The role of corporate social responsibility as a moderating factor in influencing bank performance in Indonesia

  • Received July 28, 2023;
    Accepted December 8, 2023;
    Published December 15, 2023
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/bbs.19(1).2024.01
  • Article Info
    Volume 19 2024, Issue #1, pp. 1-11
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This work is licensed under a Creative Commons Attribution 4.0 International License

An important factor in increasing public trust in banks is to show bank performance, so it is necessary to know the factors that influence bank performance. Therefore, it is important to attract the attention of bank management. This study aims to determine the factors influencing bank performance by using social responsibility as a moderating variable. This study involved 20 banks in Indonesia and used a quantitative approach. Secondary data sources were used for data collection and analyzed using a regression equation model. The results show that non-performing loans and bank size have no effect on bank performance. Meanwhile, loan-to-deposit ratio and corporate social responsibility have a positive effect at the 1% significance level. The results of testing the moderation effect obtained t-statistic values of –0.365 and –4.269. These results show that social responsibility has a negative effect, does not moderate the relationship between non-performing loans and bank performance, but has a negative effect, moderating the relationship between the loan-to-deposit ratio and bank performance. These findings have policy implications for bank performance through the implementation of corporate social responsibility policies.

Acknowledgments
The authors would like to thank the DPPMP of Stikubank University for supporting the funding of this research. Thanks also to the NGEJUS - FEB Unisbank team who helped provide the facilities needed for this study.

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    • Table 1. Description of variables
    • Table 2. Summary statistical description
    • Table 3. Determination coefficient
    • Table 4. ANOVA
    • Table 5. Regression coefficient, t-value, and t significance
    • Table 6. Expected and actual hypotheses
    • Conceptualization
      Bambang Sudiyatno, Elen Puspitasari
    • Data curation
      Bambang Sudiyatno, Batara Daniel Bagana, Siska Dwi Safitri
    • Formal Analysis
      Bambang Sudiyatno, Batara Daniel Bagana, Elen Puspitasari
    • Investigation
      Bambang Sudiyatno, Widhian Hardiyanti, Elen Puspitasari
    • Methodology
      Bambang Sudiyatno, Widhian Hardiyanti, Elen Puspitasari
    • Validation
      Bambang Sudiyatno, Widhian Hardiyanti
    • Writing – original draft
      Bambang Sudiyatno, Batara Daniel Bagana, Siska Dwi Safitri
    • Software
      Batara Daniel Bagana
    • Visualization
      Batara Daniel Bagana, Siska Dwi Safitri
    • Project administration
      Widhian Hardiyanti, Elen Puspitasari
    • Resources
      Widhian Hardiyanti, Elen Puspitasari
    • Writing – review & editing
      Widhian Hardiyanti, Elen Puspitasari, Siska Dwi Safitri
    • Supervision
      Elen Puspitasari