The role of the level of artificial intelligence adoption on business model innovation, sustainable competitive advantage, and firm performance: Integrating the TOE framework and Dynamic Capabilities theory

Drawing on the TOE framework (Technology-Organization-Environment) and Dynamic Capabilities theory, this study aims to explain the mechanisms driving the level of Artificial Intelligence adoption (AI) and its resulting impacts on firm performance. Using the Partial Least Squares Structural Equation Modeling (PLS-SEM) with a sample of 325 managers from Vietnamese firms, the findings reveal that top leadership support, government support, and cost-effectiveness of AI investment are critical determinants of AI adoption level. Furthermore, the level of AI adoption has a positive relationship with business model innovation (BMI) and sustainable competitive advantage (SCA), thereby enhancing firm performance (FP). The results reveal that the level of AI adoption strengthens the link between SCA and FP by improving firms’ capacity to identify opportunities and reconfigure strategic resources, thereby enabling SCA to be translated into FP. Theoretically, this research contributes by integrating structural (TOE) and dynamic capability perspectives to explain the level of AI adoption and its outcomes. Practically, the firm should leverage government support policies and leadership support to optimize AI adoption and translate it into sustainable business value.