Unlocking the precursors of customer service experience using artificial intelligence-driven chatbot: calibration of gratification theory and expectation confirmation model

Purpose Artificial intelligence (AI)-enabled chatbots have the potential to revolutionize the way businesses interact with customers. Nevertheless, there is a lack of empirical research that discloses factors that enhance chatbot user satisfaction and experience. The current study fills a research gap and develops a research framework that combines technology gratification theory, expectation confirmation model and technology competency to investigate artificial intelligence (AI)-driven chatbot user satisfaction and chatbot user experience. Design/methodology/approach The research design of this study is based on a quantitative research approach. The research framework has outlined multiple latent factors that are verified with empirical data. Overall, 373 respondents had participated in the chatbot research survey. Data are analyzed with structural equation modeling. Findings Findings of the structural equation modeling have unveiled that utilitarian gratification, hedonic gratification, social gratification, emotional competency, cognitive competency, relational competency and expectation confirmation explained substantial variance Rˆ2 53.4% in measuring chatbot user satisfaction. Likewise, user satisfaction and perceived anthropomorphism had explained large variance Rˆ2 55.5% in measuring chatbot user experience. Nevertheless, effect size fˆ2 analysis has revealed a large effect size of cognitive competency in measuring chatbot user satisfaction. Practical implications This study sheds light on crucial factors influencing chatbot user satisfaction and gleans numerous theoretical and practical implications. For instance, the research model is grounded in technology gratification theory, the expectation confirmation model and technology competency to investigate chatbot user satisfaction and hence enriched information system literature. Practically, this study has suggested that user expectation, utilitarian gratification and cognitive competency are influential factors that enhance chatbot user experience, and hence policymakers should consider these factors while developing new AI-driven chatbot applications. Originality/value This study is a pioneer in investigating AI-driven chatbot user experience with factors grounded in technology gratification theory, expectation the confirmation model and the technology competency model. Moreover, examining the moderating effect of anthropomorphism between chatbot user satisfaction and AI-driven chatbot user experience has made this research unique. The findings of this study are in line with United Nations Sustainable Development Goals (SDGs) and boost SDGs by promoting decent work, industry innovation and sustainable economic growth using an AI-driven chatbot.