Dynamics of the Digital Banking Ecosystem in Iran
محورهای موضوعی : Simulation Based Optimization
Farshid Farokhizadeh
1
,
Azim Zarei
2
,
AbbasAli Rastgar
3
,
Seyed Abbas Ebrahimi
4
1 - PhD, Department of Industrial Management, Faculty of Economics, Management and Administrative Sciences, Semnan University, Iran.
2 - Professor, Department of Business Administration, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran.
3 - Professor, Department of Business Administration, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran.
4 - Associate Professor, Department of Industrial Management, Faculty of Economics, Management and Administrative Sciences, Semnan University, Semnan, Iran.
کلید واژه: Ecosystem, Digital Banking, Fintech, Dynamic Simulation, Bibliometrics.,
چکیده مقاله :
This study examines the digital banking system using a cross-sectional research method that incorporates qualitative and quantitative exploratory data. Fuzzy logic is used to address the complexity and ambiguity of digital banking characteristics, particularly quality indicators and linguistic variables. The successful adoption of new technologies in digital banking depends on continuous use and habit formation. Previous models of electronic and digital banking have their strengths and weaknesses. Therefore, it is important to develop a dynamic model of the D- Banking Ecosystem that aligns with the specific characteristics of the Iranian bank under study. The research aims to analyze existing models and their strengths and weaknesses to present the boundaries, main players, and relationships within the digital banking ecosystem. Proposed models for digital banking were examined, and a new classification of dimensions and components was presented based on a systematic review method and interviews with subject matter experts. A fuzzy Delphi panel of digital banking experts was formed in three stages to determine the components. The developed model for the studied bank was simulated using dynamic analysis. Based on the findings of the simulation and examination of different scenarios, it is concluded that for this bank to enter the digital banking ecosystem, the first step should be an innovative approach to the use of new technologies and their benefits, along with special attention to cooperation and attraction of startups and Fintechs to satisfy and persuade customers and employees. Other important factors in the next stages include banking industry structure, digital transformation infrastructure, security, environmental-social factors, and laws and policies.
This study examines the digital banking system using a cross-sectional research method that incorporates qualitative and quantitative exploratory data. Fuzzy logic is used to address the complexity and ambiguity of digital banking characteristics, particularly quality indicators and linguistic variables. The successful adoption of new technologies in digital banking depends on continuous use and habit formation. Previous models of electronic and digital banking have their strengths and weaknesses. Therefore, it is important to develop a dynamic model of the D- Banking Ecosystem that aligns with the specific characteristics of the Iranian bank under study. The research aims to analyze existing models and their strengths and weaknesses to present the boundaries, main players, and relationships within the digital banking ecosystem. Proposed models for digital banking were examined, and a new classification of dimensions and components was presented based on a systematic review method and interviews with subject matter experts. A fuzzy Delphi panel of digital banking experts was formed in three stages to determine the components. The developed model for the studied bank was simulated using dynamic analysis. Based on the findings of the simulation and examination of different scenarios, it is concluded that for this bank to enter the digital banking ecosystem, the first step should be an innovative approach to the use of new technologies and their benefits, along with special attention to cooperation and attraction of startups and Fintechs to satisfy and persuade customers and employees. Other important factors in the next stages include banking industry structure, digital transformation infrastructure, security, environmental-social factors, and laws and policies.
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