Consumer Behavior in the Digital Era: A Systematic Literature Review of Internal and External Influences, Learning and Decision-making Dynamics

Purpose: This study investigates the key determinants of digital consumer habits during the swift expansion of AI-driven platforms and social commerce between 2020 and 2025. It examines how internal psychological factors, external socio-technological influences, learning processes and innovation adoption jointly shapes online purchase decisions. As digital ecosystems increasingly integrate artificial intelligence, personalization and algorithmic recommendations, understanding these multidimensional drivers become essential for explaining how consumers form. Maintain and modify habitual online behaviors Methods: A Systematic Literature Review was conducted following PRISMA guidelines. A total of 31 peer reviewed articles published between 2020 to 2025 were identified through ScienceDirect, Google Scholar and ResearchGate. Descriptive analysis mapped publication trends, geographical distribution, methodological preferences and underlying theoretical Models. Thematic synthesis was applied to extract and integrate the main determination of digital consumer habits across technological, psychological and social domain. Findings: The shows a steady global rise in research on digital consumer habits with Asian studies focusing largely on personalization, livestream commerce and AI -mediated engagement, while western studies emphasize privacy concerns, data ethics and trust. Across contexts, trust, perceived usefulness, social influence and platform usability emerged as the most consistent predictors of behavioral intention. In addition, repeated interaction, positive reinforcement, familiarity with platform features and social learning processes significantly increased consumer confidence, technology adoption likelihood and long-term loyalty. Contributions: The study offers an integrated framework that connects internal cognition, external digital ecosystems and consumer learning processes to explain the formation of digital consumption habits. It advances theoretical understanding by linking and extending TAM, TPB, DOI and S-O-R models to better capture user behavior within AI-enhanced digital environments.