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Article: Tales of Two Channels: Digital Advertising Performance Between AI Recommendation and User Subscription Channels

TitleTales of Two Channels: Digital Advertising Performance Between AI Recommendation and User Subscription Channels
Authors
Keywordsartificial intelligence
click-through rate
conversion rate
digital advertising
in-feed advertising
native advertising
recommendation
subscription
Issue Date12-Jul-2023
PublisherSAGE Publications
Citation
Journal of Marketing, 2023, v. 88, n. 2, p. 141-162 How to Cite?
Abstract

Although in-feed advertising is popular on mainstream platforms, academic research on it is limited. Platforms typically deliver organic content through two methods: subscription by users or recommendation by artificial intelligence. However, little is known about the ad performance between these two channels. This research examines how the performance of in-feed ads, regarding click-through rate (CTR) and conversion rate (CR), differs between subscription and recommendation channels and whether these effects are mediated by ad intrusiveness and moderated by ad attributes. Two ad attributes are investigated: ad appeal (informational vs. emotional) and ad link (direct vs. indirect). Study 1 finds that the recommendation channel generates higher CTRs but lower CRs than the subscription channel, and these effects are amplified by informational ad appeal and direct ad links. Study 2 explores channel differences, revealing that the recommendation channel yields less source credibility and content control, reducing consumer engagement with organic content. Studies 3 and 4 validate the mediating role of ad intrusiveness and rule out ad recognition as an alternative explanation. Study 5 uses eye-tracking technology to show that the recommendation channel has lower content engagement, lower ad intrusiveness, and greater ad interest.


Persistent Identifierhttp://hdl.handle.net/10722/337049
ISSN
2023 Impact Factor: 11.5
2023 SCImago Journal Rankings: 11.799
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorDong, Beibei-
dc.contributor.authorZhuang, Mengzhou-
dc.contributor.authorFang, Eric-
dc.contributor.authorHuang, Minxue-
dc.date.accessioned2024-03-11T10:17:42Z-
dc.date.available2024-03-11T10:17:42Z-
dc.date.issued2023-07-12-
dc.identifier.citationJournal of Marketing, 2023, v. 88, n. 2, p. 141-162-
dc.identifier.issn0022-2429-
dc.identifier.urihttp://hdl.handle.net/10722/337049-
dc.description.abstract<p>Although in-feed advertising is popular on mainstream platforms, academic research on it is limited. Platforms typically deliver organic content through two methods: subscription by users or recommendation by artificial intelligence. However, little is known about the ad performance between these two channels. This research examines how the performance of in-feed ads, regarding click-through rate (CTR) and conversion rate (CR), differs between subscription and recommendation channels and whether these effects are mediated by ad intrusiveness and moderated by ad attributes. Two ad attributes are investigated: ad appeal (informational vs. emotional) and ad link (direct vs. indirect). Study 1 finds that the recommendation channel generates higher CTRs but lower CRs than the subscription channel, and these effects are amplified by informational ad appeal and direct ad links. Study 2 explores channel differences, revealing that the recommendation channel yields less source credibility and content control, reducing consumer engagement with organic content. Studies 3 and 4 validate the mediating role of ad intrusiveness and rule out ad recognition as an alternative explanation. Study 5 uses eye-tracking technology to show that the recommendation channel has lower content engagement, lower ad intrusiveness, and greater ad interest.</p>-
dc.languageeng-
dc.publisherSAGE Publications-
dc.relation.ispartofJournal of Marketing-
dc.subjectartificial intelligence-
dc.subjectclick-through rate-
dc.subjectconversion rate-
dc.subjectdigital advertising-
dc.subjectin-feed advertising-
dc.subjectnative advertising-
dc.subjectrecommendation-
dc.subjectsubscription-
dc.titleTales of Two Channels: Digital Advertising Performance Between AI Recommendation and User Subscription Channels-
dc.typeArticle-
dc.identifier.doi10.1177/00222429231190021-
dc.identifier.scopuseid_2-s2.0-85170854985-
dc.identifier.volume88-
dc.identifier.issue2-
dc.identifier.spage141-
dc.identifier.epage162-
dc.identifier.eissn1547-7185-
dc.identifier.isiWOS:001093043000001-
dc.identifier.issnl0022-2429-

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