scholarly journals Students’ Continuance Intention to Use Moodle: An Expectation-Confirmation Model Approach

10.28945/4842 ◽  
2021 ◽  
Vol 16 ◽  
pp. 397-434
Author(s):  
Ahmad A. Rabaa'i ◽  
Shareef Abu ALmaati ◽  
Xiaodi Zhu
Keyword(s):  
Faculty Members ◽  
Management Systems ◽  
Future Research ◽  
Intention To Use ◽  
Continuance Intention ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Continuous Use ◽  
Expectation Confirmation

Aim/Purpose: This study aims at investigating the factors that influence students’ continuous intention to use Moodle, as an exemplar of learning management systems (LMSs), in the post-adoption phase. Background: Higher education institutions (HEIs) have invested heavily in learning management systems (LMSs), such as Moodle and BlackBoard, as these systems enhance students’ learning and improve their interactions with the educational systems. While most studies on LMSs have focused on the pre-adoption or acceptance phases of this technology, the determinant factors that influence students’ continuance intention to use LMSs have received less attention in the information systems (IS) literature. Methodology: The theoretical model for this study was primarily drawn from the expectation-confirmation model (ECM). A total of 387 Kuwaiti students, from a private American University in the State of Kuwait, participated in this study. Partial least squares (PLS) was employed to analyze the data. Contribution: This study contributes to the existing scientific knowledge in different ways. First, this study extends the expectation confirmation model (ECM) by integrating factors that are important to students’ continuous intention to use LMSs, including system interactivity, effort expectancy, attitude, computer anxiety, self-efficacy, subjective norms, and facilitating conditions. Second, this study adds on a Kuwaiti literature context by focusing on the continuous intention to use LMSs, which is, to the best of our knowledge, the first study that extends and empirically assesses the applicability of the ECM in the LMSs context in a developing country – Kuwait. Third, this study conceptually and empirically differentiates between satisfaction and attitude, as two separate affect constructs, which were taken as interchangeable factors in ECM, and were disregarded by a large number of prior ECM studies concerned with continuous use intention. Finally, this study aims to assist HEIs, faculty members, and systems’ developers in understanding the main factors that influence students’ continuance use intention of LMSs. Findings: While subjective norms were not significant, the results mainly showed that students’ continuous intention to use Moodle is significantly influenced by performance expectancy, effort expectancy, attitude, satisfaction, self-efficacy and facilitating conditions. The study’s results also confirmed that satisfaction and attitude are two conceptually and empirically different constructs, conflicting with the views that these constructs can be taken as interchangeable factors in the ECM. Recommendations for Practitioners: This study offers several useful practical implications. First, given the significant influence of system interactivity on performance expectancy and satisfaction, faculty members should modify their teaching approach by enabling communication and interaction among instructors, students, and peers using the LMS. Second, given the significant influence of performance expectancy, satisfaction, and attitude on continuous intention to use the LMS, HEIs should conduct training programs for students on the effective use of the LMS. This would increase students’ awareness regarding the usefulness of the LMS, enhance their attitude towards the LMS, and improve their satisfaction with the system. Third, given the significant role of effort expectancy in influencing performance expectancy, attitude, and students’ continuous intention to use Moodle, developers and system programmers should design the LMS with easy to use, high quality, and customizable user interface. This, in turn, will not only motivate students’ performance expectancy, but will also influence their attitude and continuous intention to use the system. Recommendation for Researchers: This study conceptually and empirically differentiates between satisfaction and attitude, as two separate affect constructs, which were taken as interchangeable factors in ECM and were disregarded by a large number of prior ECM studies concerned with continuous use intention. Hence, it is recommended that researchers include these two constructs in their research models when investigating continuous intention to use a technology. Impact on Society: This study could be used in other countries to compare and verify the results. Additionally, the research model of this study could also be used to investigate other LMSs, such as Blackboard. Future Research: This study focused on how different factors affected students’ continuous intention to use Moodle but did not consider all determinants of successful system, such as system quality, information quality, and instructional as well as course content quality. Thus, future research should devote attention to the effects of these quality characteristics of LMS.

scholarly journals Investigating the Determinants of Students’ Intention to Use Business Simulation Games

