Collaboration and coordination strategies for a multi-level AI-enabled healthcare supply chain under disaster

Abstract

Artificial Intelligence (AI)-based applications have been rising across the healthcare supply chain. Successful AI implementation requires proper collaboration among healthcare supply chain members. However, high investment associated with AI innovation often impedes collaboration. In this context, disruption caused by the disasters like pandemics and epidemics can add more complexity. This issue has not received substantial scholarly attention. Here, we design a multi-level AI-enabled healthcare supply chain by incorporating a three-level supply chain structure with a healthcare product manufacturer, a distributor, and a procurement agency, where the manufacturer and distributor invest in AI innovation. Here, we adopt wholesale price (W) and cost-sharing (C) contracts-based mechanisms considering four scenarios WW, WC, CW, and CC, to devise the three-level AI-enabled healthcare supply chain members’ collaboration and coordination strategies with and without disruption. Adopting a Stackelberg game-theoretic approach, we determine the supply chain members’ optimal AI innovation efforts, prices, and profits for all scenarios. We demonstrate the dominance of one scenario over other for the supply chain members’ decisions and profits and propose a scenario ranking framework. We also investigate the impact of the disruption cost-sharing between the manufacturer and retailer, the disruption probabilities, and AI innovation success on the supply chain decisions

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