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Projections Onto Efficient Frontiers: Theoretical and Computational Extensions to DEA

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  1. Juan Aparicio & Jesus T. Pastor & Jose L. Sainz-Pardo & Fernando Vidal, 2020. "Estimating and decomposing overall inefficiency by determining the least distance to the strongly efficient frontier in data envelopment analysis," Operational Research, Springer, vol. 20(2), pages 747-770, June.
  2. Aparicio, Juan & Cordero, Jose M. & Pastor, Jesus T., 2017. "The determination of the least distance to the strongly efficient frontier in Data Envelopment Analysis oriented models: Modelling and computational aspects," Omega, Elsevier, vol. 71(C), pages 1-10.
  3. Aparicio, Juan & Garcia-Nove, Eva M. & Kapelko, Magdalena & Pastor, Jesus T., 2017. "Graph productivity change measure using the least distance to the pareto-efficient frontier in data envelopment analysis," Omega, Elsevier, vol. 72(C), pages 1-14.
  4. J. Vakili & R. Sadighi Dizaji, 2021. "The closest strong efficient targets in the FDH technology: an enumeration method," Journal of Productivity Analysis, Springer, vol. 55(2), pages 91-105, April.
  5. Fukuyama, Hirofumi & Maeda, Yasunobu & Sekitani, Kazuyuki & Shi, Jianming, 2014. "Input–output substitutability and strongly monotonic p-norm least distance DEA measures," European Journal of Operational Research, Elsevier, vol. 237(3), pages 997-1007.
  6. Ke Wang & Yujiao Xian & Chia-Yen Lee & Yi-Ming Wei & Zhimin Huang, 2019. "On selecting directions for directional distance functions in a non-parametric framework: a review," Annals of Operations Research, Springer, vol. 278(1), pages 43-76, July.
  7. Juan Aparicio & Magdalena Kapelko & Juan F. Monge, 2020. "A Well-Defined Composite Indicator: An Application to Corporate Social Responsibility," Journal of Optimization Theory and Applications, Springer, vol. 186(1), pages 299-323, July.
  8. Fangqing Wei & Junfei Chu & Jiayun Song & Feng Yang, 2019. "A cross-bargaining game approach for direction selection in the directional distance function," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(3), pages 787-807, September.
  9. Paradi, Joseph C. & Zhu, Haiyan & Edelstein, Barak, 2012. "Identifying managerial groups in a large Canadian bank branch network with a DEA approach," European Journal of Operational Research, Elsevier, vol. 219(1), pages 178-187.
  10. Suzuki, Soushi & Nijkamp, Peter, 2016. "An evaluation of energy-environment-economic efficiency for EU, APEC and ASEAN countries: Design of a Target-Oriented DFM model with fixed factors in Data Envelopment Analysis," Energy Policy, Elsevier, vol. 88(C), pages 100-112.
  11. Aparicio, Juan & Pastor, Jesus T., 2014. "Closest targets and strong monotonicity on the strongly efficient frontier in DEA," Omega, Elsevier, vol. 44(C), pages 51-57.
  12. Mustapha Daruwana Ibrahim & Sahand Daneshvar & Hüseyin Güden & Bela Vizvari, 2020. "Target setting in data envelopment analysis: efficiency improvement models with predefined inputs/outputs," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1319-1336, December.
  13. Subhash C. Ray, 2005. "Shadow Profit Maximization and a Generalized Measure of Inefficiency," Working papers 2005-14, University of Connecticut, Department of Economics.
  14. Hirofumi Fukuyama & Hiroya Masaki & Kazuyuki Sekitani & Jianming Shi, 2014. "Distance optimization approach to ratio-form efficiency measures in data envelopment analysis," Journal of Productivity Analysis, Springer, vol. 42(2), pages 175-186, October.
  15. Frances X. Frei & Ravi Kalakota & Andrew J. Leone & Leslie M. Marx, 1999. "Process Variation as a Determinant of Bank Performance: Evidence from the Retail Banking Study," Management Science, INFORMS, vol. 45(9), pages 1210-1220, September.
  16. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
  17. S Lozano & G Villa, 2005. "Determining a sequence of targets in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(12), pages 1439-1447, December.
  18. Washio, Satoshi & Yamada, Syuuji & Tanaka, Tamaki & Tanino, Tetsuzo, 2012. "Improvements by analyzing the efficient frontier in DEA," European Journal of Operational Research, Elsevier, vol. 217(1), pages 173-184.
  19. Mette Asmild & Tomas Baležentis & Jens Leth Hougaard, 2016. "Multi-directional productivity change: MEA-Malmquist," Journal of Productivity Analysis, Springer, vol. 46(2), pages 109-119, December.
  20. Zhu, Qingyuan & Aparicio, Juan & Li, Feng & Wu, Jie & Kou, Gang, 2022. "Determining closest targets on the extended facet production possibility set in data envelopment analysis: Modeling and computational aspects," European Journal of Operational Research, Elsevier, vol. 296(3), pages 927-939.
