Predictors of Blockchain Technology Acceptance in Medical Imaging: The Mediating Role of Initial Trust

Authors

  • Zainab Amin Al-Sulami College of Graduate Studies, Universiti Tenaga Nasional, Malaysia | Department of Mathematics, College of Science, University of Basrah, Iraq
  • Nor’ashikin Ali Institute of Informatics and Computing in Energy, Universiti Tenaga Nasional, Malaysia
  • Rohaini Ramli Department of Informatics, College of Computing and Informatics, Universiti Tenaga Nasional, Malaysia
Volume: 14 | Issue: 4 | Pages: 15312-15319 | August 2024 | https://doi.org/10.48084/etasr.7660

Abstract

Blockchain technology (BCT) is an emerging technology that has been used mainly in supply chain and financial technology. However, the use of this technology in Medical Imaging (MI) is still limited. This study investigates the acceptability of BCT in MI in public hospitals in Iraq. Based on relevant theories, the study proposed that Effort Expectancy (EE), Performance Expectancy (PE), Social Influence (SI), and Facilitating Condition (FC) significantly affect the acceptability of BCT in MI. Similarly, EE, PE, SI, and FC are expected to affect Initial Trust (IT), which in turn is proposed to mediate the effect of EE, PE, SI, and FC on the acceptability of BCT in MI. Data were collected from 136 doctors from public hospitals in Iraq. The results indicated that EE, PE, and SI positively affected the acceptability of BCT in MI. EE and PE positively affected IT. Furthermore, IT positively affected the acceptability of BCT in MI and mediated the effect of EE and PE. The study offers valuable insights for both theoretical and practical implementations, can guide future research, and informs strategies for the effective acceptability of BCT in MI in public hospitals.

Keywords:

UTAUT, blockchain technology, medical imaging, expanded trust model, initial trust

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How to Cite

[1]
Al-Sulami, Z.A., Ali, N. and Ramli, R. 2024. Predictors of Blockchain Technology Acceptance in Medical Imaging: The Mediating Role of Initial Trust. Engineering, Technology & Applied Science Research. 14, 4 (Aug. 2024), 15312–15319. DOI:https://doi.org/10.48084/etasr.7660.

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