Factors in the Saudi Arabia Healthcare Sector’s Adoption of Cloud Business Intelligence

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Saudi Digital Library
Cloud Business Intelligence (BI) applications are hosted on a virtual network, such as the internet. They are used to provide organizations with access to BI-related data such as dashboards, KPIs and other business analytics. Enterprises are increasingly turning to cloud-based tools, like customer relationship management (CRM) applications, online file collaboration and storage and help-desk software. This trend includes business intelligence tools embracing the agility and accessibility of the Cloud. Cloud Business Intelligence (CBI) systems can significantly benefit private and public sector organizations especially during economic recessions. CBI systems have numerous benefits, including a substantial reduction in organizations’ expenditure on information technology services. Many organizations in Saudi Arabia’s healthcare system are yet to fully integrate CBI systems due to a number of factors. This study seeks to determine and recognize factors that may hinder this sector’s cloud computing adoption. It proposes a conceptual model to provide a theoretical understanding of the research problem. Moreover, it proposes a practical adoption plan to assist and direct the process of implementing CBI technology in Saudi’s healthcare sector. This study adopts a dynamic strategy to determine how suitable CBI systems are to Saudi’s healthcare system and to examine how the dynamics affect the implementation processes and measures that can be put in place to hasten the implementation process. For data collection and analysis, this study adopts a mixed-method methodology that comprises two phases. In the first, the researcher designed a survey based on existing literature and conducted a survey online. This involved 172 participants from Saudi healthcare organizations. Regression and inferential analysis were performed on quantitative data, including descriptive one-way statistics. This study tested a total of 17 hypotheses. Quantitative data were analysed to determine and evaluate the impact of the factors influencing CBI adoption, and the hypotheses were tested and verified. In the second phase, a multiple case study methodology was adopted to conduct a qualitative study. The researcher collected qualitative data by holding interview sessions with key personnel in healthcare organizations to gain a profound understanding of the characteristics of the research problem and identify a practical way to analyse the data collected from respondents. The factors were categorized into organization and technological factors, and the environmental and external pressures solution that would hasten the adoption process. Four Saudi healthcare organizations were selected for purposes of this study investigate the actual and a thematic analysis approach was used to and perceived benefits. A detailed literature review was conducted to identify research gaps and establish the potential factors influencing cloud computing adoption in Saudi’s healthcare sector. From the literature review, it was established that there is a lack of a theoretical model for the challenges and impediments surrounding cloud computing adoption. This study therefore fills the knowledge gap by proposing a new conceptual model to enable a better understanding of these factors. This study provides a bridge between theoretical concepts and practice by developing a practical plan to assist and direct organizations in the implementation of cloud BI systems. This study presents its findings in two phases. Phase 1 presents the findings from analysis of quantitative data, including factors affecting cloud BI adoption and measures of their significance. Phase 2 presents findings of the analysis of qualitative data collected through interview sessions with key personnel in healthcare organizations. The study investigates the applicability of th