Exploring the influence of security/privacy, trialability, output quality and anxiety on the adoption of mobile decision support systems among nurses: a developing country context
by Mohammed-Issa Riad Mousa Jaradat
International Journal of Mobile Learning and Organisation (IJMLO), Vol. 15, No. 3, 2021

Abstract: Nursing staff need to be highly mobile in executing their routine work. Therefore, they may need to catch, deliver and/or receive critical information, orders or alerts via mobile devices at any point of care to help them take immediate decisions/actions or orders to accomplish their tasks quickly. This paper investigates the factors that affect the adoption of mobile decision support systems among nurses in Jordan. Experience and voluntariness as moderators in the proposed model were also investigated. The model was analysed and tested using WarpPLS 5.0 software. The findings of this study have demonstrated that perceived usefulness, perceived ease-of-use, security/privacy, trialability, output quality, and anxiety are important constructs in predicting and affecting intentional behaviour to adopt decision support systems among nurses in Jordan. The model has explained 65% of the variance in behavioural intention. Theoretical contributions and practical implications are outlined. Limitations and suggestions for future studies are discussed.

Online publication date: Tue, 27-Jul-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mobile Learning and Organisation (IJMLO):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com