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The Algorithm's Boundary: When AI enhances and fails to strengthen pharmaceutical supply chain resilience
Fangzhou Song1, Siqi Li1, Pu Jian2
1The Institute for Sustainable Development, Macau University of Science and Technology, Macau, 999078, China.
Abstract:
Pharmaceutical supply chain vulnerabilities threaten patient safety, prompting firms to invest in artificial intelligence (AI) to strengthen resilience. Yet AI's resilience benefits may depend on firms' adaptive capabilities and the stressors they confront. Drawing on complex adaptive systems (CAS) theory, this study examines pharmaceutical supply chain resilience (PSCRE) and the conditions under which AI moderates these firm-level associations. We operationalize self-organization through R&D intensity, co-evolution through supply chain relationship stability, and environmental awareness through perceived policy uncertainty. Using panel data from Chinese A-share pharmaceutical manufacturers (2008-2023), we measure the engineering dimension of resilience with the bullwhip effect. The results indicate that R&D intensity and supply chain relationship stability are associated with lower bullwhip effect, whereas perceived policy uncertainty is associated with higher bullwhip effects. AI's moderating role is contingent: it strengthens the negative associations of R&D intensity and supply chain relationship stability with the bullwhip effect but does not reliably attenuate the positive association of perceived policy uncertainty with it. These findings delineate AI's boundary conditions and offer implications for managerial strategy, policy implementation, and medicine supply continuity.
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