[1] |
Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research, 1978, 2(6): 429-444.
|
[2] |
Ruiz J L, Sirvent I. Common benchmarking and ranking of units with DEA. Omega, 2016, 65: 1-9.
|
[3] |
Cook W D, Ramón N, Ruiz J L, et al. DEA-based benchmarking for performance evaluation in pay-for-performance incentive plans. Omega, 2019, 84: 45-54.
|
[4] |
Liu J S, Lu L Y, Lu W M.Research fronts in data envelopment analysis. Omega, 2016, 58: 33-45.
|
[5] |
Emrouznejad A, Yang G L. A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences, 2018, 61: 4-8.
|
[6] |
Sueyoshi T, Yuan Y, Goto M. A literature study for DEA applied to energy and environment. Energy Economics, 2017, 62: 104-124.
|
[7] |
Zhou P, Ang B W, Poh K L. A survey of data envelopment analysis in energy and environmental studies. European Journal of Operational Research, 2008, 189(1): 1-18.
|
[8] |
Lozano S. Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector. Omega, 2016, 60: 73-84.
|
[9] |
Cook W D, Zhu J. Classifying inputs and outputs in data envelopment analysis. European Journal of Operational Research, 2007, 180(2): 692-699.
|
[10] |
Adler N, Golany B. Including principal component weights to improve discrimination in data envelopment analysis. Journal of the Operational Research Society, 2002, 53(9): 985-991.
|
[11] |
Amirteimoori A, Despotis D K, Kordrostami S. Variables reduction in data envelopment analysis. Optimization, 2014, 63(5): 735-745.
|
[12] |
Toloo M, Hančlová J. Multi-valued measures in DEA in the presence of undesirable outputs. Omega, 2020, 94: 102041.
|
[13] |
Cook W D, Bala K. Performance measurement and classification data in DEA: input-oriented model. Omega, 2007, 35(1): 39-52.
|
[14] |
Shimshak D G, Lenard M L, Klimberg R K. Incorporating quality into data envelopment analysis of nursing home performance: A case study. Omega, 2009, 37(3): 672-685.
|
[15] |
Chen M H, Ang S, Jiang L J, et al. Centralized resource allocation based on cross-evaluation considering organizational objective and individual preferences. OR Spectrum, 2020, 42: 529-565.
|
[16] |
Lozano S, Hinojosa M, Mármol A. Extending the bargaining approach to DEA target setting. Omega, 2019, 85: 94-102.
|
[17] |
Stewart T J. Goal directed benchmarking for organizational efficiency. Omega, 2010, 38(6): 534-539.
|
[18] |
Azadi M, Mirhedayatian S M, Saen R F. A new fuzzy goal directed benchmarking for supplier selection. International Journal of Services and Operations Management, 2013, 14(3): 321-335.
|
[19] |
Ruiz J L, Sirvent I. Performance evaluation through DEA benchmarking adjusted to goals. Omega, 2019, 87: 150-157.
|
[20] |
Zhou X Y, Luo R., An Q X, et al. Water resource environmental carrying capacity-based reward and penalty mechanism: A DEA benchmarking approach. Journal of Cleaner Production, 2019, 229: 1294-1306.
|
[21] |
Podinovski V V. Bridging the gap between the constant and variable returns-to-scale models: Selective proportionality in data envelopment analysis. Journal of the Operational Research Society, 2004, 55(3): 265-276.
|
[22] |
Färe R, Grosskopf S, Lovell C K, et al. Multilateral productivity comparisons when some outputs are undesirable: A nonparametric approach. The Review of Economics and Statistics, 1989, 71(1): 90-98.
|
[23] |
Kuosmanen T. Weak disposability in nonparametric production analysis with undesirable outputs. American Journal of Agricultural Economics, 2005, 87(4): 1077-1082.
|
[24] |
Yang H, Pollitt M. The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants. Energy Policy, 2010, 38(8): 4440-4444.
|
[25] |
Tone K. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 2001, 130(3): 498-509.
|
[26] |
Du J, Liang L, Zhu J. A slacks-based measure of super-efficiency in data envelopment analysis: A comment. European Journal of Operational Research, 2010, 204(3): 694-697.
|
[27] |
Ripoll-Zarraga A E, Lozano S. A centralised DEA approach to resource reallocation in Spanish airports. Annals of Operations Research, 2020, 288(2): 701-732.
|
[28] |
Charnes A, Cooper W W, Golany B, et al. Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. Journal of Econometrics, 1985, 30(1-2): 91-107.
|
[29] |
Scheel H. Undesirable outputs in efficiency valuations. European Journal of Operational Research, 2001, 132(2): 400-410.
|
[30] |
Halme M, Joro T, Korhonen P, et al. A value efficiency approach to incorporating preference information in data envelopment analysis. Management Science, 1999, 45(1): 103-115.
|
[31] |
Azadi M, Saen R F, Zoroufchi K H. A new goal-directed benchmarking for supplier selection in the presence of undesirable outputs. Benchmarking: An International Journal, 2014, 21(3): 314-328.
