Design of a framework of business intelligence systems adoption in the healthcare SMEs in Nigeria: A hybrid approach
One of the major challenges for healthcare executives is effective decision-making. In today’s healthcare market, there are pressures on private healthcare organizations to adopt business intelligence systems. However, adopting business intelligence systems in private healthcare is rather scarce, an...
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://etd.uum.edu.my/11315/1/permission%20to%20deposit-embargo%2036%20months-s903706.pdf https://etd.uum.edu.my/11315/2/s903706_01.pdf https://etd.uum.edu.my/11315/3/s903706_02.pdf https://etd.uum.edu.my/11315/ |
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| Summary: | One of the major challenges for healthcare executives is effective decision-making. In today’s healthcare market, there are pressures on private healthcare organizations to adopt business intelligence systems. However, adopting business intelligence systems in private healthcare is rather scarce, and the more important factors in the adoption decision are not fully understood. Therefore, the study aims to design a framework of business intelligence systems adoption by healthcare small and medium enterprises in Nigeria. The study conducted a systematic literature review to identify the factors, and 15 experts were chosen using the snowball sampling technique to validate the factors. Further, the study applied the Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis using SmartPLS-4 to analyze the data. Accordingly, a total of 376 hospitals’ owners in Nigeria were selected using a simple random sampling technique, however, only 152 participated. Besides, the study conducted an Analytic Hierarchy Process (AHP) analysis to prioritize the significant factors. The AHP data were collected from ten experts who were chosen through the snowball sampling technique. The result of the PLS-SEM analysis indicated that relative advantage, compatibility, complexity, observability, trialability management support, organizational size, organizational resources availability, absorptive capacity presence of champion, vendor support and government support in IT knowledge and innovativeness were significantly related to the business intelligence adoption. Meanwhile, competition and attitude did not show significant results. Further, the AHP consistency ratios (< 0.1) indicated the model is consistent. Hence, the finding shows that technology is the most important characteristic, while the environment is the least important characteristic. The study emphasizes the pivotal role of various factors of business intelligence systems adoption for enhancing healthcare decision-making in Nigeria. It confirms the significant role that both technological, organizational, environmental, and individual factors play in influencing BIS adoption. It is recommended that the hospital management should consider the most important factors in making decisions when they adopt a business intelligence system. |
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