Critical success factors of the financial performance of commercial private banks: A study in a developing nation

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This study’s objective is to examine the impact of employee innovativeness, readiness to change, employee creativity, and learning capability on the financial performance of private banks in Bangladesh. The study involved 334 bank employees from three prominent private banks in Bangladesh. Those banks were selected with better ratings by the central bank and have several branches across the country. First, branch managers were contacted about this study and collected employee emails from each branch information desk. Then, email invitations were sent to each employee of the selected bank branches. This study involved branch managers, senior officers, officers, and junior bank executives. Past studies also considered senior and junior bank officers as they directly contribute to a bank’s performance. The study utilized a methodical questionnaire to assess the three independent variables: employee innovativeness, readiness to change, and learning capability. The dependent variable in this study was financial performance, which was assessed through key financial indicators such as profitability and sales growth over three years. SPSS was utilized to conduct hypothesis testing by considering 95% confidence interval. Correlation results show that all three independent variables were significantly correlated with the bank’s financial performance. The study’s regression results suggest that bank employees’ readiness to change (β value = 0.393) significantly impacts the bank’s financial performance, followed by employee innovativeness (β value = 0.338). On the other hand, employees’ learning capability (β value = 0.202) has the least significant impact on financial performance. Moreover, three independent variables explain 42.9% variance in bank financial performance.

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    • Table 1. Sources for developing the survey questionnaire
    • Table 2. Reliability and validity analysis
    • Table 3. Demographic information
    • Table 4. Correlation matrix
    • Table 5. Model summary of regression analysis
    • Table 6. Regression coefficient
    • Conceptualization
      K. M. Anwarul Islam, Mohammad Bin Amin, Sk Alamgir Hossain, Roushanara Islam, Jozsef Popp
    • Data curation
      K. M. Anwarul Islam
    • Formal Analysis
      K. M. Anwarul Islam, Mohammad Bin Amin, Sk Alamgir Hossain, Roushanara Islam, Jozsef Popp
    • Investigation
      K. M. Anwarul Islam, Mohammad Bin Amin, Sk Alamgir Hossain, Roushanara Islam
    • Methodology
      K. M. Anwarul Islam
    • Project administration
      K. M. Anwarul Islam, Mohammad Bin Amin
    • Resources
      K. M. Anwarul Islam, Mohammad Bin Amin, Sk Alamgir Hossain, Roushanara Islam, Jozsef Popp
    • Software
      K. M. Anwarul Islam
    • Supervision
      K. M. Anwarul Islam, Mohammad Bin Amin
    • Validation
      K. M. Anwarul Islam, Mohammad Bin Amin, Sk Alamgir Hossain, Jozsef Popp
    • Visualization
      K. M. Anwarul Islam, Mohammad Bin Amin, Sk Alamgir Hossain, Roushanara Islam, Jozsef Popp
    • Writing – original draft
      K. M. Anwarul Islam, Mohammad Bin Amin, Sk Alamgir Hossain, Roushanara Islam
    • Writing – review & editing
      K. M. Anwarul Islam, Mohammad Bin Amin, Sk Alamgir Hossain, Jozsef Popp
    • Funding acquisition
      Mohammad Bin Amin, Sk Alamgir Hossain, Roushanara Islam, Jozsef Popp