An Extended Technology Acceptance Model for Analyzing the Adoption of the BSI Mobile Banking Application BYOND: A Comparative Study Between Generation Y and Generation Z Customers in Indonesia

DOI: https://doi.org/10.33650/at-turas.v13i1.14500
Authors

(1) * Nuzhuliya Mega Avifa   (Universitas Trunojoyo Madura)  
        Indonesia
(2)  Nasrulloh Nasrulloh   (Universitas Trunojoyo Madura)  
        Indonesia
(*) Corresponding Author

Abstract


This study extends the Technology Acceptance Model (TAM) by integrating Sharia-based variables—Trust in Islamic Brand, Religiosity Influence, and Perceived Sharia Compliance—to examine user acceptance of the BYOND digital banking application in Indonesia’s Islamic banking sector. It also compares adoption patterns between Generation Y and Generation Z. Data were collected through an online survey of 139 respondents, the majority of whom had migrated to BYOND (96%). The model was analyzed using PLS-SEM with SmartPLS 4.0. Results indicate that the extended model demonstrates moderate predictive power (R²adj = 0.350), exceeding the explanatory capacity commonly reported for the original TAM in similar contexts. Perceived Sharia Compliance emerged as the strongest determinant of acceptance (t = 2.213), followed by Perceived Ease of Use (t = 2.194) and Perceived Usefulness (t = 2.066). Multi-group analysis reveals significant generational differences: Generation Z is more influenced by Sharia compliance and religiosity, whereas Generation Y is more responsive to functional benefits and brand trust. The findings suggest that technology adoption in Islamic digital banking cannot be explained solely by utilitarian factors but requires assurance of Islamic value integrity. However, the relatively small and user-dominant sample may limit generalizability. Future research should employ larger cross-regional samples and longitudinal designs to further validate the extended model.


Keywords

Extended Technology Acceptance Model; Sharia-Compliant Digital Banking; Perceived Sharia Compliance; Partial Least Squares Structural Equation Modeling; Generational Differences; Indonesia.



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