[1] M. Anisi, The use of linear programming in the joint relations of game theory and data envelopment analysis, Master’s thesis, Islamic Azad University, Science and Research Branch, Faculty of Basic Sciences, 2008.
[2] N. Avkiran and A. McCrystal, Dynamic network range-adjusted measures. dynamic network slacks-based measure, J. Oper. Res. Soc. Japan 57 (2014), no. 1, 1–14.
[3] R.D. Banker, A. Charnes, W.W. Cooper and R. Clarke, Constrained game formulations and interpretations for data envelopment analysis, Eur. J. Oper. Res. 40 (1989), no. 3, 299–308.
[4] F. Canbek, Analysis of the efficiency of private hospitals in Istanbul with data envelopment analysis, Master Thesis, Anadolu University, Institute of Social Sciences, Eskisehir, 2007.
[5] M. Chen, M. Chien and J. van Dalen, Measuring dynamic efficiency: theories and an integrated methodology, Eur. J. Oper. Res. 203 (2010), 749–760.
[6] Y. Chen, W.D. Cook, N. Li and J. Zhu, Additive efficiency decomposition in two-stage DEA, Eur. J. Oper. Res. 196 (2009), 1170–1176.
[7] A. Charnes, W. W. Cooper, B. Golany, R. Halek, G. Klopp, E. Schmitz and D. Thomas, Two phase data envelopment analysis approaches to policy evaluation and management of army recruiting activities: Tradeoffs between joint services and army advertising, Center for Cybernetic Studies, University of Texas-Austin Austin, Texas, USA, 1986.
[8] A. Charnes, W.W. Cooper and E. Rhodes, Measuring the efficiency of decision-making units, Eur. J. Oper. Res. 2 (1978), no. 6, 429–444.
[9] M. Chen and V.J. Dalen, Measuring dynamic efficiency: Theories and an integrated methodology, Eur. J. Oper. Res. 203 (2010), 749–760.
[10] K.D. Despotis, D. Sotiros and G. Koronakos, A network DEA approach for series multi-stage process, Omega 61 (2016), 35–48.
[11] R. Fare and S. Grosskopf, Network DEA, Socio Econ. Plan. Sci.34 (2004).
[12] E. Feroz, S. Kim and R.L. Raab, Financial statement analysis: A data envelopment analysis approach, J. Oper. Res. Soc. 54 (2003), no. 1, 48–58.
[13] H. Fukuyama and W.L. Weber, A slacks-based inefficiency measure for a two-stage system with bad outputs, Omega 38 (2010), 398–409.
[14] H. Fukuyama and W.L. Weber, Japanese bank productivity, 2007- 2012: A dynamic network approach, Pacific Econ. Rev. 22 (2017), no. 4, 649–676.
[15] J.S. Hahn, H.M. Sung, M.C. Park, S.Y. Kho and D.K. Kim, Empirical evaluation on the efficiency of the trucking industry in Korea, KSCE J. Civil Engin. 19 (2015), 1088–1096.
[16] R. Jahangoshai, M. Moini and A. Makui, Operational and non-operational performance evaluation of thermal power plants in Iran: A game theory approach, Energy 38 (2012), 96–103.
[17] C. Kao, Dynamic data envelopment analysis: A relational analysis, Eur. J. Oper. Res. 227 (2013), no. 2, 325–330.
[18] C. Kao, Efficiency decomposition in network DEA: A relational model, Eur. J. Oper. Res. 192 (2009), no. 3, 949–962.
[19] C. Kao, Network data envelopment analysis: A review, Eur. J. Oper. Res. 239 (2014), 1-16.
[20] C. Kao and S.N. Hwang, Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan, Eur. J. Oper. Res.185 (2008), no. 1, 418–429.
[21] C. Kao and S. N. Hwang, Efficiency measurement for network systems: IT impact on firm performance, Decision Support Syst.48 (2010), 437–446.
[22] A. Lalar, Measuring the efficiency of municipalities with data envelopment analysis, Doctoral Thesis, Hacettepe University, Institute of Science and Technology, Ankara, 2003.
[23] Y. Li, Y. Chen, L. Liang and J. Xie, DEA models for extended two-stage network structures, Omega 40 (2012), no. 5, 611–618.
[24] L. Liang, J. Wu, W.D. Cook and J. Zhu, The DEA game cross-efficiency model and its Nash equilibrium, Oper. Res. 56 (2008), no. 5, 1278–1288.
[25] S. Lozano, Alternative SBM model for network DEA, Comput. Ind. Engin. 82 (2015), 33–40.
[26] X.M. Luo, Evaluating the profitability and marketability efficiency of large banks: An application of data envelopment analysis, J. Bus. Res. 56 (2003), 627–635.
[27] R. Malhotra, D.K. Malhotra and P. Russel, Using data envelopment analysis to rate bonds, Proc. Northeast Bus. Econ. Assoc. 4 (200), 420–423.
[28] P. Moreno and S. Lozano, Super SBI Dynamic Network DEA approach to measuring efficiency in the provision of public services, Int. Trans. Oper. Res. 25 (2016), no. 2, 715–735.
[29] K. Nakabayashi and K. Tone, Egoist’s dilemma: a DEA game, Omega 34 (2006), 135–148.
[30] J. Nemoto and M. Goto, Dynamic data envelopment analysis: Modeling inter-temporal behavior of a firm in the presence of productive inefficiencies, Econ. Lett. 64 (1999), 51–56.
[31] J. Nemoto and M. Goto, Measurement of dynamic efficiency in production: An application of data envelopment analysis to Japanese electric utilities, J. Prod. Anal. 19 (2003), 191–210.
[32] K.O. Oru,c, Efficiency measurements in a fuzzy environment with data envelopment analysis and an application in universities, Ph.D. Thesis, Suleyman Demirel University, Institute of Social Sciences, Isparta.
[33] J. Powers and P. McMullen, Using data envelopment analysis to select efficient large market cap securities, J. Bus. Manag. 7 (2000), no. 2, 31–42
[34] S. Saviz and E. Najafi, A new expansion on multi-stage DEA methodology in supply chain management, J. Ind. Manag. 8 (2013), no. 25, 18-28.
[35] M. Sayadi and K. Azarbaijani, Technical efficiency estimation at public and private sector industries at Iran by using stochastic frontier analysis method, Bi-Quart. Sci.-Special. J. Dev. Plan. Econ. 1 (2012), no. 2, 33.
[36] L.M. Seiford and J. Zhu, Profitability and marketability of the top 55 US commercial banks, Manag. Sci. 45 (1999), 1270–1288.
[37] H. Soltanpanah, I. Dadashi and S. Zarei, The study of the efficiency levels of companies listed on the Tehran Stock Exchange based on the data envelopment analysis technique, Ind. Manag. Quart. 24 (2013).
[38] K. Tone and M. Tsutsui, Dynamic DEA: A slacks-based measure approach, Omega 38 (2010), 3–4.
[39] K. Tone and M. Tsutsui, Network DEA: A slacks-based measure approach, Eur. J. Oper. Res. 197 (2009), no. 43, 243–252.