An Initial Model of Trust in Chatbots for Customer Service—Findings from a Questionnaire Study
Open accessAbstract
Chatbots are predicted to play a key role in customer service. Users’ trust in such chatbots is critical for their uptake. However, there is a lack of knowledge concerning users’ trust in chatbots. To bridge this knowledge gap, we present a questionnaire study (N = 154) that investigated factors of relevance for trust in customer service chatbots. The study included two parts: an explanatory investigation of the relative importance of factors known to predict trust from the general literature on interactive systems and an exploratory identification of other factors of particular relevance for trust in chatbots. The participants were recruited as part of their dialogue with one of four chatbots for customer service. Based on the findings, we propose an initial model of trust in chatbots for customer service, including chatbot-related factors (perceived expertise and responsiveness), environment-related factors (risk and brand perceptions) and user-related factors (propensity to trust technology). RESEARCH HIGHLIGHTS: We extend the current knowledge base on natural language interfaces by investigating factors affecting users’ trust in chatbots for customer service. Chatbot-related factors, specifically perceived expertise and responsiveness, are found particularly important to users’ trust in such chatbots, but also environment-related factors such as brand perception and user-related factors such as propensity to trust technology. On the basis of the findings, we propose an initial model of users’ trust chatbots for customer service.
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Chatbot users need to see and experience the bots as providing answers reflecting knowledge, competence, and experience.
“Chatbot users (patients) need to see and experience the bots as ‘providing answers reflecting knowledge, competence, and experience’ (p. 24)—all of which are important to trust.”
From Chatbot breakthrough in the 2020s? An ethical reflection on the trend of automated consultations in health care (2022) · cites this paper as Nordheim et al. 2019
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- Authors
- Nordheim, C. B., Følstad, A., & Bjørkli, C. A.
- Affiliations
- University of Oslo (NO)
- SINTEF Digital (NO)
- Corresponding author
- Følstad, Asbjørn
- Venue
- Interacting with Computers
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-05-01
- Volume
- 31
- Issue
- 3
- Pages
- 317-335
- ISSN
- 0953-5438 (ISSN-L)
- 1873-7951
- OpenAlex
- W2970416896
- Cited by
- 233
- References
- 49
- Citations by year
- 2026: 44 · 2025: 45 · 2024: 41 · 2023: 40 · 2022: 35 · 2021: 24 · 2020: 3 · 2019: 1
- FWCI
- 7.18
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Interacting with Computers (publishedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
- Funders
- Research Council of Norway (270940)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Keywords
- chatbots, trust in chatbots, customer service, perceived expertise, responsiveness, brand perception, risk perception, trust model, natural language interfaces, human-chatbot interaction
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