Impact of System-Level Indicators of Chatbots on Perceived Usefulness and Intention to use for Banking Services

Technology is rapidly mounting, and AI has transformed the financial industry rapidly. The primary objective of the research is to identify factors (like Design, Information Quality, Security, and Facilitating Conditions) that influence a customer to employ chatbot technology in the banking industry. A survey of 250 respondents was carried out utilizing an online questionnaire. The study’s target respondents are customers who use banking services and chatbots through a random sampling method. The structured questionnaire employed in this study comprised two modules: one detailing the attributes of respondents and enterprises and the other containing questions on research constructs. The Stimulus Theoretical Framework and Technology Acceptance Model were tested throughout the study. The model helps to analyze the factors responsible for customer propensity that influence the use of chatbots. The research first conducted an exploratory factor analysis (EFA) to determine the measured data’s structure. The internal consistency of data was tested using Cronbach’s alpha values. Finally, the research hypothesis was assessed using Structural Equation Modeling (SEM). The research findings can help banks to meet the needs of their diverse customer base. The study would help the providers of chatbot services to reduce the complexity of communication and services for the users and make the customers adopt the technology services without any intervention. This develops trust among the consumers, thus making it a valuable contribution.