Ranking Intervals and Dominance Relations for Ratio-Based Efficiency Analysis

Published Online:https://doi.org/10.1287/mnsc.1100.1265

References

  • Ahn T., Charnes A., Cooper W. W. Some statistical and DEA evaluations of relative efficiencies of public and private institutions of public and private institutions of higher learning. Socio-Econom. Planning Sci. (1988) 22(6):259–269CrossrefGoogle Scholar
  • Allen R., Athanassopoulos A., Dyson R. G., Thanassoulis E. Weight restrictions and value judgements in data envelopment analysis: Evolution, development and future directions. Ann. Oper. Res. (1997) 73:13–34CrossrefGoogle Scholar
  • Andersen P., Petersen N. C. A procedure for ranking efficient units in DEA. Management Sci. (1993) 39(10):1261–1264LinkGoogle Scholar
  • Avkiran N. K., Parker B. R. Pushing the DEA research envelope. Socio-Econom. Planning Sci. (2010) 44(1):1–7CrossrefGoogle Scholar
  • Baker R. C., Talluri S. A closer look at the use of data envelopment analysis for technology selection. Comput. Indust. Engrg. (1997) 32(1):101–108CrossrefGoogle Scholar
  • Belton V., Gear T. On a shortcoming of Saaty's method of analytic hierarchies. Omega (1983) 11(3):228–230CrossrefGoogle Scholar
  • Bouyssou D. Using DEA as a tool for MCDM: Some remarks. J. Oper. Res. Soc. (1999) 50(9):974–978CrossrefGoogle Scholar
  • Charnes A., Cooper W. W., Rhodes E. Measuring the efficiency of decision making units. Eur. J. Oper. Res. (1978) 2(6):429–444CrossrefGoogle Scholar
  • Charnes A., Cooper W. W., Huang Z. M., Sun D. B. Polyhedral cone-ratio DEA models with an illustrative application to large commercial banks. J. Econometrics (1990) 46(1–2):73–91CrossrefGoogle Scholar
  • Cook W. D., Zhu J. CAR-DEA: Context-dependent assurance regions in DEA. Oper. Res. (2008) 56(1):69–78LinkGoogle Scholar
  • Cooper W. W., Seiford M., Tone K.Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software (2007) 2nd ed.(Springer, New York) Google Scholar
  • Doyle J., Green R. Efficiency and cross-efficiency in DEA: Derivations, meanings and uses. J. Oper. Res. Soc. (1994) 45(5):567–578CrossrefGoogle Scholar
  • Dyer J. S. Remarks on the analytic hierarchy process. Management Sci. (1990) 36(3):249–258LinkGoogle Scholar
  • Dyson R. G., Allen R., Camanho A. S., Podinovski V. V., Sarrico C. S., Shale E. A. Pitfalls and protocols in DEA. Eur. J. Oper. Res. (2001) 132(2):245–259CrossrefGoogle Scholar
  • Eilat H., Golany B., Shtub A. R&D project evaluation: An integrated DEA and balanced scorecard approach. Omega (2008) 36(5):895–912CrossrefGoogle Scholar
  • Emrouznejada A., Barnett B. R., Tavares G. Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. Socio-Econom. Planning Sci. (2008) 42(3):151–157CrossrefGoogle Scholar
  • Farzipoor S. R. Technology selection in the presence of imprecise data, weight restrictions, and nondiscretionary factors. Internat. J. Adv. Manufacturing Tech. (2009) 41(7–8):827–838CrossrefGoogle Scholar
  • Galagedera D. U. A., Silvapulle P. Experimental evidence on robustness of DEA. J. Oper. Res. Soc. (2003) 54(6):654–660CrossrefGoogle Scholar
  • Garcia F., Marcuello C., Serrano D., Urbina O. Evaluation of efficiency in primary health care centres: An application of data envelopment analysis. Financial Accountability Management (2002) 51(1):67–83Google Scholar
  • Gouveia M. C., Dias L. C., Antunes C. H. Additive DEA based on MCDA with imprecise information. J. Oper. Res. Soc. (2008) 59(1):54–63CrossrefGoogle Scholar
  • Halme M., Korhonen P. Restricting weights in value efficiency analysis. Eur. J. Oper. Res. (2000) 126(1):175–188CrossrefGoogle Scholar
  • Halme M., Joro T., Korhonen P., Salo S., Wallenius J. A value efficiency approach to incorporating preference information in data envelopment analysis. Management Sci. (1999) 45(1):103–115LinkGoogle Scholar
  • Hollingsworth B., Dawson P. J., Maniadakis N. Efficiency measurement of health care: A review of non-parametric methods and applications. Health Care Management Sci. (1999) 2(3):161–172CrossrefGoogle Scholar
  • Johnes J. Data envelopment analysis and its application to the measurement of efficiency in higher education. Econom. Ed. Rev. (2006) 25(3):273–288CrossrefGoogle Scholar
