scholarly journals Instructor Acceptance of Mobile Learning in Saudi Arabia: A Case Study of Hail University

2017 ◽  
Vol 12 (5) ◽  
pp. 27 ◽  
Author(s):  
O. Alharbi ◽  
H. Alotebi ◽  
A. Masmali ◽  
N. Alreshidi
Keyword(s):  
Saudi Arabia ◽  
Mobile Learning ◽  
Online Survey ◽  
Tertiary Education ◽  
Successful Implementation ◽  
Education Students ◽  
University Instructors ◽  
Mobile Learning Acceptance ◽  
Effort Expectancy ◽  
Facilitating Conditions

Mobile technology has influenced almost every aspect of our modern lives. The enhancement of learning in Saudi Arabia, as well as significant development in education overall, may be possible through mobile learning. However, the successful implementation of mobile learning in tertiary education profoundly relies on the acceptance of mobile learning from both students and instructors. Most mobile learning acceptance studies target higher education students. Therefore, this study aimed at examining the factors that affect university instructors’ intentions to use mobile learning at Hail University. Eighty instructors completed the online survey, and the results indicated that performance experience, effort expectancy, social influence, and facilitating conditions altogether predicted the instructors’ use of mobile learning, as 67% of the variation was found to be affected by these variables in the multiple regression analysis outcome. The results also suggested that effort expectancy is the best predictor of instructors’ behavioural intentions to use mobile learning.

scholarly journals Structural Equation Modeling for Mobile Learning Acceptance by University Students: An Empirical Study

2020 ◽  
Vol 12 (20) ◽  
pp. 8618
Author(s):  
Quadri Noorulhasan Naveed ◽  
Mohammad Mahtab Alam ◽  
Nasser Tairan
Keyword(s):  
University Students ◽  
Social Influence ◽  
Technology Acceptance ◽  
Mobile Learning ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Equation Modeling ◽  
Perceived Ease Of Use ◽  
Mobile Learning Acceptance ◽  
Facilitating Conditions

Advanced mobile devices and global internet services have enhanced the usage of smartphones in the education sector and their potential for fulfilling teaching and learning objectives. The current study is an attempt to assess the factors affecting mobile learning acceptance by Saudi university students. A theoretical model of mobile learning acceptance was developed based on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT) model. Theoretically, five independent constructs were identified as most contributory towards the use of mobile learning and tested empirically. Data were collected through an online survey and analyzed using SmartPLS. The results of the study indicate that four constructs were significantly associated with mobile learning acceptance: perceived usefulness (β = 0.085, t = 2.201, and p = 0.028), perceived ease of use (β = 0.031, t = 1.688, and p = 0.013), attitude (β = 0.100, t = 3.771, and p = 0.037), and facilitating conditions (β = 0.765, t = 4.319, and p = 0.001). On the other hand, social influence was insignificant (β = −0.061, t = 0.136, and p = 0.256) for mobile learning acceptance. The contribution of social influence towards the use of mobile learning was negative and insignificant; hence, it was neglected. Thus, finally, four constructs (perceived usefulness, perceived ease of use, attitude, and facilitating conditions) were considered as important determinants of mobile learning acceptance by university students.

Evaluating participants' customer citizenship behaviors using an Internet charity platform

2020 ◽  
Vol 48 (6) ◽  
pp. 1-15
Author(s):  
Lanying Du ◽  
Xiumei Li ◽  
Fan Chen ◽  
Yi Feng
Keyword(s):  
Nonprofit Organizations ◽  
Online Survey ◽  
Positive Impact ◽  
Citizenship Behavior ◽  
The Internet ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Customer Citizenship Behavior ◽  
The Impact

We revealed the mechanism of customer citizenship behavior through an Internet charity platform by examining the validity of the unified theory of acceptance and use of technology (UTAUT). We introduced trust in, and interactivity of, the Internet charity platform to develop a model based on the UTAUT, and conducted an online survey with 302 participants in China. The results show that performance expectancy and effort expectancy had a positive impact on reparticipation intention, which led to an increase in customer citizenship behavior, on which facilitating conditions also had a significant positive impact. Further, trust in the Internet charity platform moderated the influence of performance expectancy and effort expectancy on reparticipation intention, and the interactivity of the Internet charity platform promoted the impact of facilitating conditions on customer citizenship behavior. Practical implications for managers of nonprofit organizations are discussed.

