Digital Intelligence and Decision Optimization in Healthcare Supply Chain Management

Healthcare supply chain management operates under complex uncertainty, high risk, and the imperative of sustainable resource optimization. This study investigates the underlying mechanisms through which digital intelligence drives strategic decision optimization in healthcare supply chains. Drawing on the Resource Based View (RBV) and Dynamic Capabilities Theory (DCT), we develop a chain mediated model in which innovation capability and supply chain resilience (absorptive, response, and restorative capabilities), serve as sequential mediators. Using structural equation modeling (SEM) on data collected from healthcare supply chain organizations in China, we find that digital intelligence indirectly enhances decision optimization by fostering innovation and resilience in tandem. Specifically, digital intelligence strengthens innovation capability, which in turn activates all three dimensions of resilience, and together these capabilities produce a synergistic effect that sustains decision improvement. Our findings offer practical theoretical guidance for healthcare institutions seeking to deploy digital intelligence technologies, reinforce dynamic process management, and achieve continuous optimization of supply chain decision making.