The Impact of Smart Retail Technologies on Repurchase Intention: An Empirical Study Using the Technology Acceptance Model

Abstract

This article investigates the effect of smart marketing technologies on customer consumption and repurchase purpose in the framework of artificial intelligence-based retail systems using the Technology Acceptance Model (TAM), Expectation Confirmation Model (ECM), and Trust Theory. New applications of AI have introduced novel concepts to the modern shopping experience, such as smart payment systems, recommendation engines, and self-checkout, but limited research has investigated how cognitive, emotional, and psychological factors work together to impact customer repurchase intention, especially in the Pakistani context. The study strategy used was measurable, explanatory, and cross-sectional. Smart retail technologies helped the researcher gather data from the consumers and analyse the data using SmartPLS with the help of Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that perceived ease of use significantly influences trust (β = 0.379, p = 0.000) and satisfaction (β = 0.262, p = 0.003), while perceived usefulness significantly affects trust (β = 0.385, p = 0.000) and satisfaction (β = 0.302, p = 0.001). Trust and satisfaction also have positive effects on repurchase intention, and perceived enjoyment enhances the relationship between satisfaction and repurchase intention. Theoretically, the study extends TAM and ECM by incorporating trust, satisfaction, and perceived enjoyment in the context of smart retail environments and offers practical implications for retailers to enhance customer engagement and long-term loyalty using smart retail technologies.