International Journal of Business, Economics and Management

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Online ISSN: 2312-0916
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No. 5

Measuring Efficiency in Banks: A Brief Survey on Non – Parametric Technique (Data Envelopment Analysis)

Pages: 52-68
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Measuring Efficiency in Banks: A Brief Survey on Non – Parametric Technique (Data Envelopment Analysis)

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DOI: 10.18488/journal.62/2016.3.5/62.5.52.68

Khalad M. S. Alrafadi , Mazila Md Yusuf , Badrul Hisham Kamaruddin

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  1. Ariff, M. and L. Can, 2008. Cost and profit efficiency of Chinese banks: A non – parametric analysis. China Economic Review, 19(2): 260 – 273.
  2. Bauer, P.W., A.N. Berger, G.D. Ferrier and D.B. Humphrey, 1998. Consistency conditions for regulatory analysis of financial institutions: A comparison of frontier efficiency methods. Journal of Economics and Business, 50(8): 85 – 114.
  3. Berger, A.N. and D.B. Humphrey, 1997. Efficiency of financial institutions: International survey and directions for future research. European Journal of Operational Research, Elsevier, 98(2): 175-212.
  4. Brack, E. and R. Jimborean, 2009. Cost efficiency of French banks: 1- 30. Available from http://mpra.ub.uni-muenchen.de/23471/ [Accessed 25 August 2012].
  5. Bryce, C.L., 1996. Alternative approaches to estimating the efficiency of health maintenance organizations. ProQuest Dissertations & Theses: The Sciences and Engineering Collection.
  6. Casu, B. and P. Molyneux, 2003. A comparative study of efficiency in European banking. Applied Economics, 35(17): 1865-1876.
  7. Charnes, A., W. Cooper, A. Lewin and L. Seiford, 1994. Data envelopment analysis- theory, methodology and applications. Massachusetts, USA: Kluwer Academic Publisher Group.
  8. Charnes, A. and W.W. Cooper, 1962. Programming with linear fractional functionals. Naval Research Logistic Quarterly, 9(3 – 4): 181 – 186.
  9. Charnes, A., W.W. Cooper and E. Rhodes, 1978. Measuring the efficiency of decision making units. European Journal of Operational Research, 6(2): 429 -444. DOI 10.1016/0377-2217 (78)90138-8.
  10. Chen, X., M. Skully and K. Brown, 2005. Banking efficiency in China: Application of DEA to pre – and post – deregulation eras: 1993 – 2000. China Economic Review, 16(3): 229 – 245.
  11. Chu, S.F. and G.H. Lim, 1998. Share performance and profit efficiency of banks in an oligopolistic market: Evidence from Singapore. Journal of Multinational Financial Management, 8(2 – 3): 155 –168.
  12. Clemhout, S., 1968. The class of homothetic isoquant production functions. Review of Economic Studies, 35(1): 91-104.
  13. Cooper, W.W., L.M. Seiford and K. Tone, 2003. Data envelopment analysis: A comprehensive text with models, applications, references, and DEA solver software. Massachusetts, USA: Kluwer Academic Publisher Group.
  14. Cooper, W.W., L.M. Seiford and K. Tone, 2007. Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. 2nd Edn., New York: Springer.
  15. Cullinane, K., T.F. Wang, D.W. Song and P. Ji, 2006. The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontier analysis. Transportation Research Part A: Policy and Practice, 40(4): 354 – 374.
  16. Cummins, J.D. and H. Zi, 1996. Measuring cost efficiency in the US life insurance industry: Econometric and mathematical programming approaches. Working paper. Available from http://fic.wharton.upenn.edu/fic/papers/97/9703.pdf [Accessed 1 Feb. 2012].
  17. Farrell, M.J., 1957. The measurement of productive efficiency. Journal of the Roya Statistical Society, Series A, 120(3): 253–281.
  18. Hassan, M.K., 2006. X – efficiency in islamic banks. Islamic Economics Studies, 13(2): 49 – 78.
  19. Hassan, M.K., A. Al-Sharkas and A. Samad, 2004. An empirical study of relative efficiency of the banking industry in Bahrain. Studies in Economics and Finance, 22(2): 40-69.
  20. Isik, I. and M.K. Hassan, 2002. Technical, scale and allocative efficiencies of Turkish banking industry. Journal of Banking and Finance, 26(4): 719-766.
