EDP Sciences logo
Subscriber Authentication Point
Search
Menu
All issues Volume 56 / No 3 (May-June 2022) RAIRO-Oper. Res., 56 3 (2022) 1293-1319 References
Open Access
Issue
RAIRO-Oper. Res.
Volume 56, Number 3, May-June 2022
Page(s) 1293 - 1319
DOI https://doi.org/10.1051/ro/2022056
Published online 02 June 2022
  • T.R. Anderson, K. Hollingsworth and L. Inman, The fixed weighting nature of a cross-evaluation model. J. Prod. Anal. 17 (2002) 249–255. [CrossRef] [Google Scholar]
  • L. Angulo-Meza and M.P.E. Lins, Review of methods for increasing discrimination in data envelopment analysis. Ann. Oper. Res. 116 (2002) 225–242. [CrossRef] [MathSciNet] [Google Scholar]
  • H. Azizi, The interval efficiency based on the optimistic and pessimistic points of view. Appl. Math. Modell. 35 (2011) 2384–2393. [CrossRef] [Google Scholar]
  • H. Azizi and R. Jahed, Improved data envelopment analysis models for evaluating interval efficiencies of decision-making units. Comput. Ind. Eng. 61 (2011) 897–901. [CrossRef] [Google Scholar]
  • T. Badiezadeh, R.F. Saen and T. Samavati, Assessing sustainability of supply chains by double frontier network DEA: a big data approach. Comput. Oper. Res. 98 (2018) 284–290. [CrossRef] [MathSciNet] [Google Scholar]
  • A.Y. Chang, Prioritising the types of manufacturing flexibility in an uncertain environment. Int. J. Prod. Res. 50 (2012) 2133–2149. [CrossRef] [Google Scholar]
  • A. Charnes, W.W. Cooper and E. Rhodes, Measuring the efficiency of decision-making units. Eur. J. Oper. Res. 2 (1978) 429–444. [Google Scholar]
  • W.D. Cook, K. Tone and J. Zhu, Data envelopment analysis: prior to choosing a model. Omega 44 (2014) 1–4. [Google Scholar]
  • W.W. Daniel, Applied Nonparametric Statistics. Houghton Mifflin, Boston (1978). [Google Scholar]
  • J. Doyle and R. Green, Efficiency and cross-efficiency in DEA: derivations, meanings and uses. J. Oper. Res. Soc. 45 (1994) 567–578. [CrossRef] [Google Scholar]
  • A. Ebrahimnejad, Cost efficiency measures with trapezoidal fuzzy numbers in data envelopment analysis based on ranking functions: application in insurance organization and hospital. Int. J. Fuzzy Syst. App. (IJFSA) 2 (2012) 51–68. [Google Scholar]
  • A. Ebrahimnejad and F.H. Lotfi, Equivalence relationship between the general combined-oriented CCR model and the weighted minimax MOLP formulation. J. King Saud Univ.-Sci. 24 (2012) 47–54. [CrossRef] [Google Scholar]
  • T. Entani and H. Tanaka, Interval estimations of global weights in AHP by upper approximation. Fuzzy Sets Syst. 158 (2007) 1913–1921. [CrossRef] [Google Scholar]
  • T. Entani, Y. Maeda and H. Tanaka, Dual models of interval DEA and its extension to interval data. Eur. J. Oper. Res. 136 (2002) 32–45. [Google Scholar]
  • G. Gan, H.S. Lee, L. Lee, X. Wang and Q. Wang, Network hierarchical DEA with an application to international shipping industry in Taiwan. J. Oper. Res. Soc. 71 (2020) 991–1002. [CrossRef] [Google Scholar]
  • A. Hatami-Marbini, S. Saati and M. Tavana, An ideal-seeking fuzzy data envelopment analysis framework. Appl. Soft Comput. 10 (2010) 1062–1070. [Google Scholar]
  • A. Hatami-Marbini, A. Ebrahimnejad and S. Lozano, Fuzzy efficiency measures in data envelopment analysis using lexicographic multiobjective approach. Comput. Ind. Eng. 105 (2017) 362–376. [CrossRef] [Google Scholar]
  • Y. Huang, Y.M. Wang and J. Lin, Two-stage fuzzy cross-efficiency aggregation model using a fuzzy information retrieval method. Int. J. Fuzzy Syst. 21 (2019) 2650–2666. [CrossRef] [Google Scholar]
  • A. Jahan, F. Mustapha, S.M. Sapuan, M.Y. Ismail and M. Bahraminasab, A framework for weighting of criteria in ranking stage of material selection process. Int. J. Adv. Manuf. Technol. 58 (2012) 411–420. [CrossRef] [Google Scholar]
