Navigating low-carbon transition pathways of the mobility sector: an inquiry into experts’ mental models
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Contributors
Abstract
Finding viable pathways to a low-carbon transition of the mobility sector is central to the United Nations sustainable Development Goals. Mobility-transition research could benefit from exploring experts’ mental models on how to facilitate this transition. experts serve as intermediaries, acting as brokers between more institutionalized actors such as technology adopters and incumbents. against the backdrop of sustainability-transitions research, this
article examines the mental models of sustainable mobility experts, which shape potential pathways to the mobility transition. We employ the innovative, exploratory modeling method GABEK®, which allows for a mapping of a shared mental model of experts. the results can be input into scenario-analyses methodologies such as “backcasting,” which enables the alignment
of long-term sustainability visions on mobility with feasible short-term solutions. thus far, the method has not been employed in any comprehensive approach to navigating pathways to a low-carbon mobility transition.
article examines the mental models of sustainable mobility experts, which shape potential pathways to the mobility transition. We employ the innovative, exploratory modeling method GABEK®, which allows for a mapping of a shared mental model of experts. the results can be input into scenario-analyses methodologies such as “backcasting,” which enables the alignment
of long-term sustainability visions on mobility with feasible short-term solutions. thus far, the method has not been employed in any comprehensive approach to navigating pathways to a low-carbon mobility transition.
Details
Original language | English |
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Article number | 2478693 |
Number of pages | 21 |
Journal | Sustainability : Science, Practice and Policy |
Volume | 21 |
Issue number | 1 |
Publication status | Published - 2025 |
Peer-reviewed | Yes |
External IDs
ORCID | /0000-0002-8792-5107/work/182333612 |
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ORCID | /0000-0003-2935-303X/work/182334874 |