- Title
- Acceptance of internet of things-based innovations for improving healthcare in Saudi Arabia
- Creator
- Masmali, Feisal Hadi
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2023
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- The rapid evolution of Information Systems (IS) has ushered in a new era of digital transformation, with the Internet of Things (IoT) at the forefront. This research delves into the acceptance and integration of IoT-oriented IS applications in the healthcare sector of Saudi Arabia. With the primary objective of understanding the factors influencing the acceptance of IoT innovations in healthcare, this study offers a comprehensive analysis to capture the influence in terms of the potential benefits, challenges, and implications of integrating IoT into healthcare service delivery. Impact of IoT in IS, a paradigm shift in technology, enables essential objects equipped with sensors and software systems to communicate and exchange data over the Internet. This capability has revolutionized various industries, with healthcare being a notable beneficiary. The global healthcare sector has witnessed a surge in the acceptance of IoT innovations, particularly in remote public-healthcare atmospheres where patient monitoring and management are of paramount task. Thus, studying the impact of IoT may bring new insights for both researchers and practitioners that could contribute to create new knowledge in the target body of IS literature. In the country context of Saudi Arabia, the integration of IoT in healthcare systems presents a plethora of opportunities. The Saudi Arabian government has been proactive in endorsing the adoption of IoT technologies, establishing regulations, and fostering public-private partnerships to drive innovation. With the country's robust Internet infrastructure and government-backed initiatives like electronic health records and telehealth services, the potential for the IoT influence in relation to acceptance and integration in healthcare systems practices is immense, however existing studies are limited in this sub-field. A comprehensive study towards full-scale of IoT oriented system adoption in healthcare holds a lot of emerging challenges. This is related to data protection, privacy, infrastructure limitations, compliances and cybersecurity are of critical elements for further exploration. Additionally, issues like interoperability, financial constraints, and talent shortages need to be addressed to ensure seamless integration. Thus, it is imperative to develop new systematic empirical study in this subfield. This research adopts a mixed-methods approach, combining qualitative interviews with quantitative surveys, to investigate the aspects through a holistic viewpoint for developing new understanding to fill the significant knowledge gap in the IS literature. The qualitative phase, conducted with key stakeholders in Saudi Arabia's healthcare sector, offers in-depth insights into the current landscape and potential future trajectories. These findings then inform the quantitative phase, which aims to capture broader trends of IoT acceptance within the sector. These findings are consistent with a combined aspect of the Technology Acceptance Model (TAM) and the Diffusion of Innovation Model (DOI), which suggest that successful adoption and integration of IoT into healthcare systems requires knowledge, familiarity, and recognition of the usage of IoT. The PhD thesis is based on the combined theoretical underpinnings of Information Systems (IS) design, technology acceptance, and diffusion of innovations. In terms of technology acceptance, our study concentrates on the acceptance of Internet of Things-oriented IS applications and various service provisions, especially innovative ones, that practitioners in the healthcare sector can deploy and in terms of the diffusion of innovations, it brings the practitioners view on the cutting-edge application of IoT in the aspect of IS design. That is why, the study's theoretical foundation is rooted in the combined framework of the Technology Acceptance Model (TAM) and the Diffusion of Innovation (DOI). This integrated model offers a comprehensive perspective on the multifaceted nature of technology acceptance, encompassing both individual perceptions and broader organizational influences. Key findings from the research highlight the pivotal role of knowledge and awareness in the successful implementation of IoT. The perceived benefits of IoT, such as enhanced patient care, improved communication, and streamlined processes, act as strong motivators for adoption. However, challenges related to system compatibility, training requirements, and financial constraints emerge as potential barriers. The thesis underscores the need for targeted interventions, strategic planning, and resource allocation to overcome these challenges. In summary, the acceptance of IoT in Saudi Arabia's healthcare sector holds the promise of transformative change. While the benefits are manifold, a strategic approach, underpinned by a deep understanding of the challenges, is crucial. This research contributes significantly to the literature on IoT adoption in healthcare, offering valuable insights of new knowledge that may be used as recommendations for policymakers, healthcare professionals, and researchers. The findings serve as a beacon for future endeavours aimed at harnessing the power of IoT for a healthier and more efficient healthcare system design in Saudi Arabia.
- Subject
- internet of things; Kingdom of Saudi Arabia; diffusion of innovations; mobile health; electronic government; information systems; healthcare; innovations
- Identifier
- http://hdl.handle.net/1959.13/1507057
- Identifier
- uon:55952
- Rights
- Copyright 2023 Feisal Hadi Masmali
- Language
- eng
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT01 | Thesis | 2 MB | Adobe Acrobat PDF | View Details Download | ||
| View Details Download | ATTACHMENT02 | Abstract | 366 KB | Adobe Acrobat PDF | View Details Download |