The role of organizational commitment and demographic factors in enhancing organizational citizenship behavior among employees in financial institutions

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Organizational citizenship behavior (OCB) can improve organizational effectiveness. Individual altruism and commitment to the organization are at the core of OCB. This study aimed to examine the impact of organizational commitment and demographic factors on OCB in the Malaysian financial sector. The cross-sectional study targeted 280 employees from diverse backgrounds and positions across banking and non-banking financial institutions following conventional as well as Islamic Sharia principles in Malaysia. The respondents include individuals from management levels (upper management, middle management, non-management) and divisions (finance, operations, retail/corporate banking, and others). Data analysis included multiple regression analysis and ANOVA. The findings reveal a complex interaction where organizational and normative commitment do not significantly predict OCB, while affective commitment shows a significant positive correlation with OCB. The study revealed that employees with higher emotional attachment to their organization exhibit more OCB (r = 0.155, p < 0.009). In addition, demographic factors, such as education (r = 0.025, p < 0.067), age (r = 0017, p < 0.003), tenure (r = 0.107, p < 0.003), and management level (r = 0.17, p < 0.004) emerge as positive influencers of OCB. Thus, higher education levels, older employees, longer tenure, and managerial positions are linked to higher levels of OCB. At the same time, no significant gender-based differences are observed in employees’ OCB. The findings imply that organizations should emphasize building emotional connections with employees through supportive leadership and a positive work environment to enhance organizational effectiveness.

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    • Figure 1. Conceptual framework
    • Table 1. Dimensions of OCB
    • Table 2. Demographic statistics
    • Table 3. Reliability test
    • Table 4. Mean and standard deviation
    • Table 5. ANOVA results
    • Table 6. Model summary of R, R², and Adjusted R²
    • Table 7. Multiple regression analysis result
    • Table 8. Summary of hypotheses testing
    • Conceptualization
      Abdullah Sarwar, Mohammad Ali Tareq, Aysa Siddika, Murali Raman, Md Amirul Islam, V. Vijayalakshmi
    • Data curation
      Abdullah Sarwar, Aysa Siddika
    • Formal Analysis
      Abdullah Sarwar, Aysa Siddika
    • Investigation
      Abdullah Sarwar
    • Methodology
      Abdullah Sarwar, Mohammad Ali Tareq, Aysa Siddika
    • Project administration
      Abdullah Sarwar, Mohammad Ali Tareq, Murali Raman, Md Amirul Islam, V. Vijayalakshmi
    • Resources
      Abdullah Sarwar, Md Amirul Islam
    • Software
      Abdullah Sarwar
    • Supervision
      Abdullah Sarwar, Aysa Siddika, Murali Raman, Md Amirul Islam, V. Vijayalakshmi
    • Visualization
      Abdullah Sarwar, Murali Raman, Md Amirul Islam
    • Writing – original draft
      Abdullah Sarwar, Mohammad Ali Tareq
    • Writing – review & editing
      Abdullah Sarwar, Mohammad Ali Tareq, Aysa Siddika, Murali Raman, Md Amirul Islam, V. Vijayalakshmi
    • Validation
      Mohammad Ali Tareq, Aysa Siddika, Murali Raman, V. Vijayalakshmi
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