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Remanufacture unlocks the residual values in used products by prolonging the life cycles, whereas the inherent uncertainty in reverse logistics presents a significant challenge for operations management and brings resources into waste. To reduce the negative externality caused by uncertainty in reverse logistics, this study makes stochastic analysis of the market uncertainty and formulates an ordering strategy for environmental sustainability to minimize the carbon emissions. Further, considering the externality of environmental pollution can be internalized into the operating cost by carbon trading mechanism, we then investigate the economic behavior under the fluctuation of carbon price. Through polynomial regression, the model forecasts the carbon price in Beijing carbon trading center and quantifies the impacts of price variation on the decision process, then from which devises a balanced and sustainable EOQ strategy to optimize the economic efficiency at lower resource input. Through empirical examples that carried out with different forecasting methods, the results testify the validity and robustness of the model. • An EOQ model considering uncertainties in market demand and carbon price. • Investigate the economic behavior of firms under carbon trading mechanism. • Balanced ordering strategy considering both sustainability and efficiency. • Quantify the impacts of carbon price fluctuation on ordering decisions. • Case study of block pallet and stringer pallet remanufacturing. [ABSTRACT FROM AUTHOR]

The performance of a green supply chain shows particularity and complexity due to its multiple network features. This study aiming at digging out the logical relationship between network embedding and green supply chain performance in the context of agglomeration scenarios. In this study, taking Chinese eco-industrial park as the sample, the logic and mechanism of multiple network embedding on the performance of the green supply chain under the agglomeration scenario are empirically investigated by mediation and moderation as well as simulation method. As a result, the three dimensions of network embedding: relationship embedding, structure embedding and knowledge embedding, all significantly promote the integration of green knowledge, and green knowledge integration plays a mediating effect between multiple network embedding and green supply chain performance. As a whole, the agglomeration scenario plays a positive moderation role in logic chain of "multiple network embedding—knowledge integration—green performance" in green supply chain; to be specific, the economic performance of the green supply chain shows a trend of first improving and then stabilizing, while the environmental performance shows a "U" pattern. In conclusion, it is crucial to embed platform for knowledge integration and interaction into the industrial agglomeration and explore cooperation network of the green supply chain. By integrating the internal and external knowledge resources of the agglomeration through multiple network embedding, we can effectively and efficiently realize sustainable development and cleaner production in a green supply chain. Image 1 • Network embedding affects green supply chain performance through knowledge integration. • Internal and external knowledge integration positively affects performance. • Aggregation scenario plays a positive moderating effect in logical chain. • Comprehensive use of mediation and moderation analysis and simulation. [ABSTRACT FROM AUTHOR]

Uncertainties in acquisition, processing, market, and other stages of the closed-loop supply chain have greatly added to the complexity of remanufacturing and have reduced process efficiency, impeding the sustainable development of industries and circular economy. Recently, an increasing number of studies have been published that focus on the uncertainty analysis of closed-loop supply chain. Thus, this article aims to examine previous research on the uncertainties that are inherent characteristics of a closed-loop supply chain, and to provide constructive prospects for future research. Based on these aims, we selected 302 papers published in the "Web of Science" core database from 2004 to 2018. We analyze the causes of uncertainties at different stages, and identify appropriate methods for quantifying the impacts of the uncertainties on production processes. As a result, from a macro level, and based on a visualization method, we present the themes, development, and evolution of popular research topics in the previous literature. From a micro level, and based on the methodology, we conduct a systematic evaluation of uncertainty factors, methods, and solutions. Finally, we clarify a breakthrough point for future research. By optimizing the impacts of uncertainties on closed-loop supply chain, we can effectively and efficiently realize sustainable development and cleaner production in a closed-loop supply chain. [ABSTRACT FROM AUTHOR]