Board gender diversity and bank performance in Jordan

  • Received December 5, 2023;
    Accepted March 5, 2024;
    Published March 20, 2024
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.19(1).2024.16
  • Article Info
    Volume 19 2024, Issue #1, pp. 183-194
  • TO CITE АНОТАЦІЯ
  • Cited by
    3 articles
  • 428 Views
  • 146 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Board diversity is crucial for corporate governance and improves corporate outcomes by aligning management with stakeholders’ interests. Compared to advanced environments, Jordan’s decent sociocultural backdrop exhibits a higher level of gender bias. This study investigates the influence of board gender diversity (BGD) on Jordanian banking sector performance, an under-explored area. This quantitative paper employs Ordinary Least Squares (OLS), random, and fixed-effect approaches to analyze 182 bank-year observations for balanced longitudinal data analysis. These approaches correctly establish the BGD-Tobin’s Q nexus during 2010–2022. The coefficient of determination was 70.57%. The model confirms a positive correlation between BGD and market-based performance indicators. Findings support agency and resource dependency hypotheses, showing BGD’s role in decision-making. Hence, a one-unit increase in BGD causes a 37.2-cent increase in Tobin’s Q measure. Moreover, a one-unit change in board independence, board meetings, size, women’s representation in top management, and capital adequacy ratio, assuming all other factors remain constant, results in Tobin-Q changes of 2.57 cents, 32.8 cents, 5.78 cents, 51.2 cents, 30.55 cents, and 22.86 cents, respectively, and the same direction. The results show how BGD enhances bank performance and contributes to relevant theories. The results are vigorous in a variety of identification and estimation methodologies.

view full abstract hide full abstract
    • Table 1. Variable definitions
    • Table 2. Summary statistics for related variables throughout the study period
    • Table 3. Pairwise correlation and multicollinearity (VIF) tests
    • Table 4. Regression results for BGD and market performance (Tobin’s Q)
    • Table 5. Regression results for BGD and accounting performance (ROA)
    • Table 6. Regression results for percentage of BGD and Tobin’s Q
    • Conceptualization
      Marwan Mansour, Mo’taz Al Zobi, Dheif Allah E’leimat, Ahmad Marei
    • Data curation
      Marwan Mansour, Mo’taz Al Zobi, Ahmad Marei
    • Formal Analysis
      Marwan Mansour, Mo’taz Al Zobi, Sad Abu Alim
    • Funding acquisition
      Marwan Mansour, Dheif Allah E’leimat, Sad Abu Alim
    • Investigation
      Marwan Mansour, Mo’taz Al Zobi, Dheif Allah E’leimat, Ahmad Marei
    • Methodology
      Marwan Mansour, Mo’taz Al Zobi, Ahmad Marei
    • Resources
      Marwan Mansour, Mo’taz Al Zobi, Dheif Allah E’leimat
    • Software
      Marwan Mansour, Mo’taz Al Zobi, Ahmad Marei
    • Writing – original draft
      Marwan Mansour, Mo’taz Al Zobi, Dheif Allah E’leimat, Sad Abu Alim
    • Writing – review & editing
      Marwan Mansour, Mo’taz Al Zobi, Dheif Allah E’leimat, Sad Abu Alim, Ahmad Marei
    • Supervision
      Mo’taz Al Zobi, Dheif Allah E’leimat
    • Validation
      Dheif Allah E’leimat, Sad Abu Alim
    • Project administration
      Sad Abu Alim
    • Visualization
      Sad Abu Alim, Ahmad Marei