Lessons for model use in transition research: A survey and comparison with other research areas

• Published in: Environmental innovation and societal transitions Vol. 15; pp. 194 - 210
• Main Authors: Halbe, J., Reusser, D.E., Holtz, G., Haasnoot, M., Stosius, A., Avenhaus, W., Kwakkel, J.H.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2015
• Subjects: Model design; Model uses; Model validation; Modeling protocols; Transition modeling; Model uses; Transition modeling; Modeling protocols; Model design; Model validation
• ISSN: 2210-4224; 2210-4232
• DOI: 10.1016/j.eist.2014.10.001

•A literature survey of model uses in transition research and related research areas is conducted.•Relevant modeling experiences in related research areas are identified and compared.•A shared conceptual framework and pattern-oriented modeling can support model design and validation.•Advanced sensitivity analysis and shared modeling protocols can enhance quality and comparison of model studies.•Participatory modeling needs to be embedded in a broader process, which transition management might provide. The use of models to study the dynamics of transitions is challenging because of several aspects of transitions, notably complexity, multi-domain and multi-level interactions. These challenges are shared by other research areas that extensively make use of models. In this article we survey experiences and methodological approaches developed in the research areas of social-ecological modeling, integrated assessment, and environmental modeling, and derive lessons to be learnt for model use in transition studies. In order to account for specific challenges associated with different kinds of model applications we classify models according to their uses: for understanding transitions, for providing case-specific policy advice, and for facilitating stakeholder processes. The assessment reveals promising research directions for transition modeling, such as model-to-model analysis, pattern-oriented modeling, advanced sensitivity analysis, development of a shared conceptual framework, and use of modeling protocols.