Development of a Methodological Tool for Translating and Tracking Product-Level Sustainability Targets to the Component Level in an OEM Supplier Awarding Process.

The decarbonization of automotive value chains increasingly depends on whether higher-level climate targets can be translated into operational decision contexts, yet existing frameworks do not provide an operational mechanism for converting fleet-level Scope 3 upstream carbon dioxide equivalent (CO2-eq) objectives into component-level target values for supplier awarding decisions. The objective of this thesis is therefore to develop and validate a material-based methodological approach that translates fleet-level Scope 3 upstream CO2-eq reduction targets into component-level target values for supplier awarding decisions and progress tracking in an automotive original equipment manufacturer (OEM) context. Methodologically, the study follows a design science-inspired research approach in a single-company industrial application context and combines conceptual model development with data-based component analysis, prototype implementation and benchmark-based validation against existing fleet projection logic. The developed approach uses generic components, material compositions and material-specific product carbon footprint (PCF) factors to derive component-level target values and embeds them in a prototypical Excel-based decision-support tool that links target PCFs, actual PCFs and award volumes. This enables award-level target-to-actual comparison, deviation identification and dashboard-based monitoring of progress toward fleet-level CO2-eq objectives within the supplier awarding process. The results show that the target-allocation process is methodologically implementable, that the developed material-based logic reproduces the relevant PCF structures with sufficient consistency and accuracy for target steering and that benchmark validation against the existing fleet projection logic results in an overall deviation of 16%. The data analysis further indicates that PCF contributions differ substantially across drivetrains and organizational units, implying that component prioritization must balan ce PCF relevance with operational manageability. An illustrative application of the developed approach further shows how its results can be interpreted at award, cumulative and vehicle level. Within this illustrative setting, all exemplary awards considered indicate lower projected upstream PCF values than the respective baseline values. At the same time, the prototype is limited by current data structures and system interfaces, particularly the incompatibility between long-term planning data and the award list, incomplete award information and the need to calculate actual PCF values outside the tool.