FACTORS INFLUENCING ARTIFICIAL INTELLIGENCE (AI) ACCEPTANCE IN HEALTHCARE SERVICES OF PRIVATE HOSPITALS

Authors

  • Warakorn Setthakulanan Quality Control Engineer, DoppioTech Co., Ltd.

Keywords:

Artificial Intelligence, Technology Acceptance, Private Hospitals, Healthcare Services, Trust in AI

Abstract

This research aimed to (1) examine the level of artificial intelligence (AI) acceptance in healthcare services provided by private hospitals, (2) investigate factors influencing AI acceptance in healthcare services, and (3) propose managerial guidelines for enhancing AI adoption in private healthcare organizations. This study employed a quantitative research approach. The sample consisted of 4 0 0 private hospital users selected through purposive sampling. Data were collected using a questionnaire developed based on the Technology Acceptance Model (TAM), incorporating additional factors including trust in AI, privacy concern, and technology readiness. Data were analyzed using descriptive statistics and Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings revealed that users demonstrated a high level of AI acceptance in healthcare services (x̄= 4 .16 , S.D. = 0 .54 ) . The structural model analysis indicated that perceived usefulness had the strongest positive effect on AI acceptance (β = 0.341, p < .001), followed by trust in AI (β = 0.287, p < .001), perceived ease of use (β = 0.221, p < .001), and technology readiness (β = 0.198, p < .001 ) . In contrast, privacy concern negatively influenced AI acceptance (β = -0 .156 , p = .001 ) . The proposed model explained 68.4% of the variance in AI acceptance (R² = 0.684).
The findings suggest that private hospitals should emphasize communicating the benefits of AI, designing user-friendly AI systems, enhancing trust through transparency and reliability, and implementing effective personal data protection practices. These strategies can facilitate greater acceptance and sustainable implementation of AI in healthcare services.

Downloads

Download data is not yet available.

References

Choung, H., David, P., & Ross, A. (2022). Trust in AI and technology acceptance in healthcare applications. Computers in Human Behavior, 127, Article 107045. https://doi.org/10.1016/j.chb.2021.107045

Davenport, T. H., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94

Lambert, S. I., Madi, M., Sopka, S., Lenes, A., Stange, H., Buszello, C.-P., & Stephan, A. (2023). An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals. npj Digital Medicine, 6, Article 111. https://doi.org/10.1038/s41746-023-00852-5

Morley, J., Machado, C. C. V., Burr, C., Cowls, J., Joshi, I., Taddeo, M., & Floridi, L. (2020). The ethics of AI in health care: A mapping review. Social Science & Medicine, 260, Article 113172. https://doi.org/10.1016/j.socscimed.2020.113172

Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of Service Research, 18(1), 59–77. https://doi.org/10.1177/1094670514539730

Poirier, S., Audet, C., Croteau, A.-M., Castonguay, A., & Pare, G. (2024). AI maturity in health care: An overview of 10 OECD countries. Health Policy, 140, Article 104938. https://doi.org/10.1016/j.healthpol.2023.104938

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Downloads

Published

2026-08-23

How to Cite

Setthakulanan, W. (2026). FACTORS INFLUENCING ARTIFICIAL INTELLIGENCE (AI) ACCEPTANCE IN HEALTHCARE SERVICES OF PRIVATE HOSPITALS. Kaonawat Academic Journal, 1(4), 1–11. retrieved from https://so17.tci-thaijo.org/index.php/KAJ/article/view/2609

Issue

Vol. 1 No. 4 (2026): กรกฎาคม - สิงหาคม

Section

Research Article

Categories

License

Copyright (c) 2026 Kaonawat Academic Journal

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Submission Guidelines: Kaonawat Journal

  1. Article Characteristics and Structure

Types of Works: Accepts Research Articles and Academic Articles in fields including Business Administration, General Management, Finance and Accounting, Marketing, Tourism and Hotel Management, Linguistics, Information Science, Business Computer, Education, Communication Arts, Social Sciences, Political Science, Public Administration, Economics, Arts, Culture, Agricultural Extension, Environment, Health and Healthcare, and related interdisciplinary fields.

Content Length: The main body (excluding abstracts) must be between 5,000 – 10,000 words (counted using Microsoft Word 2013 or higher).

Language: Articles can be submitted in either Thai or English.

Article Components: Must strictly follow the journal’s official Template.

  1. Manuscript Formatting

File Format: Submissions must be in .doc or .docx (Microsoft Word) format only.

Page Setup: Single-sided printing on A4 paper with margins set according to the provided Template.

References: Must use the APA style or the latest standards specified in the ThaiJO system. Digital Object Identifiers (DOIs) or URLs for online sources must be included where available.

  1. Terms and Publication Ethics

Originality: The manuscript must not have been previously published or be under consideration by any other journal.

Review Process: Articles will undergo a Double-blind Peer Review by at least 2–3 experts.

Copyright: Content and illustrations must not infringe on any copyrights. The author(s) bear sole responsibility for any legal infringements.

  1. Submission Channel

Authors must register and submit their manuscripts through the Kaonawat Journal (ThaiJO) online system only. The latest Template can be downloaded from the journal’s homepage.