  21. Jacobs, R., 2001. Alternative methods to examine hospital efficiency: Data envelopment analysis and stochastic frontier analysis. Health Care Management Science, 4(2): 103 – 115.
  22. Kounetas, K. and K. Tsekouras, 2007. Measuring scale efficiency change using a translog distance function. International Journal of Business and Economics, 6(1): 63 – 69.
  23. Manadhar, R. and J. Tang, 2002. The evaluation of bank branch performance using data envelopment analysis: A framework. Journal of High Technology Management Research, 13(1): 1–17.
  24. McAllister, P.H. and D. McManus, 1993. Resolving the scale efficiency puzzle in banking. Journal of Banking and Finance, 17(213): 389-405.
  25. Mokhtar, H.S.A., N. Abdullah and M.S. Al – Habashi, 2008. Efficiency and competitions of islamic banking in Malaysia. Humanomics, 24(1): 28 – 48.
  26. Norman, M. and B. Stoker, 1991. Data envelopment analysis: The assessment of performance. England: John Wiley & Sons Ltd.
  27. Qureshi, M.A. and M. Shaikh, 2012. Efficiency of islamic and conventional banks in Pakistan: A non-parametric approach. International Journal of Business and Management, 7(7): 40 – 50.
  28. Sanchez, I., 2009. Technical and scale efficiency in Spanish urban transport: Estimating with data envelopment analysis. Available from http://www.hindawi.com/journals/aor/2009/721279 [Accessed 1 Feb 2012].
  29. Sathye, M., 2001. X – efficiency in Australian banking: An empirical investigation. Journal of Banking & Finance, 25(3): 613 – 630.
  30. Shahooth, K., A.H. Battall, K. Al – Delaimi and Al – Ani, 2006. Using data envelopment analysis to measure cost efficiency with an application on islamic banks. Scientific Journal Administrative Development, 4: 134 –156.
  31. Tecles, P.L. and B.M. Tabak, 2010. Determinants of bank efficiency: The case of Brazil. European Journal of Operational Research, 207(3): 1587–1598.
  32. Thanassoulis, E., 2003. Introduction to the theory and application of data envelopment analysis. Text Book, Library of Congress Control Number: 2001034441.
  33. Wheelock, D.C. and P.W. Wilson, 1999. Technical progress, inefficiency and productivity changes in US banking 1984-1993. Journal of Money, Credit and Banking, 31(2): 212 - 234.
  34. Zhu, J., 2003. Quantitative models for performance evaluation and benchmarking: Data envelopment analysis with spreadsheets and DEA excel solver. Massachusetts, USA: Worcester Polytechnic Institute.
Khalad M. S. Alrafadi , Mazila Md Yusuf , Badrul Hisham Kamaruddin (2016). Measuring Efficiency in Banks: A Brief Survey on Non – Parametric Technique (Data Envelopment Analysis). International Journal of Business, Economics and Management, 3(5): 52-68. DOI: 10.18488/journal.62/2016.3.5/62.5.52.68
Objective: This paper provides a survey of efficiency in banks using Data Envelopment Analysis (DEA) in developed and developing countries. Methods: There are two ways were used; the first one is analyse previous reviews, and the other one is systemic search from ProQuest, Emerald, Scopus and Science Direct. The search conducted to identify efficiency in banks in developed and developing countries. Originality: This study contributes in the existing literature in measuring efficiency in banks using DEA as a non – parametric technique. Results: Studies that was survey showed that the score of allocative efficiency was more than technical and cost efficiencies. Also, Studies showed that the scores of cost efficiency were more than the scores of profit efficiency. Conclusion: This paper shows that most of these studies were conducted in developed countries context, Also many studies were in developing countries. But, very few studies were conducted in the context of banking industry in Arab countries.

Contribution/ Originality
This study contributes to fill the gap in literature for studies were conducted to measure the efficiency of banking industry. Also it contributes in the body of knowledge by understanding the status of efficiency in the banking industry using non – parametric approach.