Decision support systems for a resilient and sustainable closed loop supply chain under risk: A systematic review and future research directions

Abstract

Recently, designing resilient and sustainable closed-loop supply chain (CLSC) has been an emerging agenda of scholars. The number of publications regarding sustainable CLSC under risk has grown significantly in the last decade. However, the extant literature on sustainable CLSC is scattered in various research streams. The aim of this study is to synthesize literature and identify gaps and cutting-edge research agendas by conducting a PRISMA based comprehensive review on decision support systems for a resilient and sustainable CLSC under risk. 185 articles were selected for thorough content analysis. We categorize these articles into five clusters. The results of content analysis reveal that the single uncertain parameter is the most frequently considered uncertainty category. The most popular uncertainty modeling technique employed to combat sustainable CLSC problems under risk is stochastic programming. It also shows that the most frequently considered decision problem and level are facility location-flow allocation problems and simultaneous strategic and tactical decisions, respectively. Collection-recycle is the most frequently employed waste management technique. Moreover, it illustrates that carbon policies have played a crucial role in reducing carbon emissions. Similarly, backup supplier is the most frequently employed resilient strategy. The study reveals that despite the insight for designing resilient and sustainable CLSC has grown fast, its application to reduce waste, disruptive risks, and environmental pollution and thereby bring circular economy sustainably has rarely been explored in the extant literature. The study provides substantial contributions for both scholars and practitioners and identifies breakthrough future research avenues.