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Bridging Faith and Digital Financial Technologies: A Predictive Multidimensional Analysis of Islamic FinTech
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Author(s): Mohamed Bouteraa (Qatar Foundation - American University in Qatar, Qatar), Abderrahmane Baddou (University of Algiers 3, Algeria), Mohammed Soufiane Benmoussa (University of Algiers 3, Algeria), Anes Hebbaz (University of Algiers 3, Algeria), Abderrahmane Elkheloufi (Universiti Utara Malaysia, Malaysia), Mourad Boudiab (University Centre of Mila-Abdalhafid Boussouf, Algeria), Meshari Al-Daihani (University of Malaya, Malaysia)and Brahim Chekima (University Malaysia Sabah, Malaysia)
Copyright: 2026
Pages: 36
Source title:
AI and Digital Technologies Transforming Global Industries
Source Author(s)/Editor(s): Patricia Ordóñez de Pablos (The University of Oviedo, Spain), Xi Zhang (Tianjin University, China), Muhammad Anshari (Universiti Brunei Darussalam, Brunei)and Mohammad Nabil Almunawar (Universiti Brunei Darussalam, Brunei)
DOI: 10.4018/979-8-3373-6097-3.ch006
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Abstract
This study investigates the adoption of Islamic FinTech services by integrating multidimensional Islamic religiosity into a predictive behavioral model. Drawing on data from Muslim consumers in the UAE, the study applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine how various aspects of religiosity influence behavioral intention. Findings reveal that religiosity significantly shapes trust, perceived usefulness, and attitude toward Islamic FinTech adoption. The study addresses key barriers such as cybersecurity concerns, opaque Shariah governance, and limited financial literacy, while highlighting the need for transparency, ethical alignment, and culturally sensitive design. Theoretically, it advances understanding of FinTech adoption through a faith-based lens. Practically, it offers actionable insights for FinTech providers, regulators, and policymakers aiming to enhance financial inclusion and ethical innovation. Future research is encouraged to explore cross-religious and cross-sectoral applications of this model.
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