  21. Lozano, Sebastián & Calzada-Infante, Laura, 2018. "Computing gradient-based stepwise benchmarking paths," Omega, Elsevier, vol. 81(C), pages 195-207.
  22. Fangqing Wei & Yanan Fu & Feng Yang & Chun Sun & Sheng Ang, 2023. "Closest target setting with minimum improvement costs considering demand and resource mismatches," Operational Research, Springer, vol. 23(3), pages 1-29, September.
  23. Karima Kourtit & Peter Nijkamp & Soushi Suzuki, 2023. "Quantitative performance assessment of Asian stellar cities by a DEA cascade system: a capability interpretation," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 70(1), pages 259-286, February.
  24. Kao, Chiang, 2022. "Closest targets in the slacks-based measure of efficiency for production units with multi-period data," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1042-1054.
  25. J. Vakili, 2017. "New Models for Computing the Distance of DMUs to the Weak Efficient Boundary of Convex and Nonconvex PPSs in DEA," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(06), pages 1-20, December.
  26. Ando, Kazutoshi & Minamide, Masato & Sekitani, Kazuyuki & Shi, Jianming, 2017. "Monotonicity of minimum distance inefficiency measures for Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 260(1), pages 232-243.
  27. Amineh Ghazi & Farhad Hosseinzadeh Lotfı & Masoud Sanei, 2022. "Finding the strong efficient frontier and strong defining hyperplanes of production possibility set using multiple objective linear programming," Operational Research, Springer, vol. 22(1), pages 165-198, March.
  28. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
  29. Juan Aparicio & José Ruiz & Inmaculada Sirvent, 2007. "Closest targets and minimum distance to the Pareto-efficient frontier in DEA," Journal of Productivity Analysis, Springer, vol. 28(3), pages 209-218, December.
  30. Lozano, Sebastián & Khezri, Somayeh, 2021. "Network DEA smallest improvement approach," Omega, Elsevier, vol. 98(C).
  31. Subhash Ray, 2007. "Shadow profit maximization and a measure of overall inefficiency," Journal of Productivity Analysis, Springer, vol. 27(3), pages 231-236, June.
  32. Krüger, Jens J., 2018. "Direct targeting of efficient DMUs for benchmarking," International Journal of Production Economics, Elsevier, vol. 199(C), pages 1-6.
  33. Lee, Chia-Yen, 2014. "Meta-data envelopment analysis: Finding a direction towards marginal profit maximization," European Journal of Operational Research, Elsevier, vol. 237(1), pages 207-216.
  34. Javad Vakili & Hanieh Amirmoshiri & Rashed Khanjani Shiraz & Hirofumi Fukuyama, 2020. "A modified distance friction minimization approach in data envelopment analysis," Annals of Operations Research, Springer, vol. 288(2), pages 789-804, May.
  35. Sebastián Lozano & Gabriel Villa, 2010. "Gradual technical and scale efficiency improvement in DEA," Annals of Operations Research, Springer, vol. 173(1), pages 123-136, January.
  36. Walter Briec & Hervé Leleu, 2003. "Dual Representations of Non-Parametric Technologies and Measurement of Technical Efficiency," Journal of Productivity Analysis, Springer, vol. 20(1), pages 71-96, July.
  37. Gonzalez, Eduardo & Alvarez, Antonio, 2001. "From efficiency measurement to efficiency improvement: The choice of a relevant benchmark," European Journal of Operational Research, Elsevier, vol. 133(3), pages 512-520, September.
  38. Sekitani, Kazuyuki & Zhao, Yu, 2023. "Least-distance approach for efficiency analysis: A framework for nonlinear DEA models," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1296-1310.
  39. Maria Silva Portela & Pedro Borges & Emmanuel Thanassoulis, 2003. "Finding Closest Targets in Non-Oriented DEA Models: The Case of Convex and Non-Convex Technologies," Journal of Productivity Analysis, Springer, vol. 19(2), pages 251-269, April.
  40. Soushi Suzuki & Peter Nijkamp, 2021. "High urban population density as a facilitator of energy–environment–economy performance–development of an autoconfiguration target model in data envelopment analysis," Asia-Pacific Journal of Regional Science, Springer, vol. 5(1), pages 261-287, February.
  41. Somayeh Razipour-GhalehJough & Farhad Hosseinzadeh Lotfi & Gholamreza Jahanshahloo & Mohsen Rostamy-malkhalifeh & Hamid Sharafi, 2020. "Finding closest target for bank branches in the presence of weight restrictions using data envelopment analysis," Annals of Operations Research, Springer, vol. 288(2), pages 755-787, May.
  42. Zhu, Qingyuan & Wu, Jie & Ji, Xiang & Li, Feng, 2018. "A simple MILP to determine closest targets in non-oriented DEA model satisfying strong monotonicity," Omega, Elsevier, vol. 79(C), pages 1-8.
  43. Kao, Chiang, 2024. "Maximum slacks-based measure of efficiency in network data envelopment analysis: A case of garment manufacturing," Omega, Elsevier, vol. 123(C).
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