Logo des Repositoriums
 

Potential of Facebook’s artificial intelligence for marketing

dc.contributor.authorJanssen, Martin
dc.contributor.editorGandorfer, Markus
dc.contributor.editorHoffmann, Christa
dc.contributor.editorEl Benni, Nadja
dc.contributor.editorCockburn, Marianne
dc.contributor.editorAnken, Thomas
dc.contributor.editorFloto, Helga
dc.date.accessioned2022-02-24T13:34:39Z
dc.date.available2022-02-24T13:34:39Z
dc.date.issued2022
dc.description.abstractDue to the Corona pandemic and the age of digitization, online food platforms have become more and more important. Therefore, the trend to buy food online is increasing. Nevertheless, many direct sellers and especially conventional farmers are not familiar with selling their products online. Different barriers can affect the acceptance of selling food online. Artificial Intelligence (AI) can help to reduce barriers and fill the gap of missing know-how. This study uses Facebook’s AI for targeted marketing campaigns to find the potential audiences that consist of online food buyers based on significant results of a quantitative online survey (n=172). As a result, people with properties such as animal welfare proponents had a positive mood towards buying local food online.en
dc.identifier.isbn978-3-88579-711-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/38383
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof42. GIL-Jahrestagung, Künstliche Intelligenz in der Agrar- und Ernährungswirtschaft
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-317
dc.subjectArtificial Intelligence (AI)
dc.subjectmarketing
dc.subjectdirect marketer
dc.subjectFacebook Targeting
dc.subjectquantitative survey
dc.titlePotential of Facebook’s artificial intelligence for marketingen
dc.typeText/Conference Paper
gi.citation.endPage134
gi.citation.publisherPlaceBonn
gi.citation.startPage129
gi.conference.date21.-22. Februar 2022
gi.conference.locationTänikon, Online

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
GIL2022_Janssen_129-134.pdf
Größe:
181.71 KB
Format:
Adobe Portable Document Format