Aghayi, N. (2017). Ranking of Decision-Making Units based on Cross Efficiency by Undesirable Outputs and Uncertainity. Journal of New Research in Mathematics, 3 (11), 19-30. (in Persian)
Azadeh, A., Motevali Haghighi, S., Zarrin, M. & Khaefi, S. (2015). Performance evaluation of Iranian electricity distribution units by using stochastic data envelopment analysis, Electrical Power and Energy Systems, 73, 919-931.
Banker, R.D., Charnes, A. & Cooper, W.W. (1984). Some Models for Estimating Technical and Scale Efficiencies in Data Envelopment Analysis. Management Science, 30: 1078-92.
Bi, G.B., Song, W., Zhou, P. & Liang, L. (2014) Does environmental regulation affect energy efficiency in China's thermal power generation? Empirical evidence from a slacks-based DEA model. Energy Policy, 66, 537-546.
Chambers, R. G., Chung, Y., Fare, R., (1996). Benefit and distance function. Journal of Economic Theory, 70 (2), 407-419.
Charnes, A., Cooper, W. W. & Rhodes, E. (1978). Measuring the efficiency of decision- making units. European Journal of Operational Research, 2: 429–44.
Chen Y, Liang L, Zhu J (2009) Equivalence in two-stage DEA approaches. European Journal of Operational Research, 193, 600-604.
Chung, Y. H., Fare, R., Grosskopf, S., (1997). Productivity and undesirable outputs a directional distance function approach. Journal of Environmental Management, 51 (3), 229-240.
Dasilva, A. V., Costa, M.A., Ahn, H. & Lopes, A.L.M. (2019). Performance benchmarking models for electricity transmission regulation: Caveats concerning the Brazilian case. Utilities Policy, 60, 1-10.
Fallahi, A., Fallahi, F., Sarhadi, H., Ghaderi, S.F. & Ebrahimi, R., (2019). Application of a robust data envelopment analysis model for performance evaluation of electricity distribution companies. International Journal of Energy Sector Management, 15 (4), 724-742.
Fare, R. & S. Grosskopf (2000). Network DEA. Socio-Economic Planning Sciences, 34(1): 35–49.
Fare, R., Grosskopf, S., Lovell, C. A. K. & Pasurka, C. (1989). Multilateral productivity comparisons when some outputs are undesirable: a nonparametric approach. The review of economics & statistics, 71, 90–98.
Farell, M. (1957). The measurement of productive efficiency. Journal of the Royal Statistics Society, Series A, 120 (3): 253-281.
Goto, M. & Tsutsui, M. (2008). Technical efficiency and impacts of deregulation: An analysis of three functions in U.S. electric power utilities during the period from 1992 through 2000. Energy Economics, 30, 15–38.
Hafsal, K., Suvvari, A. & Sethu Durai, S.R. (2020).Efficiency of Indian banks with non‑performing assets: evidence from two‑stage network DEA. Future Business Journal, 6 (1), 1-9.
Hasanzadeh, A. (2017). Developing model of Network DEA to Evaluate the Supply Chains Performance of Firms with Continuous Production System, PhD dissertation, Faculty of Management, University of Tehran. (in Persian)
Islamic Consultative Assembly Research Center (2016). Electricity crisis this year and years to come, Report No. 14392, Office of Energy, Industry and Mining Studies. (in Persian)
Kao, C. (2014). Efficiency decomposition for general multi-stage systems in data envelopment analysis. European Journal of Operational Research, 232, 117–124.
Kao, C., Hwang, S.N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research, 185, 418–429.
Kao, C., Hwang, S. N. (2011). Decomposition of technical and scale efficiencies in two-stage production systems. European Journal of Operational Research, 211, 515–519.
Khalili-Damghani, K. & Shahmir, Z. (2015). Uncertain network data envelopment analysis with undesirable outputs to evaluate the efficiency of electricity power production and distribution processes, Computers & Industrial Engineering, 88, 131-150.
