The Design of a Sustainable Location-Routing-Inventory Model Considering Consumer Environmental Behavior
Our aim is to design a sustainable supply chain (SSC) network, which takes into consideration consumer environmental behaviors (CEBs). CEBs not only affect consumers’ demand for products with low carbon emissions, they also affect their willingness to pay premium prices for products with low carbon...
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| Published in | Sustainability Vol. 8; no. 3; p. 211 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
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MDPI AG
29.02.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2071-1050 2071-1050 |
| DOI | 10.3390/su8030211 |
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| Abstract | Our aim is to design a sustainable supply chain (SSC) network, which takes into consideration consumer environmental behaviors (CEBs). CEBs not only affect consumers’ demand for products with low carbon emissions, they also affect their willingness to pay premium prices for products with low carbon emissions. We incorporate CEBs into the SSC network model involving location, routing and inventory. Firstly, a multi-objective optimization model comprised of both the costs and the carbon emissions of a joint location-routing-inventory model is proposed and solved, using a multi-objective particle swarm optimization (MOPSO) algorithm. Then, a revenue function including CEBs is presented on the basis of a Pareto set of the trade-off between costs and carbon emissions. A computational experiment and sensitivity analysis are conducted, employing data from the China National Petroleum Corporation (CNPC). The results clearly indicate that our research can be applied to actual supply chain operations. In addition, some practical managerial insights for enterprises are offered. |
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| AbstractList | Our aim is to design a sustainable supply chain (SSC) network, which takes into consideration consumer environmental behaviors (CEBs). CEBs not only affect consumers' demand for products with low carbon emissions, they also affect their willingness to pay premium prices for products with low carbon emissions. We incorporate CEBs into the SSC network model involving location, routing and inventory. Firstly, a multi-objective optimization model comprised of both the costs and the carbon emissions of a joint location-routing-inventory model is proposed and solved, using a multi-objective particle swarm optimization (MOPSO) algorithm. Then, a revenue function including CEBs is presented on the basis of a Pareto set of the trade-off between costs and carbon emissions. A computational experiment and sensitivity analysis are conducted, employing data from the China National Petroleum Corporation (CNPC). The results clearly indicate that our research can be applied to actual supply chain operations. In addition, some practical managerial insights for enterprises are offered. |
| Author | Jiang, Liwen Ji, Shoufeng Tang, Jinhuan |
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| SubjectTerms | algorithms Behavior business enterprises Carbon China Consumers Costs Emission standards emissions Emissions trading Environmental tax income inventories Inventory petroleum prices Sensitivity analysis supply chain Supply chains Sustainability system optimization willingness to pay |
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