Recycling Common Materials: Effectiveness, Optimal Decisions, and Coordination Mechanisms. Cui, H. & Sošić, G. European Journal of Operational Research, November, 2018.
Recycling Common Materials: Effectiveness, Optimal Decisions, and Coordination Mechanisms [link]Paper  doi  abstract   bibtex   
A growing amount of municipal solid waste (MSW) is generated worldwide, and common materials (paper, plastic, metals, and glass), which account for more than half of MSW, exhibit low recovery rates. In this paper, we aim to investigate some key questions about recycling across three dimensions: greenhouse gas emissions, operational costs, and aggregate costs (social costs of emissions plus operational costs.) First, we build supply chain models for cradle-to-grave and cradle-to-cradle supply chains to derive an analytical condition for recycling effectiveness, and use U.S. emissions and cost data to empirically validate that recycling is effective in reducing emissions for all the abovementioned materials. Furthermore, our analysis shows that recycling is effective for all materials, with the exception of glass, with respect to both operational and aggregate costs. Second, we study optimal recycling decisions in terms of collection and yield rates in a socially optimal case, as well as in scenarios in which recycling decisions are made by a local government, a product manufacturer, and an independent recycling firm. Unlike some of existing findings, we show that there are instances in which a product manufacturer or an independent firm might be the best choice for organizing recycling operations. Finally, we discuss and analyze incentives that a social planner should offer to recyclers to bring their efforts closer to the socially optimal choice. We obtain a novel result, which shows that a deposit/refund scheme implemented by a social planner with a refund to local governments might lead to a socially optimal collection rate.
@article{cui_recycling_2018,
	title = {Recycling {Common} {Materials}: {Effectiveness}, {Optimal} {Decisions}, and {Coordination} {Mechanisms}},
	issn = {0377-2217},
	shorttitle = {Recycling {Common} {Materials}},
	url = {http://www.sciencedirect.com/science/article/pii/S0377221718309354},
	doi = {10.1016/j.ejor.2018.11.010},
	abstract = {A growing amount of municipal solid waste (MSW) is generated worldwide, and common materials (paper, plastic, metals, and glass), which account for more than half of MSW, exhibit low recovery rates. In this paper, we aim to investigate some key questions about recycling across three dimensions: greenhouse gas emissions, operational costs, and aggregate costs (social costs of emissions plus operational costs.) First, we build supply chain models for cradle-to-grave and cradle-to-cradle supply chains to derive an analytical condition for recycling effectiveness, and use U.S. emissions and cost data to empirically validate that recycling is effective in reducing emissions for all the abovementioned materials. Furthermore, our analysis shows that recycling is effective for all materials, with the exception of glass, with respect to both operational and aggregate costs. Second, we study optimal recycling decisions in terms of collection and yield rates in a socially optimal case, as well as in scenarios in which recycling decisions are made by a local government, a product manufacturer, and an independent recycling firm. Unlike some of existing findings, we show that there are instances in which a product manufacturer or an independent firm might be the best choice for organizing recycling operations. Finally, we discuss and analyze incentives that a social planner should offer to recyclers to bring their efforts closer to the socially optimal choice. We obtain a novel result, which shows that a deposit/refund scheme implemented by a social planner with a refund to local governments might lead to a socially optimal collection rate.},
	language = {en},
	urldate = {2018-11-19},
	journal = {European Journal of Operational Research},
	author = {Cui, Hailong and Sošić, Greys},
	month = nov,
	year = {2018}
}

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