Khodadadipour, M., Hadi-Vencheh, A., Behzadi, M.H. & Rostamy-malkhalifeh, M. (2021). Undesirable factors in stochastic DEA cross-efficiency evaluation: An application to thermal power plant energy efficiency, Economic Analysis and Policy, 9, 613-628.
Khosravi, M. R., & Shahroudi, K. (2014). The Use of Network Data Envelopment Analysis Approach for Evaluating the Efficiency of Power Transmission companies in the Electric Power Industry of Iran, Journal of Industrial Management, 6 (2), 263-282. (in Persian)
Khosravi, M. R., Shahroudi, K., Amirteymoori, A., & Delafrooz, N. (2021). Presenting an Integrated Model of Organizational Ambidexterity and Network Data Envelopment Analysis in order to Evaluate the Efficiency of regional electricity companies in Iran, Iranian Electric Industry Journal Quality & Productivity, 10(3), 62-74. (in Persian)
Khosravi, M.R., & Shahroodi, K. (2015). Applying Network Data Envelopment Analysis to Determine a Criterion for Benchmarking in Regional Electricity Companies of Iran. International journal of Data Envelopment Analysis, 3 (2), 709-722.
Kuosmanen, T. (2005). Weak disposability in nonparametric production analysis with undesirable outputs. American Journal of Agricultural Economics, 87(4), 1077-1082.
Li, Y., Chen, Y., Liang, L. & Xie, J. (2012). DEA models for extended two stage network structures. Omega, 40(5), 611–618.
Lim, S., Zhu, J. (2015). A note on two-stage network DEA model: frontier projection and duality, European Journal of Operational Research. 248 (1), 342-346.
Ma, J., Qi, Linan, Deng, L. (2017). Efficiency measurement and decomposition in hybrid twostage DEA with additional inputs. Expert Systems with Applications, 79(3), 348-357.
Matthews, K. (2013). Risk management and managerial efficiency in Chinese banks: A network DEA framework. Omega, 41, 207–215.
Mohamadinejadrashti, H., Amirteimoori, A., Kordrostami, S., Hosseinzadeh Lotfi, F. (2021). Resource allocation and target setting based on DEA with managerial disposability: evaluation and optimization the greenhouse gas emissions reduction in international airlines. Journal of Decisions and Operations Research, 6 (3), 365-381. (in Persian)
Mohsin, M., Hanif, I., Taghizadeh-Hesary, F., Abbas, Q., & Iqbal, W. (2021). Nexus between energy efficiency and electricity reforms: A DEA-Based way forward for clean power development, Energy Policy, 149, 112052.
Monenco Iran Consulting Engineers (2014). Electricity industry Restructuring in Iran. Tehran: Shivah Publications. (in Persian)
Monzeli, A., Daneshian, B., Tohidi, G., Sanei, M., Razavian, S. (2020). Efficiency study with undesirable inputs and outputs in DEA. Journal of fuzzy extension and applications, 1(1), 78-84.
Mullarkey, Sh., Caulfield, B., McCormack, S., & Basu, B. (2015). A framework for establishing the technical efficiency of Electricity Distribution Counties (EDCs) using Data Envelopment Analysis, Energy Conversion and Management, 94, 112–123.
Munisamy S, Arabi B. (2015). Eco-efficiency change in power plants: using a slacks-based measure for the meta-frontier Malmquist–Luenberger productivity index. Journal of Cleaner Production, 105, 218–232.
Park, K. S., Park, K. (2009). Measurement of multiperiod aggregative efficiency. European Journal of Operational Research, 193, 567–580.
Peykani, P., & Mohammadi, E. (2019). Performance Measurement of Decision-Making Units with Network Structure in the Presence of Undesirable Output, Jouranal of New Research in Mathematics, 5 (17), 157-166. (in Persian)
Radser, M., Kazemi, A., Mehregan, M. R., & Razavi Haji1gha, H. (2021). Designing an Algorithm based on Network Data Envelopment Analysis with Desirable and Undesirable Indicators for the Evaluation of the Iranian Power Industry, Journal of Industrial Management, 13 (1), 1-26. (in Persian)
Salehzadeh, J., Hejazi, R., Arkan, A., & Hosseini, M. (2011), Proposing an Integrative Approach for Evaluatng of the Efficiency of Network Structures Including Tour and Allocation Link, Journal of Production and Operations Management, 1(2), 47-60.
