An Integrated Dynamic Generalized Trapezoidal Fuzzy AHP-TOPSIS Approach for Evaluating Sustainable Performance of Bank

Vu Thi Nhu Quynh

doi:10.47654/v27y2023i1p68-86

Authors

Vu Thi Nhu Quynh Vietnam Maritime University Corresponding Author

DOI:

https://doi.org/10.47654/v27y2023i1p68-86

Keywords:

Dynamic Fuzzy AHP, Dynamic Fuzzy TOPSIS, Generalized Trapezoidal Fuzzy Numbers, MCDM

Abstract

Purpose: The assessment of sustainable performance is critical in enhancing the bank's competitive advantages. To evaluate sustainable banking performance, it is necessary to consider various economic, environmental, and social criteria. Therefore, sustainable banking performance assessment can be regarded as a multiple-criteria decision-making (MCDM) problem in a vague environment. This paper proposes a new MCDM approach to assess the sustainable performance of banks in Vietnam.

Design/methodology/approach: This study proposes a new integrated approach that combines the dynamic fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) methods to evaluate the sustainable performance of banks in Vietnam. The proposed approach is demonstrated using an application to show its applicability and efficiency.

Findings: The findings reveal that the proposed integrated dynamic GTrF-AHP-TOPSIS approach is more efficient and effective than previous relevant studies.

Originality/value: The proposed approach utilizes generalized trapezoidal fuzzy numbers (GTrFNs) to represent the banks' ratings and criteria weights. The dynamic GTrF-AHP approach is developed to determine the criteria weights over time. The banks' ranking order is determined using a closeness coefficient that calculates the distance between the banks and the ideal/negative-ideal solutions.

References

Alghassab, H. (2022). Quantitative assessment of sustainable renewable energy through soft computing: Fuzzy AHP-TOPSIS method. Energy Reports, 8, 12139-12152.

Azam, M.; Ftiti, Z.; Hunjra, A.I.; Louhichi, W.; Verhoeven, P. (2022). Do market-supporting institutions promote sustainable development? Evidence from developing economies. Economic Modelling, 116, 106023.

Aksoy, M.Y.; Karabayır, A.N.; Güngör, Z.Ö.C. (2022). Extension of Classical TOPSIS Method Using Q-Rung Orthopair Triangular Fuzzy Number. Advances in Decision Sciences, 26(1), 163-187.

Alibeigi, A.; Asemi, A.; Munir, A.B.; Baba, M.S. (2021). Evaluating ASEAN E-commerce Laws Using Fuzzy Multi-Criteria Decision Making. Advances in decision sciences, 25(2), 1-52.

Bogers, M.; Biermann, F.; Kalfagianni, A.; Kim, R.E.; Treep, H.; Vos, M.G.D (2022). The impact of the Sustainable Development Goals on a network of 276 international organizations. Global Environmental Change, 76, 102567.

Chang, D.Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 3, 649-655.

Chen, S.H. (1985). Operations on fuzzy numbers with function principal. Tamkang Journal of International Affairs, 6, 13-25.

Chen, L.; Yang, D. (2021). Dynamic Pythagorean fuzzy probabilistic linguistic TOPSIS method with psychological preference and its application for COVID-19 vaccination. Soft Computing Letters, 3, 100022.

Ekmekcioğlu, Ö.; Koc, K.; Özger, M. (2021). Stakeholder perceptions in flood risk assessment: A hybrid fuzzy AHP-TOPSIS approach for Istanbul, Turkey. International Journal of Disaster Risk Reduction, 60, 102327.

Hsieh, C.H.; Chen, S.H. (1999). Similarity of generalized fuzzy numbers with graded mean integration representation. Proc 8th International fuzzy System Association World Congress, Taipei, Taiwan, Republic of China, 2, 551-555.

Hue, T.T.; Tuan, N.A.; Van, L.H.; Lien, L.T.; Huong, D.D.; Anh, L.T.; Huy, N.X.; Dat, L.Q. (2022). Prioritization of Factors Impacting Lecturer Research Productivity Using an Improved Fuzzy Analytic Hierarchy Process Approach. Sustainability, 14, 6134.

Jiang, Y.; Zhang, J.; Asante, D.; Yang, Y. (2019). Dynamic evaluation of low-carbon competitiveness (LCC) based on improved Technique for Order Preference by similarity to an Ideal Solution (TOPSIS) method: A case study of Chinese steelworks. Journal of Cleaner Production, 217, 484e492.

