Factors Influencing YouTube as a Learning Tool and Its Influence on Academic Achievement in a Bilingual Environment Using Extended Information Adoption Model (IAM) with ML Prediction—Jordan Case Study

Journal of Open Innovation: Technology, Market, and Complexity

Abu-Tayeh³

et al. 2022

Self Cite

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.

Section: Moderating Factors Hypothesesmentioning

confidence: 99%

Continued Intention to Use of M-Banking in Jordan by Integrating UTAUT, TPB, TAM and Service Quality with ML

Journal of Open Innovation: Technology, Market, and Complexity

Abu-Tayeh³

et al. 2022

Self Cite

“…This study used an extended model TAM to study the influence of parents’ anxiety and depression on children’s anxiety and depression when using SNs. The research used CFA, SEM, and five ML methods to validate and verify the findings as in [ 88 , 89 , 90 , 91 ]. The research found that there is a high correlation between parents’ depression and anxiety with children’s depression and a weak correlation with children’s anxiety.…”

Section: Discussion Implications and Conclusionmentioning

confidence: 99%

Factors Affecting the Use of Social Networks and Its Effect on Anxiety and Depression among Parents and Their Children: Predictors Using ML, SEM and Extended TAM

Masa’deh

et al. 2022

IJERPH

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Previous research has found support for depression and anxiety associated with social networks. However, little research has explored parents’ depression and anxiety constructs as mediators that may account for children’s depression and anxiety. The purpose of this paper is to test the influence of different factors on children’s depression and anxiety, extending from parents’ anxiety and depression in Jordan. The authors recruited 857 parents to complete relevant web survey measures with constructs and items and a model based on different research models TAM and extended with trust, analyzed using SEM, CFA with SPSS and AMOS, and ML methods, using the triangulation method to validate the results and help predict future applications. The authors found support for the structural model whereby behavioral intention to use social media influences the parent’s anxiety and depression which correlate to their offspring’s anxiety and depression. Behavioral intention to use social media can be enticed by enjoyment, trust, ease of use, usefulness, and social influences. This study is unique in exploring rumination in the context of the relationship between parent–child anxiety and depression due to the use of social networks.

“… 3: Excellent. [ 3 , 48 , 66 , 75 ] Attitude (ATT) ATT1: Using the SANAD APP would be a good idea. ATT2: Using the SANAD APP would be a foolish idea.…”

Section: Table A1mentioning

confidence: 99%

Predictors for E-Government Adoption of SANAD App Services Integrating UTAUT, TPB, TAM, Trust, and Perceived Risk

Alkhawaldeh

et al. 2022

IJERPH

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Using mobile applications in e-government for the purpose of health protection is a new idea during COVID-19 epidemic. Hence, the goal of this study is to examine the various factors that influence the use of SANAD App As a health protection tool. The factors were adopted from well-established models like UTAUT, TAM, and extended PBT. Using survey data from 442 SANAD App from Jordan, the model was empirically validated using AMOS 20 confirmatory factor analysis, structural equation modeling (SEM) and machine learning (ML) methods were performed to assess the study hypotheses. The ML methods used are ANN, SMO, the bagging reduced error pruning tree (RepTree), and random forest. The results suggested several key findings: the respondents’ performance expectancy, effort expectancy, social influence, facilitating conditions, perceived risk, trust, and perceived service quality of this digital technology were significant antecedents for their attitude to using it. The strength of these relationships is affected by the moderating variables, including age, gender, educational level, and internet experience on behavioral intention. Yet, perceived risk did not have a significant effect on attitude towards SANAD App The study adds to literature by empirically testing and theorizing the effects of SANAD App on public health protection.