(in Persian)
Salimi, M. & Keramati, M. A. (2016). Evaluation and Analysis of Technical Efficiency of Regional Electricity Companies in Iran Using a Three-Step Data Envelopment Analysis, Iranian Electric Industry Journal of Quality and Productivity, 4 (8), 37-48. (in Persian)
Seifert, S., Cullmann, A. & Hirschhausen, Ch.v. (2016). Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector, Energy Economics, 56, 9-19.
Seiford, L. M., Zhu, J. (2002). Modeling undesirable factors inefficiency valuation. European Journal of Operational Research, 142 (1), 16-20.
Shafiei Nikabadi, M. R, Yakideh, K. and & Oveysi Omran, A. (2017). Presenting a Network Data Envelopment Analysis Model by a Combination of Desired And Undesired Intermediate and Final outputs, Journal of Operational Research and its Applications, 1(52), 95-116. (in Persian)
Shafiei Nikabadi, M., Yakideh, K., & Oveysi Omran, A. (2017). An Integrated Approach of Data Envelopment Analysis with a Variety of Outputs and Window Analysis for Evaluating the Efficiency of the Power Industry. Journal of Industrial Management Perspective, 6 (4), 157-180. (in Persian)
Shahriari, S., Lahiji, S. (2017). Performance Evaluation of the National Innovation Systems by Network Data Envelopment Analysis. Industrial Management Journal, 9(3), 455-474.
(in Persian)
Shephard, R. W. (1970). Theory of cost and production functions. In Theory of Cost and Production Functions. Princeton University Press.
Siriopoulos, C. & Tziogkidis, P. (2010). How do Greek banking in stitutions react after significant events? A DEA approach. Omega, 38(5), 294–308.
Soleymani Damaneh, R. (2019). Evaluation of Continuous Two-stage Structures: A New Multi-objective Network Data Envelopment Analysis (MO-NDEA) Approach. Industrial Management Journal, 11(3), 487-516. (in Persian)
Sotiros, D., Koronakos, G. & Despotis D.k. (2018). Dominance at the divisional efficiencies level in network DEA: the case of two-stage processes, Omega, 84, 144-155.
Sueyoshi, T., & Goto, M. (2017). World trend in energy: an extension to DEA applied to energy and environment. Economic Structures, 6 (13), 1-23.
Sueyoshi, T., Qu, J., Li, A. & Xie, Ch., (2020). Understanding the efficiency evolution for the Chinese provincial power industry: A new approach for combining data envelopment analysis-discriminant analysis with an efficiency shift across periods. Journal of Cleaner Production, 277, 1-11.
Sueyoshi, T., Yuan, Y., & Goto, M. (2016). A Literature Study for DEA Applied to Energy and Environment, Energy Economics, 64: 104-124.
Tan, Y., Wanke, P., Antunes, J. & Emrouznejad, A. (2021). Unveiling endogeneity between competition and efficiency in Chinese banks: a two‑stage network DEA and regression analysis, Annals of Operations Research, 306, 131-171.
Tavassoli, M., Faramarzi, G.R., Farzipoor Saen, R. (2015). Ranking electricity distribution units using slacks-based measure, strong complementary slackness condition, and discriminant analysis. International Journal of Electrical Power & Energy Systems, 64:1214–1220.
Tavassoli, M., Ketabi, S. & Ghandehari, M. (2020). Developing a network DEA model for sustainability analysis of Iran’s electricity distribution network, International Journal of Electrical Power & Energy Systems, 122, 1-13.
Wei, Q. L., Yan, H., Pang, L. Y. (2011). Composite network data envelopment analysis model. International Journal of Information Technology and Decision Making, 10, 613–633.
Wu, J., Yin, P., Sun, J., Chu, J., & Liang L. (2016). Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspective, European Journal of Operational Research, 254, 1047-1062.
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