Kien, P.V.; Wong, W.K.; Moslehpour, M.; Musyoki, D. (2018). Simultaneous Adaptation of AHP and Fuzzy AHP to Evaluate Outsourcing Services in East and Southeast Asia. Journal of Testing and Evaluation, 1-27. https://doi.org/10.1520/JTE20170420.ISSN,0090-3973.

Kumar, K.; Prakash, A. (2019). Developing a framework for assessing sustainable banking performance of the Indian banking sector. Social Responsibility Journal, 15(5), 689-709.

Long, R.; Li, H.; Wu, M.; Li, W. (2021). Dynamic evaluation of the green development level of China's coal-resource-based cities using the TOPSIS method. Resources Policy, 74, 102415.

Liang, X.B.; Ma, W.F.; Ren, J.J.; Dang, W.; Wang, K.; Nie, H.; Cao, J.; Yao, T. (2022). An integrated risk assessment methodology based on fuzzy TOPSIS and cloud inference for urban polyethylene gas pipelines. Journal of Cleaner Production, 376, 134332.

Li, J.; Chen, G. (2014). Water footprint assessment for service sector: A case study of gaming industry in water scarce Macao. Ecological Indicators, 47, 164-170.

Lin, A.J.; Chang, H.Y. (2019). Business Sustainability Performance Evaluation for Taiwanese Banks-A Hybrid Multiple-Criteria Decision-Making Approach. Sustainability, 11, 2236.

Marzouqi, A.H.A.; Khan, M.; Hussain, M. (2019). Employee social sustainability: Prioritizing dimensions in the UAE’s airlines industry. Social Responsibility Journal, doi:10.1108/SRJ-07-2018-0166.

Nazim, M.; Mohammad, C.W.; Sadiq, M. (2022) A comparison between fuzzy AHP and fuzzy TOPSIS methods to software requirements selection. Alexandria Engineering Journal, 61, 10851-10870.

Nosratabadi, S.; Pinter, G.; Mosavi, A.; Semperger, S. (2020). Sustainable Banking; Evaluation of the European Business Models. Sustainability, 12, 2314.

Raut, R.; Naoufel, C.; Kharat, M. (2017). Sustainability in The Banking Industry: A Strategic Multi-Criterion Analysis. Business Strategy and the Environment, 26(4), 550-568.

Raufirad, V.; Heidari, Q.; Ghorbani, J. (2022). Comparing socioeconomic vulnerability index and land cover indices: Application of fuzzy TOPSIS model and geographic information system. Ecological Informatics, 72, 101917.

Ramasubramanian, S.; Avinash, Y.; Chitra, S.P.; Geetha, T.; Anand, S. (2009). An activity-based approach to minimize energy usage of service sector infrastructure. In Proceedings of the Second International Conference on Infrastructure Systems and Services: Developing 21st Century Infrastructure Networks (INFRA), Nager, India, 9-11 December 2009, 1-6.

Rebai S. (2014). New Banking Performance Evaluation Approach: Sustainable Finance and Sustainable Banking Based. PhD dissertation Higher Institute of Management, University of Tunis: Tunisia.

Sadat, S.A.; Fini, M.V.; Hashemi-Dezaki, H.; Nazififard, M. (2021). Barrier analysis of solar PV energy development in the context of Iran using fuzzy AHP-TOPSIS method. Sustainable Energy Technologies and Assessments, 47, 101549.

Solangi, Y.A.; Longsheng, C.; Shah, S.A.A. (2021). Assessing and overcoming the renewable energy barriers for sustainable development in Pakistan: An integrated AHP and fuzzy TOPSIS approach. Renew. Energy, 173, 209-222.

Schleich, J. (2009). Barriers to energy efficiency: A comparison across the German commercial and services sector. Ecological Economics, 68, 2150-2159.

Zaitseva, N.A.; Larionova, A.A.; Takhumova, O.V.; Eroshenko, V.I.; Lebedeva, J.A.; Stadolin, M.E. (2019). Problems and directions of application of environmental technologies in the service sector. Ekoloji, 28, 489-494.

Zhang, K.; Dai, J. (2022). A novel TOPSIS method with decision-theoretic rough fuzzy sets. Information Sciences, 608, 1221-1244.

Yang, S.; Pan, Y.; Zeng, S. (2022). Decision making framework based Fermatean fuzzy integrated weighted distance and TOPSIS for green low-carbon port evaluation. Engineering Applications of Artificial Intelligence, 114, 105049.