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Closest targets and strong monotonicity on the strongly efficient frontier in DEA

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  1. Pastor, Jesus T. & Aparicio, Juan & Alcaraz, Javier & Vidal, Fernando & Pastor, Diego, 2015. "An enhanced BAM for unbounded or partially bounded CRS additive models," Omega, Elsevier, vol. 56(C), pages 16-24.
  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. Atwood, Joseph & Shaik, Saleem, 2020. "Theory and statistical properties of Quantile Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 649-661.
  4. 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.
  5. 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.
  6. Ruiz, José L. & Sirvent, Inmaculada, 2016. "Common benchmarking and ranking of units with DEA," Omega, Elsevier, vol. 65(C), pages 1-9.
  7. Fukuyama, Hirofumi & Matousek, Roman & Tzeremes, Nickolaos G., 2023. "Estimating the degree of firms’ input market power via data envelopment analysis: Evidence from the global biotechnology and pharmaceutical industry," European Journal of Operational Research, Elsevier, vol. 305(2), pages 946-960.
  8. Xiaohong Liu & Qingyuan Zhu & Junfei Chu & Xiang Ji & Xingchen Li, 2019. "Environmental Performance and Benchmarking Information for Coal-Fired Power Plants in China: A DEA Approach," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1287-1302, December.
  9. Simar, Leopold & Zelenyuk, Valentin, 2018. "Improving Finite Sample Approximation by Central Limit Theorems for DEA and FDH efficiency scores," LIDAM Discussion Papers ISBA 2018020, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  10. 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.
  11. Gawiejnowicz, Stanisław & Kurc, Wiesław, 2015. "Structural properties of time-dependent scheduling problems with the lp norm objective," Omega, Elsevier, vol. 57(PB), pages 196-202.
  12. Juan Aparicio & Magdalena Kapelko & Bernhard Mahlberg & Jose L. Sainz-Pardo, 2017. "Measuring input-specific productivity change based on the principle of least action," Journal of Productivity Analysis, Springer, vol. 47(1), pages 17-31, February.
  13. Aparicio, Juan & Pastor, Jesús T. & Vidal, Fernando & Zofío, José L., 2017. "Evaluating productive performance: A new approach based on the product-mix problem consistent with Data Envelopment Analysis," Omega, Elsevier, vol. 67(C), pages 134-144.
  14. Tone, Kaoru & Chang, Tsung-Sheng & Wu, Chen-Hui, 2020. "Handling negative data in slacks-based measure data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 282(3), pages 926-935.
  15. Lozano, S. & Hinojosa, M.A. & Mármol, A.M., 2015. "Set-valued DEA production games," Omega, Elsevier, vol. 52(C), pages 92-100.
  16. Alcaraz, Javier & Anton-Sanchez, Laura & Aparicio, Juan & Monge, Juan F. & Ramón, Nuria, 2021. "Russell Graph efficiency measures in Data Envelopment Analysis: The multiplicative approach," European Journal of Operational Research, Elsevier, vol. 292(2), pages 663-674.
  17. Ruiz, José L. & Sirvent, Inmaculada, 2019. "Performance evaluation through DEA benchmarking adjusted to goals," Omega, Elsevier, vol. 87(C), pages 150-157.
  18. 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.
  19. Lozano, Sebastián & Calzada-Infante, Laura, 2018. "Computing gradient-based stepwise benchmarking paths," Omega, Elsevier, vol. 81(C), pages 195-207.
  20. Aparicio, Juan & Cordero, Jose M. & Gonzalez, Martin & Lopez-Espin, Jose J., 2018. "Using non-radial DEA to assess school efficiency in a cross-country perspective: An empirical analysis of OECD countries," Omega, Elsevier, vol. 79(C), pages 9-20.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. Aparicio, Juan & Pastor, Jesus T. & Vidal, Fernando, 2016. "The directional distance function and the translation invariance property," Omega, Elsevier, vol. 58(C), pages 1-3.
  26. Lozano, Sebastián & Khezri, Somayeh, 2021. "Network DEA smallest improvement approach," Omega, Elsevier, vol. 98(C).
  27. Shogo Eguchi & Hirotaka Takayabu & Mitsuki Kaneko & Shigemi Kagawa & Shunichi Hienuki, 2021. "Proposing effective strategies for meeting an environmental regulation with attainable technology improvement targets," Business Strategy and the Environment, Wiley Blackwell, vol. 30(7), pages 2907-2921, November.
  28. Kapelko, Magdalena & Oude Lansink, Alfons & Zofío, José L., 2022. "Endogenous dynamic inefficiency and optimal resource allocation: An application to the European Dietetic Food Industry," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1444-1457.
  29. Cook, Wade D. & Ruiz, José L. & Sirvent, Inmaculada & Zhu, Joe, 2017. "Within-group common benchmarking using DEA," European Journal of Operational Research, Elsevier, vol. 256(3), pages 901-910.
  30. 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.
  31. 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.
  32. Jie Wu & Jun-Fei Chu & Liang Liang, 2016. "Target setting and allocation of carbon emissions abatement based on DEA and closest target: an application to 20 APEC economies," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 279-296, November.
  33. 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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