Reverse engineering of stakeholder preferences – A multi-criteria assessment of the German passenger car sector

  • Germany is a frontrunner in setting frameworks for the transition to a low-carbon system. The mobility sector plays a significant role in this shift, affecting different people and groups on multiple levels. Without acceptance from these stakeholders, emission targets are out of reach. This research analyzes how the heterogeneous preferences of various stakeholders align with the transformation of the mobility sector, looking at the extent to which the German transformation paths are supported and where stakeholders are located. Under the research objective of comparing stakeholders' preferences to identify which car segments require additional support for a successful climate transition, a status quo of stakeholders and car performance criteria is the foundation for the analysis. Stakeholders' hidden preferences hinder the derivation of criteria weightings from stakeholders; therefore, a ranking from observed preferences is used. This study's inverse multi-criteria decision analysis means that weightings can be predicted and used together with a recalibrated performance matrix to explore future preferences toward car segments. Results show that stakeholders prefer medium-sized cars, with the trend pointing towards the increased potential for alternative propulsion technologies and electrified vehicles. These insights can guide the improved targeting of policy supporting the energy and mobility transformation. Additionally, the method proposed in this work can fully handle subjective approaches while incorporating a priori information. A software implementation of the proposed method completes this work and is made publicly available.

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Metadaten
Author:Imke Rhoden, Christopher Stephen Ball, Matthias GrajewskiORCiD, Wilhelm Kuckshinrich
DOI:https://doi.org/10.1016/j.rser.2023.113352
ISSN:1364-0321
Parent Title (English):Renewable and Sustainable Energy Reviews
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Article
Language:English
Year of Completion:2023
Date of first Publication:2023/05/16
Date of the Publication (Server):2023/05/22
Tag:E-Mobility; Mobility transition; Multi-criteria decision analysis; Preference assessment; Regionalization
Volume:181
Issue:July 2023
First Page:Article number: 113352
Link:https://doi.org/10.1016/j.rser.2023.113352
Zugriffsart:bezahl
Institutes:FH Aachen / Fachbereich Medizintechnik und Technomathematik
collections:Verlag / Elsevier
Licence (German):License LogoUrheberrechtlich geschützt