Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/288088 
Erscheinungsjahr: 
2023
Quellenangabe: 
[Journal:] Psychology & Marketing [ISSN:] 1520-6793 [Volume:] 40 [Issue:] 11 [Publisher:] Wiley [Place:] Hoboken, NJ [Year:] 2023 [Pages:] 2291-2305
Verlag: 
Wiley, Hoboken, NJ
Zusammenfassung: 
Digital companions are an advanced form of digital agents that do not only provide advice and support but accompany people on their day‐to‐day customer journeys. This article sheds light on the psychological processes underlying customers’ responses to these digital companions (i.e., virtual friends or co‐consumers). We propose that framing them as matched with customers on goal‐relevant attributes (i.e., attributes related to customers’ consumption goals) fosters positive customer outcomes (i.e., consumption enjoyment and positive word‐of‐mouth), mediated by perceived similarity in these attributes. Importantly, in this matching context, humanlikeness serves as a boundary condition for perceived similarity to occur. Furthermore, the effect of perceived similarity on customer outcomes is driven by perceived connectedness. In Study 1, in the context of experiential learning, we identified shared interest and personality as goal‐relevant attributes underlying perceived similarity. With the manipulation of the match frame and humanlike versus artificial voice of the digital companion, Study 2 supports our propositions and highlights shared interest, but not personality, as the core driver. We provide recommendations on how to design and market digital companions to foster connection and favorable customer outcomes.
Schlagwörter: 
co‐consumers
consumption enjoyment
digital agents
digital companions
human‐likeness
perceived connectedness
perceived goal‐relevant similarity
virtual friends
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by Logo
Dokumentart: 
Article
Dokumentversion: 
Published Version

Datei(en):
Datei
Größe





Publikationen in EconStor sind urheberrechtlich geschützt.