Artikel
How gamifying AI shapes customer motivation, engagement, and purchase behavior
Recently, firms started to gamify conversational artificial intelligence (AI) agents, such as chatbots, to improve purchase outcomes. This article explores strategies for incorporating gamification into AI systems by investigating the impact of utilitarian and hedonic motivations facilitated by gamified chatbots on various dimensions of customer engagement (cognitive, emotional, and behavioral), as well as the subsequent effects of these dimensions on customers' purchase behavior. By conducting one cross‐sectional and two experimental studies involving real interactions with gamified chatbots, this research identifies two crucial paths that warrant attention: an optimal path from hedonic motivation to behavioral engagement, resulting in enhanced purchase, and a detrimental path from utilitarian motivation to emotional engagement, which reduces purchase. Furthermore, the research compares the effects of two types of gamified chatbots and reveals that a game‐of‐chance‐based chatbot, as opposed to a knowledge‐sharing gamified chatbot, aligns with the optimal path, leading to higher purchasing while at the same time avoiding that customers feel obligated to play the game. Based on these findings, the article provides actionable insights for eliciting favorable psychological and behavioral responses through gamified AI interactions.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Psychology & Marketing ; ISSN: 1520-6793 ; Volume: 41 ; Year: 2023 ; Issue: 1 ; Pages: 134-150 ; Hoboken, NJ: Wiley
- Klassifikation
-
Management
- Thema
-
artificial intelligence
customer engagement
gamification
gamified chatbots
perceived autonomy
purchase behavior
utilitarian and hedonic motivations
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Elmashhara, Maher Georges
De Cicco, Roberta
Silva, Susana C.
Hammerschmidt, Maik
Silva, Maria Levi
- Ereignis
-
Veröffentlichung
- (wer)
-
Wiley
- (wo)
-
Hoboken, NJ
- (wann)
-
2023
- DOI
-
doi:10.1002/mar.21912
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Elmashhara, Maher Georges
- De Cicco, Roberta
- Silva, Susana C.
- Hammerschmidt, Maik
- Silva, Maria Levi
- Wiley
Entstanden
- 2023
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