Volume 13, Issue 5 (May 2026), Pages: 96-109

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 Original Research Paper

Analytics-based modeling of organizational resistance and resilience in Saudi healthcare supply chains

 Author(s): 

Islam El-Nakib *

 Affiliation(s):

College of Business, Effat University, Jeddah 22332, Saudi Arabia

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 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0002-6981-6492

 Digital Object Identifier (DOI)

 
https://doi.org/10.21833/ijaas.2026.05.010

 Abstract

This study develops an integrated analytical framework that combines partial least squares structural equation modeling (PLS-SEM) and agent-based simulation to examine and address resistance to blockchain-based digital transformation in healthcare supply chains. Data were collected from 619 healthcare supply chain professionals working in public and private organizations in Saudi Arabia. The study investigates technological, organizational, and environmental factors, with competitive intensity as a moderating variable and AI-enabled Physical Internet (AI-PI) readiness as a mitigating strategy. The structural model explains 66.5% of the variance in organizational resistance, with key drivers including technological complexity, system immaturity, high implementation costs, and limited knowledge. Simulation results indicate that AI-PI coordination can achieve up to 25% reduction in operational costs, 20% decrease in emissions, and improved disruption recovery performance. These findings provide empirical support for decision-making in the digital transformation of Saudi healthcare supply chains within the Vision 2030 framework.

 © 2026 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

Healthcare supply chains, Blockchain adoption, Organizational resistance, Artificial intelligence, Saudi Arabia

 Article history

Received 14 December 2025, Received in revised form 21 April 2026, Accepted 8 May 2026

 Acknowledgment

The author would like to express sincere thanks to Effat University for its generous support and resources, and to the participating Saudi healthcare professionals for their time, cooperation, and valuable contributions to the study. 

 Compliance with ethical standards

 Ethical considerations

This study adhered to internationally recognized ethical standards, including the principles outlined in the Declaration of Helsinki and its amendments. Ethical approval was granted by the Research Ethics Committee of Effat University (Decision No. RCI_REC/12.Marh.2025/7-7.1.Exp./1(103); approval date: March 12, 2025). All participation was voluntary, and respondents provided informed consent before participating in the study. Participants were thoroughly briefed on the research aims, methods, potential risks, and their rights to privacy, anonymity, and the right to withdraw at any time without repercussions. The collected data were anonymized and used exclusively for scholarly research purposes. 

 Citation:

El-Nakib I (2026). Analytics-based modeling of organizational resistance and resilience in Saudi healthcare supply chains. International Journal of Advanced and Applied Sciences, 13(5): 96-109

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