Examining the Competitiveness in European Banking Industry with Fuzzy AHP and Fuzzy TOPSIS Approaches

Year 2021, Volume: 3 Issue: 1, 47 - 68, 29.06.2021

Serhat Yuksel , Hasan Dinçer

https://doi.org/10.51524/uhusbad.843949

Abstract

This study aims to evaluate the competitiveness in European banking industry. For this purpose, 5 European countries, which have the highest GDP, are considered in this study that are Germany, France, United Kingdom, Italy, and Spain. Moreover, 6 different criteria are selected based on the literature review. Fuzzy AHP method is considered to understand the significance of the dimensions and criteria. On the other side, fuzzy TOPSIS model is used to rank these 5 European countries according to competitiveness in the banking industry. The findings show that low cost is the most significant criterion for this condition. In addition to this issue, it is also concluded that Germany and France are on the first ranks regarding the competitiveness in the banking industry. Hence, it is recommended that European banks should firstly concentrate on the cost effectiveness in order to increase the competitive power. In this framework, a detailed analysis should be conducted to understand which cost types are greater in comparison with the others. Hence, it can be possible to minimize the costs of the banks so that these banks can offer lower prices to their customers. This situation has a positive impact on the competitive power of the banks.

Keywords

European Banking Sector, Competitiveness, Fuzzy AHP, Fuzzy TOPSIS

Examining the Competitiveness in European Banking Industry with Fuzzy AHP and Fuzzy TOPSIS Approaches

Abstract

Bu çalışma, Avrupa bankacılık sektöründeki rekabet gücünü değerlendirmeyi amaçlamaktadır. Bu doğrultuda, en yüksek GSYİH'ye sahip 5 Avrupa ülkesi olan Almanya, Fransa, Birleşik Krallık, İtalya ve İspanya bu çalışmanın kapsamına dahil edilmiştir. Ayrıca, literatür taraması sonuçlarına göre, 6 farklı kriter seçilmiştir. Bulanık AHP yöntemi ile boyutların ve kriterlerin önem ağırlıkları hesaplanmıştır. Öte yandan, bulanık TOPSIS modeli, bankacılık sektöründeki rekabet gücüne göre bu 5 Avrupa ülkesini sıralamak için kullanılmaktadır. Bulgular düşük maliyetin bu durum için en önemli kriter olduğunu göstermektedir. Bu konuya ek olarak, Almanya ve Fransa'nın da bankacılık sektöründe rekabet gücü açısından ilk sıralarda yer aldığı sonucuna varılmıştır. Bu nedenle Avrupa bankalarının rekabet gücünü artırmak için öncelikle maliyet etkinliğine odaklanmaları önerilmektedir. Bu çerçevede, hangi maliyet türlerinin diğerlerine göre daha yüksek olduğunu anlamak için ayrıntılı bir analiz yapılmalıdır. Böylelikle, bu bankaların müşterilerine daha düşük fiyatlar sunabilmeleri için bankaların maliyetlerini minimize edebilmek mümkün olabilecektir. Bu durum, bankaların rekabet gücünün artmasına katkı sağlayacaktır.

