An integrated stochastic fuzzy MCDM approach to the balanced scorecard-based service evaluation
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CitationDinçer, H. ve Yüksel, S. (2019). An integrated stochastic fuzzy MCDM approach to the balanced scorecard-based service evaluation. Mathematics and Computers in Simulation, 166, 93-112. https://hdl.handle.net/20.500.12511/844
The purpose of the study is to analyse the balanced scorecard (BSC)-based evaluation of the new service development (NSD) in Turkish banking sector. The proposed model includes fuzzy ANP (FANP), Monte Carlo Simulation, fuzzy TOPSIS (FTOPSIS), and fuzzy VIKOR (FVIKOR) respectively. FANP has been used for weighting the criteria, Monte Carlo Simulation has been applied to provide the stochastic values of BSC-based dimensions of NSD in banking sector. FTOPSIS and FVIKOR have been considered to rank the banks by their dimension performances. The novelty of the study is to provide an integrated model including FANP, FTOPSIS, FVIKOR, and Monte Carlo Simulation respectively. Additionally, BSC-based analysis of NSD has been applied for evaluating Turkish banking sector. The results demonstrate that the comparative analysis is coherent for ranking the alternatives and the stochastic values facilitate to obtain the immense expert evaluations under the fuzzy environment. It is identified that the performance of the foreign banks is lower than private and state banks. Hence, it can be said that especially foreign banks should develop new services to attract the attention of their customers. Within this framework, customer expectations should be defined by conducting a detailed analysis. As a result, it can be possible to increase comparative advantage in comparison with the other banks.