Leveraging IoT for business model innovation in banking: The role of data-driven decision-making, Fintech innovation and artificial intelligence

Drawing on Resource Orchestration Theory (ROT), this study examines whether data-driven decision-making (DDS) and adoption of Fintech innovations serves as serial mediation mechanisms linking IoT adoption and business model innovation (BMI). Moreover, it examines whether Artificial Intelligence (AI) capability significantly moderates the relationship between IoT adoption, DDS, and BMI. Using Partial Least Squares Structural Equation Modeling (PLS-SEM) on data from 689 bank managers, we found that IoT adoption positive direct relationship with BMI, DDS, and Fintech innovation adoption. Moreover, DDS and Fintech innovation adoption positively affect BMI. DDS and Fintech innovation adoption mediated and serially mediated the relationship between IoT adoption and BMI. Finally, AI capability positively moderates between IoT adoption and BMI, and IoT adoption and DDS. This study advances digital innovation research by explaining how banks transform IoT adoption into business model innovation through data-driven decision-making, Fintech innovation adoption, and AI-enabled resource orchestration. The findings offer practical implications for banking leaders seeking to enhance their innovation capabilities through IoT-driven decision-making and AI-enabled resource management.