2019 ◽  
Vol 58 (2) ◽  
pp. 433-458 ◽  
Author(s):  
Yu-Yin Wang ◽  
Yi-Shun Wang ◽  
Shi-En Jian
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Partial Least Square ◽  
Intention To Use ◽  
Business Simulation ◽  
Simulation Games ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

Business simulation games (BSGs) are educational tools that help students develop business management knowledge and skills. However, to date, relatively little research has investigated the factors that influence students’ BSG usage intention. Grounded on the extended unified theory of acceptance and use of technology, this study helped to fill this gap by exploring intention to use BSGs. Specifically, this study investigated the influence of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and price value on behavioral intention to use BSGs. Data collected from 141 useful respondents were tested against the research model using partial least square approach. The results of this study indicated that behavioral intention to use BSGs was influenced by facilitating conditions, hedonic motivation, and price value. Unexpectedly, performance expectancy, effort expectancy, and social influence were not predictive of students’ behavioral intention to use BSGs. These findings enhanced our understanding of students’ BSG usage behavior and provided several important theoretical and practical implications for the application of BSG in the context of business and management education.

The Factors Influencing Taxpayers' Acceptance of E-Taxation System

2015 ◽  
pp. 105-121
Author(s):  
Adnan Gercek ◽  
Tolga Demirbas ◽  
Filiz Giray ◽  
Ayse Oguzlar ◽  
Mehmet Yuce
Keyword(s):  
Perceived Risk ◽  
Structural Equation ◽  
Model Performance ◽  
Equation Modeling ◽  
Intention To Use ◽  
Government Services ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Taxation System

E-taxation is one of the most popular e-government services. Most countries are focused on implementing an e-taxation system. The success of an e-taxation system depends on the taxpayers' acceptance of it. The taxpayers' intention to use an e-taxation system is determined by various factors. This chapter, based on empirical data collected from a survey of 505 respondents in Turkey, seeks to identify the factors that influence the taxpayers' acceptance of e-taxation system. It test various constructs of the UTAUT model – performance expectancy, trust perception, perceived risk, effort expectancy and facilitating conditions – on Turkish taxpayers' intention to use the e-taxation system. Structural equation modeling is used to analyze the effects of these variables on intention to use. The results indicate that performance expectancy and perceived risk have a significant impact on behavioral intention and that effort expectancy and facilitating conditions have a significant impact on intention to use.

scholarly journals Factors that influence the use of the Internet for job-seeking purposes amongst a sample of final-year students in the Eastern Cape province of South Africa

2017 ◽  
Vol 15 (0) ◽  
Author(s):  
Juliet R. Chiwara ◽  
Willie T. Chinyamurindi ◽  
Themba Q. Mjoli
Keyword(s):  
The Internet ◽  
Intention To Use ◽  
Eastern Cape ◽  
Job Seekers ◽  
Job Seeking ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Managerial Implications ◽  
Use Of The Internet ◽  
Facilitating Conditions

Orientation: Organisations are turning to the Internet in search for talent. A constituency often targeted are those students nearing the end of their tenure of study who are making a transition into the working world. Given this, it is important to understand not only those factors that influence the use of the Internet within the Human Resources (HR) talent search process, but also how such factors relate to actual intent to apply for jobs.Research purpose: Drawing on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study investigates factors that influence the adoption of the Internet for purposes of job seeking.Motivation for the study: Calls have been made for research that investigates factors that influence the intention to use the Internet to apply for jobs in developing countries such as South Africa.Research approach, design and method: The study used the quantitative approach (relying on a survey) to test the hypotheses into factors that influence the use of Internet for the purpose of job seeking amongst a sample of 346 prospective job seekers in their final year of study at a South African university.Main findings: Through correlation and regression analysis, findings reveal a positive relationship to exist between (1) performance expectancy with intention to use the Internet to apply for jobs, (2) effort expectancy with intention to use the Internet to apply for jobs, (3) individual effort expectancy and performance expectancy and (4) individual trust and the intention to use the Internet for job seeking. However, no relationship was found to exist between facilitating conditions and intention to use the Internet for job seeking.Practical/managerial implications: The findings magnify the role of salient factors in the intention to use the Internet for job-seeking purposes. Efforts from applicants, universities, recruitment agencies and organisations, potentially, have an effect on the intention to use the Internet for job-seeking purposes. Such efforts may enhance the students’ online experience and minimise problems that accompany technology adoption for the purposes of recruitment. Findings from this research may help enhance the online recruitment experience both from the end-user and recruiter perspective.Contribution/value-add: The study contributes to the recruitment literature in three ways: Firstly, UTAUT is shown to be a useful framework to explain final-year, job-seeking students’ intention to use the Internet to apply for jobs. Furthermore, the findings illustrate the value of the UTAUT as a model useful in enhancing understanding on intentions. Secondly, the study places focus on the human factor rather than facilitating conditions as important issues regarding intention to use the Internet to apply for a job. Finally, based on these findings, future angles of research that have academic and practitioner implications are proposed.

