Decisions in supply chain management (SCM) are subject to numerous conflicting criteria and multiple objectives. For such decisions, multiple criteria decision making (MCDM) methods are definitely appropriate. The implementation of the healthcare supply chain (HSC) is more complex to manage than any other supply chains, as it involves human life, causing conflicts of interest and hindering the final decision. Previous researchers suggested different SC models for healthcare products such as drugs, vaccines, and other medical equipment. This article provides an overview of published articles in the application of MCDM methods in HSCM at the strategic, tactical, and operational levels. We studied and categorized 139 articles published in 2006–2021, providing academic researchers, practitioners, and governments with insights into the application of different MCDM methods. The review allows us to establish guidelines for the selection of appropriate methods for HSC management and provide support to the management of issues in the healthcare and pharmaceutical sector.

In this article, there is established a reverse logistics (RL) system to collect unwanted medications (UMs) in households. A reverse supply chain (RSC) is proposed in a decentralized state including manufacturer, and retailer involving a strategic consumer. The novelty of this article is that the model is investigated from the consumer's perspective, whereas in the previous studies, the proposed models were from other upstream members' perspectives such as manufacturer and retailer. Furthermore, inducement and advertising strategies are proposed for stimulating consumers to engage more in an RSC. To analyse the effect of these two strategies, the three‐person RSC game‐theoretical approach is used. A three‐person supply chain consists of a pharmaceutical manufacturer and a retailer who will interact with a strategic consumer in several non‐cooperative Stackelberg games. Three Stackelberg games are established and, each member takes a turn as a leadership role and the other two players assume the role of the follower.

Supply Chains have been more and more suffering from unexpected industrial, natural events, or epidemics that might disrupt the normal flow of materials, information, and money. The recent pandemic triggered by the outbreak of the new COVID-19 has pointed out the increasing vulnerability of supply chain networks, prompting companies (and governments) to implement specific policies and actions to control and reduce the spread of the disease across the network, and to cope with exogenous shocks. In this paper, we present a stochastic Susceptible-Infected-Susceptible (SIS) framework to model the spread of new epidemics across different distribution networks and determine social distancing/treatment policies in the case of local and global networks. We highlight the relevance of adaptability and flexibility of decisions in unstable and unpredictable scenarios.

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