Environmental concerns have increased within the last decades. Supply chain activities have contributed to these global environmental problems. Namely, the production, transport, storage and consumption of goods have caused harm to the environment. Companies are therefore pushed to rethink their existing supply chain (SC) to contribute to the environmental challenges. Companies have to balance business performance measures with environmental performance measures. This issue is part of the green supply chain management (GSCM) field, which deals with supply chain management, where environmental considerations are taken into account [Sarkis et al., 2011]. One of the main environmental considerations within GSCM of companies is decreasing the supply chain’s emissions. From the literature review, a knowledge gap is identified where further research should focus on the impact of specifically supply chain design/coordination (SCD/C) decisions on emissions in global supply chains [Chelly et al., 2019]. These decisions include routing decisions, transport mode selection and facility location, to name a few. The consumer goods industry is an industry lacking such research [Ansari and Kant, 2017]. Next to emissions, the business performance criteria costs and transport times are included in the research question. Therefore, the main research question is: what impact do supply chain design and coordination (SCD/C) decisions in a global supply chain have on the supply chain’s emissions, costs and transport times? This question is answered by building a quantitative emission model of a part of the supply chain of L, a company that creates loyalty programmes for international retailers. In this way, a case-study methodology is applied in this research. The designed model is applied to the supply chain of L, but the model can also be applied to a different supply chain. Therefore the model can be seen as a tool that a company can use to understand the impact of SCD/C decisions on emissions, costs and time. After first defining a theoretical conceptual model and a case-specific conceptual model, the scope of the research was set up. Figure 0.1 shows a high-level visualisation of the emissions and criteria (green) included in the model and the parameters (blue) and variables (white) that influence these criteria. Based on this diagram, the model is created in the tool Excel.