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