In the context of AI-based conversational agents, existing trust theories are fragmented. Researchers may get lost and feel confused in reading existing literature with diverse perspectives. Based on prior literature, there is a need to expand existing frameworks by integrating different views into one comprehensive model. In this paper, we aim to clarify all different views in trust antecedents and identify a comprehensive framework that can be generalized to various contexts. Our research question is: What factors affect the trust beliefs of users to interact with AI-based conversational agents (AICA) in customer service? Grounded on the theory of ABI (i.e., Ability, Benevolence, Integrity) (Mayer et al. 1995) for trusting beliefs, we take unique characteristics of AI-based conversational agents for customer service into account to study trust antecedents. Specifically, we propose a theoretical framework to empirically examine the trust antecedents on trusting beliefs in AI-based conversational agents, and the impact of trusting beliefs on the trusting intentions towards AI-based conversational agents. Our proposed framework differs from previous articles in several ways: 1) We clarify definitions and categorization for trust-related concepts; 2) We incorporate existing literature in trust antecedents into a comprehensive framework; 3) We apply the comprehensive framework to the context of AI-based conversational agents in the customer service. The proposed research model is illustrated in Figure 1.
Wang, Wenting, "Trust in AI-based conversational agents in the customer service - a theoretical framework" (2021). AMCIS 2021 TREOs. 45.
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