Abstract
Humanizing customer service chatbots have sparked significant interest for companies across industries. These years have witnessed some controversy on trust issues of such booming application. Previous researches have proposed some antecedents of customer service chatbots adoption (e.g., anthropomorphic features, algorithm aversion, emotional state). However, consumers’ trust mechanism and trust boundary on humanizing customer service chatbots are not clear. Hence, we pay attention to personalization and contextualization grounded on above antecedents of customer service, incorporating personal habit, task creativity and social presence to investigate trust mechanism and trust boundary. We propose a research model, in which personal habit and task creativity are captured as independent variables, trust in humanizing customer service chatbots as dependent variable, and social presence as moderating variable. Hypotheses are developed and between-subjects scenario experiments are conducted to test hypotheses. Results of analysis of covariance (ANCOVA) and moderating effect test show that there exists positive effect between personal habit and trust in humanizing customer service chatbots, giving insights on complementary and substitutive influences on the interaction of independent variables and social presence for trust boundary. This paper provides practical and theoretical implications for e-commerce practitioners to improve the collaboration performance of intelligent customer service and human customer service.
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Acknowledgements
This research is supported by the National Natural Science Foundation of China through grant 72171187, and partially supported by the Key Project of Shaanxi International Science and Technology Cooperation through grant 2018KWZ-04.
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Qi, Y., Du, R., Yang, R. (2022). Consumers’ Trust Mechanism and Trust Boundary on Humanizing Customer Service Chatbots in E-commerce. In: Fui-Hoon Nah, F., Siau, K. (eds) HCI in Business, Government and Organizations. HCII 2022. Lecture Notes in Computer Science, vol 13327. Springer, Cham. https://doi.org/10.1007/978-3-031-05544-7_36
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