Exploring the influence of skepticism, attitude, and religiosity on consumer intentions to adopt Sharia banking in Indonesia
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DOIhttp://dx.doi.org/10.21511/bbs.20(4).2025.09
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Article InfoVolume 20 2025, Issue #4, pp. 100-113
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Type of the article: Research Article
Abstract
Indonesia, with its position as the world’s largest Muslim-majority country, still shows a striking paradox: conventional banks remain dominant, while the market share of Sharia banks is stuck at 7.83% by the end of 2023. To address this issue, this study examines the role of compliance, Islamic financial literacy (IFL), skepticism, attitude, and religiosity in shaping Muslim consumers’ intention to adopt Sharia banking. The target population was Muslim individuals aged 17 years and above who had not yet opened an account in a Sharia bank, as they represent potential adopters. Data were gathered through an online survey conducted from July to August 2023, involving 210 respondents, with the majority being female (60%), aged 17-25 years (41%), and already employed (70%). Using Partial Least Squares Structural Equation Modeling (SmartPLS 3.0), the findings reveal that perceived Sharia compliance directly increases intention (β = 0.114; p < 0.01) and reduces skepticism (β = –0.556; p < 0.001). IFL does not directly influence intention (β = 0.053; p = 0.134), but it lowers skepticism (β = –0.225; p < 0.01). Skepticism erodes positive attitudes (β = –0.412; p < 0.001), while attitude emerges as the strongest predictor of intention (β = 0.795; p < 0.001). Religiosity further strengthens the link between IFL and intention (β = 0.089; p < 0.01). These findings highlight that authentic Sharia compliance and positive consumer attitudes play a more decisive role than IFL, with religiosity serving as a key factor in shaping decisions to adopt Sharia banking.
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JEL Classification (Paper profile tab)G21, D12, M31, Z12
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References57
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Tables8
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Figures0
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- Table 1. Profile of respondents
- Table 2. Factor loadings
- Table 3. Heterotrait–Monotrait ratio (HTMT)
- Table 4. Fornell-Larcker criteria
- Table 5. Cross-loadings
- Table 6. Internal consistency reliability
- Table 7. Full collinearity estimates (variance inflation factors/VIFs)
- Table 8. Hypotheses testing
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