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Actors, decision-making, and institutions in quantitative system modelling

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.
- Eni (Italy) Italy
- Ca Foscari University of Venice Italy
- RFF-CMCC European Institute on Economics and the Environment Italy
- European Institute United States
- Netherlands Environmental Assessment Agency Netherlands
ABM, Q5, Q4, Q00, Institutions, Modelling, Scenarios, Management of Technology and Innovation, Taverne, Transition Pathways, Business and International Management, Transition pathways, Applied Psychology, Research Methods/ Statistical Methods, O10, Governance, P16, IAM, Actors, C63, ABM; Actors; Governance; IAM; Institutions; Modelling; Scenarios; Transition pathways; Business and International Management; Applied Psychology; Management of Technology and Innovation, ddc: ddc:330
ABM, Q5, Q4, Q00, Institutions, Modelling, Scenarios, Management of Technology and Innovation, Taverne, Transition Pathways, Business and International Management, Transition pathways, Applied Psychology, Research Methods/ Statistical Methods, O10, Governance, P16, IAM, Actors, C63, ABM; Actors; Governance; IAM; Institutions; Modelling; Scenarios; Transition pathways; Business and International Management; Applied Psychology; Management of Technology and Innovation, ddc: ddc:330
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