A stochastic model for analyzing the combined effect of demand uncertainty and carbon tax within the context of Green Supply Chain Design
Résumé
Carbon emission legislations are implemented for the purpose of pushing companies to pay more attention to their carbon emissions beyond Supply Chain (SC) activities and encouraging them to invest in cleaner technologies. Within this context, the present work studies the combined effect of carbon legislation and demand uncertainty on one of the strategic decisions related to green supply chain design (GSCD): the selection of production technologies. We consider a stochastic demand and we develop a stochastic newsvendor-based mathematical model for the problem of production planning and technology selection under carbon tax regulation. The majority of works that have studied this problem have developed deterministic models and studied the trade-off between emission reduction and cost increase under carbon legislations. Through a numerical example, we compare the economic and environmental performances of both deterministic and stochastic models. With this example, we show how the carbon legislations tend to push companies to invest in cleaner production technologies when demand uncertainty is considered. The obtained results also illustrate the robustness of the stochastic model to demand uncertainty over the deterministic model.