scholarly journals The Examination of Factors Influencing Saudi Small Businesses’ Social Media Adoption, by Using UTAUT Model

2019 ◽  
Vol 10 (2) ◽  
pp. 96 ◽  
Author(s):  
Abeer Bin Humaid ◽  
Yasser Sabri
Keyword(s):  
Social Media ◽  
Small Business ◽  
Small Businesses ◽  
Online Survey ◽  
Low Cost ◽  
Utaut Model ◽  
Use Of Technology ◽  
Wide Range ◽  
Effort Expectancy ◽  
Facilitating Conditions

Social media is becoming a major development in electronic commerce among a wide range of sectors, for example, education, government, health care, and business. In Saudi Arabia, a major movement toward social media has taken place, especially among small business entrepreneurs, due to its low cost and the powerful role it can play in globalization.The goal of this paper is to add to the theoretical knowledge base regarding the adoption of social media among Saudi small businesses, by applying the Unified Theory of Acceptance and Use of Technology (UTAUT) model to examine the influences of Saudi small businesses’ social media adoption. An empirical study was carried out using online survey research among 73 Saudi business entrepreneurs. The major findings of the paper are that Saudi small business entrepreneurs tend to use social media for the major constructs of performance expectancy, effort expectancy, social influence, and facilitating conditions. However, although the moderator of gender proved to be effective on the construct of effort expectancy, the effects of the moderators of age, gender, and experience on the other major constructs were not salient.It is believed that the findings will be useful for understanding adoption phenomena better, to help business entrepreneurs to make superior decisions based on them.

scholarly journals Validation of Non-Linear Relationships-Based UTAUT Model on Higher Distance Education Students’ Acceptance of WhatsApp for Supporting Learning

2020 ◽  
Vol 7 (2) ◽  
pp. 27-39
Author(s):  
Douglas Yeboah
Keyword(s):  
Distance Education ◽  
Social Influence ◽  
Self Efficacy ◽  
Structural Equation ◽  
Equation Modeling ◽  
Education Students ◽  
Cape Coast ◽  
Utaut Model ◽  
Effort Expectancy ◽  
Facilitating Conditions

This study examined relationships among the exogenous constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model to identify those that significantly predict others. Questionnaires were used to collect data from 273 distance education students pursuing various diploma, bachelor’s degree and post-graduate diploma programs at the Cape Coast study center of the Institute for Distance and e-Learning (IDeL) of the University of Education, Winneba in Ghana. Proportional stratified random sampling technique was employed to obtain the sample of students. The data were analyzed using Partial Least Squares – Structural Equation Modeling (PLS-SEM). The results indicated that in acceptance of WhatsApp for supporting higher distance learning, effort expectancy and social influence predict performance expectancy; mobile self-efficacy and facilitating conditions predict effort expectancy; and facilitating conditions predict social influence. Also, mobile self-efficacy was found to significantly predict behavioral intention. We recommend that prior to introduction of a new technology such as WhatsApp for supporting learning, necessary resources and training should be provided by educational administrators and faculty to the students. This would make the students perceive that they can use the technology effectively to bring about gains in their learning; and subsequently accept the technology.

scholarly journals Performance Expectancy, Effort Expectancy, and Facilitating Conditions as Factors Influencing Smart Phones Use for Mobile Learning by Postgraduate Students of the University of Ibadan, Nigeria

10.28945/4085 ◽  
2018 ◽  
Vol 14 ◽  
pp. 095-115 ◽  
Author(s):  
sodiq onaolapo ◽  
Olawale Oyewole
Keyword(s):  
Developing Countries ◽  
Mobile Learning ◽  
Smart Phone ◽  
Smart Phones ◽  
Postgraduate Students ◽  
Utaut Model ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
The University

