Stereotype Content Model (SCM) and Chatbots / Conversational Interfaces – an experiment comparing trust, competence and warmth dimensions
(A2019-8468)

AUTHORS

Roger Seiler, Zurich University of Applied Sciences (ZHAW); Steffen Müller, ZHAW School of Management and Law; Markus Beinert, Hochschule Weihenstephan-Triesdorf

KEYWORDS

stereotype content model (SCM); chatbots; trust

ABSTRACT

With the rising popularity of chatbots this research paper seeks to answer the question if the stereotype content model (SCM) applies to the domain of chatbots or broader to conversational interfaces. This study answers this research question by conducting an experiment containing different stereotypes (lovable star and incompetent jerk). The SCM applies to the domain of chatbots. The lovable star stereotype chatbot is perceived as more trustworthy as well as more competent and warmer compared to the incompetent jerk. Participants pointed out that they want to know if they are talking to a chatbot and not to a real human. Nevertheless, further research is required regarding traditional text chatbots because the lovable star did not show higher trustworthiness than the text chatbot. Furthermore, these research results suggest, that data privacy is a further, important aspect as customers typically share information when engaging in a conversation with a chatbot.