Continued intention to use of m-banking in Jordan by integrating UTAUT, TPB, TAM and service quality with ML

Mobile banking is a service provided by a bank that allows full remote control of customers' financial data and transactions with a variety of options to serve their needs. With m-banking, the banks can cut down on operational costs whilst maintaining client satisfaction. This research examined the most crucial factors that could predict the Jordanian customer's continued intention toward the use of m-banking. Following the proposed model, the research was conducted by using a self-conducted questionnaire and the responses were collected electronically from a convenience sample of 403 Jordanian customers of m-banking through social networks. The suggested model was adapted from the theory of planned behavior (TPB), the unified theory of acceptance and use of technology (UTAUT), and the technology acceptance model (TAM). The research model was further expanded by considering the factors of service quality and moderating factors (age, gender, educational level, and Internet experience). The collected data of customers were analyzed, validated, and verified by using a structural equation modeling (SME) approach including a confirmatory factor analysis (CFA), in addition to machine learning (ML) methods, artificial neural network (ANN), support vector machine (SMO), bagging reduced error pruning tree (RepTree), and random forest. Results showed that effort expectancy, performance expectancy, perceived risk, perceived trust, social influence, and service quality impacted behavioral intention, whereas facilitating conditions did not. Furthermore, behavioral intention impacted upon word of mouth and facilitating conditions (the latter regarding the continued intention to use m-banking), and had the highest coefficient value. Results also confirmed that all moderating factors affect the behavioral intention to continue using m-banking applications.