A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption
Adopting the CloudIoT-based healthcare paradigm provides various prospects for medical IT and considerably enhances healthcare services. However, compared to the advanced development of CloudIoT-based healthcare systems, their usage is relatively low among healthcare professionals in hospitals. Thus...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer Science and Business Media
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/116145/ http://psasir.upm.edu.my/id/eprint/116145/1/116145.pdf |
| _version_ | 1848866935694950400 |
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| author | Altawaiha, Iyad Atan, Rodziah Yaakob, Razali Abdullah, Rusli |
| author_facet | Altawaiha, Iyad Atan, Rodziah Yaakob, Razali Abdullah, Rusli |
| author_sort | Altawaiha, Iyad |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Adopting the CloudIoT-based healthcare paradigm provides various prospects for medical IT and considerably enhances healthcare services. However, compared to the advanced development of CloudIoT-based healthcare systems, their usage is relatively low among healthcare professionals in hospitals. Thus, a study on the healthcare professionals acceptance and adoption of CloudIoT-based healthcare is critical. This study explores factors influencing healthcare professionals adoption of CloudIoT-based healthcare solutions by extending the Unified Theory of Acceptance and Use of Technology 2 model. Data was collected from 300 healthcare professionals in Jordan through an online questionnaire developed using the Google® form application. The Bayesian Network and Structural Equation Modeling techniques were used to analyze and validate the proposed model. The results revealed that the healthcare professional’s behavioral intention is directly affected by seven factors: performance expectancy, effort expectancy, facilitating conditions, habit, trust, privacy, and security. The results also indicate that trust mediates the influence of privacy, facilitating conditions, and performance expectancy on behavioral intention. The research results will aid CloudIoT service providers, healthcare organizations, designers, and developers by offering comprehensive knowledge of the significant factors of CloudIoT-based healthcare adoption. A better understanding of these factors will help these stakeholder groups enhance their services and speed up the adoption of CloudIoT in the healthcare area. |
| first_indexed | 2025-11-15T14:28:30Z |
| format | Article |
| id | upm-116145 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T14:28:30Z |
| publishDate | 2024 |
| publisher | Springer Science and Business Media |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1161452025-03-28T01:04:33Z http://psasir.upm.edu.my/id/eprint/116145/ A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption Altawaiha, Iyad Atan, Rodziah Yaakob, Razali Abdullah, Rusli Adopting the CloudIoT-based healthcare paradigm provides various prospects for medical IT and considerably enhances healthcare services. However, compared to the advanced development of CloudIoT-based healthcare systems, their usage is relatively low among healthcare professionals in hospitals. Thus, a study on the healthcare professionals acceptance and adoption of CloudIoT-based healthcare is critical. This study explores factors influencing healthcare professionals adoption of CloudIoT-based healthcare solutions by extending the Unified Theory of Acceptance and Use of Technology 2 model. Data was collected from 300 healthcare professionals in Jordan through an online questionnaire developed using the Google® form application. The Bayesian Network and Structural Equation Modeling techniques were used to analyze and validate the proposed model. The results revealed that the healthcare professional’s behavioral intention is directly affected by seven factors: performance expectancy, effort expectancy, facilitating conditions, habit, trust, privacy, and security. The results also indicate that trust mediates the influence of privacy, facilitating conditions, and performance expectancy on behavioral intention. The research results will aid CloudIoT service providers, healthcare organizations, designers, and developers by offering comprehensive knowledge of the significant factors of CloudIoT-based healthcare adoption. A better understanding of these factors will help these stakeholder groups enhance their services and speed up the adoption of CloudIoT in the healthcare area. Springer Science and Business Media 2024 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/116145/1/116145.pdf Altawaiha, Iyad and Atan, Rodziah and Yaakob, Razali and Abdullah, Rusli (2024) A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption. International Journal of Information Technology (Singapore). pp. 1-21. ISSN 2511-2104; eISSN: 2511-2112 https://link.springer.com/article/10.1007/s41870-024-01743-y?error=cookies_not_supported&code=37031c04-f769-4485-8d32-549f5f23672a 10.1007/s41870-024-01743-y |
| spellingShingle | Altawaiha, Iyad Atan, Rodziah Yaakob, Razali Abdullah, Rusli A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption |
| title | A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption |
| title_full | A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption |
| title_fullStr | A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption |
| title_full_unstemmed | A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption |
| title_short | A three-step SEM-Bayesian network approach for predicting the determinants of CloudIoT-based healthcare adoption |
| title_sort | three-step sem-bayesian network approach for predicting the determinants of cloudiot-based healthcare adoption |
| url | http://psasir.upm.edu.my/id/eprint/116145/ http://psasir.upm.edu.my/id/eprint/116145/ http://psasir.upm.edu.my/id/eprint/116145/ http://psasir.upm.edu.my/id/eprint/116145/1/116145.pdf |