The performance evaluation of banks using balanced scorecard, fuzzy AHP and fuzzy TOPSIS techniques and the offering of solutions to performance improvement of banks

2020 ◽  
Vol 35 (2) ◽  
pp. 204
Author(s):  
Negin Akbarei ◽  
Mostafa Vaezi Monfard ◽  
Elahe Sarfi
Keyword(s):  
Performance Evaluation ◽  
Performance Improvement ◽  
Balanced Scorecard ◽  
Fuzzy Ahp ◽  
Fuzzy Topsis

A Modified Balanced Scorecard Based Hybrid Pythagorean Fuzzy AHP-Topsis Methodology for ATM Site Selection Problem

2020 ◽  
Vol 19 (02) ◽  
pp. 365-384 ◽  
Author(s):  
Aslihan Yildiz ◽  
Ertugrul Ayyildiz ◽  
Alev Taskin Gumus ◽  
Coskun Ozkan
Keyword(s):  
Balanced Scorecard ◽  
Delphi Method ◽  
Site Selection ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Fuzzy Topsis ◽  
Selection Problem ◽  
Modified Delphi Method ◽  
Modified Delphi ◽  
Comparison Results

Researchers work on facility location problems in different structures and solve them by developing different models over the years. In this study, we focus on the automated teller machine (ATM) site selection problem for a public bank in İstanbul. Twenty-five districts, which are located at the European side of İstanbul, are designated as ATM candidate districts. The balanced scorecard (BSC) model is modified to determine the criteria according to the literature review and experts’ judgments for this problem. Internal, Customer, and Financial perspectives of the traditional BSC model are used as the main criteria and an external perspective is considered as the fourth criterion for modified balanced scorecard. The experts’ criteria evaluations are gained and consolidated by the Modified Delphi Method. The criteria weights are determined by the Pythagorean Fuzzy-AHP method using the final pairwise comparison results obtained from the Modified Delphi Method. Subsequently, the Pythagorean Fuzzy TOPSIS method is applied to determine the best alternative site among alternatives to locate the ATM according to these criteria. Finally, the results are presented and discussed by sensitivity analysis.

A hybrid MCDM approach for performance evaluation in the banking industry

Kybernetes ◽  
2017 ◽  
Vol 46 (8) ◽  
pp. 1386-1407 ◽  
Author(s):  
Mohammad Ali Beheshtinia ◽  
Sedighe Omidi
Keyword(s):  
Performance Evaluation ◽  
Balanced Scorecard ◽  
Banking Industry ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Topsis ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Environmental Care ◽  
Hybrid Approaches ◽  
Copeland Method

Purpose This paper aims to propose a hybrid multiple criteria decision-making (MCDM) technique for performance evaluation of banks in which the banks are assessed and ranked according to the criteria of the balanced scorecard (BSC) methodology and corporate social responsibility (CSR) views. Design/methodology/approach To clarify the performance of the proposed model, the MCDM technique was implemented in four banks in Iran as a pilot. First, proper criteria for banking industry are identified considering BSC and CSR. Consequently, analytic hierarchy process (AHP) and modified digital logic (MDL) techniques are used to determine the weights of criteria. The banks are ranked by fuzzy TOPSIS (FTOPSIS) and fuzzy VIKOR (FVIKOR). Using a combination of these techniques, four methods, namely, AHP-FTOPSIS, AHP-FVIKOR, MDL-FTOPSIS and MDL-FVIKOR, are obtained, each of which provides a different set of rankings for banks. Eventually, the obtained ranks are integrated using the Copeland method. Findings The results showed that the return on investment, debt ratio and lower energy consumption criteria are the most important, and enhancement of brand value, increasing customer loyalty and environmental care criteria have the lowest percentage of importance. Also, the final bank ranking is determined by the proposed method. Originality/value This paper identifies 6 criteria and 25 sub-criteria for evaluating the banks considering BSC and CSR viewpoints including some new sub-criteria that has not been considered before. Moreover, these hybrid approaches and especially MDL techniques have not been used by previous researchers.

scholarly journals Research on the Construction of Performance Indicators for the Marketing Alliance of Catering Industry and Credit Card Issuing Banks by Using the Balanced Scorecard and Fuzzy AHP

2020 ◽  
Vol 12 (21) ◽  
pp. 9005
Author(s):  
Jui-Te Chiang ◽  
Chei-Chang Chiou ◽  
Shuh-Chyi Doong ◽  
I-Fang Chang
Keyword(s):  
Performance Evaluation ◽  
Balanced Scorecard ◽  
Strategic Alliances ◽  
Credit Card ◽  
Fuzzy Ahp ◽  
Academic Community ◽  
Catering Industry ◽  
Marketing Alliance ◽  
Marketing Alliances ◽  
Process Factors

In recent years, strategic alliances have seen explosive growth in various practical fields. Various forms of strategic alliances and cooperation models have been widely used among various organizations and have received considerable attention from academic and practical circles. However, there are many factors that affect the success of marketing alliances, and the academic community has not reached a conclusion and consensus. Among them, the establishment and monitoring of a performance evaluation mechanism is one of the key points. In the past, many academic studies have devoted themselves to the establishment of performance evaluation mechanisms for many different industries, but few of them have focused on the establishment of performance evaluation mechanisms for marketing alliances between the service industry and the banking industry. The purpose of this study is to assist in the establishment of performance evaluation indicators for marketing alliance between the catering industry and credit card issuing banks by using expert Delphi, fuzzy analytic hierarchy process and balanced scorecard methods. The main result of this study is to establish five key performance evaluation indicators including customer factors, cooperative alliance factors, financial factors, learning and growth factors, and internal process factors. In terms of secondary indicators, there are seven customer sub-factors, six cooperative alliance sub-factors, five financial sub-factors, seven internal processes sub-factors, and five learning and growth sub-factors, totaling 30 sub-factors. The research results can be used as a reference for academic and practical areas.

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