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Manuscript ID : 537058 Visit : 158 Page: 29 - 46

Article Type: Original Research

Design a Hybrid Model of Multi-Criteria Decision-Making Techniques for Ranking the Bank Branches

Subject Areas : Industrial Management

Pegah Aminijam 1 , Milad Jasemi Zargani 2

1 - MSc. in Industrial Engineering, Department of Industrial Engineering, Islamic Azad University, Masjed Soleyman Branch, Masjed Soleyman, Iran
2 - Assistant Professor at Industrial Engineering Department of Khaje Nasir Toosi University of Technology, Khaje Nasir Toosi University of Technology University, Tehran, Iran.

Received: 2016-02-28 Accepted : 2016-07-18 Published : 2016-09-08

Keywords:

Abstract :

Due to the importance of ranking bank branches and the lack of a comprehensive ranking model, which can lead to improved performance of the bank and the country economic growth, offering a hybrid multiple criteria decision-making (MCDM) model for ranking among bank branches is necessary. However, with the passing of time, MCDM methods have helped a lot in the rankings. But the choice of which methods is accepted as the best solution is always an ambiguity. Since the comprehensive hybrid algorithm that can identify the top branches not provided, yet. This research is trying to achieve the final ranking of the branches. Thus the optimal solution is to introduce a hybrid algorithm that determines the optimal weights of the MADM methods by a linear model. This approach is especially applicable when we cannot prefer any ranking method to others. Thus, in this paper, the criteria weights are obtained using DEMATEL and ANP methods. Afterward, the bank branches are ranked using TOPSIS, VIKOR, PROMETHEE II, SAW, WPM and DEA methods, each of which is important and significant. Finally, using proposed hybrid algorithm the optimal weights of different methods and the ranks are calculated.

References:


