An empirical study on the relationship between service capability and perceived service quality of AI chatbot

초록

Research Objective This study aims to empirically test the key antecedents of AI chatbot service quality from the perspective of AI-based Customer Relationship Management (AI-CRM). Those antecedents interactivity, personalization, empathy, and enjoyment, which has a positive impact on contextual interaction, service competence, and perceived service quality of AI chatbots. Research Design/Methodology Data were collected through a survey targeting respondents with experience using AI chatbot services. A total of 347 valid responses were analyzed using Structural Equation Modeling(SEM) to test the proposed hypotheses. Research Findings Interactivity, personalization, and enjoyment positively influenced contextual interaction, while empathy did not have a significant impact. Contextual interaction positively affected functional customer orientation but did not influence relational customer orientation. Furthermore, both functional and relational customer orientation competencies had a positive impact on perceived service quality. Trust in AI chatbots was found to enhance this relationship. The findings highlight the importance of functional customer orientation in AI-CRM systems, suggesting that AI chatbots should focus on meeting customers' practical needs and improving operational efficiency. Additionally, the study emphasizes the need for strategic approaches to strengthen relational customer orientation in AI chatbot interactions.

키워드