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Research . 2017
Data sources: EconStor
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Technological Forecasting and Social Change
Article . 2020 . Peer-reviewed
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Article . 2017 . Peer-reviewed
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https://dx.doi.org/10.22004/ag...
Other literature type . 2017
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Research . 2017
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http://dx.doi.org/10.1016/j.te...
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Actors, decision-making, and institutions in quantitative system modelling

Authors: Jonathan Köhler; Detlef P. van Vuuren; Detlef P. van Vuuren; Enrica De Cian; Enrica De Cian; Enrica De Cian; Benjamin Pfluger; +7 Authors

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

Abstract

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.

Countries
Netherlands, Italy
Keywords

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

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    41
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
41
Top 10%
Top 10%
Top 10%
Green
bronze