Keywords

Avrupa Bankacılık Sektörü, Rekabet Gücü, Bulanık AHP, Bulanık TOPSIS

References

• Adams, A. M., Bashiru, M., & Abdulai, I. A. (2016). Customer satisfaction in the banking industry in Ghana: A case of GCB bank limited in Wa municipality. Journal of Social Science Studies, 3(2), 217.
• Agolla, J. E., Makara, T., & Monametsi, G. (2018). Impact of banking innovations on customer attraction, satisfaction and retention: the case of commercial banks in Botswana. International Journal of Electronic Banking, 1(2), 150-170.
• Alshubaily, N. F., & Altameem, A. A. (2017). The Role of Strategic Information Systems (SIS) in Supporting and Achieving the Competitive Advantages (CA): An Empirical Study on Saudi Banking Sector. Int. J. Adv. Comput. Sci. Apllocations, 8(7), 128-139.
• Awasthi, A., Govindan, K., & Gold, S. (2018). Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. International Journal of Production Economics, 195, 106-117.
• Bapat, D. (2017). Linking strategic orientation with performance: Implication for Indian banks. Strategic Change, 26(4), 403-411.
• Basheer, M. F., Hussain, T., Hussan, S. G., & Javed, M. (2015). Impact of customer awareness, competition and interest rate on growth of Islamic banking in Pakistan. International Journal of Scientific & Technology Research, 4(8), 33-40.
• Bereznoi, A. (2015). Business model innovation in corporate competitive strategy. Problems of Economic Transition, 57(8), 14-33.
• Beskese, A., Demir, H. H., Ozcan, H. K., & Okten, H. E. (2015). Landfill site selection using fuzzy AHP and fuzzy TOPSIS: a case study for Istanbul. Environmental Earth Sciences, 73(7), 3513-3521.
• Bos, J. W., Kolari, J. W., & Van Lamoen, R. C. (2013). Competition and innovation: Evidence from financial services. Journal of Banking & Finance, 37(5), 1590-1601.
• Burks, J. J., Cuny, C., Gerakos, J., & Granja, J. (2018). Competition and voluntary disclosure: Evidence from deregulation in the banking industry. Review of Accounting Studies, 23(4), 1471-1511.
• Carbó, S., Humphrey, D., Maudos, J., & Molyneux, P. (2009). Cross-country comparisons of competition and pricing power in European banking. Journal of International Money and Finance, 28(1), 115-134.
• Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European journal of operational research, 95(3), 649-655.
• Chen, J. F., Hsieh, H. N., & Do, Q. H. (2015). Evaluating teaching performance based on fuzzy AHP and comprehensive evaluation approach. Applied Soft Computing, 28, 100-108.
• Chiaramonte, L., & Casu, B. (2017). Capital and liquidity ratios and financial distress. Evidence from the European banking industry. The British Accounting Review, 49(2), 138-161.
• Claessens, S., & Van Horen, N. (2015). The impact of the global financial crisis on banking globalization. IMF Economic Review, 63(4), 868-918.
• Coccorese, P., & Pellecchia, A. (2013). Multimarket contact, competition and pricing in banking. Journal of International Money and Finance, 37, 187-214.
• Cornaggia, J., Mao, Y., Tian, X., & Wolfe, B. (2015). Does banking competition affect innovation?. Journal of financial economics, 115(1), 189-209.
• Dal Colle, A. (2018). The mechanics of commercial banking liberalization and growth. Journal of Banking & Finance, 86, 194-203.
• Dinçer, H., & Yüksel, S. (2018). Comparative evaluation of BSC-based new service development competencies in Turkish banking sector with the integrated fuzzy hybrid MCDM using content analysis. International Journal of Fuzzy Systems, 20(8), 2497-2516.
• Dinçer, H., & Yüksel, S. (2019a). Multidimensional evaluation of global investments on the renewable energy with the integrated fuzzy decision‐making model under the hesitancy. International Journal of Energy Research, 43(5), 1775-1784.
