Abstract

The integration of consumer behavior models into bank-owned e-commerce strategies has emerged as a critical focal point for enhancing customer engagement, improving transaction volumes, and fostering competitive advantage in the digital economy. This technical review examines the theoretical foundations and practical applications of key consumer behavior models such as the Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and the Unified Theory of Acceptance and Use of Technology (UTAUT) within the context of bank-operated e-commerce ecosystems. Banks are increasingly leveraging e-commerce platforms not only as transactional interfaces but also as value-driven ecosystems aimed at providing personalized financial and non-financial services. However, the adoption and sustained usage of these platforms hinge significantly on understanding consumer motivation, perceived value, trust, convenience, and digital literacy. The review explores how predictive behavioral models inform digital platform design, influence user interface optimization, guide recommendation engines, and support omnichannel banking strategies. By mapping consumer psychological and sociocultural factors to technological engagement metrics, banks can better tailor user experiences, segment markets, and optimize conversion pathways. Furthermore, the paper evaluates the integration of machine learning and data analytics in modeling dynamic consumer behaviors and preferences across different demographic and regional segments. Challenges such as data privacy concerns, algorithmic bias, and the digital divide are also addressed, with proposed solutions focusing on ethical AI, inclusive design, and adaptive learning systems. Case studies from leading African and global banks illustrate diverse implementation pathways and outcomes. This review concludes that a data-informed understanding of consumer behavior, when aligned with agile technology architectures, can significantly enhance the effectiveness of bank-owned e-commerce strategies. Future research directions include the co-evolution of behavioral models with emerging technologies like blockchain, embedded finance, and generative AI.