Consumer Segmentation Based on Perceptions of Generative AI-Assisted Sustainable Product Recommendations: A K-Means Cluster Analysis

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Roshni Kumari
 Sandeep Kumar Rawat
Shweta Yadav
Deepti Maurya
Poonam Vij

Abstract

Generative Artificial Intelligence (GenAI) has revolutionised online retail, with intelligent, personalised, and interactive product recommendation systems. Despite the increased use of AI-based recommendation technologies, consumers differ significantly in their perceptions of recommendation quality, their trust in recommendations, their understanding of how the algorithm works, its personalisation, and, most importantly, their confidence in AI's influence when deciding to purchase. When designing such AI-driven shopping experiences, it is crucial to understand these differences. This study aims to identify consumer segments based on their perceptions of sustainable product recommendations through Generative AI. The analysis yielded a stable three-cluster solution.

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[1]
Roshni Kumari,  Sandeep Kumar Rawat, Shweta Yadav, Deepti Maurya, and Poonam Vij , Trans., “Consumer Segmentation Based on Perceptions of Generative AI-Assisted Sustainable Product Recommendations: A K-Means Cluster Analysis”, IJMH, vol. 13, no. 1, pp. 1–9, Sep. 2026, doi: 10.35940/ijmh.A1902.13010926.
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