Evaluating the Performance of an Ambidextrous Bank Using an Agent-based Modeling Approach: A Case Study of Sepah Bank
محورهای موضوعی : Econometrics and Financial Applications of other Theories (Stochastic Processes, (Stochastic) Partial Differential Equations, Dynamical Systems)
Farzaneh Jahanseir Khararoudi
1
(Department of Management and Finance, Faculty of Management and Accounting, Farabi Campus, University of Tehran, Qom, Iran)
Adel Azar
2
(Department of Industrial Management, School of Management and Economics, Tarbiat Modares University, Tehran, Iran)
Tooraj Karimi
3
(Department of Management and Finance, Faculty of Management and Accounting, Farabi Campus, University of Tehran, Qom, Iran)
کلید واژه: Organizational ambidexterity, Agent-based modeling, Banking industry, performance,
چکیده مقاله :
Banks are the financial institutions that collect assets from various sources and allocate them to the sectors that require liquidity. Therefore, banks are an inherent element in the system of every country. As private banks enter financial markets, the demand for diverse banking services increases dramatically. Banks seek to use various techniques to improve their performance in attracting customers to increase their market share and profitability. In this regard, assessing the performance of banks is of utmost importance and has become a major activity of bank managers. With the constant changes in the modern world and incessant attempts of competitors to increase their market share by gaining competitive advantage, special attention should be paid to ambidexterity as a key strategy to increase competitive advantage and achieve high performance in dynamic business environments. The present study aimed to identify the ambidextrous factors affecting the performance of banks and present a model to assess the performance of an ambidextrous bank using an agent-based modeling approach. The main objective of the research is to achieve an applied model for managing the performance of the banking industry. The simulation model is processed using the agent-based modeling approach in AnyLogic software environment.
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