Please use this identifier to cite or link to this item: https://bspace.buid.ac.ae1234/1457
Title: Critical Success Factors for Implementing Artificial Intelligence (AI) Projects in Dubai Government United Arab Emirates (UAE) Health Sector: Applying the Extended Technology Acceptance Model (TAM)
Authors: ALHASHMI, SHAIKHA ALI MOHSIN ALATTAR
Keywords: critical success factors
United Arab Emirates (UAE)
Artificial Intelligence (AI)
health care sector
Issue Date: Mar-2019
Publisher: The British University in Dubai (BUiD)
Abstract: Recently, the government of United Arab of Emirates (UAE) is focusing on Artificial Intelligence (AI) strategy for future projects that will serve various sectors. Health care sector is one of the significant sectors they are focusing on and the planned (AI) projects of it is aiming to minimize chronic and early prediction of dangerous diseases affecting human beings. Nevertheless, project success depends on the adoption and acceptance by the physicians, nurses, decision makers and patients. The main purpose of this dissertation is to explore out the critical success factors assist in implementing artificial intelligence projects in the health sector. Besides, the founded gap for this topic was explored as there is no enough sharing of multiple success factors that assist in implementing artificial intelligence projects in the health sector precisely. First of all, this dissertation analyze the mostly used external factors of the Technology Acceptance Model (TAM), by highlighting studies that address these factors, mainly Perceived Ease of Use, Perceived Usefulness, Attitude towards use and Behavioral intention to use. In order, to identify the most widely used factors a systematic review approach was conducted for 23 related research studies between 2015 and 2018 having quantitative and qualitative data. Second, a modified proposed model for this research was developed by using the extended TAM model and the most widely used factors. Third, to fit the purpose of this research a validation to the new model was used by the partial least squares-structural equation modelling (PLS-SEM). Data of this study was collected through survey from employees working in the health and IT sectors in UAE and total number of participants is 53 employees. The outcome of this questionnaire illustrated that managerial, organizational, operational and IT infrastructure factors have a positive impact on (AI) projects perceived ease of use and perceived usefulness.
URI: https://bspace.buid.ac.ae1234/1457
Appears in Collections:Dissertations for Informatics (Knowledge and Data Management)

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