Hamad S. J. Rashid

Dr. Hamad S. J. Rashid

orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2019 in Operations Research Perspectives
Verified
Journal Article
Open access
AAAbdullah ALKHORAIF
Abdullah ALKHORAIF
HRHamad S. J. Rashid
Hamad S. J. Rashid
PMPatrick McLaughlin
Patrick McLaughlin

1 November 2010 in International Journal of Industrial Ergonomics
Verified
Journal Article
Closed access
HRHamad S. J. Rashid
Hamad S. J. Rashid
CPC.S. Place
C.S. Place
GBG.R. Braithwaite
G.R. Braithwaite

25 December 2017 in Journal of Human Resources Management Research
Verified
Journal Article
Open access
MSMohammed Al Shehri
Mohammed Al Shehri
PMPatrick McLaughlin
Patrick McLaughlin
AAAhmed Al-Ashaab
Ahmed Al-Ashaab
HRHamad S. J. Rashid
Hamad S. J. Rashid

2 September 2012 in Cognition, Technology & Work
Verified
Journal Article
Closed access
PDF file
HRHamad S. J. Rashid
Hamad S. J. Rashid
CPC. S. Place
C. S. Place
GBG. R. Braithwaite
G. R. Braithwaite

2 March 2012 in Cognition, Technology & Work
Verified
Journal Article
Closed access
PDF file
HRHamad S. J. Rashid
Hamad S. J. Rashid
CPC. S. Place
C. S. Place
GBG. R. Braithwaite
G. R. Braithwaite

5 September 2024 in Sustainability
Verified
Journal Article
Open access
PDF file
KAKhalid Mohamed Ali Alshehhi
Khalid Mohamed Ali Alshehhi
ACAli Cheaitou
Ali Cheaitou
HRHamad S. J. Rashid
Hamad S. J. Rashid
This study investigates the critical success factors (CSFs) influencing the procurement of artificial intelligence (AI) systems within the United Arab Emirates (UAE) public sector. While AI holds immense potential to enhance public service delivery, its successful integration hinges on critical factors. This research utilizes Interpretive Structural Modeling (ISM) to analyze the CSFs impacting AI procurement within the UAE public sector. Through ISM, a structural model is developed to highlight the interrelationships between these CSFs and their influence on the procurement process, outlining the key elements for successful AI procurement within the UAE public sector. Based on the literature review and expert validation from the UAE public sector, ten CSFs were identified. This study found that clear needs assessment is the most influential CSF, while the long-term value of AI systems or services is the least influential. This study provides policymakers and public sector leaders with valuable insights, enabling them to formulate effective strategies to optimize the procurement process and establish a strong foundation for AI adoption. Finally, this will lead to an improved and more efficient public service delivery in the UAE.