Smartphone Alcohol Use Disorder Recovery Apps: an Survey of Behavioral Intention to Use using UTAUT (Preprint)

2021 ◽  
Author(s):  
Rijuta Menon ◽  
Julien Meyer ◽  
Pria Nippak ◽  
Housne Begum
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Alcohol Use Disorder ◽  
Survey Study ◽  
P Value ◽  
Intention To Use ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

BACKGROUND Alcohol Use Disorder (AUD) carries a huge health and economic cost to society. Effective interventions exist but numerous challenges limit their adoption, especially in a pandemic context. AUD recovery apps (AUDRA) have emerged as a potential complement to in-person interventions. They are easy to access and show promising results in terms of efficacy. However, they rely on individual adoption decision and remain underused. OBJECTIVE The aim of this survey study is to explore the beliefs that determine the intention to use AUDRA. METHODS We conducted a cross-sectional survey study of people suffering from AUD. We used the Unified Theory of Acceptance and Use of Technology, which predicts use and behavioral intention to use based on performance expectancy, effort expectancy, social influence and facilitating conditions. Participants were recruited directly from two sources: first, respondents at addiction treatment facilities in Ontario, Canada were contacted in person and filled a paper form; second, members from AUD recovery support groups on social media were contacted and invited to fill an online sruvey. The survey was conducted between October 2019 and June 2020. RESULTS The final sample was comprised of 159 participants (124 online and 35 paper based) self-identifying somewhat or very much with AUD. Most participants (85.5%) were aware of AUDRA and those participants scored higher on performance expectancy, effort expectancy and social influence. Overall, the model explains 35.4% of the variance in behavioral intention to use AUDRA and 11.1% of the variance in use. Social influence (p-value 0.314), especially for women (p-value 0.227) and effort expectancy (p value 0.247) were key antecedents of behavioral intention. Facilitating conditions was not significant overall but was moderated by age (p value 0.231) suggesting that it matters for older participants. Performance expectancy did not predict behavioral intention, which is unlike many other technologies but confirms other findings with mhealth. Open-ended questions suggest that privacy concerns may play a significant role for AUDRA. CONCLUSIONS This study suggests that unlike many other technologies, the adoption of AUDRA is not mainly determined by utilitarian factors such as performance expectancy. Rather, effort expectancy and social influence play a key role in determining the intention to use AUDRA.

scholarly journals Exploring the Determinants of Students' Satisfaction and Continuance Intention Using Online Learning in Jordan

2021 ◽  
pp. 28-41
Author(s):  
Hadeel Mahmoud Jebril
Keyword(s):  
Online Learning ◽  
Structural Equation ◽  
Equation Modeling ◽  
System Quality ◽  
Continuance Intention ◽  
School Students ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Students Satisfaction

This research investigates factors affecting online learning satisfaction and continuance intention by Jordan school students. To this end, an integrated model of Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Information System Success (ISS) model has been used. A questionnaire was handed out to students from five Jordanian schools to collect data from 346 students, and the Structural Equation Modeling (SEM) technique was utilized to evaluate the proposed model. The findings indicated that the students' satisfaction is directly influenced by performance expectancy, effort expectancy, facilitating conditions, system quality. Besides, the empirical results showed that the continuance intention is directly influenced by students' satisfaction, performance expectancy, habit, effort expectancy, hedonic motivation, and facilitating conditions. The findings of this study will serve as a valuable resource for educational institutions, decision-makers, developers, and academics looking to enhance online learning systems by identifying the most important factors influencing students' satisfaction and continuance intention.

scholarly journals Technology Supporting Nursing at Homecare – Seems to Be Lacking

