Amani, N., & Bagherzadeh Valami, H. (2018). Efficiency evaluation of regional electronic companies in Iran by network DEA: a based on the conversion of the structures into a uniform structure. Journal of decisions and operations research, 3(3), 249-280. (In Persian). DOI: 10.22105/dmor.2018.81213
Amini, A., & Alinezhad, A. (2019). Developing network DEA model with undesirable outputs for evaluation of green supply chain management. Iranian journal of supply chain management, 21(63), 51-63.
Amirteimoori, A., & Kordrostami, S. (2010). Multi-period efficiency analysis in data envelopment analysis. International journal of mathematics in operational research, 2(1), 113-128.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
Ben-Tal, A., & Nemirovski, A. (2000). Robust solutions of linear programming problems contaminated with uncertain data. Mathematical programming, 88(3), 411-424.
Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations research, 52(1), 35-53.
Chen, Y., Cook, W. D., Li, N., & Zhu, J. (2009). Additive efficiency decomposition in two-stage DEA. European journal of operational research, 196(3), 1170-1176.
Cook, W. D., Zhu, J., Bi, G., & Yang, F. (2010). Network DEA: additive efficiency decomposition. European journal of operational research, 207(2), 1122-1129.
Despotis, D. K., Koronakos, G., & Sotiros, D. (2016). The “weak-link” approach to network DEA for two-stage processes. European journal of operational research, 254(2), 481-492.
Du, J., Liang, L., Chen, Y., Cook, W. D., & Zhu, J. (2011). A bargaining game model for measuring performance of two-stage network structures. European journal of operational research, 210(2), 390-397.
Emrouznejad, A., & Yang, G. L. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-economic planning sciences, 61, 4-8.
Esmaeilzadeh, A., & Kazemi Matin, R. (2019). Multi-period efficiency measurement of network production systems. Measurement, 134, 835-844.
Färe, R., & Grosskopf, S. (2000). Network DEA. Socio-economic planning sciences, 34(1), 35–49.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the royal statistical society: series A (General), 120(3), 253-281.
Fathollah Bayati, M., & Sajjadi, S. J. (2017). Robust network data envelopment analysis approach to evaluate the efficiency of regional electricity power networks under uncertainty.
PloS One,
12(9), e0184103.
https://doi.org/10.1371/journal.pone.0184103
Holod, D., & Lewis, H. F. (2011). Resolving the deposit dilemma: a new DEA bank efficiency model. Journal of banking & finance, 35(11), 2801-2810.
Huang, J., Chen, J., & Yin, Z. (2014). A network DEA model with super efficiency and undesirable outputs: an application to bank efficiency in China.
Mathematical problems in engineering,
2014.
https://doi.org/10.1155/2014/793192
Jablonsky, J. (2016). Efficiency analysis in multi-period systems: an application to performance evaluation in Czech higher education. Central European journal of operations research, 24(2), 283-296.
Jafari, M., & Dezfouli Khajehzadeh, M. (2015). Robust fuzzy multi objective optimization model for portfolio selection.
Journal of decision engineering,
1(1), 31-56. (
In Persian).
http://jde.khu.ac.ir/article-1-26-en.html
Jahani Sayyad Noveiri, M., Kordrostami, S., Amirteimoori, A. (2017). Cost efficiency of closed–loop supply chain in the presence of dual-role and undesirable factors.
Journal of new researches in mathematics,
3(9), 5-16. (
In Persian).
https://jnrm.srbiau.ac.ir/article_10404.html?lang=en
Kaffash, S., Azizi, R., Huang, Y., & Zhu, J. (2020). A survey of data envelopment analysis applications in the insurance industry 1993–2018. European journal of operational research, 284(3), 801-813.
Kao, C. (2009). Efficiency decomposition in network data envelopment analysis: a relational model. European journal of operational research, 192(3), 949-962.
Kao, C. (2009). Efficiency measurement for parallel production systems. European journal of operational research, 196(3), 1107-1112.
Kao, C. (2019). Inefficiency identification for closed series production systems. European journal of operational research, 275(2), 599-607.
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(1), 418-429.
Kao, C., & Hwang, S. N. (2010). Efficiency measurement for network systems: IT impact on firm performance. Decision support systems, 48(3), 437-446.
Kao, C., & Liu, S. T. (2014). Multi-period efficiency measurement in data envelopment analysis: the case of Taiwanese commercial banks. Omega, 47, 90-98.
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.