  • D. Julong, Introduction to grey system theory. J. Grey Syst. 1 (1989) 1–24. [Google Scholar]
  • C. Kao and S.N. Hwang, Efficiency decomposition in two-stage data envelopment analysis: an application to non-life insurance companies in Taiwan. Eur. J. Oper. Res. 185 (2008) 418–429. [Google Scholar]
  • C. Kao and S.T. Liu, Cross efficiency measurement and decomposition in two basic network systems. Omega 83 (2019) 70–79. [CrossRef] [Google Scholar]
  • M. Khodabakhshi and K. Aryavash, The cross-efficiency in the optimistic–pessimistic framework. Oper. Res. 17 (2017) 619–632. [Google Scholar]
  • M.D. Kremantzis, P. Beullens and J. Klein, A fairer assessment of DMUs in a generalised two-stage DEA structure. Expert Syst. App. 187 (2022) 115921. [CrossRef] [Google Scholar]
  • Y. Kuo, T. Yang and G.W. Huang, The use of grey relational analysis in solving multiple attribute decision-making problems. Comput. Ind. Eng. 55 (2008) 80–93. [CrossRef] [Google Scholar]
  • F. Li, Q. Zhu, Z. Chen and H. Xue, A balanced data envelopment analysis cross-efficiency evaluation approach. Expert Syst. App. 106 (2018) 154–168. [CrossRef] [Google Scholar]
  • F. Li, H. Wu, Q. Zhu, L. Liang and G. Kou, Data envelopment analysis cross efficiency evaluation with reciprocal behaviors. Ann. Oper. Res. 302 (2021) 173–210. [CrossRef] [MathSciNet] [Google Scholar]
  • L. Liang, J. Wu, W.D. Cook and J. Zhu, Alternative secondary goals in DEA cross-efficiency evaluation. Int. J. Prod. Econ. 113 (2008) 1025–1030. [CrossRef] [Google Scholar]
  • W. Liu and Y.M. Wang, Ranking DMUs by using the upper and lower bounds of the normalized efficiency in data envelopment analysis. Comput. Ind. Eng. 125 (2018) 135–143. [CrossRef] [Google Scholar]
  • F.H. Lotfi, G.R. Jahanshahloo, A. Ebrahimnejad, M. Soltanifar and S.M. Mansourzadeh, Target setting in the general combined-oriented CCR model using an interactive MOLP method. J. Comput. Appl. Math. 234 (2010) 1–9. [CrossRef] [MathSciNet] [Google Scholar]
  • F.H. Lotfi, G.R. Jahanshahloo, M. Soltanifar, A. Ebrahimnejad and S.M. Mansourzadeh, Relationship between MOLP and DEA based on output-orientated CCR dual model. Expert Syst. App. 37 (2010) 4331–4336. [CrossRef] [Google Scholar]
  • C. Ma, D. Liu, Z. Zhou, W. Zhao and W. Liu, Game cross efficiency for systems with two-stage structures. J. Appl. Math. 2014 (2014) 8. [Google Scholar]
  • F. Meng and B. Xiong, Logical efficiency decomposition for general two-stage systems in view of cross efficiency. Eur. J. Oper. Res. 294 (2022) 622–632. [Google Scholar]
  • H.H. Örkcü, V.S. Özsoy, M. Örkcü and H. Bal, A neutral cross efficiency approach for basic two stage production systems. Expert Syst. App. 125 (2019) 333–344. [CrossRef] [Google Scholar]
  • H.H. Örkcü, V.S. Özsoy, M. Örkcü and H. Bal, An optimistic-pessimistic DEA model based on game cross efficiency approach. RAIRO: Oper. Res. 54 (2020) 1215–1230. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • P. Peykani, F. Hosseinzadeh Lotfi, S.J. Sadjadi, A. Ebrahimnejad and E. Mohammadi, Fuzzy chance-constrained data envelopment analysis: a structured literature review, current trends, and future directions. Fuzzy Optim. Decision Making 21 (2022) 197–261. [CrossRef] [MathSciNet] [Google Scholar]
  • S.A. Rakhshan, Efficiency ranking of decision making units in data envelopment analysis by using TOPSIS-DEA method. J. Oper. Res. Soc. 68 (2017) 906–918. [CrossRef] [Google Scholar]
  • J. Rezaei, Best-worst multi-criteria decision-making method: some properties and a linear model. Omega 64 (2016) 126–130. [CrossRef] [Google Scholar]
