1. Azadeh, A., Haghighi, S., Zarrin, M. & Khaefi, S. (2015). Performance evaluation of Iranian electricity distribution units by using stochastic data envelopment analysis. International Journal of Electrical Power & Energy Systems. 73. 919-931. [DOI:10.1016/j.ijepes.2015.06.002]

2. 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. [DOI:10.1287/mnsc.30.9.1078]

3. Birkinshaw, J., & Gupta, K., (2013). Clarifying the distinctive contribution of ambidexterity to the field of organization studies. The Academy of Management Perspectives, amp-2012. [DOI:10.5465/amp.2012.0167]

4. Çelen, A., (2013a). A review and synthesis of empirical studies on technical efficiency measurement in Turkish electricity market. Competition Journal (published by Turkish Competition Authority), 14 (2) , 43-64.

5. Çelen, A., (2013b). Efficiency and productivity (TFP) of the Turkish electricity distribution companies: An application of two-stage (DEA & Tobit) analysis, Energy Policy, 63, 300-310. [DOI:10.1016/j.enpol.2013.09.034]

6. Charnes, A., Cooper, W. W., and Rhodes, E., (1978). Measuring the efficiency of decision- making units. European Journal of Operational Research, 2: 429-44. [DOI:10.1016/0377-2217(78)90138-8]

7. Chen, C., & Yan, H. , (2011). Network DEA model for supply chain performance evaluation. European Journal of Operational Research, 213(1): 147-155. [DOI:10.1016/j.ejor.2011.03.010]

8. Cook, W.D., Zhu, J., Bi, G. & Yang, F., (2010). Network DEA: additive efficiency decomposition. European Journal of Operational Research, 207: 1122-9. [DOI:10.1016/j.ejor.2010.05.006]

9. Derbyshire, J. (2014). The impact of Ambidexterity on enterprise performance: Evidence from 15 countries and 14 sectors, Technovation, 34 (10), pp. 574-581. [DOI:10.1016/j.technovation.2014.05.010]

10. Duncan, R. B., (1976). The ambidextrous organization: Designing dual structures for innovation. The management of organization, 1, 167-188.

11. 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. [DOI:10.1108/IJESM-08-2018-0008]

12. Fare, R., & Grosskopf, S., (2000). Network DEA. socio-economic plannig science, 34: 35-49. [DOI:10.1016/S0038-0121(99)00012-9]

13. Farell, M., (1957). The measurement of productive efficiency. Journal of the Royal Statistics Society, Series A, 120 (3): 253-281. [DOI:10.2307/2343100]

14. Gomez-Calvet, R., Conesa, D., Gómez-Calvet, A.R. & Tortosa-Ausina, E., (2014). Energy efficiency in the European :union:: What can be learned from the joint application of directional distance functions and slacks-based measures?, Applied Energy, 132, 137-154. [DOI:10.1016/j.apenergy.2014.06.053]

15. Hoefs, j. (2012). The relationship between Contextual Ambidexterity and Innovative Ambidexterity: The mediating role of Knowledge Sharing Ambidexterity. Master thesis. University of Amsterdam,

16. Hsu, Ch., Lien, Y. & Chen, H., (2013). International ambidexterity and firm performance in small emerging economies, Journal of World Business, 48, 58-67. [DOI:10.1016/j.jwb.2012.06.007]

17. 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. [DOI:10.1016/j.ejor.2006.11.041]

18. Kao, C., (2009). Efficiency decomposition in network DEA: A relational model. European Journal of Operational Research., 192(3): 949-962. [DOI:10.1016/j.ejor.2007.10.008]

19. Kitapci, H. & Celik, V., (2013). Ambidexterity and Firm Productivity Performance: The Mediating Effect of Organizational Learning Capacity, Procedia - Social and Behavioral Sciences, 99, 1105-1113. [DOI:10.1016/j.sbspro.2013.10.584]

20. Kuosmanen, T., Saastamoinen, A., & Sipiläinen, T., (2013). What is the best practice for benchmark regulation of electricity distribution? Comparison of DEA, SFA and StoNED methods, Energy Policy, 61, 740-750. [DOI:10.1016/j.enpol.2013.05.091]

21. Lee, K., Woo, H.G., & Joshi, K., (2017). Pro-innovation culture, ambidexterity and new product development performance: Polynomial regression and response surface analysis. European Management Journal, 35, pp 249-260. [DOI:10.1016/j.emj.2016.05.002]

22. Li, Y., Chen, Y., Liang, L. & Xie, J., (2012). DEA models for extended two-stage network structures. Omega, 40: 611-18. [DOI:10.1016/j.omega.2011.11.007]

23. March J. G., (1991). Exploration and exploitation in organizational learning. Organization science, 2(1), 71-87. [DOI:10.1287/orsc.2.1.71]

24. Mihalache, M. & Mihalache, O., (2016). Organizational ambidexterity and sustained performance in the tourism industry, Annals of Tourism Research, 101, 165-181. [DOI:10.1016/j.annals.2015.10.011]

25. Mullarkey, S., 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. [DOI:10.1016/j.enconman.2015.01.049]

26. 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. [DOI:10.1016/j.jclepro.2014.12.081]

27. O'Reilly, Ch. A. & Tushman, M.L., (2013). Organizational Ambidexterity: Past, Present and Future. The Academy of Management Perspectives, 27 (4). pp. 324-338. [DOI:10.5465/amp.2013.0025]

28. Omrani, H., Gharizadeh Beiragh, R., & Shafiei Kaleibari, S., (2015). Performance assessment of Iranian electricity distribution companies by an integrated cooperative game data envelopment analysis principal component analysis approach, International Journal of Electrical Power & Energy Systems, 64, 617-625. [DOI:10.1016/j.ijepes.2014.07.045]

29. Seifert, S., Cullmann, A. & von Hirschhausen, Ch., (2016). Technical efficiency and CO2 reduction potentials - An analysis of the German electricity and heat generating sector, Energy Economics, 56, 9-19. [DOI:10.1016/j.eneco.2016.02.020]

30. Shahroodi, K., Khosravi, M.R, (2017). Comparison of the Efficiency of Power Transmission Companies in the Electric Power Industry of Iran Applying Conventional and Network Data Envelopment Analysis Methods. Iranian Journal of Optimization, 9 (2), 85-92.

31. Sueyoshi, T., & Goto, M., (2017). World trend in energy: an extension to DEA applied to energy and environment, Economic Structures, 6 (13): 1-23. [DOI:10.1186/s40008-017-0073-z]

32. 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. [DOI:10.1016/j.jclepro.2020.122371]

33. 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. [DOI:10.1016/j.ijepes.2014.09.018]

34. Tone, K. & Tsutsui, M., (2009). Network DEA: A slacks-based measure approach. European Journal of Operational Research, 197(1), 243-252. [DOI:10.1016/j.ejor.2008.05.027]

35. Van Assen, M. F., (2020). Empowering leadership and contextual ambidexterity- the mediating role of committed leadership for continuous improvement. European Management Journal. 38 (3), pp 435-449. [DOI:10.1016/j.emj.2019.12.002]