Chatbot task-technology fit and conversational intelligence on customer service encounter satisfaction in the Zimbabwean banking sector - Nqobani Ncube; More Chinakidzwa; Tawanda Mushayavanhu (Journal of Research and Innovation for Sustainable Society)
The study explores the interactions among chatbot tasks, technology, and conversational intelligence, and their effect on customer service encounter satisfaction to improve customer gratification in the Zimbabwean banking sector. The aim of the research study is to determine the influence of chatbot tasktechnology on conversational intelligence characteristics and customer service encounter satisfaction in the Zimbabwean banking sector. The empirical evidence was acquired using structured questionnaires from 365 bank employees and 500 bank customers in Zimbabwe, using a concurrent nested approach. The study indicated that chatbot task and technology characteristics directly influenced chatbot task-technology fit, customer service encounter satisfaction, proactivity, and communicability. The study contributes to chatbot task-technology theory and chatbot-human interaction studies. The research shows that conversational intelligence must align with chatbot task and technology characteristics to achieve a better fit between the task and technology in the banking sector, which can help improve customer service encounter satisfaction. The study contextualizes the framework in the banking sector in Zimbabwe, and the outlined research questions may apply to other service sectors where service digitalization is occurring (i.e., health care). Additional research studies in different regions of the world might be conducted to provide cross-cultural comparability and empirical validation.