• Dincer, H., & Yuksel, S. (2019b). Balanced scorecard-based analysis of investment decisions for the renewable energy alternatives: A comparative analysis based on the hybrid fuzzy decision-making approach. Energy, 175, 1259-1270.
• Dinçer, H., & Yüksel, S. (2019c). An integrated stochastic fuzzy MCDM approach to the balanced scorecard-based service evaluation. Mathematics and Computers in Simulation.
• Dincer, H., Hacioglu, U., & Yuksel, S. (2016). Balanced scorecard-based performance assessment of Turkish banking sector with analytic network process. International Journal of Decision Sciences & Applications-IJDSA, 1(1), 1-21.
• Dinçer, H., Hacıoğlu, Ü., & Yüksel, S. (2016b). The Impacts of Financial Variables on Employment Planning in Turkish Banking Sector. International Journal of Sustainable Entrepreneurship and Corporate Social Responsibility (IJSECSR), 1(2), 1-20.
• Dinçer, H., Hacıoğlu, Ü., & Yüksel, S. (2017). A Strategic Approach to Global Financial Crisis in Banking Sector: A Critical Appraisal of Banking Strategies Using Fuzzy ANP and Fuzzy Topsis Methods. International Journal of Sustainable Economies Management (IJSEM), 6(1), 1-21.
• Dinçer, H., Hacıoğlu, Ü., & Yüksel, S. (2017b). Türk Bankacılık Sektöründe Dengeli Skorkart Temelli Yeni Hizmet Geliştirme Yetkinliğinin Bulanık Mantık Çerçevesinde Hibrit Çok Kriterli Karar Verme Yöntemiyle Karşılaştırmalı Analizi. Bankacılar Dergisi, 103, 3-33.
• Dincer, H., Hacioglu, U., Tatoglu, E., & Delen, D. (2016). A fuzzy-hybrid analytic model to assess investors' perceptions for industry selection. Decision Support Systems, 86, 24-34.
• Dinçer, H., Yüksel, S., & Martínez, L. (2019). Analysis of Balanced Scorecard-based SERVQUAL Criteria based on Hesitant Decision-making Approaches. Computers & Industrial Engineering.
• Dincer, H., Yüksel, S., & Martinez, L. (2019d). Balanced scorecard-based Analysis about European Energy Investment Policies: A hybrid hesitant fuzzy decision-making approach with Quality Function Deployment. Expert Systems with Applications, 115, 152-171.
• Dinçer, H., Yüksel, S., Eti, S., & Tula, A. (2019f). Effects of Demographic Characteristics on Business Success: An Evidence From Turkish Banking Sector. In Handbook of Research on Business Models in Modern Competitive Scenarios (pp. 304-324). IGI Global.
• Dinçer, H., Yüksel, S., Kartal, M. T., & Alpman, G. (2019e). Corporate Governance-Based Evaluation of Alternative Distribution Channels in the Turkish Banking Sector Using Quality Function Deployment With an Integrated Fuzzy MCDM Method. In Intergenerational Governance and Leadership in the Corporate World: Emerging Research and Opportunities(pp. 39-77). IGI Global.
• Dincer, Hasan, and Umit Hacioglu. "Performance evaluation with fuzzy VIKOR and AHP method based on customer satisfaction in Turkish banking sector." Kybernetes 42.7 (2013): 1072-1085.
• Ervural, B. C., Zaim, S., Demirel, O. F., Aydin, Z., & Delen, D. (2018). An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable and Sustainable Energy Reviews, 82, 1538-1550.
• Eti, S. (2019). The Use of Quantitative Methods in Investment Decisions: A Literature Review. In Handbook of Research on Global Issues in Financial Communication and Investment Decision Making (pp. 256-275). IGI Global.
• Eti, S., Dinçer, H., & Yüksel, S. (2019). G20 Ülkelerinde Bankacılık Sektörünün 5 Yıllık Geleceğinin Arıma Yöntemi İle Tahmin Edilmesi. Uluslararası Hukuk ve Sosyal Bilim Araştırmaları Dergisi, 1(1), 26-38.
• Eti, S., Kalkavan, H., Dinçer, H., & Yüksel, S. (2020). Predicting the Role of Islamic Banking on Sustainable Economic Development: An Analysis for Turkey With ARIMA Model. In Handbook of Research on Creating Sustainable Value in the Global Economy (pp. 146-164). IGI Global.
