Information technology adoption and continuance: A longitudinal study of individuals’ behavioral intentions

Sun, Yuan; Jeyaraj, Anand

doi:10.1016/j.im.2013.07.005

Cited by 103 publications

(78 citation statements)

References 23 publications

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“…For instance, Donaldson (2011) used it to understand the determinants of students' acceptance and use of mobile technologies for learning in the USA. Sun and Jeyaraj (2013) used the UTAUT model to evaluate the adoption of a Blackboard system by Chinese students. Khechine et al (2014b) chose the UTAUT model to find factors that explained the acceptance of a webinar system in a blended learning course by students in Canada.…”

Section: Research Variablesmentioning

confidence: 99%

Technology as a Double-Edged Sword: From Behavior Prediction with UTAUT to Students’ Outcomes Considering Personal Characteristics

Khechine

Lakhal

2018

JITE:Research

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Aim/Purpose: We aim to bring a better understanding of technology use in the educational context. More specifically, we investigate the determinants of webinar acceptance by university students and the effects of this acceptance on students’ outcomes in the presence of personal characteristics such as anxiety, attitude, computer self-efficacy, and autonomy. Background: According to literature in information systems, understanding the determinants of technology use and their effect on outcomes can help ensure their effective deployment, which might yield productivity payoffs. Methodology: Data collection with an online quantitative questionnaire yielded to 377 valid responses from students enrolled in an undergraduate management information systems course. SPSS software allowed obtaining descriptive statistics and Smart-PLS was used for validity and hypotheses testing. Contribution: Previous studies assessed either the determinants of technology use or the effect of their use on students’ outcomes, and often omitted to assess the role of personal characteristics. This research fulfills the gap about the scarcity of studies that link goals to intentions and behavior, while considering personal cognitive characteristics. Findings: Results showed that performance expectancy, social influence, facilitating conditions, and voluntariness of use explained the behavioral intention and webinar usage. Some of these relationships were direct and others were moderated. Satisfaction was the only student outcome affected by the use of webinars. Anxiety, attitude, and autonomy are the personal characteristics that exerted direct and moderating effects on the relationships between the main variables of the research model. Recommendations for Practitioners: Results gave rise to interesting managerial recommendations for adopting technologies in universities. Among them, teachers are encouraged to promote the webinars’ advantages and to exert less pressure on students to use webinars. Recommendation for Researchers: On the theoretical side, we brought a holistic view of the use of technologies in higher education by linking goals to intentions and behavior, and integrating personal cognitive characteristics into the same model. Results allowed enriching the literature about technology adoption in the educational context. Future Research: Future research should follow closely the results of studies on generation Z to find better explanatory variables of technology adoption. We also propose to consider new variables from the updated technology acceptance models to further understand the derteminants of technology use by students.

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Section: Research Variablesmentioning

confidence: 99%

Technology as a Double-Edged Sword: From Behavior Prediction with UTAUT to Students’ Outcomes Considering Personal Characteristics

Khechine

Lakhal

2018

JITE:Research

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“…Diffusion of innovation through a population has been dominated by two types of effects -mass media communications and interpersonal relationships (Sun & Jeyaraj, 2013). Taking innovation attributes (relative advantage, complexity, and compatibility) proposed by Rogers (2013) into account, these attributes have an impact on the person's intention to adopt and use an innovation.…”

Section: Resultsmentioning

confidence: 99%

“…Taking innovation attributes (relative advantage, complexity, and compatibility) proposed by Rogers (2013) into account, these attributes have an impact on the person's intention to adopt and use an innovation. More specifically, personal innovativeness covering individuals' willingness to use new technologies might be considered as one of the key factors for applying innovation (Sun & Jeyaraj, 2013). That is why some indirect components having an effect on personal adoption of new technologies play an important role.…”

Section: Resultsmentioning

confidence: 99%

“…Zarmpou et al (2012) suggested that personal innovativeness covering motivational elements has the strongest effect among other factors to adopt new technologies. Beside personal factors, social influence and contextual influences drive individuals' intention to adopt or continue the innovation, most notably in the later stage of the new technologies (Sun & Jeyaraj, 2013). When time as one of the components of the process is taken into consideration, the actual adoption period becomes even more important.…”

Section: Introductionmentioning

confidence: 99%

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Tendencies of Engineering Students on Applying Technological Innovations

Tınmaz

Yakin

2015

Procedia - Social and Behavioral Sciences

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As Information and Communication Technologies (ICTs) infuse more into our daily lives, their effects and significance become more visible for everyone. On the other hand, not all ICTs are welcomed by everyone. Some technologies or tools are more preferable whereas some people totally ignore some ICTs. In that sense, diffusion of any innovation is significant to implement research studies. Therefore, this study aimed to reveal current situation on diffusion of innovation tendencies for Faculty of Engineering (92 students from Computer, Industry and Mechatronic engineering, and departments) who will be the prospective adapters of ICTs into different sectors in their jobs. Tendency on adapting and implementing current ICTs could be listed within the most important competencies of any engineering department. The study instrument which was adapted by researchers starts with 10 demographic questions (gender, department, what social media tools they use, and etc…) one question asks for possible barriers, 20 questions on 5-point-Likert scale focusing on unfolding their tendencies on diffusion of innovations. The concept of time and administration gained prominence made a statistically significant difference among participants in revealing current situation on diffusion of innovation tendencies for students from faculty of engineering.

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“…Several studies based on ICT adoption have mainly focused on adopter and non-adopter categories, considering the adopt/not adopt pair as a unique choice outcome (Ozdemir & Trott, 2009;Sun & Jeyaraj, 2013). Although the combination is useful, it does not consider the possible heterogeneity of non-adopters, thus it has not explained the range of behaviors involved (Patsiotis, Hughes, & Webber, 2012).…”

Section: Ict Adoptionmentioning

confidence: 99%

Is ICT good for employees? An analysis of its effects on sales agents’ perceptions of service cannibalization

Díaz

Martín‐Consuegra

Talaya

2015

Computers in Human Behavior

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Information technology adoption and continuance: A longitudinal study of individuals’ behavioral intentions

Cited by 103 publications

References 23 publications

Technology as a Double-Edged Sword: From Behavior Prediction with UTAUT to Students’ Outcomes Considering Personal Characteristics

Technology as a Double-Edged Sword: From Behavior Prediction with UTAUT to Students’ Outcomes Considering Personal Characteristics

Tendencies of Engineering Students on Applying Technological Innovations

Is ICT good for employees? An analysis of its effects on sales agents’ perceptions of service cannibalization

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