Khoveyni, M., Fukuyama, H., Eslami, R., & Yang, G. L. (2019). Variations effect of intermediate products on the second stage in two-stage processes. Omega, 85, 35-48.
Kordrostami, S., & Noveiri, M. J. S. (2017). Evaluating the efficiency of firms with negative data in multi-period systems: an application to bank data. International journal of industrial mathematics, 9(1), 27-35.
Lewis, H. F., & Sexton, T. R. (2004). Network DEA: efficiency analysis of organizations with complex internal structure. Computers & operations research, 31(9), 1365-1410.
Lim, S., & Zhu, J. (2019). Primal-dual correspondence and frontier projections in two-stage network DEA models. Omega, 83, 236-248.
Liu, J. S., & Lu, W. M. (2012). Network-based method for ranking of efficient units in two-stage DEA models. Journal of the operational research society, 63(8), 1153-1164.
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), 76-84.
Najafi, S. E., Jaberi, M., Hoseinzadeh Lotfi, F., & Haji Molana, M. (2021). A comprehensive hybrid Ndea-Bsc model and a new neural network for predicting organizational performance indicators.
Journal of decisions and operations research,
6(2), 271-287. (
In Persian). DOI:
10.22105/DMOR.2020.254632.1243
Nemoto, J., & Goto, M. (2003). Measurement of dynamic efficiency in production: an application of data envelopment analysis to Japanese electric utilities. Journal of productivity analysis, 19(2), 191-210.
Pérez-Reyes, R., & Tovar, B. (2009). Measuring efficiency and productivity change (PTF) in the Peruvian electricity distribution companies after reforms. Energy policy, 37(6), 2249-2261.
Peykani, P., Mohammadi, E., & Emrouznejad, A. (2021). An adjustable fuzzy chance-constrained network DEA approach with application to ranking investment firms.
Expert systems with applications,
166, 113938.
https://doi.org/10.1016/j.eswa.2020.113938
Peykani, P., Mohammadi, E., Farzinpour Saen, R., Sadjadi, S. J., & Rostamy‐Malkhalifeh, M. (2020). Data envelopment analysis and robust optimization: a review.
Expert systems,
37(4), e12534.
https://doi.org/10.1111/exsy.12534
Ramos-Real, F. J., Tovar, B., Iootty, M., De Almeida, E. F., & Pinto Jr, H. Q. (2009). The evolution and main determinants of productivity in Brazilian electricity distribution 1998–2005: an empirical analysis. Energy economics, 31(2), 298-305.
Razavi Hajiagha, S. H., Hashemi, S. S., Mahdiraji, H. A., & Azaddel, J. (2015). Multi-period data envelopment analysis based on Chebyshev inequality bounds. Expert systems with applications, 42(21), 7759-7767.
Saleh, H., Shafiee, M., & Sanji, M. (2020). Modifying the interconnecting activities through an adjusted dynamic DEA model: a slacks-based measure approach. Journal of applied research on industrial engineering, 7(3), 287-300.
Sarkhosh-Sara, A., Tavassoli, M., & Heshmati, A. (2020). Assessing the sustainability of high-, middle-, and low-income countries: a network DEA model in the presence of both zero data and undesirable outputs. Sustainable production and consumption, 21, 252-268.
Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. Management science, 45(9), 1270-1288.
Shafiei Nikabadi, M., Yakideh, K., & Oveysi Omran, A. (2017). An integrated approach of DEA with a variety of outputs and windows analysis for evaluating efficiency of the power industry.
Journal of industrial management perspective,
6(4), 157-180. (
In Persian).
https://jimp.sbu.ac.ir/article_87218.html?lang=en
Shakouri, R., Salahi, M., & Kordrostami, S. (2019). Stochastic p-robust approach to two-stage network DEA model. Quantitative finance and economics, 3(2), 315-346.
Sokhanvar, M., Sadeghi, H., Assari, A., Yavari, K., & Mehregan, N. (2012). Structural analysis and efficiency trend of electricity distribution companies in Iran by using window data envelopment analysis.
Economic growth and development research,
1(4), 145-182. (
In Persian).
https://egdr.journals.pnu.ac.ir/?_action=articleInfo&article=63&lang=en
Soyster, A. L. (1973). Convex programming with set-inclusive constraints and applications to inexact linear programming. Operations research, 21(5), 1154-1157.
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498-509.
Zhou, X., Xu, Z., Chai, J., Yao, L., Wang, S., & Lev, B. (2019). Efficiency evaluation for banking systems under uncertainty: a multi-period three-stage DEA model. Omega, 85, 68-82.
)