• Fernández, R. O., & Garza-García, J. G. (2015). The relationship between bank competition and financial stability: a case study of the Mexican banking industry. Ensayos Revista de Economía (Ensayos Journal of Economics), 34(1), 103-120.
• Fontin, J. R., & Lin, S. W. (2019). Comparison of banking innovation in low-income countries: A meta-frontier approach. Journal of Business Research, 97, 198-207.
• Ghosh, A. (2017). How does banking sector globalization affect economic growth?. International Review of Economics & Finance, 48, 83-97.
• Gozman, D., Liebenau, J., & Mangan, J. (2018). The innovation mechanisms of fintech start-ups: insights from SWIFT’s innotribe competition. Journal of Management Information Systems, 35(1), 145-179.
• Gunasekaran, A., Subramanian, N., & Papadopoulos, T. (2017). Information technology for competitive advantage within logistics and supply chains: A review. Transportation Research Part E: Logistics and Transportation Review, 99, 14-33.
• Guo, S., & Zhao, H. (2015). Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective. Applied Energy, 158, 390-402.
• Gupta, H., & Barua, M. K. (2017). Supplier selection among SMEs on the basis of their green innovation ability using BWM and fuzzy TOPSIS. Journal of Cleaner Production, 152, 242-258.
• Hes, A., & Jílková, P. (2016). Position of Low-Cost Banks on the Financial Market in the Czech Republic. European Research Studies, 19(4), 42.
• Hu, T., & Xie, C. (2016). Competition, innovation, risk-taking, and profitability in the chinese banking sector: An empirical analysis based on structural equation modeling. Discrete Dynamics in Nature and Society, 2016.
• Hwang, C.L. K. Yoon. (1981). Multiple Attributes Decision Making Methods and Applications. Springer, Berlin Heidelberg.
• Jun, Q., Dinçer, H., & Yüksel, S. (2020). Stochastic hybrid decision‐making based on interval type 2 fuzzy sets for measuring the innovation capacities of financial institutions. International Journal of Finance & Economics.
• Kalkavan, H. (2020). The Relation Between Corporate Social Responsibility and Financial Performance: Reviewing Empirical Studies and Discussing the Ethical Aspect. In Strategic Outlook for Innovative Work Behaviours (pp. 179-191). Springer, Cham.
• Kalkavan, H., & Ersin, I. (2019). Determination of Factors Affecting the South East Asian Crisis of 1997 Probit-Logit Panel Regression: The South East Asian Crisis. In Handbook of Research on Global Issues in Financial Communication and Investment Decision Making (pp. 148-167). IGI Global.
• Kalkavan, H., Eti, Serkan, & Yüksel, S. (2020). Türkiye’deki Bankacilik Sektörü, Sanayi Gelişimi ve Ekonomik Büyüme Arasindaki İlişkinin VAR Analizi ile İncelenmesi. Akademik Araştırmalar ve Çalışmalar Dergisi (AKAD), 12(22), 56-74.
• Karabag, S. F. (2019). Factors impacting firm failure and technological development: A study of three emerging-economy firms. Journal of Business Research, 98, 462-474.
• Kasasbeh, E. A., Harada, Y., & Noor, I. M. (2017). Developing A Conceptual Model For the Relationship Between Human Resource Management, E-Business Strategies and Competitive Advantage. The Journal of Internet Banking and Commerce, 22(1).
• Kasımoğlu, M., Göre, Z. S., & Altın, E. (2016). Competitiveness Analysis of Istanbul Financial Center. Procedia-Social and Behavioral Sciences, 235, 771-781.
• Kim, J. B., Ma, M. L., & Wang, H. (2015). Financial development and the cost of equity capital: Evidence from China. China Journal of Accounting Research, 8(4), 243-277.
• Kotarba, M. (2016). New factors inducing changes in the retail banking customer relationship management (CRM) and their exploration by the FinTech industry. Foundations of management, 8(1), 69-78.
