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The Effect of Perceived Similarity in Dominance on Customer Self-Disclosure to Chatbots in Conversational Commerce

Gnewuch, Ulrich; Yu, Meng; Maedche, Alexander

Abstract:
Recent years have seen increased interest in the application of chatbots for conversational commerce. However, many chatbots are falling short of their expectations because customers are reluctant to disclose personal information to them (e.g., product interest, email address). Drawing on social response theory and similarity-attraction theory, we investigated (1) how a chatbot’s language style influences users’ perceived similarity in dominance (i.e., an important facet of personality) between them and the chatbot and (2) how these perceptions influence their self-disclosure behavior. We conducted an online experiment (N=205) with two chatbots with different language styles (dominant vs. submissive). Our results show that users attribute a dominant personality to a chatbot that uses strong language with frequent assertions, commands, and self-confident statements. Moreover, we find that the interplay of the user’s own dominance and the chatbot’s perceived dominance creates perceptions of similarity. These perceptions of similarity increase users’ degree of self-disclosure via an increased likelihood of accepting the chatbot’s advice. ... mehr



Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2020
Sprache Englisch
Identifikator KITopen-ID: 1000120358
Erschienen in Proceedings of the 28th European Conference on Information Systems (ECIS 2020)
Veranstaltung 28th European Conference on Information Systems (ECIS 2020), Marrakesch, Marokko, 15.06.2020 – 17.06.2020
Verlag AIS eLibrary
Bemerkung zur Veröffentlichung Die Veranstaltung fand wegen der Corona-Pandemie als Online-Event statt
Schlagwörter chatbot, language style, dominance, self-disclosure, personality similarity
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