Artificial Intelligence and Consumer Decision-Making in Business Administration: A Systematic Literature Review and the Enhanced TTG Framework

Abstract

This systematic literature review examines how Artificial Intelligence (AI) is reshaping business administration, with particular emphasis on consumer decision-making. Following PRISMA guidelines, the review synthesizes evidence from 85 peer-reviewed studies published between 2010 and 2024 and retrieved from Scopus, Web of Science, and ScienceDirect. The analysis identifies four dominant mechanisms through which AI influences consumer decisions: personalization and recommender systems, predictive analytics, dynamic pricing, and AI-enabled customer service. While these applications can improve decision efficiency, relevance, and convenience, the literature also reports persistent risks, including algorithmic bias, limited transparency, perceived unfairness, and potential erosion of consumer autonomy. To integrate these insights, the study proposes an enhanced Trust-Transparency-Governance (TTG) framework that conceptualizes responsible consumer-facing AI as the interaction of (a) trust in algorithmic outputs, (b) transparency of models and decision logic, and (c) organizational governance structures that ensure accountability and ethical alignment. Extending prior AI ethics frameworks, the enhanced TTG model specifies mechanism-based linkages, how transparency shapes trust, how governance operationalizes transparency, and under which conditions these components jointly support responsible AI deployment. The review concludes with implications for managers and policymakers and highlights research gaps, notably the need for empirical studies on consumer responses to transparency interventions, fairness trade-offs, and algorithmic influence on autonomy across diverse market contexts.