A Study on Consumer Trust In AI-Recommended Products Towards E-Commerce Platforms With Reference to Flipkart

Artificial intelligence (AI) is increasingly used by e-commerce platforms to recommend products based on browsing behaviour, purchase history, product preferences and other signals. These recommendations may help consumers discover relevant products and make shopping more convenient. However, consumer trust can be affected by recommendation accuracy, transparency, the quality of product information, customer reviews and concerns about personal data. This study examines consumer trust in AI-recommended products on e-commerce platforms with particular reference to Flipkart. It considers awareness of recommendations, perceived relevance, trust, factors influencing purchase intention, privacy concerns and preferred improvements. A descriptive research framework and structured questionnaire are used. For demonstrating the required analysis format, the tables in this draft contain an illustrative dataset of 55 responses. These figures are simulated for project preparation and must be replaced with actual questionnaire results before the project is submitted as empirical research. The illustrative pattern suggests that consumers are more likely to engage with recommendations when they appear relevant and are supported by reliable product details and reviews. Clear explanations and accessible privacy controls are proposed as ways to strengthen trust.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-04
DOI
https://doi.org/10.5281/zenodo.23943356
Primary Topic
Technology Adoption and User Behaviour
Type
article
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article

A Study on Consumer Trust In AI-Recommended Products Towards E-Commerce Platforms With Reference to Flipkart

James Christopherm Mrs. Srilaya Babu
Zenodo (CERN European Organization for Nuclear Research)
Technology Adoption and User Behaviour
article

A Study on Consumer Trust In AI-Recommended Products Towards E-Commerce Platforms With Reference to Flipkart

James Christopherm Mrs. Srilaya Babu
article en

Abstract

Artificial intelligence (AI) is increasingly used by e-commerce platforms to recommend products based on browsing behaviour, purchase history, product preferences and other signals. These recommendations may help consumers discover relevant products and make shopping more convenient. However, consumer trust can be affected by recommendation accuracy, transparency, the quality of product information, customer reviews and concerns about personal data. This study examines consumer trust in AI-recommended products on e-commerce platforms with particular reference to Flipkart. It considers awareness of recommendations, perceived relevance, trust, factors influencing purchase intention, privacy concerns and preferred improvements. A descriptive research framework and structured questionnaire are used. For demonstrating the required analysis format, the tables in this draft contain an illustrative dataset of 55 responses. These figures are simulated for project preparation and must be replaced with actual questionnaire results before the project is submitted as empirical research. The illustrative pattern suggests that consumers are more likely to engage with recommendations when they appear relevant and are supported by reliable product details and reviews. Clear explanations and accessible privacy controls are proposed as ways to strengthen trust.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 10%
Technology Adoption and User Behaviour
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