ADOPTION OF MOBILE PAYMENT SYSTEMS USING TECHNOLOGY ACCEPTANCE MODEL (TAM) AND STRUCTURAL EQUATION MODELING

Abstract

The rapid proliferation of mobile payment (m-payment) systems has transformed the global financial landscape, offering enhanced convenience, speed, and financial inclusion. This study investigates the factors influencing the adoption of mobile payment systems through the lens of the Technology Acceptance Model (TAM) and employs Structural Equation Modeling (SEM) for empirical validation. Grounded in core TAM constructs Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) the research examines how these variables, along with attitude toward use, shape users’ behavioral intention to adopt m-payments. The study extends the basic TAM framework by incorporating additional determinants such as trust, perceived risk (financial, privacy, performance, and psychological), social influence, compatibility, and subjective norms. Methodological approaches including covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM), as well as hybrid SEM-ANN techniques, are discussed to address both theory confirmation and predictive accuracy. Regional variations, generational differences, and the perspectives of Small and Medium Enterprises (SMEs) are also analyzed to provide a comprehensive understanding of adoption dynamics across contexts. Findings from existing empirical literature highlight the dominant roles of perceived usefulness, trust, and compatibility, while perceived risk emerges as a significant barrier. The paper underscores the evolving technological trajectory toward AI-driven invisible payments and biometric authentication. This research contributes to a deeper understanding of m-payment adoption and offers practical implications for policymakers, financial institutions, and technology providers aiming to accelerate digital payment ecosystems and promote financial inclusion