Digital Assistants in Online Retail Shopping

This book tackles a critical paradox in contemporary e-commerce: despite rapid proliferation of AI-powered digital assistants—from chatbots to voice-enabled shopping tools like Alexa and Siri—consumer adoption remains surprisingly low. This book tackles a critical paradox in contemporary e-commerce: despite rapid proliferation of AI-powered digital assistants—from chatbots to voice-enabled shopping tools like Alexa and Siri—consumer adoption remains surprisingly low. Why do shoppers hesitate to trust these technologies, and what motivates those who embrace them? Through rigorous empirical research and innovative theoretical frameworks, this book addresses these pressing questions, offering insights into the psychological, social, and technological factors shaping consumer acceptance of AI-driven shopping assistance. The book introduces the Acceptance of Digital Assistants in Online Shopping (ADAiOS) model, extending the Technology Acceptance Model (TAM) by integrating Social Presence Theory (SPT) and the Computers Are Social Actors (CASA) paradigm. Through systematic literature review, bibliometric analysis, and advanced multi-criteria decision-making techniques—including Gray-DEMATEL and Gray Influence Analysis (GINA)—the authors identify 12 key factors influencing consumer acceptance: usefulness, ease of use, performance, enjoyment, anthropomorphism, social presence, sociability, privacy concerns, technology anxiety, and trust. Drawing on empirical data from India's rapidly developing e-commerce market, it reveals that human-like attributes, social validation, and perceived presence are critical to acceptance, providing actionable strategies for designing trustworthy digital assistants. This book will interest students, researchers, and academics in digital marketing, consumer behavior, e-commerce, artificial intelligence, human-computer interaction, and decision sciences. It will also serve industry practitioners, including marketing managers, digital strategists, e-commerce developers, UX designers, and policymakers seeking to optimize AI-powered retail technologies.