AI-Generated Review Summaries And Consumer Purchase Decisions: A Conceptual Framework For Indian Gen Z Consumers

Abstract Generative artificial intelligence is changing how consumers search for, evaluate and use information in digital marketplaces. One emerging application is the use of AI-generated review summaries, which condense large volumes of online consumer reviews into concise statements about product strengths, weaknesses and frequently mentioned attributes. Such summaries can reduce information overload and improve search efficiency, but they also raise concerns regarding credibility, transparency, objectivity, selective omission and consumer reliance on machine-generated interpretations of peer opinions. This study examines AI-generated review summaries and their potential influence on purchase decisions among Indian Gen Z consumers. The study is primarily secondary-research-led and synthesises recent literature on AI-mediated electronic word-of-mouth, review credibility, transparency, trust and perceived diagnosticity. To complement the secondary evidence, an exploratory primary survey of 120 respondents collected through Google Forms is incorporated as an empirical component. The study adopts the Stimulus-Organism-Response (S-O-R) perspective and signalling theory to structure the relationships among perceived transparency, perceived usefulness, perceived objectivity, consumer trust, perceived diagnosticity and purchase intention. The paper proposes that trust and diagnosticity function as important mechanisms through which characteristics of AI-generated review summaries can influence purchase intention. The empirical component is designed to provide descriptive and exploratory evidence rather than to replace the broader secondary research base. Statistical analysis includes respondent profiling, descriptive statistics, reliability assessment, correlation analysis and appropriate hypothesis testing, subject to the structure of the 120-response dataset. The study contributes to understanding how AI-mediated review information can support consumer decision-making while highlighting the importance of transparency, balanced representation and access to original reviews.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-30
DOI
https://doi.org/10.5281/zenodo.23012753
Primary Topic
Digital Marketing and Social Media
Type
article
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article

AI-Generated Review Summaries And Consumer Purchase Decisions: A Conceptual Framework For Indian Gen Z Consumers

Arpita Nayak, shahid ahmad Shiza Mohommad, Sneha Naik, Nikita Sharma
Zenodo (CERN European Organization for Nuclear Research)
Digital Marketing and Social Media
article

AI-Generated Review Summaries And Consumer Purchase Decisions: A Conceptual Framework For Indian Gen Z Consumers

Arpita Nayak, shahid ahmad Shiza Mohommad, Sneha Naik, Nikita Sharma
article en

Abstract

Abstract Generative artificial intelligence is changing how consumers search for, evaluate and use information in digital marketplaces. One emerging application is the use of AI-generated review summaries, which condense large volumes of online consumer reviews into concise statements about product strengths, weaknesses and frequently mentioned attributes. Such summaries can reduce information overload and improve search efficiency, but they also raise concerns regarding credibility, transparency, objectivity, selective omission and consumer reliance on machine-generated interpretations of peer opinions. This study examines AI-generated review summaries and their potential influence on purchase decisions among Indian Gen Z consumers. The study is primarily secondary-research-led and synthesises recent literature on AI-mediated electronic word-of-mouth, review credibility, transparency, trust and perceived diagnosticity. To complement the secondary evidence, an exploratory primary survey of 120 respondents collected through Google Forms is incorporated as an empirical component. The study adopts the Stimulus-Organism-Response (S-O-R) perspective and signalling theory to structure the relationships among perceived transparency, perceived usefulness, perceived objectivity, consumer trust, perceived diagnosticity and purchase intention. The paper proposes that trust and diagnosticity function as important mechanisms through which characteristics of AI-generated review summaries can influence purchase intention. The empirical component is designed to provide descriptive and exploratory evidence rather than to replace the broader secondary research base. Statistical analysis includes respondent profiling, descriptive statistics, reliability assessment, correlation analysis and appropriate hypothesis testing, subject to the structure of the 120-response dataset. The study contributes to understanding how AI-mediated review information can support consumer decision-making while highlighting the importance of transparency, balanced representation and access to original reviews.

Zenodo (CERN European Organization for Nuclear Research)
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Digital Marketing and Social Media
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AI-Generated Review Summaries And Consumer Purchase Decisions: A Conceptual Framework For Indian Gen Z Consumers — Arpita Nayak, shahid ahmad Shiza Mohommad, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS