Journal of Industrial and Systems Engineering

Journal of Industrial and Systems Engineering

Designing a model to evaluate the effectiveness of the digital transformation of the banking system

Document Type : Research Paper

Authors
Mohammad Shirkhoda 1
Ladan Riazi 1
Faramarz Fathnejad 2
1 Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Department of Information Technology Management, Electronic Branch, Islamic Azad University, Tehran, Iran
Abstract
Examining the countries' financial systems shows that this field has also been affected by technological developments and has benefited from its advantages and benefits to overcome challenges and create opportunities. Therefore, technology development in the banking sector has meaningful implicit concepts in bank marketing, especially in digital banking, because it affects the standard level of customers. This research aims to design a model for evaluating the effectiveness of the digital transformation of the banking system. Based on the purpose, this research is of developmental and evaluation type, and in terms of method, it is considered descriptive research of mathematical modeling type. In this research, in the quantitative part, two categories of statistical techniques are used using SPSS software. Also, in the second part of the research, content analysis was used to identify the model, dimensions, main categories, and subcategories. In the final part, it was used to analyze the banking system to establish digital transformation based on system dynamics and fuzzy network data coverage analysis method. The research findings showed that identifying and analyzing the practical components in the digital transformation of the banking system is essential for designing a model to evaluate the effectiveness of these transformations.
Keywords
banking system
digital transformation
system dynamics
data mining
fuzzy network data envelopment analysis
Subjects
Aliahmadi, A., & Nozari, H. (2023, January). Evaluation of security metrics in AIoT and blockchain-based supply chain by Neutrosophic decision-making method. In Supply chain forum: an international journal (Vol. 24, No. 1, pp. 31-42). Taylor & Francis.
Aliahmadi, A., Nozari, H., Ghahremani-Nahr, J., & Szmelter-Jarosz, A. (2022). Evaluation of key impression of resilient supply chain based on artificial intelligence of things (AIoT). arXiv preprint arXiv:2207.13174.
Berown, P., Souto-Otero, M., & Sadik, S. (2022). Digital transformation and the future of work. Digital Society, 559.
Chikazhe, E., & Cormican, K. (2017). The rise of the prosumer: An analysis of self-service technology adoption in a corporate context. SciKA-Association for Promotion and Dissemination of Scientific Knowledge, 5(2), 25–39.
Deng, D. M., & Pikon, R. (2017). An introduction to derivatives and risk management. South-Western, Cengage Learning.
Dogera, T. S., Tone, K., & Wu, C. H. (2023). Nested dynamic network data envelopment analysis models with infinitely many decision making units for portfolio evaluation. European journal of operational research, 291(2), 766-781.
Elinzenberg, K. (2017). The handbook of key customer relationship management: the definitive guide to winning, managing and developing key account business. (No Title).
Emiran, D. M., Mawengkang, H., & Nasution, S. (2021). Measurement of DEA-Based ICT Development Efficiency Level with Modified CCR Method. Jurnal Varian, 6(1), 97-104.
Galeyamooa, D. (2021). Building a Successful Customer‐Service Culture: A Guide for Library and Information Managers. Library Review, 53(5), 285-286.
Goshal, I. J., & Bartelat, K. (2009). Understanding customer relationship management (CRM): People, process and technology. Business process management journal, 9(5), 672-688.
Karvey, A., Schierholz, R., Kolbe, L. M., & Brenner, W. (2019). Improving performance of customer‐processes with knowledge management. Business Process Management Journal, 11(5), 573-588.
Ketisos, J. A. (2021). Testing for Imperfeet Competition on EU Deposit and Loan Markets with Bresnahan’s Market Power Model. Credit and Capital Markets–Kredit und Kapital, (2), 167-212.
Mena, H. H., Grether, M., & Leach, M. (2024). Building customer relations over the Internet. Industrial Marketing Management, 31(2), 155-163.
Nadkarny, S. T., & Perogel, T. (2021). Forecasting default with the Merton distance to default model. The Review of Financial Studies, 21(3), 1339-1369.
Nozari, H., & Ghahremani-Nahr, J. (2021). Provide a framework for implementing agile big data-based supply chain (case study: FMCG companies). Innovation management and operational strategies, 2(2), 128-136.
Soy, J. H., & Rosha, G. (2019). The theory of bank risk taking and competition revisited. The Journal of finance, 60(3), 1329-1343.
Teichert, C. (2019). Strategic issues in customer relationship management (CRM) implementation. Business process management Journal, 9(5), 592-602.
Terncan, Z. & Monoz, P. (2023). Chinese bank efficiency during the global financial crisis: A combined approach using satisficing DEA and Support Vector Machines☆. The North American Journal of Economics and Finance, 43, 71-86.
Tesinden, M. (2021). Leverage regulation and market structure: A structural model of the UK mortgage market. The Journal of Finance, 76(6), 2997-3053.
Weideya, A. S. (2021). A simple note on the Japanese firm. Journal of the Japanese and International Economies, 7(3), 238-255.
Journal of Industrial and Systems Engineering
Volume 15, Issue 2 - Serial Number 2
Spring 2023
Pages 155-165

  • Receive Date 03 November 2022
  • Revise Date 04 February 2023
  • Accept Date 07 March 2023