  • T.L. Saaty and L.G. Vargas, The analytic network process. In: Decision Making with the Analytic Network Process. Springer, Boston, MA (2013) 1–40. [Google Scholar]
  • F.J. Santos Arteaga, A. Ebrahimnejad and A. Zabihi, A new approach for solving intuitionistic fuzzy data envelopment analysis problems. Fuzzy Optim. Model. J. 2 (2021) 46–56. [Google Scholar]
  • F. Sarraf and S.H. Nejad, Improving performance evaluation based on balanced scorecard with grey relational analysis and data envelopment analysis approaches: case study in water and wastewater companies. Eval. Program Planning 79 (2020) 101762. [CrossRef] [Google Scholar]
  • T.R. Sexton, R.H. Silkman and A.J. Hogan, Data envelopment analysis: critique and extensions. New Directions Program Eval. 1986 (1986) 73–105. [CrossRef] [Google Scholar]
  • K. Sugihara, H. Ishii and H. Tanaka, Interval priorities in AHP by interval regression analysis. Eur. J. Oper. Res. 158 (2004) 745–754. [CrossRef] [Google Scholar]
  • M. Tavana, A. Ebrahimnejad, F.J. Santos-Arteaga, S.M. Mansourzadeh and R.K. Matin, A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia. Soc. Econ. Planning Sci. 61 (2018) 70–89. [CrossRef] [Google Scholar]
  • M. Toloo and T. Tichý, Two alternative approaches for selecting performance measures in data envelopment analysis. Measurement 65 (2015) 29–40. [CrossRef] [Google Scholar]
  • Y.M. Wang and K.S. Chin, A neutral DEA model for cross-efficiency evaluation and its extension. Expert Syst. App. 37 (2010) 3666–3675. [CrossRef] [Google Scholar]
  • Y.M. Wang and T.M. Elhag, A goal programming method for obtaining interval weights from an interval comparison matrix. Eur. J. Oper. Res. 177 (2007) 458–471. [CrossRef] [Google Scholar]
  • Y.M. Wang and Y. Luo, DEA efficiency assessment using ideal and anti-ideal decision-making units. Appl. Math. Comput. 173 (2006) 902–915. [MathSciNet] [Google Scholar]
  • Y.M. Wang and J.B. Yang, Measuring the performances of decision-making units using interval efficiencies. J. Comput. Appl. Math. 198 (2007) 253–267. [CrossRef] [MathSciNet] [Google Scholar]
  • Y.M. Wang, K.S. Chin and J.B. Yang, Measuring the performances of decision-making units using geometric average efficiency. J. Oper. Res. Soc. 58 (2007) 929–937. [CrossRef] [Google Scholar]
  • D. Wu, A note on DEA efficiency assessment using ideal point: an improvement of Wang and Luo’s model. Appl. Math. Comput. 183 (2006) 819–830. [MathSciNet] [Google Scholar]
  • J. Wu, J. Chu, J. Sun, Q. Zhu and L. Liang, Extended secondary goal models for weights selection in DEA cross-efficiency evaluation. Comput. Ind. Eng. 93 (2016) 143–151. [Google Scholar]
  • F. Yang, S. Ang, Q. Xia and C. Yang, Ranking DMUs by using interval DEA cross efficiency matrix with acceptability analysis. Eur. J. Oper. Res. 223 (2012) 483–488. [CrossRef] [Google Scholar]
  • L. Zhang and K. Chen, Hierarchical network systems: an application to high-technology industry in China. Omega 82 (2019) 118–131. [CrossRef] [Google Scholar]
  • Z. Zhou, L. Sun, W. Yang, W. Liu and C. Ma, A bargaining game model for efficiency decomposition in the centralized model of two-stage systems. Comput. Ind. Eng. 64 (2013) 103–108. [CrossRef] [Google Scholar]
  • J. Zhu, Data Envelopment Analysis: A Handbook of Models and Methods. Vol. 221. Springer, (2015). [Google Scholar]
  • Q. Zhu, F. Li, J. Wu and J. Sun, Cross-efficiency evaluation in data envelopment analysis based on the perspective of fairness utility. Comput. Ind. Eng. 151 (2021) 106926. [CrossRef] [Google Scholar]
  • H.J. Zimmermann, Fuzzy Set Theory – And Its Applications. Springer Science & Business Media (2011). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.