Skip to main content

Congestion

Its Identification and Management with DEA

  • Chapter
Handbook on Data Envelopment Analysis

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 71))

Abstract

Congestion is a term that is applicable in a variety of disciplines which range from medical science to traffic engineering. It also has many uses in practical everyday life. This brings with it a certain looseness in usage. We therefore expand (and refine) our discussion of congestion with reference to its use in economics where we have access to a precise meaning which we can develop in this chapter. This chapter covers the standard approaches used for treating congestion in DEA

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 74.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Balakrishnan, R. and N.S. Soderstrom, 2000, “The cost of system congestion: Evidence from the health care sector,” Journal of Management Accounting Research 12, 97–114.

    Google Scholar 

  2. Brockett, P.L., W.W. Cooper, H. Deng, L.L. Golden and T.W. Ruefli, 2003, “Using DEA to identify and manage congestion,” Journal of Productivity Analysis (submitted).

    Google Scholar 

  3. Brockett, P.L., W.W. Cooper, H.C. Shin and Y. Wang, 1998, “Inefficiency and congestion in Chinese production before and after the 1978 economic reforms,” Socio-Economic Planning Sciences, 32, 1–20.

    Article  Google Scholar 

  4. Charnes, A. and W.W. Cooper, 1961, Management Models and Industrial Applications of Linear Programming. John Wiley and Sons, Inc. New York.

    Google Scholar 

  5. Cherchye, L., T. Kuosmanen and T. Post, 2001, “Alternative treatments of congestion in DEA: A rejoinder to Cooper, Gu and Li,” European Journal of Operational Research 132, 75–80.

    MathSciNet  Google Scholar 

  6. Cooper, W.W., H. Deng, B. Gu, S. Li and R.M. Thrall, 2001a, “Using DEA to improve the management of congestion in Chinese industry (1981–1997)” Socio-Economic Planning Sciences 35, 1–16.

    Google Scholar 

  7. Cooper, W.W., H. Deng, Z. Huang and S.X. Li, 2003, “Chance Constrained Programming approaches to congestion in stochastic Data Envelopment Analysis.” European Journal of Operational Research, (to appear).

    Google Scholar 

  8. Cooper, W.W., H. Deng, Z. Huang and S.X. Li, 2002a, “A one-model approach to the analysis of congestion in Data Envelopment Analysis,” Socio-Economic Planning Sciences 36, 231–238.

    Article  Google Scholar 

  9. Cooper, W.W., H. Deng, Z. Huang and S.X. Li, 2002b, “Chance Constrained Programming approaches to technical efficiencies and inefficiencies in stochastic Data Envelopment Analysis.” Journal of the Operational Research Society, 53, 1–10.

    Article  Google Scholar 

  10. Cooper, W.W., B. Gu, and S. Li, 2001a, “Alternative treatments of congestion in DEA: A response to the Cherchye, Kuosmanen and Post critique,” European Journal of Operational Research 132 81–87.

    MathSciNet  Google Scholar 

  11. Cooper, W.W., B. Gu and S. Li, 2001b, “Comparisons and evaluations of alternative approaches to evaluating congestion in DEA,” European Journal of Operational Research 32/1, 1–13.

    Google Scholar 

  12. Cooper, W.W., K.S. Park and J.T. Pastor, 1999, “RAM: A range adjusted measure of inefficiency for use with additive models and relations to other models and measures in DEA”, Journal of Productivity Analysis, 11, 5–42.

    Article  Google Scholar 

  13. Cooper, W.W., L.M. Seiford and K. Tone, 2000, Data Envelopment Analysis: A Comprehensive Text with Uses, Example Applications, References and DEA-Solver Software. Kluwer Academic Publishers, Norwell, Mass.

    Google Scholar 

  14. Cooper, W.W., L.M. Seiford and J. Zhu, 2000, “A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA,” Socio-Economic Planning Sciences 34, 1–25.

    Article  Google Scholar 

  15. Cooper, W.W., L.M. Seiford and J. Zhu, 2001c, “Slacks and congestion: A response to comments by Färe and Grosskopf,” Socio-Economic Planning Sciences 35, 1–11.

    Google Scholar 

  16. Cooper, W.W., R.G. Thompson and R.M. Thrall, 1996, “Introduction: Extensions and new developments in DEA,” Annals of Operations Research 66, 3–45.

    MathSciNet  Google Scholar 

  17. Deng, H.H. (2003) Congestion and its management in Chinese production. Ph.D. Thesis, Austin, Texas: The Red McCombs School of Business, University of Texas at Austin. Also available from University Microfilms, Inc., Ann Arbor, Mich.

    Google Scholar 

  18. Färe, R. and S. Grosskopf, 1998, “Congestion: A note” Socio-Economic Planning Sciences 33, 21–23.

    Google Scholar 

  19. Färe, R. and S. Grosskopf, 2000a, “Congestion: A response,” Socio-Economic Planning Sciences 34, 35–50.

    Google Scholar 

  20. Färe, R. and S. Grosskopf, 1983, “Measuring congestion in production,” Zeitschrift Für Nationalökonomie 43, 251–271.

    Google Scholar 

  21. Färe, R. and S. Grosskopf, 2000b, “Slacks and congestion: A comment,” Socio-Economic Planning Sciences 34, 27–33.

    Google Scholar 

  22. Färe, R., S. Grosskopf and C.A.K. Lovell, 1994, Production Frontiers, Cambridge University Press, Cambridge, England.

    Google Scholar 

  23. Färe, R., S. Grosskopf and C.A.K. Lovell, 1985, The Measurement of Efficiencies of Production, Kluwer-Nihoff Publishing, Boston, Mass.

    Google Scholar 

  24. Färe, R., S. and L. Svensson, 1980, “Congestion of factors of production,” Econometrica 48 1743–1753.

    Google Scholar 

  25. Leibenstein, H., 1966, “Allocative efficiency vs. X-Efficiency,” American Economic Review 56, 392–415.

    Google Scholar 

  26. Leibenstein, H., 1976, Beyond Economic Man, Harvard University Press, Cambridge, Mass.

    Google Scholar 

  27. Samuelson, 1947, Foundations of Economics, Harvard University Press, Cambridge, Mass.

    Google Scholar 

  28. Seiford, L.M., 1994, “References” in A. Charnes, W.W. Cooper, and A.Y. Lewin eds, Data Envelopment Analysis: Theory, Methodology and Applications, Kluwer Academic Publisher, Norwell, Mass.

    Google Scholar 

  29. Stigler, G.J., 1976, “The X-istence of X-efficiency,” American Economic Review 66, 213–216.

    Google Scholar 

  30. Varian, H., 1984, Microeconomic Analysis, 2nd ed. W.W. Norton, Inc., New York, N.Y.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Kluwer Academic Publishers

About this chapter

Cite this chapter

Cooper, W.W., Deng, H., Seiford, L.M., Zhu, J. (2004). Congestion. In: Cooper, W.W., Seiford, L.M., Zhu, J. (eds) Handbook on Data Envelopment Analysis. International Series in Operations Research & Management Science, vol 71. Springer, Boston, MA. https://doi.org/10.1007/1-4020-7798-X_7

Download citation

  • DOI: https://doi.org/10.1007/1-4020-7798-X_7

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7797-5

  • Online ISBN: 978-1-4020-7798-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics