Enhancing Circular Economy Decision-Making at Vehicle End-of-Life: Industry-Based Verification of Requirements for a Data-Driven Decision Support System

The transition towards a circular automotive industry requires data-driven decision-making at the end-of-life to support the selection of appropriate circular economy strategies for vehicle components. While emerging regulations, such as the End-of-Life Vehicles Regulation and the Digital Product Passport, are expected to increase the availability of lifecycle data, derived and industry-validated requirements for corresponding decision support systems are still lacking. This paper presents the industry-based verification of the requirements for a data-driven Circular Economy Assistant supporting end-of-life decision-making in the automotive industry. The study follows the Design Research Methodology proposed by Blessing and Chakrabarti. Based on a reference model, key factors, success criteria and an intended impact model are developed to derive the core functionalities and requirements of the Circular Economy Assistant. The requirements are verified through a Microsoft Forms questionnaire involving industrial stakeholders from different phases of the automotive product lifecycle. Stakeholders are identified using a combination of question-method matrix analysis and stakeholder mapping. The results confirm the relevance of the derived requirements and demonstrate that their verification requires complementary expertise from stakeholders across the entire product lifecycle. Consequently, this work provides a methodologically sound and industry-validated foundation for the development of data-driven decision support systems for end-of-life decision-making.