Aim/Purpose: This study examines the influence of Performance Expectancy (PE), Effort Expectancy (EE), and Facilitating Conditions (FC) on the use of smart phones for mobile learning by postgraduate students in University of Ibadan, Nigeria. Background: Due to the low level of mobile learning adoption by students in Nigeria, three base constructs of the Unified Theory of Acceptance and Use of Technology (UTAUT) model were used as factors to determine smart phone use for mobile learning by the postgraduate students in the University of Ibadan. Methodology: The study adopted a descriptive survey research design of the correlational type, the two-stage random sampling technique was used to select a sample size of 217 respondents, and a questionnaire was used to collect data. Descriptive statistics (frequency counts, percentages, mean, and standard deviation), test of norm, and inferential statistics (correlation and regression analysis) were used to analyze the data collected. Contribution: The study empirically validated the UTAUT model as a model useful in predicting smart phone use for mobile learning by postgraduate students in developing countries. Findings: The study revealed that a significant number of postgraduate students used their smart phones for mobile learning on a weekly basis. Findings also revealed a moderate level of Performance Expectancy (𝑥 =16.97), Effort Expectancy (𝑥 =12.57) and Facilitating Conditions (𝑥 =15.39) towards the use of smart phones for mobile learning. Results showed a significant positive relationship between all the independent variables and use of smart phones for mobile learning (PE, r=.527*; EE, r=.724*; and FCs, r=.514*). Out of the independent variables, PE was the strongest predictor of smart phone use for mobile learning (β =.189). Recommendations for Practitioners: Librarians in the university library should organize periodic workshops for postgraduate students in order to expose them to the various ways of using their smart phones to access electronic databases. Recommendation for Researchers: There is a need for extensive studies on the factors influencing mobile technologies adoption and use in learning in developing countries. Impact on Society: Nowadays, mobile learning is increasingly being adopted over conventional learning systems due to its numerous benefits. Thus, this study provides an insight into the issues influencing the use of smart phones for mobile learning by postgraduate students from developing countries. Future Research: This study utilized the base constructs of the UTAUT model to determine smart phone use for mobile learning by postgraduate students in a Nigerian university. Subsequent research should focus on other theories to ascertain factors influencing Information Technology adoption and usage by students in developing countries.

Evaluating the Effects of Facilitating Conditions and Usage Experience on Mobile Payment

2021 ◽  
Vol 13 (4) ◽  
pp. 88-106
Author(s):  
Ling Long Tsai
Keyword(s):  
Online Survey ◽  
Mobile Payment ◽  
Research Model ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
And Performance ◽  
Facilitating Conditions ◽  
Major Factors ◽  
The Relationship

The following research attempts to investigate the determinants influencing consumers' intention to adopt mobile payment (MP). The research model was adapted based on three constructs from the unified theory of acceptance and use of technology (UTAUT), including performance expectancy, effort expectancy, and facilitating conditions in the research model. In addition, usage experience was also added to the model to test for moderating effect. An online survey conducted through Taiwanese chat rooms resulted in 348 valid responses, which were analyzed using Smart PLS. Results indicated that (1) effort expectancy, performance expectancy, and facilitating conditions were three major factors influencing intention to use mobile payment; (2) facilitating conditions played a significant role in impacting effort expectancy and performance expectancy; (3) usage experience positively moderated the relationship between facilitating conditions and performance expectancy; and (4) usage experience also positively moderated the relationship between facilitating conditions and effort expectancy.

(Preprint)

2018 ◽  
Author(s):  
Alaa Ali Abd-Alrazaq ◽  
Bridgette Bewick ◽  
Tracey Farragher ◽  
Peter Gardner
Keyword(s):  
Structural Equation ◽  
Behavioural Intention ◽  
Successful Implementation ◽  
Privacy And Security ◽  
Convenience Sample ◽  
Factors Associated ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
The Relationship

