Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Non-parametric models for spatial efficiency

  • 125 Accesses

  • 17 Citations


This research develops a nonconvex model for measuring the spatial efficiency of siting decisions and demonstrates the virtues of such measurements in comparison to those of convex approaches. Working with a case study from the public sector, we develop relative spatial efficiency (RSE) models which access the sufficiency of a location decision in relation to a best practice decision on the efficient (or most accessible) frontier. The paper also compares the results of the nonconvex methodology with that of the convex model and suggests the strengths and weaknesses of each in terms of the type of support they offer to decisionmakers concerned with actual siting decisions.

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


  1. Adolphson, D., G. Cornia and L. Walters. (1991). “A Unified Framework for Classifying DEA Models.” In H. Bradley (ed.),Operational Research '90, Oxford: Pergamon Press, 647–657.

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

  3. Brill, E., S. Chang and L. Hopkins. (1982). “Modeling to Generate Alternatives: The HSJ Approach and an Illustration Using a Problem in Land Use Planning,”Management Science, 28, 221–235.

  4. Church, R. and D. Huber. (1979). “On Determining Many Close to Optimal Configurations for Single and Multiple Objective Location Problems.” Research Series No. 34, Department of Civil Engineering, University of Tenessee, Knoxville, July.

  5. Cohon, J. (1978).Multiobjective Programming and Planning, New York: Academic Press.

  6. Charnes, A., W.W. Cooper, B. Golany, L. Seiford, and J. Stutz. (1985). “Foundations of Data Envelopment Analysis for Pareto-Koopmans Efficient Empirical Production Functions,”Journal of Econometrics, 30 91–107.

  7. Charnes, A., W.W. Cooper, Z. Huang and D. Sun. (1990). “Polyhedral Cone-Ratio DEA Models with an Illustrative Application to Large Commercial Banks.”Journal of Econometrics, 46, 73–91.

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

  9. Deprins, D., L. Simar and H. Tulkens. (1984). “Measuring Labor Efficiency in Post Offices.” In Marchand, M., P. Pestieau and H. Tulkens. (eds.),The Performance of Public Enterprises Concepts and Measurement, Amsterdam: North-Holland.

  10. Desai, A. and J. Storbeck. (1990). “A Data Envelopment Analysis for Spatial Efficiency.”Computers, Environment and Urban Systems, 14, 145–156.

  11. Desai A., K. Haynes and J. Storbeck. (1995). “A Spatial Efficiency Framework, for the Support of Locational Decisions.” In A. Charnes, W.W. Cooper, A. Lewin and L. Seiford, (eds.),Data Envelopment Analysis: Theory, Methodology, and Applications, Kluwer Academic Publishers.

  12. Dyson, R. and E. Thanassoulis, (1988). “Reducing Weight Flexibility in Data Envelopment Analysis.”Journal of the Operational Research Society, 39, 563–576.

  13. Epstein, M. and J. Henderson. (1989). “Data, Envelopment Analysis for Managerial Control and Diagnosis.”Decision Sciences, 20, 90–119.

  14. Färe, R., S. Grosskopf and C.A.K. Lovell. (1985).The Measurement of Efficiency of Production, Boston: Kluwer Academic Publishers.

  15. Fisher, H. and G. Rushton. (1979). “Spatial Efficiency of Service Locations and the Regional Development Process.”Papers in the Regional Science Association, 42, 83–97.

  16. Ghosh, A. and S. McLafferty. (1987).Location Strategies for Retail and Service Firms, Lexington: Lexington Books.

  17. Grosskopf, S. (1986). “The Role of Reference Technology in Measuring Productive Efficiency.”Economic Journal, 96, 499–513.

  18. Haynes, K., T. Gulledge, H. Schroff, A. Desai and J. Storbeck. (1991). “Multiple Objective Programming for Siting Decisions Sensitivity: A DEA Approach.”Regional Science Review, 18, 71–80.

  19. Macmillan, W. (1986). “The Estimation and Application of Multi-Regional Economic Planning, Models Using Data Envelopment Analysis.”Papers of the Regional Science Association, 60, 41–57.

  20. Macmillan, W. (1987). “The Measurement of Efficiency in Multiunit Public Services.”Environment and Planning A, 19, 1511–1524.

  21. Petersen, N.C. (1990). “Data Envelopment Analysis on a Relaxed Set of Assumptions.”Management Science 36, (3), 305–314.

  22. Schilling, D., A. McGarity and C. ReVelle. (1982). “Hidden Attributes and the Display of Information in Multiobjective Analysis.”Management Science, 28, 236–242.

  23. The Warwick DEA Package V.6. (1992). c/o Thanassoulis, E., Warwick Business School, Warwick University, Coventry, UK.

  24. Thanassoulis, E. and R. Dyson. (1992). “Estimating Preferred Target Input-Output Levels Using Data Envelopment Analysis.”European Journal of Operational Research, 56, 80–97.

  25. Tulkens, H. (1993). “On FDH Efficiency Analysis: Some Methodological Issues and Applications to Retail Banking, Courts and Urban Transit.”Journal of Productivity Analysis, 4, 183–210.

Download references

Author information

Additional information

The authors express their gratitude to Professors, Knox Lovell, Gerard Rushton, and two anonymous referrees for their helpful comments on an earlier draft.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Athanassopoulos, A.D., Storbeck, J.E. Non-parametric models for spatial efficiency. J Prod Anal 6, 225–245 (1995). https://doi.org/10.1007/BF01076977

Download citation


  • Convexity
  • data envelopment analysis
  • disposability
  • spatial efficiency