• Li, X., Zhu, S., Yüksel, S., Dinçer, H., & Ubay, G. G. (2020). Kano-based mapping of innovation strategies for renewable energy alternatives using hybrid interval type-2 fuzzy decision-making approach. Energy, 211, 118679.
• Li, Y. X., Wu, Z. X., Dinçer, H., Kalkavan, H., & Yüksel, S. (2021). Analyzing TRIZ-based strategic priorities of customer expectations for renewable energy investments with interval type-2 fuzzy modeling. Energy Reports, 7, 95-108.
• Lima-Junior, F. R., & Carpinetti, L. C. R. (2016). Combining SCOR® model and fuzzy TOPSIS for supplier evaluation and management. International Journal of Production Economics, 174, 128-141.
• Litvintseva, G. P., & Gakhova, N. A. (2016, October). Trends in high-technologic industries development in Russia. In 2016 13th International Scientific-Technical Conference on Actual Problems of Electronics Instrument Engineering (APEIE) (Vol. 3, pp. 256-262). IEEE.
• Mangla, S. K., Kumar, P., & Barua, M. K. (2015). Risk analysis in green supply chain using fuzzy AHP approach: A case study. Resources, Conservation and Recycling, 104, 375-390.
• Mosadeghi, R., Warnken, J., Tomlinson, R., & Mirfenderesk, H. (2015). Comparison of Fuzzy-AHP and AHP in a spatial multi-criteria decision making model for urban land-use planning. Computers, Environment and Urban Systems, 49, 54-65.
• Nowakowski, M., & Karasiewicz, G. (2016). Market structure and price-cost margins in European retail gasoline industry. Journal of Management and Business Administration, 24(3), 105-124.
• Parameswar, N., Dhir, S., & Dhir, S. (2017). Banking on innovation, innovation in banking at ICICI bank. Global Business and Organizational Excellence, 36(2), 6-16.
• Paul, J., Mittal, A., & Srivastav, G. (2016). Impact of service quality on customer satisfaction in private and public sector banks. International Journal of Bank Marketing, 34(5), 606-622.
• Perçin, S., & Aldalou, E. (2018). Financial Performance Evaluation of Turkish Airline Companies Using Integrated Fuzzy AHP Fuzzy TOPSIS Model. Uluslararası İktisadi ve İdari İncelemeler Dergisi,(18. EYİ Özel Sayısı), 583-598.
• Qiu, D., Dinçer, H., Yüksel, S., & Ubay, G. G. (2020). Multi-Faceted Analysis of Systematic Risk-Based Wind Energy Investment Decisions in E7 Economies Using Modified Hybrid Modeling with IT2 Fuzzy Sets. Energies, 13(6), 1423.
• Rahman, A. (2017). Assessment of Self-Service Banking in Bangladesh: Are Private Commercial Banks One Step Further Building Customer Centric Model or Becoming Money Making Machines in Market Competition?. Available at SSRN 2919778.
• Raičević, B., Ignjatijević, S., & Milojević, I. (2016). Financial analysis of foreign direct investment on economic growth of developing countries. Economics of agriculture, 63(2), 649-663.
• Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of mathematical psychology, 15(3), 234-281.
• Schliephake, E. (2016). Capital regulation and competition as a moderator for banking stability. Journal of Money, Credit and Banking, 48(8), 1787-1814.
• Şengül, Ü., Eren, M., Shiraz, S. E., Gezder, V., & Şengül, A. B. (2015). Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renewable Energy, 75, 617-625.
• Setyawati, I., Widyastuti, T., Suryati, A., & Hartani, N. (2019). Intellectual capital performance of Islamic banks in Indonesia: Towards competitive advantages. Management Science Letters, 9(12), 1999-2008.
• Sircar, S., Agrawal, R., Shanthi, S. K., Reddy, K. S., Bapat, D., & Mazumdar, D. (2015). Assessment of business strategy: Implication for Indian banks. Journal of Strategy and Management.
• Stenbacka, R., & Takalo, T. (2019). Switching costs and financial stability. Journal of Financial Stability, 41, 14-24.
