Skip to main content
Log in

Explicit representation of the two-dimensional section of a production possibility set

  • Published:
Journal of Productivity Analysis Aims and scope Submit manuscript

Abstract

Technical and scale efficiencies of Data Envelope Analysis are associated with a two dimensionalsection (a convex set) representing the amounts by which the input and output vectors of a reference decision making unit, may be scaled and still lie in the production possibility set. We describe a simple algorithm, closely resembling the simplex algorithm of linear programming, to traverse the boundary of this set. Given the output of our algorithm, the scalar efficiency measures and return-to-scale characterization are trivially determined. Moreover, the set may be graphically displayed for any problem in any number of dimensions with only a minimum of additional computing effort.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Banker, R.D. (1984). “Estimating Most Productive Scale Size Using Data Envelope Analysis,”European Journal of Operations Research, 17, 35–44.

    Google Scholar 

  • Banker, R.D., A. Charnes, and W.W. Cooper (1984). “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis.”Management Science, 30., 1078–1092.

    Google Scholar 

  • Banker, R.D., Thrall, R.M. (1992). “Estimation of Returns to Scale Using Data Envelopment Analysis.”European Journal of Operational Research, 62, 74–84.

    Google Scholar 

  • E.R. Barnes, A.J. Hoffman and Uriel G. Rothblum. (1992). “Optimal Partitions having Disjoint Convex and Conic Hulls.”Mathematical Programming, 54, 69–86.

    Google Scholar 

  • Byrnes, P., R. Fare and S. Grosskopf. (1984). “Measuring Productive Efficiency: an Application to Illinois Strip Mines.”Management Science, 30, 671–680.

    Google Scholar 

  • Charnes, A. (1952). “Optimality and Degeneracy in Linear Programming.”Econometrica 20, 160–170.

    Google Scholar 

  • Charnes, A., W.W. Cooper and E. Rhodes. (1978). “Measuring the Efficiency of Decision Making Units.”European Journal of Operations Research 2, 429–444.

    Google Scholar 

  • Charnes, A., W.W. Cooper, and R.M. Thrall. (1986). “Classifying and Characterizing Efficiencies and Inefficiencies in Data Envelopment Analysis”.Operations Research Letters., 105–110.

  • Charnes, A., W.W. Cooper, and R.M. Thrall. (1991). “A Structure of Characterizing and Classifying Efficiencies and Inefficiencies in Data Envelopment Analysis,”The Journal of Productivity Analysis, 2, 197–237.

    Google Scholar 

  • Charnes, A., W.W. Cooper, Q.L. Wei, and Z.M. Huang. (1987). “Cone Ratio Data Envelope Analysis and Multi-Objective Programming.” Research Report CCS559, Center for Cybernetic Studies, The University of Texas at Austin.

  • Thompson, R.G., F.D. Singleton, R.M. Thrall and B.A. Smith. (1986). “Comparative Site Evaluations for Locating a High-Energy Lab in Texas,”Interfaces, 16, 35–49.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hackman, S.T., Passy, U. & Platzman, L.K. Explicit representation of the two-dimensional section of a production possibility set. J Prod Anal 5, 161–170 (1994). https://doi.org/10.1007/BF01073852

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF01073852

Keywords

Navigation