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Purpose By applying a systematic literature review, this paper aims to identify the major healthcare problem domains (i.e. target areas) for lean supply chain management (LSCM) and to provide a list of the most common techniques for implementing LSCM in healthcare. Moreover, this study intends to investigate various contingency factors that may have influenced the selection of LSCM target areas or the application of LSCM techniques by healthcare organizations. Design/methodology/approach A systematic literature review was carried out following the method presented by Tranfield et al. (2003). Thereby, 280 peer-reviewed journal articles, published between 1995 and 2018, were selected, profiled and reviewed. In total, 75 papers were also selected for a qualitative analysis, known as meta-study, on the basis of high relevancy to the research objectives. Findings This work extracts, from previous research, a set of target areas for improving supply chain in healthcare by applying lean approaches. The work also unifies the language of lean thinking and supply chain in healthcare by defining metaphors in circumstances under which healthcare organizations pursue similar objectives from their supply chain management and lean programs (Schmitt, 2005). This paper also outlines a list of applications of lean for supply chain improvement in healthcare. Finally, a set of contingency factors in the field of lean supply chain in healthcare is found via the published literature. Practical implications This paper provides insights for decision-makers in the healthcare industry regarding the benefits of implementing LSCM, and it identifies contingency factors affecting the implementation of LSCM principles for healthcare. Implementing LSCM can help healthcare organizations improve the following domains: internal interaction between employees, supply chain cost management, medication distribution systems, patient safety and instrument utilization. Social implications The research shows potential synthesis of LSCM with the healthcare industry’s objectives, and, thus, the outcome of this research is likely to have positive influence on the quality and cost of healthcare services. The objectives of the healthcare industry are cost reduction and providing better service quality, and LSCM implementation could be an effective solution to help healthcare to achieve these objectives. Originality/value The prime value of this paper lies in conducting a systematic literature review using a meta-study to identify the major factors of implementing LSCM in healthcare. Only a few other studies have been published in the literature about LSCM in healthcare.

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This paper presents a dual-objective facility programming model for a green supply chain network. The main objectives of the presented model are minimizing overall expenditure and negative environmental impacts of the supply chain. This study contributes to the existing literature by incorporating uncertainty in customer demand, suppliers, production, and casting capacity. An industrial case study is also analyzed to reveal the feasibility of the proposed model and its application. A fuzzy approach which is known as TH is used to solve the suggested dualobjective model. TH approach is integration of a max-min method (LH) and modified version of Werners' approach (MW). The outcome of this study reveals that the presented model can support green supply chain network in different levels of uncertainty. In presented model, cost and negative environmental impacts derived from the supply chain network will increase of higher levels of uncertainty.

Since being environment-friendly has become more important for manufacturers, green supplier evaluation is one of the most crucial challenges for supply chain in the industry. This study aims to evaluate and choose the best green suppliers by integrating fuzzy AHP and fuzzy Copras for seven green suppliers. Fuzzy AHP is used to determine the importance of green supplier performance criteria. Because the criteria and options that are considered in this study are associated with uncertainty, the fuzzy theory is applied as one of the key tools for modeling uncertainties. In this study, a set of criteria for evaluating the green suppliers is identified. Afterwards, fuzzy Copras is employed to evaluate and choose the best green supplier. The contribution of this study lies in the integration of Copras and analytic hierarchy process techniques for green supplier evaluation. That is fuzzy Copras reveals a solution as an optimized respond when the uncertainty is a significant factor in decision-making process, this enhances the accuracy of AHP pairwise comparison. The findings of this study are beneficial for manufacturers, suppliers, and organizations which attempt to improve the supply chain network by eliminating waste.