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ZENODO
Journal . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
ZENODO
Journal . 2026
License: CC BY
Data sources: Datacite
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A COMPARATIVE STUDY OF TRADITIONAL VS. AI-DRIVEN ADVERTISING: CONSUMER PERCEPTIONS, PREFERENCES, AND IMPACT

Authors: Prof. Prajakta Bapat, Pratham Gujral, Logaigh Biju & Hardik Gehlot;

A COMPARATIVE STUDY OF TRADITIONAL VS. AI-DRIVEN ADVERTISING: CONSUMER PERCEPTIONS, PREFERENCES, AND IMPACT

Abstract

Advertising has undergone significant transformation due to technological advancement. While traditional advertising methods such as television, print media, radio, and outdoor displays have long dominated the industry, artificial intelligence-based advertising has emerged as a powerful digital alternative. This study comparatively examines consumer perceptions, preferences, trust levels, privacy concerns, and perceived effectiveness of traditional and artificial intelligence-based advertising. Primary data were collected through a structured questionnaire consisting of twenty questions and distributed online to more than one hundred forty participants across different age groups and genders. Quantitative data were analyzed using percentage analysis, and qualitative responses were examined using thematic analysis. The findings indicate that artificial intelligence-based advertising is perceived as more personalized, relevant, and efficient, whereas traditional advertising is considered more trustworthy and emotionally appealing. The study also reveals that privacy concerns significantly influence consumer attitudes toward artificial intelligence based advertisements. The results suggest that integrating personalization with credibility may offer the most effective advertising strategy for contemporary consumers.

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green