Performance Evaluation of Banking Organizations Using the New Proposed Integrated DEA-BSC Model

محورهای موضوعی : Manufacturing process monitoring and control

Kianoosh Kianfar ¹ , Mahnaz Ahadzadeh Namin ² , Akbar Alam Tabriz ³ , Esmaeil Najafi ⁴ , Farhad Hosseinzadeh Lotfi ⁵

1 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Department of Mathematics, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
3 - Department of Management, Shahid Beheshti University, Tehran, Iran
4 - Department of Industrial Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran
5 - Department of Mathematics, Science and Research branch, Islamic Azad University, Tehran, Iran

تاریخ دریافت : 1398/04/04 تاریخ پذیرش : 1398/09/27 تاریخ انتشار : 1397/11/12

کلید واژه: goal programming, Data envelopment analysis, Balanced Scorecard, Decision Making Units, Weighting Objective Function, Multi Objective Programming,

چکیده مقاله :

Data envelopment analysis (DEA) is a nonparametric approach to estimate relative efficiency of Decision Making Units (DMUs). DEA is one of the best quantitative approaches and balanced scorecard (BSC) is one of the best qualitative methods to measure efficiency of an organization. Since simultaneous evaluation of network performance of the quad areas of BSC model is considered as a necessity and separate use of DEA and BSC is not effective and leads to miscalculation of performance, integrated DEA-BSC model is applied. Regarding to multi-objective nature of the proposed model, two techniques including goal programming and weighted average method are used to solve such problems. At the end of the study, based on data relating to indexes of quad areas of BSC model, the results of the mentioned methods are compared. Besides assessing validation of the proposed model, the overall efficiency and each of the different stages of BSC are obtained. So that, finding a model for decision making units in various stages of BSC is the innovation of this research study.

منابع و مأخذ:

[1] Varmazyar, M., Dehghanbaghi ,M. and Afkhami, M. 2016. A Novel Hybrid MCDM Model for Performance Evaluation of Research and Technology Organizations based on BSC Approach. Evaluation and Program Planning. 58: 125–140.

[2] Wang, J., Liu, S-Y. and Zhang, J. 2005. An Extension of TOPSIS for Fuzzy MCDM Based on Vague Set Theory. Journal of Systems Science and Systems Engineering. 14(1): 73–84.

[3] Yin, Y., Qin, S. and Holland R. 2011. Development of a Design Performance Measurement Matrix for Improving Collaborative Design During a Design Process. International Journal of Productivity and Performance Management. 60(2): 152–184.

[4] Tansel, Y. 2012. An Experimental Design Approach Using TOPSIS Method for the Selection of Computer-Integrated Manufacturing Technologies. Robotics and Computer-Integrated Manufacturing. 28(2): 245-256.

[5] Sexton, T.R. and Lewis, H.F. 2003. Two-stage DEA: An Application to Major League Baseball. Journal of Productivity Analysis. 19(2): 227-249.

[6] Despotis, D.K. and Koronakos, G. 2014. Efficiency Assessment in Two-stage Processes: A Novel Network DEA Approach. Pro. Computer Science. 31: 299-307.

[7] Carayannis, E.G., Goletsis Y. and Grigoroudis, E. 2015. Multi-level Multi-Stage Efficiency Measurement: The Case of Innovation Systems. Operations Research. 15(2): 253–274.

[8] Jarosz, P., Kusiak, J., MaBecki, S.B., Oprocha, P., Sztangret, A. and Wilkus, M. A. 2015. Methodology for Optimization in Multistage Industrial Processes: A Pilot Study. Mathematical Problems in Engineering. 1-10.

[9] Gang, D., Li, C., Yin-Zhen, L., Jie-Yan, S. and Tanweer, A. 2012. Optimization on Production-Inventory Problem with Multistage and Varying Demand.Journal of Applied Mathematics. 1-17.

[10] Charnes, A., Cooper, W.W. and Rhodes, E. 1978. Measuring the Efficiency of Decision Making Units. European Journal of Operational Research. 2(6): 429-444.

[11] Banke, R., Charnes, A. and Cooper, W.W.  1984. Some models for estimating technical and scale inefficiencies in data envelopment analysis.Management Science. 30 (9): 1078-1092.

[12] KazemiMatin, R. and Azizi R. 2015. A Unified Network-DEA Model for Performance Measurement of Production Systems. Measurement. 60: 186–193.

[13] Chiang, C.Y. and Lin, B. 2009. An Integration of Balanced Scorecards and Data Envelopment Analysis for Firm's Benchmarking Management. Journal of Total Quality Management & Business Excellence. 20(11): 1153-1172.

[14] Kádárová, J., Durkáčová, M., Teplická, K. and Kádár, G. 2015. The Proposal of an Innovative Integrated BSC – DEA Model. Procedia Economics and Finance. 23: 1503 – 1508.

[15] Kaplan, R.S. and Norton D.P. 1996. The Balanced Scorecard: Translating Strategy into Action. Boston: Harvard Business School Press.

[16] Ehsanbakhsh, H. and Izadikhah, M. 2015. Applying BSC-DEA Model to Performance Evaluation of Industrial Cooperatives: An Appliction of Fuzzy Inference System. Applied Research Journal. 1(1): 9-26.