Stein WallaceSchots, ManonManonSchots2025-05-142025-05-142025-05-142022https://hdl.handle.net/2078.2/27272Climate change is affecting the way business is being done around the world. Companies need to learn to adapt to its consequences and operate in a sustainable way if they wish to perdure on the market. In order to mitigate climate change, Carbon Pricing Instruments are being implemented across the world and set a price on carbon emissions as to incentivize companies to reduce their pollution level. The cost of carbon is becoming an increasingly important share of companies’ costs, thereby forcing them to invest in emissions abatement practices in order to maintain their profitability. The aim of this thesis is to, firstly, gain a solid understanding of the largest emissions abatement mechanisms in place today and to analyze their evolution over the past decades. Then, cost-minimization models outlining the supply chain of four different companies are constructed with the objective to identify how they should invest to prepare for the likely evolution of the carbon market, depending on the degree of uncertainty of this evolution and the level of risk aversion that they face. The carbon prices are forecasted based on insight from the literature review and historical data and are used in the models along with their probabilities of occurrence as to include the uncertainty of their evolution in the decision-making process. The results do not allow for conclusions to be drawn on the differences in reactions of companies confronted to varying levels of risk aversion or degrees of uncertainty of the evolution of the carbon market. However, it can be concluded that the investment decisions depend on the coverage of the carbon pricing instrument in place and that a long-term view should be adopted in order for these investments to truly be profitable, both in terms of operational and carbon costs reductions.carbon pricing instrumentStrategic emissions reductions in the supply chain based on the evolution of carbon regulations. A cost-minimization model under uncertainties.text::thesis::master thesisthesis:35067