Factors Influencing Decision Support System Acceptance

Rania Shibl; Meredith A Lawley; Justin Debuse

doi:10.1016/j.dss.2012.09.018

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Factors Influencing Decision Support System Acceptance

Journal article

Open access

Peer reviewed

Factors Influencing Decision Support System Acceptance

Rania Shibl, Meredith A Lawley and Justin Debuse

Decision Support Systems, Vol.54(2), pp.953-961

2013

DOI: https://doi.org/10.1016/j.dss.2012.09.018

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Abstract

decision support systems

UTAUT

general practitioners

technology acceptance

While clinical DSS have many proven benefits, their uptake by GPs (general practitioners) is limited. The purpose of this research was to develop and explore a UTAUT (Unified Theory of Acceptance and Use of Technology) based model of how and why GPs accept DSS. Insight into the reasons why GPs do not use clinical DSS combined with knowledge of why GPs use DSS will allow the development of strategies to facilitate more widespread adoption with consequent improvements across many areas. Depth interviews were conducted with 37 GPs comprising a mix of education backgrounds, experience and gender. The developed model indicated that four main factors influence DSS acceptance and use including usefulness (incorporating consultation issue, professional development and patient presence), facilitating conditions (incorporating workflow, training and integration), ease of use and trust in the knowledge base.

Details

Title: Factors Influencing Decision Support System Acceptance
Authors: Rania Shibl (Author) - Griffith University
Meredith A Lawley (Author) - University of the Sunshine Coast - Faculty of Arts and Business
Justin Debuse (Author) - University of the Sunshine Coast - Faculty of Arts and Business
Publication details: Decision Support Systems, Vol.54(2), pp.953-961
Publisher: Elsevier BV, North-Holland
Date published: 2013
DOI: 10.1016/j.dss.2012.09.018
ISSN: 0167-9236; 1873-5797
Organisation Unit: School of Business and Creative Industries; University of the Sunshine Coast, Queensland; USC Business School - Legacy; School of Science, Technology and Engineering
Language: English
Record Identifier: 99450013802621
Output Type: Journal article

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Collaboration types: Domestic collaboration
Web Of Science research areas: Computer Science, Artificial Intelligence; Computer Science, Information Systems; Operations Research & Management Science

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