Cited by 100AI in Service InteractionsDigital Marketing and Social MediaConsumer Behavior and Marketing Influence

A comparative study on the effect of ChatGPT recommendation and AI recommender systems on the formation of a consideration set

Chang, Woondeog, Park, Jungkun·2024·Journal of Retailing and Consumer Services

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Registry

Crossref · 10.1016/j.jretconser.2024.103743

Cites

68 of 68 references verified0 citation errors · 0 not checkable

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  • In making product recommendations, ChatGPT may have a significant impact on consumers' trust in it, leading to higher consumer intention to adopt its consideration set than those of other AI recommenders (e.g., Amazon).

    “In making product recommendations, ChatGPT may have a significant impact on consumers' trust in it, leading to higher consumer intention to adopt its consideration set than those of other AI recommenders (e.g., Amazon) [29].”

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Authors
Chang, W., & Park, J.
Affiliations
Hanyang University (KR)
Corresponding author
Park, Jungkun
Venue
Journal of Retailing and Consumer Services
Publisher
Elsevier BV
Published
2024-05
Volume
78
Pages
103743
ISSN
0969-6989 (ISSN-L)
OpenAlex
W4391979556
Cited by
92
References
68
Citations by year
2026: 47 · 2025: 33 · 2024: 12
FWCI
13.58
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Retailing and Consumer Services (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
  • Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
  • Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
Keywords
ChatGPT, consideration sets, consumer choice, brand awareness, perceived performance, purchase intention, moderating effect, generative AI in marketing

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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