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Digital retailing is increasingly transitioning toward hyper-personalized and AI-enabled consumer experiences, necessitating theoretical frameworks that integrate neurobiological data processing, advanced computational efficiency, and consumer psychological responses. This study develops and empirically validates a neuroadaptive engagement framework examining how multimodal biometric integration and quantum-enhanced processing efficiency influence real-time marketing optimization and neuroadaptive consumer engagement through the mediating mechanisms of cognitive load optimization and emotional congruence alignment. Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT), the study further investigates the moderating roles of privacy calculus acceptance and technology readiness. Using data collected from 500 Chinese e-commerce consumers and analyzed through partial least squares structural equation modeling (PLS-SEM), the findings reveal that neuroadaptive system responsiveness primarily enhances consumer engagement through emotional congruence alignment, whereas quantum-enhanced processing efficiency operates through both cognitive and emotional pathways. The results further indicate that privacy calculus acceptance and technology readiness significantly strengthen these relationships under conditions of higher consumer acceptance. The proposed model explains substantial variance in neuroadaptive consumer engagement and personalization effectiveness. This study contributes to the literature by extending UTAUT into neuroadaptive digital retail environments, introducing the constructs of quantum-enhanced processing efficiency and consumer digital twin fidelity, and identifying the boundary conditions under which biometric personalization enhances engagement rather than consumer resistance. The findings also provide strategic implications for retailers seeking to optimize neuroadaptive personalization investments based on consumer privacy perceptions and technological readiness.
Sun et al. (Tue,) studied this question.