2020 ◽  
Author(s):  
Eija Kivekäs ◽  
Santtu Mikkonen ◽  
Samuli Koponen ◽  
Kaija Saranto
Keyword(s):  
Internet Of Things ◽  
Historical Perspective ◽  
Intention To Use ◽  
Unified Theory ◽  
Home Setting ◽  
Medical Technologies ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Facilitating Conditions

The use of welfare technologies in the home setting has drawn increased attention in healthcare. From a historical perspective, medical technologies were designed for hospital settings. Digitalization and internet of things have changed the structure of our society. The aim of this paper is to describe the factors that determine a user’s intent to adopt new welfare technologies in the context of homecare. The phenomenon was being examined by the unified theory of acceptance and use of technology. This study was to show that performance expectancy, effort expectancy, and facilitating conditions are significant factors in determining a user’s intention to use new welfare technologies. While, the use of welfare technologies was rare in homecare.

scholarly journals Analysis of Factors Affecting Behavioral Intention to Use E-Learning Uses the Unified Theory of Acceptance and Use of Technology Approach

2020 ◽  
Author(s):  
Ramllah . ◽  
Ahmad Nurkhin
Keyword(s):  
Social Influence ◽  
Behavioral Intention ◽  
Intention To Use ◽  
Performance Expectancy ◽  
Learning Intention ◽  
Effort Expectancy ◽  
E Learning ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use ◽  
Descriptive Statistical Analysis

The purpose of this study isto analyze the influence of performance expectancy, effort expectancy, social influence, facilitating conditions, perceived creadibility, and anxiety on e-learning behavioral intention to use who are moderated by experience and voluntariness of use.The study population was 215 students who used e-learning in the Accounting Department of SMK N 1 Karanganyar. The sample selection using Slovin method with an error rate of 5% and sampling area technique obtained by respondents as many as 140 students. The technique of collecting data using a questionnaire. Data analysis techniques used descriptive statistical analysis and SEM-PLS. Data analysis tool using WarpPLS 5.0.The results of the descriptive statistical analysis show that the behavioral intention to use e-learning, performance expectancy, effort expectancy, social influence, facilitating conditions, perceived creativity, anxiety, experience and voluntariness of use are in the sufficient category. Hypothesis test results show the influence of performance expectancy on e-learning behavioral intention to use, effort expectancy does not affect the behavioral e-learning intention to use, social influence has an effect on behavioral e-learning intention to use, facilitating conditions have no effect on behavioral intention to Using e-learning, perceived creativity does not affect e-learning behavior, anxiety influences the behavioral intention to use e-learning, voluntary moderating negative social influences the behavioral e-learning intention to use, experience moderates the effect of effort expectancy on The behavior of e-learning intention to use, experience does not moderate the influence of social influence on the behavioral e-learning intention to use, experience does not moderate the effect of facilitating conditions on e-learning behavioral intention to use e-learning the conclusion of this study states that of the ten hypotheses proposed there are five types of hypotheses accepted. Keywords: E-learning, Behavioral Intention, UTAUT.

scholarly journals Healthcare providers’ acceptance of telemedicine and preference of modalities during COVID-19 pandemics in a low-resource setting: An extended UTAUT model

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250220
Author(s):  
Kirubel Biruk Shiferaw ◽  
Shegaw Anagaw Mengiste ◽  
Monika Knudsen Gullslett ◽  
Atinkut Alamirrew Zeleke ◽  
Binyam Tilahun ◽  
...  
Keyword(s):  
Low Income ◽  
Self Efficacy ◽  
Structural Model ◽  
Healthcare Providers ◽  
Intention To Use ◽  
Middle Income ◽  
Performance Expectancy ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Behavioral Intention To Use

