Trust-Supporting Design Elements as Signals for AI-Based Chatbots in Customer Service: A Behavior-Based Explanatory Model

Martin Sonntag, Jens Mehmann and Frank Teuteberg
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Martin Sonntag: Jade University of Applied Sciences, Germany
Jens Mehmann: Jade University of Applied Sciences, Germany
Frank Teuteberg: Osnabrück University, Germany

International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 2023, vol. 14, issue 1, 1-16

Abstract: In the present study, different trust factors regarding customers' perceptions of their intention to interact with or without trust-supporting design elements as signals (stimuli) in an artificial intelligence (AI)-based chatbot in customer service are identified. Based on 199 publications, a research model is derived for identifying and evaluating various variables influencing customers' views of their intention to interact with or without trust-supporting design elements as signals (stimuli) in AI-based chatbots in customer service. The research approach of the study model includes the influencing variables of perceived security and traceability, perceived social presence, and trust. A survey with 158 survey participants is used to empirically evaluate the model developed. One of the main findings of this research study is that perceived security and comprehensibility have a significant influence on the usage intention of an AI-based chatbot with trust-supporting design elements as signals (stimuli) in customer service.

Date: 2023
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International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) is currently edited by Ahmad Taher Azar

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