. Cooper, W. W. & Seiford, L. M. & Zhu, J., 2001. "Slacks and congestion: response to a comment by R. Fare and S. Grosskopf," Socio-Economic Planning Sciences, Elsevier, vol. 35(3), pages 205-215, September.
    14. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    15. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    16. Brockett, Patrick L. & Cooper, William W. & Wang, Yuying & Shin, Hong-Chul, 1998. "Inefficiency and congestion in Chinese production before and after the 1978 economic reforms," Socio-Economic Planning Sciences, Elsevier, vol. 32(1), pages 1-20, March.
    17. Fare, Rolf & Grosskopf, Shawna, 2001. "When can slacks be used to identify congestion? An answer to W.W. Cooper, L. Seiford and J. Zhu," Socio-Economic Planning Sciences, Elsevier, vol. 35(3), pages 217-221, September.
    18. P. Byrnes & R. Färe & S. Grosskopf, 1984. "Measuring Productive Efficiency: An Application to Illinois Strip Mines," Management Science, INFORMS, vol. 30(6), pages 671-681, June.
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