• Sudha, K., & Kavita, A. (2019). Implementation of Business Process Re-engineering and its impact on Financial Performance of Banks (With Special Reference to State Bank of India). Advances in Management, 12(1), 71-73.
• Suhidayat, T., Affandi, A., & Sidharta, I. (2016). Service Quality on Customer Value; Perspective from Rural Banking Sectors in Bandung, Indonesia. International Journal of Academic Research in Business and Social Sciences, 6(12), 609-616.
• Tadeu, H. F. B., Duarte, A. L. D. C. M., Taurion, C., & Jamil, G. L. (2019). Digital Transformation: Digital Maturity Applied to Study Brazilian Perspective for Industry 4.0. In Best Practices in Manufacturing Processes (pp. 3-27). Springer, Cham.
• Tan, Y., & Floros, C. (2018). Risk, competition and efficiency in banking: Evidence from China. Global Finance Journal, 35, 223-236.
• Vera-Gilces, P., Camino-Mogro, S., Ordeñana-Rodríguez, X., & Cornejo-Marcos, G. (2019). A look inside banking profitability: Evidence from a dollarized emerging country. The Quarterly Review of Economics and Finance.
• Vives, X. (2019). Competition and Stability in Modern Banking: A Post-Crisis Perspective. International Journal of Industrial Organization.
• Vozková, K., & Teplý, P. (2018). Determinants of bank fee income in the EU banking industry-does market concentration matter?. Prague Economic Papers, 27(1), 3-20.
• Wang, C., Zhou, H., Dınçer, H., Yüksel, S., Ubay, G. G., & Uluer, G. S. (2020). Analysis of electricity pricing in emerging economies with hybrid multi-criteria decision-making technique based on interval-valued intuitionistic hesitant fuzzy sets. IEEE Access, 8, 190882-190896.
• Wu, L., & Chiu, M. L. (2015). Organizational applications of IT innovation and firm's competitive performance: A resource-based view and the innovation diffusion approach. Journal of Engineering and Technology Management, 35, 25-44.
• Yıldırım, H., Aydoğan, H., Özcan, S., & Eti, S. (2018). Fazi Kontrol Grafikleri İle Klasik Kontrol Grafiklerinin Karşılaştırılması Üzerine Bir Deneme. Journal of Research in Business, 3(2), 150-173.
• Yilmaz, A. (2016). The Impact Of Hris Usage On Organizational Efficiency And Employee Performance: A Research In Industrial And Banking Sector In Ankara And Istanbul Cities. International Journal of Business and Management, 4(4), 14-52.
• Yuan, J., Zhang, Z. M., Yüksel, S., & Dinçer, H. (2020). Evaluating recognitive balanced scorecard-based quality improvement strategies of energy investments with the integrated hesitant 2-tuple interval-valued pythagorean fuzzy decision-making approach to QFD. IEEE Access, 8, 171112-171128.
• Yuksel, S., Dincer, H., & Hacioglu, U. (2015). CAMELS-based Determinants for the Credit Rating of Turkish Deposit Banks. International Journal of Finance & Banking Studies, 4(4), 1-19.
• Yüksel, S., Dinçer, H., & Meral, Y. (2019). Financial analysis of international energy trade: a strategic outlook for EU-15. Energies, 12(3), 431.
• Yuliansyah, Y., Rammal, H. G., & Rose, E. (2016). Business strategy and performance in Indonesia’s service sector. Journal of Asia Business Studies, 10(2), 164-182.
• Zhong, J., Hu, X., Yüksel, S., Dinçer, H., & Ubay, G. G. (2020). Analyzing the investments strategies for renewable energies based on multi-criteria decision model. IEEE Access, 8, 118818-118840.
• Zuhroh, I., Ismail, M., & Maskie, G. (2015). Cost Efficiency of Islamic Banks in Indonesia–A Stochastic Frontier Analysis. Procedia-Social and Behavioral Sciences, 211, 1122-1131.
• Zyoud, S. H., Kaufmann, L. G., Shaheen, H., Samhan, S., & Fuchs-Hanusch, D. (2016). A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS. Expert Systems with Applications, 61, 86-105.