The impact of carbon emission costs on manufacturers' production and location decision
International Journal of Production Economics
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Wu, P., Jin, Y., Shi, Y., & Shyu, H. (2017). The impact of carbon emission costs on manufacturers' production and location decision. International Journal of Production Economics, 193 193-206. https://doi.org/10.1016/j.ijpe.2017.07.005
This paper investigates how emerging carbon emission costs may affect the joint production and location decisions for a manufacturer across the world's regions. Specifically, we develop a new theoretical model which explicitly links product demand, production costs and carbon emission levels to location decisions, and investigate the manufacturer's optimal decisions between two distinct regions. The results show that the influence of carbon emissions on manufacturers' decisions can vary greatly under different circumstances: both off-shoring and near-shoring are possible under rising carbon emission costs; manufacturers with high or low demand have different tolerance levels to the rising carbon emission costs when considering an alternative location; trade costs can change the pattern of relocation. To gain policy insights for those who pursue reducing carbon emissions, different product examples are used to calculate the critical carbon price which triggers different location choices. The results suggest that if production technology is stable, raising carbon cost itself has only limited effects on reducing total carbon emissions, especially for high-value-low-emission industries. The location shift, which is more sensitive to changes in variable carbon emissions, may lead to a significant emission reduction when completed. Additional pricing decision from the manufacturer shows no significant effect on the location decisions; however, if demand is linked directly to carbon emission footprint of the product, then it is more hopeful that a raised carbon price would reduce the carbon emissions significantly through relocation.
carbon emission, Economic Order Quantity (EOQ) model, location modelling
This research is partially supported by National Science Foundation of China (NSFC No. 71401117) for Peng Wu and by a special fund of Key Laboratory of Eco Planning & Green Building, Ministry of Education (Tsinghua University), China plus the UK Engineering and Physical Sciences Research Council (EPSRC) Centre for Smart Infrastructure and Construction (EPSRC reference E/KP000314/1) for Ying Jin.
Technology Strategy Board (920035)
External DOI: https://doi.org/10.1016/j.ijpe.2017.07.005
This record's URL: https://www.repository.cam.ac.uk/handle/1810/269023
Attribution-NonCommercial-NoDerivatives 4.0 International
Licence URL: http://creativecommons.org/licenses/by-nc-nd/4.0/
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