This study explores the factors affecting CliQ payment service adoption in Jordan as it represents a major shift in the Jordanian market to Fintech and mobile marketing. This study presented a distinctive model by integrating the “unified theory of acceptance” and the “technology acceptance model” TAM with the “use of technology UTAUT” to measure the behavioral intention of consumers and the satisfaction of the users towards utilizing the CliQ service. The study measured the linkage between four predictors (perceived usefulness, social influence, perceived ease of use, and financial risk) as well as both utilizers’ intention to CliQ service usage and utilizers’ satisfaction with using the service, along with observing the association between these predictors to determine their contribution to the users’ satisfaction mediated by the users’ intention to utilize the service mentioned above. A survey instrument was distributed to 604 respondents, and it was developed and validated by academics, as a pilot test. As well as a pre-test. Hypotheses were tested with multiple linear regression analysis using SmartPLS software to interpret path coefficients, and reliability and validity within the outer model were tested through correlation analysis. Additionally, internal consistency was explored by applying Cronbach’s alpha. The outcomes proved that the predictors significantly affect both utilizers’ behavioral attitudes and satisfaction with using the CliQ service, except for financial risk. The data analysis also indicated a significant indirect influence of all the independent variables on utilizers’ satisfaction through behavioral intention to utilize the CliQ service, except for financial risk, which had an insignificant indirect influence on utilizers’ satisfaction through behavioral intention for service usage. The findings of the current article close the gap found in the literature concerning measuring usability to enhance user satisfaction and adoption of Fintech services. Therefore, bank managers and policy planners can find insights for developing and improving mobile banking apps.

Mobile Applications offer a new style to service sectors, for instance, in higher education, mobile applications are utilized to provide access to academic resources and academic services. Despite the wealth of mobile applications, they encounter various challenges that have attracted the interest of academia and software developers. The usability issues of mobile applications may cause performance degradation, resulting in the company's loss in terms of cost. This study aims to investigate the usability of the Prince Sattam bin Abdulaziz University (PSAU) mobile application by adopting data mining as a descriptive and predictive process. The first step was gathering data of the usability of the PSAU mobile application using the system usability scale. Afterwards, data was preprocessed into a suitable format to apply data mining methods. Specifically, the explanatory model has been employed to describe and investigate insights related to the usability factors and features of the PSAU mobile application. Furthermore, this study adopted the Four Clustering methods to segment the usability levels of the PSAU mobile application into homogenous groups based on user behavior. Additionally, the predictive model was used to build models for predicting the usability level and Grade and five classification algorithms were employed to predict the usability level and Grade. Most algorithms have given positive results in all performance indicators, where the accuracy rate achieved is 98% to 95% for most methods. The results revealed that the PSAU mobile application has an acceptable usability level, and the data mining methods helped to discover hidden patterns. Furthermore, the findings will help the developers and policymakers understand users' and stakeholders' behavior to find the most common usability problems for each group, and customize the PSAU mobile application.