BACKGROUND Electronic Personal Health Records (ePHRs) are secure web-based tools that enable individuals to access, manage, and share their medical records. England recently introduced a nationwide ePHR called Patient Online. As with ePHRs in other countries, adoption rates of Patient Online remain low. Understanding factors affecting patients’ use of ePHRs is important to increase adoption rates and improve the implementation success of ePHRs. OBJECTIVE This study aims to examine factors associated with patients’ use of ePHRs in England. METHODS The Unified Theory of Acceptance and Use of Technology (UTAUT) was adapted to the use of ePHRs. To empirically examine the adapted model, a cross-sectional survey of a convenience sample was carried out in four general practices in West Yorkshire, England. Factors associated with use of ePHRs were explored using Structural Equation Modelling (SEM). RESULTS Of 800 eligible patients invited to take part in the survey, 624 (78%) participants returned a valid questionnaire. Behavioural intention was significantly influenced by performance expectancy (β=0.57, P<0.001), effort expectancy (β=0.16, P<0.001), and perceived privacy and security (β=0.24, P<0.001). The path from social influence to behavioural intention was not significant (β=0.03, P=0.183). Facilitating conditions and behavioural intention significantly influenced use behaviour (β=0.25, P<0.001; β=0.53, P<0.001, respectively). Performance expectancy significantly mediated the effect of effort expectancy and perceived privacy and security on behavioural intention (β=0.19, P<0.001; β=0.28, P=0.001, respectively). Age significantly moderated three paths; PEBI, EEBI, and FCUB. Sex significantly moderated only the relationship between performance expectancy and behavioural intention. Two paths were significantly moderated by education and internet access: EEBI and FCUB. Income moderated the relationship between facilitating conditions and use behaviour. The adapted model accounted for 51% of the variance in performance expectancy, 76% of the variance in behavioural intention, and 48% of the variance in use behaviour. CONCLUSIONS This study identified the main factors that affect patients’ use of ePHRs in England, which should be taken into account for the successful implementation of these systems. For example, developers of ePHRs should involve patients in the process of designing the system to consider functions and features that fit patients’ preferences and skills, thereby, create a useful and easy to use system. The proposed model accounted for 48% of the variance in use behaviour, indicating the existence of other, as yet unidentified, factors that influence adoption of ePHRs. Future studies should confirm the effect of the factors included in the current model and to identify additional factors.

A Structural Equation Model (SEM) of Governing Factors Influencing patients' acceptance of mobile health in Saudi Arabia (Preprint)

2021 ◽  
Author(s):  
Tamim Alkhalifah
Keyword(s):  
Saudi Arabia ◽  
Technology Acceptance ◽  
Structural Equation ◽  
Behavioural Intention ◽  
System Quality ◽  
Theoretical Frameworks ◽  
Utaut Model ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions

BACKGROUND In line with the National Transformation Programme 2020 (NTP), a component of the Saudi Vision 2030, the Ministry of Health (MOH) of Saudi Arabia has taken the initiative to improve healthcare provision through the introduction of mobile technology. It is anticipated that mhealth services will be more and more in demand, given the growing proportion of Internet users in Saudi Arabia as well as the global epidemic. Moreover, the Saudi government has pledged ongoing backing for e-health projects geared towards expanding the extent of technology acceptance among all concerned groups [1]. Under these circumstances, the determinants of mHealth acceptance within developing regions are receiving fresh attention owing to the latest healthcare developments. Health ICT research has embraced the UTAUT model because it is widely applicable to investigations of technology acceptance. OBJECTIVE To gain insight into the determinants of mHealth acceptance among patients in Saudi Arabia, a modified version of the UTAUT model is implemented in this study. Incorporating eight theoretical frameworks of individual acceptance, this model has been employed in healthcare settings since it was first developed and has been confirmed to be suitable for shedding light on technology acceptance within a healthcare context. METHODS Google Forms was used to develop an online questionnaire during the second semester (September) of the academic year 2019. Data were reported from 320 patients who had used mHealth applications developed by the MOH of Saudi Arabia. The questionnaire was distributed via different social media sites. RESULTS According to the results of this study, performance expectancy (PE) construct estimated the behavioural intention (BI) construct (β = 0.163, p < 0.05) positively, which supported H1. Further, effort expectancy (PE) predicted BI (β = 0.236, p < 0.05) positively, which supported H2. On the other hand, social influence (SI) failed to predict BI (β = -0.071 p > 0.05) significantly, thus rejecting H3. Facilitating conditions (FC), however, predicted BI (β = 0.511 p < 0.05) positively, which supported H4. Finally, system quality (SQ) predicted BI (β = 0. 0.367 p < 0.05) positively, which supported H5; and finally, trust (Tr) positively predicted behavioural intent (β = 0. 0.278 p < 0.05), thus providing support for H6. CONCLUSIONS The study has made valuable contributions by exploring and identifying the critical factors that affect mHealth acceptance in Saudi Arabia and identifying the major challenges when implementing mHealth. The UTAUT model identified a selection of factors that influenced the uptake of mHealth services. Performance expectancy, effort expectancy, facilitating conditions, system quality and trust in the ICT system were all positively influential. However, social factors did not appear to affect the behavioural intention to use mHealth.

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