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Original Article | Volume 2 Issue 4 (ACR, 2025) | Pages 3216 - 3224
AI and Consumer Psychology: Personalization, Ethical Nudging, and Digital Decision-Making
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Associate Professor, Department: Commerce, Institute: SRM Institute of Science and Technology, Ramapuram, District: Chennai, City: Chennai, State: Tamilnadu
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Assistant Professor Amity University Jharkhand Ranchi
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Associate Professor, Department: Commerce, Institute: Dr. Babasaheb Ambedkar College Aundh , Pune.-411067. Maharashtra
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Assistant Professor, Department: Management Institute: Savitribai Phule University- S. B. Patil Institute of Management, District: Pune, City: Pune, State: Maharashtra
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Assistant Professor, Department of Business Management, Sankalchand Patel College of Engineering, Sankalchand Patel University, Visnagar
Under a Creative Commons license
Open Access
Abstract

The embracement of Artificial Intelligence (AI) within the sphere of consumer culture is redefining the manner in which people perceive, analyze and make decisions within the virtual world. The paper will analyze the interaction between ethics nudges, aspects of personalization that use AI, and consumer choices on e-commerce and personalized online services. We base findings on a hybrid approach to behavioral data analytics, controlled online experiments, and user sentiment analytics of user interactions, to examine how algorithmic personalization functions on tendencies of purchase intent, trust, and perceived autonomy. The experimental design involved 1,200 members of the three demographic clusters, urban millennium, mid-career professionals, and senior digital adopters, who received different levels of intensities of personalization, ethically targeted nudges. Findings show that hyper-personalized recommendations have achieved a 34 percent better engagement rate and vice versa created an additional algorithmic transparency and data privacy apprehension among the consumers. Setting ethical nudges in autonomy supportive language also resulted in a large increase in decision satisfaction with no reduction in conversion measures. A predictive decision making model that was constructed on the use of Gradient Boosting Machines was able to show accuracy of about 87 percent of accurately predicting likelihood of purchase based on personalization-nudge interaction variables. The results highlight the twin challenge that AI systems should in equal measure maximize business performance and consumer agency, and ethically designed principles. The study avails practical implications to marketers, designers of the platforms, and policy makers aimed at striking the balance between personalization effectiveness and ethical accountability of AI mediated markets.

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