Extended UTAUT to Examine the Acceptance of Web Based Training System by Public Sector

Alrawashdeh, Thamer A.; Al-Mahadeen, Bassam M.

doi:10.3991/ijim.v7i1.2044

Cited by 9 publications

(6 citation statements)

References 15 publications

(47 reference statements)

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“…Performance expectancy was found to have a positive influence on behavioral intention (β = 0.293, t = 3.045, p < 0.01), as well as social influence (β = 0.219, t = 2.456, p < 0.05). It is consistent with previous research (Alrawashdeh & Al-Mahadeen, 2013;Cokins et al, 2020;Jaradat & Banikhaled, 2013;Le, Ngo, Trinh, & Nguyen, 2020;Park & Lee, 2021;Tarhini et al, 2016;Venkatesh et al, 2003). This study found that customers' intention to use pick-up apps depends on customers' usability and social leverage assessment.…”

Section: Discussionsupporting

confidence: 92%

Understanding the Customers’ Acceptance of Pick-up Apps Over the COVID-19 Pandemic Period, Stay-at-Home Orders: An Integrated Model of UTAUT

Julianita

Tjhin

2021

JEHCP

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Current technological developments allow online sellers to request pick-ups via mobile apps. During the COVID-19 outbreak and with the stay-at-home orders, a survey in Indonesia showed that online transactions are increased, which led to the rise of pick-up and delivery activities. However, the pick-up order cancellation possibly happens, bad reviews appear, and apps abandonment cannot be avoided. The purpose of this study is to examine user acceptance of the pick-up apps and observe its correlation with the COVID-19 stay-at-home orders using the Unified Theory of Acceptance and Usage of Technology (UTAUT) model with subjective norm to stay at home from the Theory of Planned Behavior (TPB) model as an additional variable. The sample was obtained from 205 users of one of the pick-up apps in Indonesia through a structured questionnaire based on a five-point Likert scale. The results showed that the stay-at-home order due to the impact of the COVID-19 pandemic affects customers' intention to use pick-up apps and performance expectancy and social influence. Then, the non-linear UTAUT variables influence each other, which is the effect of effort expectancy and social influence on performance expectancy. Finally, the main factor influencing the use behavior of pick-up apps is behavioral intention. This study can contribute to IS research on technology acceptance and provides an overview of customer behavior using the pick-up apps from a pick-up service provider viewpoint.

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Section: Discussionsupporting

confidence: 92%

Understanding the Customers’ Acceptance of Pick-up Apps Over the COVID-19 Pandemic Period, Stay-at-Home Orders: An Integrated Model of UTAUT

Julianita

Tjhin

2021

JEHCP

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“…Most studies based on UTAUT focus on behavioural intentions as predicted by performance expectancy, effort expectancy and social influence. Researchers also confirm facilitating conditions as it predicts use behaviour (Attuquayefio and Addo, 2014; Chang, 2013; Wong et al , 2013; Oye et al , 2012a, 2012b; Alrawashdeh and Al-Mahadeen, 2013; Nair et al , 2015; Ali and Arshad, 2016). This study also finds this to be true.…”

Section: Discussionmentioning

confidence: 90%

Justifying students’ performance

Ukut

Krairit

2019

ITSE

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Purpose The purpose of this study is to compare students and instructors’ perspectives on students’ performance based on unified theory of acceptance and use of technology (UTAUT) framework. This study also aims to propose additional variables that might be used to extend the UTAUT model to make it more appropriate for the educational setting. Design/methodology/approach The study was carried out using a three-pronged methodology, namely, literature review, expert interviews and self-administered survey of 430 students and 55 information and communication technology (ICT) instructors from tertiary institutions in Akwa Ibom State, Nigeria. Validity analysis were conducted using IBM SPSS version 24 and two structural equation models were finally obtained using AMOS version 24. Findings This study finds UTAUT constructs including social influence, facilitating condition and voluntariness of use to have direct and significant impact on students’ performance from the students and the instructors’ perspective. The result of the instructors’ perspective shows that ICT use behaviour of students have direct and significant impact on students’ performance, but the students’ result shows an insignificant direct effect of use behaviour on students’ performance. From the students and the instructors’ perspective, gender, age and experience have statistically significantly direct impact on performance expectancy in this study. The result also shows that additional variables including ICT instructors’ characteristics, motivation and personal environment directly affect students’ performance from the students’ perspective, but the result of the instructors’ perspective shows that the influence of ICT instructors’ characteristics, motivation and personal environment does not directly and significantly affect students’ performance. Research limitations/implications This study was limited to tertiary institutions in Akwa Ibom State, Nigeria. Consequently, the findings of this study are limited to Akwa Ibom State, Nigeria, and may not be generalised to cover other countries. Originality/value This research shows that the students and instructors have different views on variables that impact on students’ performance. This study finds empirical evidence to support the direct impact of use behaviour on students’ performance from the instructors’ perspective, while the students disagree but indicated an empirical evidence to show that instructors’ characteristics, environment and motivation contribute a greater impact on students’ performance. From the students and the instructors’ perspective, gender, age and experience have statistically significantly direct impact on performance expectancy in this study. This adds to the findings in the original UTAUT that indicated that performance expectancy is moderated by gender and age.

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“…Through learners themselves and learners' interaction with the organization itself, the interactions between instructors and learners are the critical elements of the learning process (Abbad et al, 2009 ). The development of technologies used in the online learning context increases individuals' ability to interact from anywhere (Alrawashdeh and Al-Mahadeen, 2013 ). Abbad et al ( 2009 ) suggested that system interactivity indirectly impacts users' intention to use online learning systems through perceived usefulness and ease of use.…”

Section: Research Model and Hypothesis Developmentmentioning

confidence: 99%

An Extended UTAUT Model to Explain Factors Affecting Online Learning System Amidst COVID-19 Pandemic: The Case of a Developing Economy

Batucan

Gonzales

Balbuena

et al. 2022

Front. Artif. Intell.

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From a developing country perspective, this study explains the factors affecting online learning amidst the COVID-19 pandemic. The paper empirically tests the proposed extended unified theory of acceptance and use of technology (e-UTAUT) model in the students' intention and use behavior toward the online learning system. Understanding the acceptance of online learning technology is crucial, especially among developing countries caught off-guard by the abrupt transition of face-to-face classes to pure online learning. The enjoyment, interactivity, flexibility, and quality of online learning systems were added as antecedent variables to the UTAUT model. Eight hundred eighty valid responses from selected college students in the Visayas regions, Philippines, were collected. Structural equation modeling (SEM) was employed to verify the research hypotheses. The results supported the proposed model with acceptable fit measures and substantial explanatory power. The extended constructs provide different views on online learning based on the significant cluster of antecedents to explain technology acceptance through behavioral intentions and actual system usage. The paper implies that despite the challenges of connectivity in developing countries, the variations still conform with emerging literature about the topic. Insights for higher education institutions and policy directions are recommended.

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Extended UTAUT to Examine the Acceptance of Web Based Training System by Public Sector

Cited by 9 publications

References 15 publications

Understanding the Customers’ Acceptance of Pick-up Apps Over the COVID-19 Pandemic Period, Stay-at-Home Orders: An Integrated Model of UTAUT

Understanding the Customers’ Acceptance of Pick-up Apps Over the COVID-19 Pandemic Period, Stay-at-Home Orders: An Integrated Model of UTAUT

Justifying students’ performance

An Extended UTAUT Model to Explain Factors Affecting Online Learning System Amidst COVID-19 Pandemic: The Case of a Developing Economy

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