Author ORCID Identifier
Linda Sagnier Eckert: https://orcid.org/0009-0007-7927-0052
Ann-Sophie Finner: https://orcid.org/0000-0001-8421-2876
Daniel Heinz: https://orcid.org/0000-0003-0321-0989
Gerhard Satzger: https://orcid.org/0000-0001-8731-654X
Abstract
The automotive industry faces environmental challenges due to fossil fuels reliance and linear production models. Transitioning to a circular economy (CE) is essential for reducing emissions and achieving sustainability. This study uses backcasting to envision a circular automotive industry by 2050, aligned with the European Green Deal’s carbon neutrality objectives. Our envisioned future leverages digital technologies like AI, digital twins, and product passports to enhance data sharing, traceability, and decision making across the supply chain. We examine how these technologies improve lifecycle management of electric vehicles, enhance circularity in design and manufacturing, and ensure transparency from production to end-of-life. While these technologies extend product lifecycles and minimize waste, transitioning towards circularity presents challenges such as data sharing, emphasizing the need for collaborative industry platforms. By engaging key stakeholders, we developed a pathway from the current state to the envisioned circular future. Focusing on CE principles, the study seeks to foster a systemic shift towards circularity, bridging the gap between information systems and CE research. Strategic policy interventions and cooperative frameworks are recommended to enable the transition. The paper contributes insights into digitalization’s impact on CE, providing actionable strategies for industry stakeholders aiming to implement sustainable practices amid global resource constraints.
Recommended Citation
Sagnier, L., Finner, A., Heinz, D., & Satzger, G. (In press). Backcasting the Future of the Automotive Industry: Leveraging Digital Technologies for the Circular Economy. Communications of the Association for Information Systems, 58, pp-pp. Retrieved from https://aisel.aisnet.org/cais/vol58/iss1/30
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