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_||_

  1. Aghaei, M., Asadollahi, A. & Pakari, A. (2013). Ranking of Saman bank’s branches in Tehran on the basis of customer satisfaction factors by F.M.C.D.M models, International Journal of Scientific Management and Development, 1(1), 46-61.
    2.
  2. Alidade, B. & Ghasemi, M. (2015). Ranking the branches of bank Sepah of Sistan Baluchistan using balanced score card and fuzzy multi-attribute decision-making methods, Research Journal of Recent Sciences, 4(1), 17-24.
    3.
  3. Anvary rostami, A.A., Hoseinian, Sh. & Rezaeiasl, M. (2012). Ranking Tehran Stock Exchange Corporations Using MADM, Management College of Tehran University, 14(1), 31-54. (in Persian).
    4.
  4. Asgharpoor, M.J. (2013). Multiple Criteria Decision Making. 11st edition, University of Tehran press, Iran. (in Persian).
    5.
  5. Azadeh, A., Ghaderi, S.F., Mirjalili, M. & Moghaddam, M. (2011). Integration of analytic hierarchy process and data envelopment analysis for assessment and optimization of personnel productivity in a large industrial bank. Expert System with Applications, 38, 5212-5225.
    6.
  6. Azar, A. & Vafaei, F. (2010). Ranking MADM methods using fuzzy multi-criteria decision-making methods in comparison with DEA method. Daneshvar (Raftar) Management and Achievement, 17th Year, 41, 23-38. (in Persian).
    7.
  7. Brans, J. P., Vincke, P. (1985). A preference ranking organization method (the PROMETHEE method for multiple criteria decision making). Management Science, 31(6), 647–656.
    8.
  8. Bridgman, P.W. (1922). Dimensional Analysis. Yale University Press: New Haven, CT.
    9.
  9. Charnes, A., Cooper, W.W. and Rhodes, E. (1978). Measuring efficiency of decision making units. European Journal of Operations Research, 2, 429-444.
    10.
  10. Eslami, Z., Bahramizenouz, M., Rajabi, M., & Mihani, M. (2011). The necessity of compiling the pattern ranking of banks and the proposed model.Investigation and risk control of Bank Sepah. (in Persian).
    11.
  11. Fazli, S. and Jafari, H. (2012). Developing a hybrid multi-criteria model for investment in stock exchange. Management Science Letters, 2, 457–468.
    12.
  12. Fishburn, P.C. (1967). Additive Utilities with Incomplete Product Set: Applications to Priorities and Assignments. Operations Research Society of America (ORSA), Baltimore.
    13.
  13. Gabus, A., & Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Geneva, Switzerland: Battelle Geneva Research Centre.
    14.
  14. Garcia, F., Guijarro, F., & Moya, I. (2010) Ranking Spanish savings banks: A multicriteria approach. Matematical and Computer Modelling, 52(7-8), 1058-1065.
    15.
  15. Hosseinzade Lotfi, F., Fallahnejad, R. & Navidi, N. (2011). Ranking efficient units in DEA by using TOPSIS method. Applied Mathematical Sciences, 5(17), 805-815.
    16.
  16. Hwang, C.L. and Yoon. K. (1981). Multiple attribute decision making: methods and applications. Lecture Notes in Economics and Mathematical Systems, (186). Now York: Springer-Verlag.
    17.
  17. Kazemi, A.  &Mousavi, J. (2013). Ranking Iranian private banks using multi-criteria decision-making methods. Journal of Quantitative Research in Management, 3, 121-140. (in Persian).
    18.
  18. Mahmudi, A. & Bagherlou, H. (2014). Ranking the bank stock with multi-criteria decision-making method. 3th Iranian Management & Accounting Conference, Tehran University. (in Persian).
    19.
  19. Miller, D. W. & Starr, M. K. (1969). Executive Decisions and Operation Research, Prentice-Hall, Inc: Englewood Cliffs, NJ.
    20.
  20. Mohammadizanjirani, d., Salimifard, Kh.k. & Yousefidehbidi, sh. (2014). Check the performance of the most common multi-criteria decision-making techniques with optimization approach. Journal of Operational Research in Its Applications, 1(40), 84-65. (in Persian).
    21.
  21. Momeni, M. (2006). Modern discussion about operational research, 1st edition, Management College of Tehran University, Tehran, Iran. (in Persian).
    22.
  22. Motameni, A.R., Javadzadeh, M. & Tizfahm, M. (2010). The strategy performance evaluation of the banks. Journal of Strategic Management Studies, 1, 159-141.
    23.
  23. Najafipashaki K., (2002). Performance evaluation of the Etka organization’s factories using functional models AHP and TOPSIS (M.A thesis in industrial management). University of Tehran, Tehran, Iran. (in Persian).
    24.
  24. Nilashi, M., Zakaria, R., Ibrahim, O., Majid, M. Z. A., Zin, R. M., & Farahmand, M. (2014). MCPCM: A DEMATEL-ANP based multi-criteria decision-making approach to evaluate the critical success factors in construction projects. Arabian Journal for Science and Engineering, 40(2), 343-361.
    25.
  25. Onder, E., Tas, N. & Hepsen, A. (2013). Performance Evaluation of Turkish Banks Using Analytical Hierarchy Process and TOPSIS Methods. Journal of International Scientific Publication: Economy & Business, 7, Part 1, 470-503.
    26.
  26. Opricovic, S. (1998). Multicriteria Optimization of Civil Engineering Systems, Faculty of Civil Engineering, Belgrade, Serbia.
    27.
  27. Paradi, J. C., Rouatt, S. & Zhu, H. (2011). Two-stage evaluation of bank branch efficiency using data envelopment analysis, Omega, 39, 99-109.
    28.
  28. Paradi, J. C., & Zhu, H. (2013). A survey on bank branch efficiency and performance research with data envelopment analysis. Omega, 41(1), 61-79.
    29.
  29. Peng, Y., Kou, G., Wang, G. & Shi, Y. (2011). FAMCDM: A fusion approach of MCDM methods to rank multiclass classification algorithms, Omega, 39, 677-689.
    30.
  30. Pourkazemi, M.H. (2007). Grading bank branches. Economics Research, 26, 305-348. (in Persian).
    31.
  31. Rasoulinejad, E. (2009). Ranking of selected branches of Bank Saderat in Tehran using the integrated model DEAHP and ANP (M.A thesis in industrial management). University of Tehran, Tehran, Iran. (in Persian).
    32.
  32. Rosenzweig, V., Volarević, H. & Varović, M. (2012). Profitability as a business goal: the multicriteria approach to the ranking of the five largest Croatian banks. Business Systems Research, 3(1), 37-48.
    33.
  33. Saaty, T.L. (1996). The Analytic Network Process: Decision Making with Dependence and Feedback. the Organization and Prioritization of Complexity, RWS publications.
    34.
  34. Saaty, T.L. (2005). The analytic hierarchy and analytic network processes for the measurement of intangible criteria and for decision-making. In: Multiple Criteria Decision Analysis: State of the Art Surveys. Springer, New York, 345–405.
    35.
  35. Secme, N. Bayrakdaroglu, A., & Kahraman, C. (2009). Fuzzy  performance  evaluation  in  Turkish  Banking Sector using Analytic Hierarchy Process and TOPSIS. Expert Systems with Applications, 36(9), 11699–11709.
    36.
  36. Shahbandarzadeh, h. (2006). Design the method evaluated the performance bank branches by using multi criteria decision making techniques (Doctoral dissertation). University of Tehran. Tehran, Iran. (in Persian)
    37.
  37. Stanujkic, D., Dordevic, B. & Dordevic, M. (2013). Comparative Analysi of Some Prominent MCDM Methods: A Case of Ranking Serbian Banks, Serbian Journal of Management, 8(2), 213 – 241.
    38.
  38. Triantaphyllou, E. (2000). Multi-Criteria Decision Making: A Comparative Study. Dordrecht, The Netherlands: Kluwer Academic Publishers (now Springer).
    39.
  39. Tzeng. G-H and Huang. J-J. (2011). Multiple Attribute Decision Making Methods and applications. CRC Press is an imprint of Taylor & Francis Group, an Informa business A CHAPMAN & HALL BOOK. International Standard Book Number: 978-1-4398-6157-8 (Hardback).
    40.
  40. Wang, J-J., Jing, Y-Y., Zhang, C-F. & Zhao, J-H. (2009). Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Reviews,13(9), 2263–2278.
    41.

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