Predicting uptake of technology innovations in online family dispute resolution services: An application and extension of the UTAUT

Casey, Tristan; Wilson‐Evered, Elisabeth

doi:10.1016/j.chb.2012.05.022

Cited by 121 publications

(101 citation statements)

References 83 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Users would adapt the technology if they agree that the technology would improve their performance. Most researchers found a positive or strong positive influence of PE on BI (Casey & Wilson-Evered, 2012;Gupta, Dasgupta, & Gupta, 2008;Zhou, Lu, & Wang, 2010). Even Venkatesh et al (2003) in his original development of this model claimed that PE is the strongest predictor of BI and the recent meta-analysis of 27 UTAUT researches showed the same .…”

Section: Research Model and Hypothesesmentioning

confidence: 81%

Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender

Dečman

2015

Computers in Human Behavior

201

157

View full text Add to dashboard Cite

Section: Research Model and Hypothesesmentioning

confidence: 81%

Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender

Dečman

2015

Computers in Human Behavior

201

157

View full text Add to dashboard Cite

“…PEOU has a significant influence on BI of CRM [64], MP3 players and internet banking [32], and family dispute resolution service [9]. Other prior studies have found that PEOU is also a key predictor on BI of online banking and payment [28] and online store [36].…”

Section: Perceived Ease-of-usementioning

confidence: 97%

“…PU is a significant predictor for behavioral intention (BI) of classroom IT [46], family dispute resolution service [9], internet banking [32], MP3 players, online stores [36], and online banking and payment [28]. Previous studies have also found that PU is a key indicator of technology acceptance [73,74].…”

Section: Perceived Usefulnessmentioning

confidence: 99%

Predicting Drivers of Mobile Entertainment Adoption: A Two-Stage SEM-Artificial-Neural-Network Analysis

Hew

Leong

Ooi

et al. 2016

Journal of Computer Information Systems

View full text Add to dashboard Cite

This study aims to understand users' motivations to adopt mobile entertainment (m-entertainment). Extending the Technology Acceptance Model (TAM), this study examined the effects of trust, perceived financial cost (PFC), and quality of the service on consumers' decision in adopting the m-entertainment. Survey data were collected from 524 mobile users and analyzed using both structural equation modeling (SEM) and neural network (NN) . The result showed that perceived usefulness (PU), perceived ease of use (PEOU), and quality of service (QS) are important predictors of m-entertainment adoption. The study contributes to the existing literature by extending the TAM model as well as examining m-entertainment, an important and emerging business model in mobile commerce. A new analytical approach using both SEM and NN was also employed in this study.

show abstract

“…The UTAUT model has successfully been used in numerous studies, including projects involving various health-related technologies [28], robotics [29], procurement recommendation systems [30], booking systems in rural tourism [31], energy efficiency [32], and technologies for social innovation [33]. The UTAUT model has also increased its relevance in recent decades due to the fact that numerous investigations have developed the model in the area of innovation and adaptation of ICT [34].…”

Section: Unified Theory Of Acceptance and Use Of Technologymentioning

confidence: 99%

The Effect of Internet Searches on Afforestation: The Case of a Green Search Engine

Palos-Sánchez

Saura

2018

Forests

View full text Add to dashboard Cite

Abstract:Ecosia is an Internet search engine that plants trees with the income obtained from advertising. This study explored the factors that affect the adoption of Ecosia.org from the perspective of technology adoption and trust. This was done by using the Unified Theory of Acceptance and Use of Technology (UTAUT2) and then analyzing the results with PLS-SEM (Partial Least Squares-Structural Equation Modeling). Subsequently, a survey was conducted with a structured questionnaire on search engines, which yielded the following results: (1) the idea of a company helping to mitigate the effects of climate change by planting trees is well received by Internet users. However, few people accept the idea of changing their habits from using traditional search engines; (2) Ecosia is a search engine believed to have higher compatibility rates, and needing less hardware resources, and (3) ecological marketing is an appropriate and future strategy that can increase the intention to use a technological product. Based on the results obtained, this study shows that a search engine or other service provided by the Internet, which can be audited (visits, searches, files, etc.), can also contribute to curb the effects of deforestation and climate change. In addition, companies, and especially technological start-ups, are advised to take into account that users feel better using these tools. Finally, this study urges foundations and non-governmental organizations to fight against the effects of deforestation by supporting these initiatives. The study also urges companies to support technological services, and follow the behavior of Ecosia.org in order to positively influence user satisfaction by using ecological marketing strategies.

show abstract

Predicting uptake of technology innovations in online family dispute resolution services: An application and extension of the UTAUT

Cited by 121 publications

References 83 publications

Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender

Modeling the acceptance of e-learning in mandatory environments of higher education: The influence of previous education and gender

Predicting Drivers of Mobile Entertainment Adoption: A Two-Stage SEM-Artificial-Neural-Network Analysis

The Effect of Internet Searches on Afforestation: The Case of a Green Search Engine

Contact Info

Product

Resources

About