|
[32] |
Khoveyni M, Eslami R. Managerial goals directed benchmarking for organised efficiency in data envelopment analysis. International Journal of Information and Decision Sciences, 2016, 8(1): 1-23.
|
[33] |
Tao Y, Zhang S L. Environmental efficiency of electric power industry in the Yangtze River delta. Mathematical and Computer Modelling, 2013, 58(5-6): 927-935.
|
[34] |
Reinhard S, Lovell C K, Thijssen G J. Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA. European Journal of Operational Research, 2000, 121(2): 287-303.
|
[35] |
Wu J, Li M J, Zhu Q Y, et al. Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs. Energy Economics, 2019, 78: 468-480.
|
[36] |
Chu J F, Wu J, Song M L. An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: A transportation system application. Annals of Operations Research, 2018, 270(1-2): 105-124.
|
[37] |
Wu J, Xia P P, Zhu Q Y, et al. Measuring environmental efficiency of thermoelectric power plants: A common equilibrium efficient frontier DEA approach with fixed-sum undesirable output. Annals of Operations Research, 2019, 275(2): 731-749.
|
[38] |
Zhou P, Poh K L, Ang B W. A non-radial DEA approach to measuring environmental performance. European Journal of Operational Research, 2007, 178(1): 1-9.
|
[39] |
Yang H, Pollitt M. Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants. European Journal of Operational Research, 2009, 197(3): 1095-1105.
|
[40] |
Chen L, Wang Y M, Lai F J. Semi-disposability of undesirable outputs in data envelopment analysis for environmental assessments. European Journal of Operational Research, 2017, 260(2): 655-664.
|
[41] |
Wu X, Tan L, Guo J, et al. A study of allocative efficiency of PM 2.5 emission rights based on a zero sum gains data envelopment model. Journal of Cleaner Production, 2016, 113: 1024-1031.
|
[42] |
Chen N, Xu L, Chen Z.Environmental efficiency analysis of the Yangtze River economic zone using super efficiency data envelopment analysis (SEDEA) and tobit models. Energy, 2017, 134: 659-671.
|
[43] |
Ruiz F, Cabello J M, Luque M. An application of reference point techniques to the calculation of synthetic sustainability indicators. Journal of the Operational Research Society, 2017, 62(1): 189-197.
|
[1] |
Charnes A, Cooper W W, Rhodes E. Measuring the efficiency of decision making units. European Journal of Operational Research, 1978, 2(6): 429-444.
|
[2] |
Ruiz J L, Sirvent I. Common benchmarking and ranking of units with DEA. Omega, 2016, 65: 1-9.
|
[3] |
Cook W D, Ramón N, Ruiz J L, et al. DEA-based benchmarking for performance evaluation in pay-for-performance incentive plans. Omega, 2019, 84: 45-54.
|
[4] |
Liu J S, Lu L Y, Lu W M.Research fronts in data envelopment analysis. Omega, 2016, 58: 33-45.
|
[5] |
Emrouznejad A, Yang G L. A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences, 2018, 61: 4-8.
|
[6] |
Sueyoshi T, Yuan Y, Goto M. A literature study for DEA applied to energy and environment. Energy Economics, 2017, 62: 104-124.
|
[7] |
Zhou P, Ang B W, Poh K L. A survey of data envelopment analysis in energy and environmental studies. European Journal of Operational Research, 2008, 189(1): 1-18.
|
[8] |
Lozano S. Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector. Omega, 2016, 60: 73-84.
|
[9] |
Cook W D, Zhu J. Classifying inputs and outputs in data envelopment analysis. European Journal of Operational Research, 2007, 180(2): 692-699.
|
[10] |
Adler N, Golany B. Including principal component weights to improve discrimination in data envelopment analysis. Journal of the Operational Research Society, 2002, 53(9): 985-991.
|
[11] |
Amirteimoori A, Despotis D K, Kordrostami S. Variables reduction in data envelopment analysis. Optimization, 2014, 63(5): 735-745.
|
[12] |
Toloo M, Hančlová J. Multi-valued measures in DEA in the presence of undesirable outputs. Omega, 2020, 94: 102041.
|
[13] |
Cook W D, Bala K. Performance measurement and classification data in DEA: input-oriented model. Omega, 2007, 35(1): 39-52.
|
[14] |
Shimshak D G, Lenard M L, Klimberg R K. Incorporating quality into data envelopment analysis of nursing home performance: A case study. Omega, 2009, 37(3): 672-685.
|
[15] |
Chen M H, Ang S, Jiang L J, et al. Centralized resource allocation based on cross-evaluation considering organizational objective and individual preferences. OR Spectrum, 2020, 42: 529-565.
|
[16] |
Lozano S, Hinojosa M, Mármol A. Extending the bargaining approach to DEA target setting. Omega, 2019, 85: 94-102.
|
[17] |
Stewart T J. Goal directed benchmarking for organizational efficiency. Omega, 2010, 38(6): 534-539.