  • Joro T., Korhonen P., Wallenius J. Structural comparison of data envelopment analysis and multiple objective linear programming. Management Sci. (1998) 44(7):962–970LinkGoogle Scholar
  • Korhonen P., Soismaa M., Siljamäki A. On the use of value efficiency analysis and some further developments. J. Productivity Anal. (2002) 17(1–2):49–64CrossrefGoogle Scholar
  • Korhonen P., Tainio R., Wallenius J. Value efficiency analysis of academic research. Eur. J. Oper. Res. (2001) 130(1):121–132CrossrefGoogle Scholar
  • Köksalan M., Büyükbaşaran T., Özpeynirci Ö., Wallenius J. A flexible approach to ranking with an application to MBA programs. Eur. J. Oper. Res. (2010) 201(2):470–476CrossrefGoogle Scholar
  • Liu N. C., Cheng Y. The academic ranking of world universities. Higher Ed. Eur. (2005) 30(2):127–316CrossrefGoogle Scholar
  • Ozcan Y. A.Health Care Benchmarking and Evaluation: An Assessment Using Data Envelopment Analysis (2008) (Springer, New York) Google Scholar
  • Podinovski V. V. DEA models for the explicit maximization of relative efficiency. Eur. J. Oper. Res. (2001) 131(3):572–586CrossrefGoogle Scholar
  • Podinovski V. V. The explicit role of weight bounds in models of data envelopment analysis. J. Oper. Res. Soc. (2005) 56(12):1408–1481CrossrefGoogle Scholar
  • Salo A. Interactive decision aiding for group decision support. Eur. J. Oper. Res. (1995) 84(1):134–149CrossrefGoogle Scholar
  • Salo A., Hämäläinen R. P. Preference assessment by imprecise ratio statements. Oper. Res. (1992) 40(6):1053–1061LinkGoogle Scholar
  • Salo A., Hämäläinen R. P. On the measurement of preferences in the analytic hierarchy process. J. Multi-Criteria Decision Anal. (1997) 6(6):309–319CrossrefGoogle Scholar
  • Salo A., Hämäläinen R. P. Preference ratios in multiattribute evaluation (PRIME)—Elicitation and decision procedures under incomplete information. IEEE Trans. Systems, Man, Cybernetics (2001) 31(6):533–545CrossrefGoogle Scholar
  • Sarrico S. C., Dyson R. G. Using DEA for planning in UK universities—An institutional perspective. J. Oper. Res. Soc. (2000) 51(7):789–800Google Scholar
  • Seiford L. M., Zhu J. Sensitivity analysis of DEA models for simultaneous changes in all of the data. J. Oper. Res. Soc. (1998a) 49(10):1060–1071Google Scholar
  • Seiford L. M., Zhu J. Stability regions for maintaining efficiency in data envelopment analysis. Eur. J. Oper. Res. (1998b) 108(1):127–139CrossrefGoogle Scholar
  • Sexton T. R., Silkman R. H., Hogan A., Silkman R. H. Data envelopment analysis: Critique and extensions. Measuring the Efficiency: An Assessment of Data Envelopment Analysis (1986) (American Evaluation Association, Jossey Bass Inc., San Francisco) 73–104Google Scholar
  • Shafer S. M., Bradford J. W. Efficiency measurements of alternate machine component grouping solutions via data envelopment analysis. IEEE Trans. Engrg. Management (1995) 42(2):159–165CrossrefGoogle Scholar
  • Stewart T. J. Relationships between data envelopment analysis and multicriteria decision analysis. J. Oper. Res. Soc. (1996) 47(5):654–665Google Scholar
  • Talluri S., Yoon K. P. A cone-ratio DEA approach for AMT justification. Internat. J. Production Econom. (2000) 66(2):119–129CrossrefGoogle Scholar
  • Tauer L. W., Fried H. O., Fry W. E. Measuring efficiencies of academic departments within a college. Ed. Econom. (2007) 15(4):473–489Google Scholar
  • Thanassoulis E., Portela M. C., Allen R., Cooper W. W., Seiford L. M., Zhu J. Incorporating value judgements in DEA. Handbook on Data Envelopment Analysis (2004) (Kluwer, Boston) 99–137Google Scholar
  • Thompson R. G., Singleton F., Thrall R., Smith B. Comparative site evaluations for locating a high-energy physics lab in Texas. Interfaces (1986) 16(6):35–49LinkGoogle Scholar
  • Thompson R. G., Langemeier L. N., Lee C. T., Lee E., Thrall R. M. The role of multiplier bounds in efficiency analysis with application to Kansas farming. J. Econometrics (1990) 46(1–2):93–108CrossrefGoogle Scholar
  • Zhu J. Robustness of the efficient DMUs in data envelopment analysis. Eur. J. Oper. Res. (1996) 90(3):451–460CrossrefGoogle Scholar
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