Background In almost all lower and lower middle-income countries, the healthcare system is structured in the customary model of in-person or face to face model of care. With the current global COVID-19 pandemics, the usual health care service has been significantly altered in many aspects. Given the fragile health system and high number of immunocompromised populations in lower and lower-middle income countries, the economic impacts of COVID-19 are anticipated to be worse. In such scenarios, technological solutions like, Telemedicine which is defined as the delivery of healthcare service remotely using telecommunication technologies for exchange of medical information, diagnosis, consultation and treatment is critical. The aim of this study was to assess healthcare providers’ acceptance and preferred modality of telemedicine and factors thereof among health professionals working in Ethiopia. Methods A multi-centric online survey was conducted via social media platforms such as telegram channels, Facebook groups/pages and email during Jul 1- Sep 21, 2020. The questionnaire was adopted from previously validated model in low income setting. Internal consistency of items was assessed using Cronbach alpha (α), composite reliability (CR) and average variance extracted (AVE) to evaluate both discriminant and convergent validity of constructs. The extent of relationship among variables were evaluated by Structural equation modeling (SEM) using SPSS Amos version 23. Results From the expected 423 responses, 319 (75.4%) participants responded to the survey questionnaire during the data collection period. The majority of participants were male (78.1%), age <30 (76.8%) and had less than five years of work experience (78.1%). The structural model result confirmed the hypothesis “self-efficacy has a significant positive effect on effort expectancy” with a standardized coefficient estimate (β) of 0.76 and p-value <0.001. The result also indicated that self-efficacy, effort expectancy, performance expectancy, facilitating conditions and social influence have a significant direct effect on user’s attitude toward using telemedicine. User’s behavioral intention to use telemedicine was also influenced by effort expectancy and attitude. The model also ruled out that performance expectancy, facilitating conditions and social influence does not directly influence user’s intention to use telemedicine. The squared multiple correlations (r2) value indicated that 57.1% of the variance in attitude toward using telemedicine and 63.6% of the variance in behavioral intention to use telemedicine is explained by the current structural model. Conclusion This study found that effort expectancy and attitude were significantly predictors of healthcare professionals’ acceptance of telemedicine. Attitude toward using telemedicine systems was also highly influenced by performance expectancy, self-efficacy and facilitating conditions. effort expectancy and attitude were also significant mediators in predicting users’ acceptance of telemedicine. In addition, mHealth approach was the most preferred modality of telemedicine and this opens an opportunity to integrate telemedicine systems in the health system during and post pandemic health services in low-income countries.

E-Government Acceptance and Trust

2021 ◽  
Vol 12 (2) ◽  
pp. 1-16
Author(s):  
Rania Fakhoury ◽  
Bilal Chebaro
Keyword(s):  
Structural Equation ◽  
Research Direction ◽  
Equation Modeling ◽  
Future Research ◽  
Performance Expectancy ◽  
Significant Relationships ◽  
Effort Expectancy ◽  
Facilitating Conditions ◽  
Shed Light

Lebanon is a small developing market that is making significant investments in e-government technology. The expectation is that it will improve the quality of life and decrease corruption. The current research is survey-based using a structural equation modeling technique that investigates citizens' behavioral intentions towards using e-services and cross-validates a previous study with a new matching data sample. One hundred six questionnaires were analyzed, and findings showed significant relationships between UTAUT2 constructs (performance expectancy, habit, social influence, price value, and trust in the internet) and intention to use e-government services in Lebanon. The results also shed light on e-government adoption inhibitors (effort expectancy, facilitating conditions, hedonic motivation, and trust in government). Therefore, the findings will be beneficial to the Lebanese government to develop and improve the e-services. Despite achieving its aim, this study has its limitations, which constitute the future research direction.

Dynamic Analysis of UTAUT

2016 ◽  
Vol 11 (3) ◽  
pp. 40-54
Author(s):  
Wejdan Abualbasal ◽  
Emad Abu-Shanab ◽  
Heba Al-Quraan
Keyword(s):  
Longitudinal Study ◽  
New Technology ◽  
Intention To Use ◽  
Unified Theory ◽  
Cross Sectional ◽  
Performance Expectancy ◽  
Use Of Technology ◽  
Effort Expectancy ◽  
Adoption Of New Technology ◽  
Facilitating Conditions

The technology adoption domain is rich with studies that utilized a cross-sectional snapshot of subjects' perceptions regarding the adoption of new technology. This research tried to implement a longitudinal study that took three measures within 4 months to estimate the influence of time and experience on students' perceptions. The study adopted a modified version of the Unified Theory of Acceptance and use of Technology (UTAUT) with effort expectancy, performance expectancy, facilitating conditions, and locus of control predicting the intention to use Microsoft Project. Results supported the UTAUT and its prediction. Also, this study fitted two types of dynamic research typologies (learning curve and equilibrium circles) to the UTAUT relationships and across time.

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