Increasing the realism with respect to the representation of actors, decision-making, and institutions is critical to better understand the transition towards a low-carbon sustainable society since actors, decision-making, and institutions are the defining elements of transition pathways. In this paper, we explore how this can be done by conducting a model-based scenario analysis. The increasing focus on implementation and transition dynamics towards long-term objectives requires a better comprehension of what drives change and how those changes can be accelerated. We explore opportunities that arise from a deeper engagement of quantitative systems modeling with socio-technical transitions studies, initiative-based learning, and applied economics. We argue that a number of opportunities for enriching the realism in model-based scenario analysis can arise through model refinements oriented towards a more detailed approach in terms of actor heterogeneity, as well as through integration across different analytical and disciplinary approaches.


Suggested citation: De Cian, E., S. Dasgupta, A. F. Hof, M. A. E. van Sluisveld, J. Köhler, B. Pfluger, D. P. van Vuuren, (2017), ‘Actors, Decision-making, and Institutions in Quantitative System Modelling’, Nota di Lavoro 46.2017, Milano, Italy: Fondazione Eni Enrico Mattei