|
[18] |
Azadi M, Mirhedayatian S M, Saen R F. A new fuzzy goal directed benchmarking for supplier selection. International Journal of Services and Operations Management, 2013, 14(3): 321-335.
|
[19] |
Ruiz J L, Sirvent I. Performance evaluation through DEA benchmarking adjusted to goals. Omega, 2019, 87: 150-157.
|
[20] |
Zhou X Y, Luo R., An Q X, et al. Water resource environmental carrying capacity-based reward and penalty mechanism: A DEA benchmarking approach. Journal of Cleaner Production, 2019, 229: 1294-1306.
|
[21] |
Podinovski V V. Bridging the gap between the constant and variable returns-to-scale models: Selective proportionality in data envelopment analysis. Journal of the Operational Research Society, 2004, 55(3): 265-276.
|
[22] |
Färe R, Grosskopf S, Lovell C K, et al. Multilateral productivity comparisons when some outputs are undesirable: A nonparametric approach. The Review of Economics and Statistics, 1989, 71(1): 90-98.
|
[23] |
Kuosmanen T. Weak disposability in nonparametric production analysis with undesirable outputs. American Journal of Agricultural Economics, 2005, 87(4): 1077-1082.
|
[24] |
Yang H, Pollitt M. The necessity of distinguishing weak and strong disposability among undesirable outputs in DEA: Environmental performance of Chinese coal-fired power plants. Energy Policy, 2010, 38(8): 4440-4444.
|
[25] |
Tone K. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 2001, 130(3): 498-509.
|
[26] |
Du J, Liang L, Zhu J. A slacks-based measure of super-efficiency in data envelopment analysis: A comment. European Journal of Operational Research, 2010, 204(3): 694-697.
|
[27] |
Ripoll-Zarraga A E, Lozano S. A centralised DEA approach to resource reallocation in Spanish airports. Annals of Operations Research, 2020, 288(2): 701-732.
|
[28] |
Charnes A, Cooper W W, Golany B, et al. Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. Journal of Econometrics, 1985, 30(1-2): 91-107.
|
[29] |
Scheel H. Undesirable outputs in efficiency valuations. European Journal of Operational Research, 2001, 132(2): 400-410.
|
[30] |
Halme M, Joro T, Korhonen P, et al. A value efficiency approach to incorporating preference information in data envelopment analysis. Management Science, 1999, 45(1): 103-115.
|
[31] |
Azadi M, Saen R F, Zoroufchi K H. A new goal-directed benchmarking for supplier selection in the presence of undesirable outputs. Benchmarking: An International Journal, 2014, 21(3): 314-328.
|
[32] |
Khoveyni M, Eslami R. Managerial goals directed benchmarking for organised efficiency in data envelopment analysis. International Journal of Information and Decision Sciences, 2016, 8(1): 1-23.
|
[33] |
Tao Y, Zhang S L. Environmental efficiency of electric power industry in the Yangtze River delta. Mathematical and Computer Modelling, 2013, 58(5-6): 927-935.
|
[34] |
Reinhard S, Lovell C K, Thijssen G J. Environmental efficiency with multiple environmentally detrimental variables; estimated with SFA and DEA. European Journal of Operational Research, 2000, 121(2): 287-303.
|
[35] |
Wu J, Li M J, Zhu Q Y, et al. Energy and environmental efficiency measurement of China's industrial sectors: A DEA model with non-homogeneous inputs and outputs. Energy Economics, 2019, 78: 468-480.
|
[36] |
Chu J F, Wu J, Song M L. An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: A transportation system application. Annals of Operations Research, 2018, 270(1-2): 105-124.
|
[37] |
Wu J, Xia P P, Zhu Q Y, et al. Measuring environmental efficiency of thermoelectric power plants: A common equilibrium efficient frontier DEA approach with fixed-sum undesirable output. Annals of Operations Research, 2019, 275(2): 731-749.
|
[38] |
Zhou P, Poh K L, Ang B W. A non-radial DEA approach to measuring environmental performance. European Journal of Operational Research, 2007, 178(1): 1-9.
|
[39] |
Yang H, Pollitt M. Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants. European Journal of Operational Research, 2009, 197(3): 1095-1105.
|
[40] |
Chen L, Wang Y M, Lai F J. Semi-disposability of undesirable outputs in data envelopment analysis for environmental assessments. European Journal of Operational Research, 2017, 260(2): 655-664.
|
[41] |
Wu X, Tan L, Guo J, et al. A study of allocative efficiency of PM 2.5 emission rights based on a zero sum gains data envelopment model. Journal of Cleaner Production, 2016, 113: 1024-1031.
|
[42] |
Chen N, Xu L, Chen Z.Environmental efficiency analysis of the Yangtze River economic zone using super efficiency data envelopment analysis (SEDEA) and tobit models. Energy, 2017, 134: 659-671.
|
[43] |
Ruiz F, Cabello J M, Luque M. An application of reference point techniques to the calculation of synthetic sustainability indicators. Journal of the Operational Research Society, 2017, 62(1): 189-197.
|