This study examines the association between telemedicine adoption and healthcare management efficiency, with leadership support acting as a mediator, at King Fahad Hospital in Saudi Arabia. A core issue is that adopting technology alone does not automatically improve managerial efficiency, as organisational elements especially leadership backing often determine the extent of the benefits achieved. Grounded in the Resource-Based View framework, we propose that telemedicine adoption improves efficiency both directly and indirectly via leadership commitment, resource allocation, and strategic direction. We employed a positivist, correlational cross-sectional design. We collected data from 422 healthcare professionals and administrative staff through a structured, self-administered questionnaire. We analysed the data using Partial Least Squares Structural Equation Modelling with 5,000 bootstrap subsamples. The measurement model showed satisfactory psychometric properties: all indicator loadings were above 0.70, composite reliability exceeded 0.91, and average variance extracted values exceeded 0.57. Discriminant validity was established by applying the Heterotrait-Monotrait ratio. The structural model explained 58% of the variance in healthcare management efficiency. All direct effects were statistically significant at p < 0.001. Telemedicine adoption had a notable positive direct effect on efficiency (? = 0.29, t = 4.85) and a robust effect on leadership support (? = 0.64, t = 13.27). Leadership support was associated with a notable increase in efficiency (? = 0.46, t = 7.62). Mediation analysis indicated that leadership support partially mediated the relationship, with an indirect effect of 0.294 (t = 6.18, p < 0.001) and a Variance Accounted For of approximately 50.3%. The total effect of telemedicine adoption on efficiency was 0.584. These results indicate that the productivity gains from telemedicine are greatly reinforced when hospital administrators actively champion its implementation. Hence, healthcare administrators and policymakers should recognise that successful digital health transformation depends on both technology funding and active organisational direction to achieve operational and administrative benefits.
Aday, L., Begley, C., Lairson, D., & Balkrishnan, R. (2004). Evaluating the healthcare system: Effectiveness, efficiency, and equity. books.google.com.
Alenezi, S., Alanazi, F., Alaqeel, S. (2026). A systematic review of telemedicine applications and outcomes in emergency department settings. Genetics and Molecular Research.
Al-Habsi, N., Luo, M., & Zighan, S. (2022). A systematic literature review exploring the impact of digitalisation on leadership towards a new style of leadership—International Journal of Business Innovation and Research.
Alnefaie, M., & Ali, A. (2025). The impact of digital transformation on enhancing the performance of health practitioners working at King Faisal Medical Complex in Taif—International Journal of Philosophy of Culture and Axiology.
Arif, M., & Selvarajh, G. (2026). Integrating transformational, participative, and digital leadership for effective healthcare digital transformation. International Journal of Social Sciences and Management Review.
Babbie, E. (2020). The practice of social research. books.google.com.
Baron, R., & Kenny, D. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology.
Brislin, R. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology.
Changalima, I., & Chuwa, M. (2025). Partial least squares structural equation modeling (PLS-SEM) in business research: A simple guide for novice researchers. International Journal of Research in Business and Social Science.
Cohen, J. (2013). Statistical power analysis for the behavioural sciences. books.google.com.
Fah, L., & Sirisena, A. (2014). Relationships between the knowledge, attitudes, and behaviour dimensions of environmental literacy: A structural equation modeling approach using smartpls. Jurnal Pemikir Pendidikan.
FD, V., & Davis, G. (2003). User acceptance of information technology: Toward a unified view. MIS Q, 2003.
Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error—Journal of Marketing Research.
Hajesmaeel-Gohari, S., Khordastan, F., Fatehi, F. (2022). The most used questionnaires for evaluating satisfaction, usability, acceptance, and quality outcomes of mobile health. BMC Medical Informatics and Decision Making.
He, H., Ghazilla, R. R., & Abdul?Rashid, S. (2025). Factors influencing the intention to use telemedicine services among older adults in china. Scientific Reports.
Henseler, J., Ringle, C., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science.
Judijanto, L., Anurogo, D., Zani, B. (2024). Implementation of telemedicine in health services: Challenges and opportunities—Journal of World Health.
Khatri, B., Saxena, C., & Gawshinde, S. (2025). Moderating role of technology readiness of individuals to embrace telemedicine. 2025 International Conference on Ambient Intelligence in Health Care (ICAIHC).
Lange, F. (2023). Behavioral paradigms for studying pro-environmental behavior: A systematic review. Behavior Research Methods.
Liu, J., Baskaran, A., & Li, S. (2009). Building technological-innovation-based strategic capabilities at firm level in china: A dynamic resource-based-view case study. Industry and Innovation.
Mohize, A., Alsalem, A., Bojbara, A. (2025). Sustainable healthcare practices: Advancing eco-friendly laboratory management, integrating green initiatives in nursing education, and promoting value-based …. Saudi Journal of Medicine and Public Health.
Oldenburg, B., & Glanz, K. (2008). Diffusion of innovations. Encyclopedia of Epidemiology.
Preacher, K., & Hayes, A. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods.
Rady, M., Kineber, A., Hamed, M., & Daoud, A. (2023). Partial least squares structural equation modeling of constraint factors affecting project performance in the egyptian building industry. Mathematics.
Ringle, C., Sarstedt, M., Mitchell, R., et al. (2020). Partial least squares structural equation modelling in HRM research—International Journal of Human Resource Management.
Tasnime, B. B. (2024). Digital health applications and their role in improving the quality of health care services: Study the experience of Saudi Arabia. dspace.univ-bba.dz.
Teece, D., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal.
Trist, E. (1981). The evolution of socio-technical systems. lmmiller.com.
Twycross, A. (2004). Research design: Qualitative, quantitative and mixed methods approaches. Nurse Researcher (Through 2013).
Yamane, T. (1973). Statistics: An introductory analysis. researchgate.net.
Alzahrani, A. Y. K., & Sohail, N. (2026). The Mediating Role of Leadership Support in the Relationship between Telemedicine Adoption and Healthcare Management Efficiency at King Fahad Hospital, Saudi Arabia. International Journal of Academic Research in Business and Social Sciences, 16(9), 850–868.
Copyright: © 2026 The Author(s)
Published by Knowledge Words Publications (www.kwpublications.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode