Smart Retail, Smarter Decisions: Conceptualizing the Antecedents of Consumer Intention to Use Intelligent Retail Systems

Abstract

Smart retail technologies are reshaping the retail landscape by integrating advanced digital innovations such as artificial intelligence, the Internet of Things, and automation into consumer shopping experiences. These intelligent systems, which include features like automated checkouts, AI-driven product recommendations, and smart shopping carts, promise to enhance operational efficiency and deliver personalized, seamless customer interactions. However, despite their potential, consumer intention to adopt such technologies varies significantly across different markets and cultural contexts. This conceptual paper investigates the underlying antecedents influencing consumer intention to use intelligent retail systems by synthesizing insights from established technology adoption theories including the Technology Acceptance Model, the Unified Theory of Acceptance and Use of Technology, and hedonic motivation theory. Through a systematic review of 93 recent studies on smart retail technologies, this study identifies various influential factors such as trust, perceived usefulness, perceived ease of use, animacy, emotional engagement, and motivational drivers. The paper also highlights global trends in smart retail adoption while emphasizing the unique challenges and opportunities in emerging markets such as Malaysia. By proposing a comprehensive conceptual framework, this study offers theoretical and practical insights for designing consumer-centric intelligent retail solutions that foster greater acceptance and sustainable engagement.