The integration of artificial intelligence into market systems has fundamentally altered the mechanisms through which consumers perceive, evaluate, and trust economic exchanges. This study investigates how algorithmic decision architectures reshape consumer trust within digital marketplaces, particularly in contexts where transparency is limited and personalization is high. By synthesizing behavioral economics with marketing theory, the paper develops a conceptual framework explaining trust formation under algorithmic influence. A mixed-method research design was employed, combining simulated consumer environments with perception-based surveys. Findings reveal that trust is no longer solely derived from brand reputation or prior experience but is increasingly mediated by perceived algorithmic fairness, interpretability, and control. The study also identifies paradoxical effects, where increased personalization simultaneously enhances convenience and triggers skepticism. The research contributes to emerging discourse on digital trust by offering new theoretical insights and practical implications for firms navigating AI-integrated market ecosystems. The rapid integration of artificial intelligence (AI) into digital marketplaces has fundamentally transformed consumer decision-making processes, raising critical questions about trust formation in algorithmically mediated environments. This study examines how AI-driven decision architectures reshape consumer trust through the lens of behavioral economics and cognitive psychology. The objective is to understand the mechanisms through which algorithmic recommendations influence perceived credibility, decision confidence, and behavioral outcomes in platform-based economies.

A qualitative-analytical research design is employed, drawing upon established theories of bounded rationality, trust in automation, and behavioral heuristics. The study synthesizes prior empirical findings on algorithm aversion, automation bias, and digital persuasion to construct an integrative framework explaining consumer responses to AI systems.

Algorithmic trust, consumer behavior, digital marketplaces, AI personalization, behavioral economics, marketing systems

Alden, P. R., & Kovarik, L. J. (2021). Adaptive consumption in machine-mediated environments. Journal of Digital Market Behavior, 14(3), 211–229.

Breslin, T. M. (2020). Cognitive shortcuts in automated decision systems. International Review of Behavioral Economics, 9(2), 88–104.

Carroway, S. D., & Imber, F. N. (2022). Perceived fairness in algorithmic pricing models. Journal of Economic Interface Studies, 11(4), 301–320.

Demeris, H. K. (2019). Trust recalibration in virtual consumption spaces. Global Journal of Marketing Systems, 7(1), 55–73.

Eldridge, V. P., & Solano, R. T. (2023). Algorithmic opacity and consumer skepticism. Advances in Digital Economics, 18(2), 144–162.

Fenton, C. L. (2021). Behavioral implications of predictive recommendation systems. Journal of Applied Market Psychology, 6(3), 177–195.

Garron, E. J. (2020). Personalization thresholds and privacy perception. Marketing Intelligence Quarterly, 12(1), 66–84.

Havik, D. S., & Renshaw, B. (2022). Ethical AI in consumer markets. Journal of Contemporary Economic Ethics, 5(2), 98–117.

Iversen, K. P. (2019). Heuristic trust formation in digital interfaces. Review of Consumer Dynamics, 10(4), 233–251.

Jorvik, L. M. (2023). Interface design and perceived control. International Journal of Market Interaction, 15(1), 120–138.

Kestrel, A. V. (2021). Algorithmic bias and trust erosion. Journal of Economic Behavior Studies, 13(3), 201–219.

Lornis, F. D., & Paxton, E. (2020). Trust signals in automated commerce. Digital Economy Review, 8(2), 77–93.

Mirek, T. J. (2022). Consumer cognition in AI environments. Journal of Market Cognition, 9(4), 289–307.

Norwell, C. H. (2019). Adaptive systems and user perception. Global Review of Marketing Science, 6(1), 44–62.

Ortega, P. S., & Linford, M. (2023). Decision transparency in algorithmic platforms. Journal of Economic Systems Design, 17(2), 156–174.

Perrin, J. L. (2021). Trust asymmetry in digital consumption. Marketing Behavior Insights, 11(3), 199–217.

Quade, R. T. (2020). Perceived legitimacy of automated systems. Journal of Behavioral Market Theory, 7(2), 134–150.

Ravelle, S. M. (2022). User agency in AI-driven markets. International Journal of Digital Commerce Studies, 14(4), 275–293.

Selwick, D. A. (2019). Psychological responses to predictive analytics. Journal of Consumer Psychology Trends, 5(3), 90–108.

Torrence, B. K., & Yalin, G. (2023). Trust reconstruction in algorithmic ecosystems. Journal of Emerging Market Structures, 16(1), 188–206.

Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.

Dietvorst, B. J., Simmons, J. P., & Massey, C. (2015). Algorithm aversion: People erroneously avoid algorithms after seeing them err. Journal of Experimental Psychology: General, 144(1), 114–126.

Logg, J. M., Minson, J. A., & Moore, D. A. (2019). Algorithm appreciation: People prefer algorithmic to human judgment. Organizational Behavior and Human Decision Processes, 151, 90–103.

Gigerenzer, G. (2008). Rationality for Mortals: How People Cope with Uncertainty. Oxford University Press.

Lee, J. D., & See, K. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46(1), 50–80.

Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors, 39(2), 230–253.

Castelo, N., Bos, M. W., & Lehmann, D. R. (2019). Task-dependent algorithm aversion. Journal of Marketing Research, 56(5), 809–825.

.Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age. W. W. Norton & Company.

Zuboff, S. (2019). The Age of Surveillance Capitalism. PublicAffairs.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

Sunstein, C. R. (2015). Choosing Not to Choose: Understanding the Value of Choice Architecture. Oxford University Press.

Thaler, R. H., & Sunstein, C. R. (2008). Nudge: Improving Decisions About Health, Wealth, and Happiness. Yale University Press.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Langer, E. J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311–328.

Mousavi, S., & Gigerenzer, G. (2014). Risk, uncertainty, and heuristics. Journal of Business Research, 67(8), 1671–1678.

Kleinberg, J., Ludwig, J., Mullainathan, S., & Obermeyer, Z. (2015). Prediction policy problems. American Economic Review, 105(5), 491–495.

Kietzmann, J., Paschen, J., & Treen, E. (2018). Artificial intelligence in advertising. Journal of Advertising Research, 58