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| Source | Subject | Findings/recommendations |
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| [27] | The suitability of a range of cross-disciplinary socio-technological modelling approaches in adequately capturing key features pertinent to the dynamics of sustainability transitions, for example, energy-economy models, integrated assessment models, evolutionary economic models, complex system models, agent-based models, system dynamic models, and socioecological system models | All modelling types can tackle several aspects of sustainability research, but most fare poorly in dealing with fundamental and deep uncertainty and in representing either qualitative or quantitative changes in complex social system states and structures |
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| [26] | A complexity-based framework for modelling complex systems’ core properties, based on a rigorous interpretation of complexity theory. It goes beyond modelling deterministic mechanisms that underpin complex dynamic system behaviour | Requisite elements of a complexity-based modelling approach should include integrative and probabilistic methods that can accommodate human-environment system interactions and their uncertainties and modelling techniques that are participatory-based and adaptive to real-world changes in the system structures under scrutiny |
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| [28] | A narrative within the frame of the economic modelling of low-carbon transitions. Equilibrium (under constrained optimisation) economic models that typically dominate the economic domain are less successful at dealing with real-world complexities. Any observed deviations from a theoretically assumed optimal state of equilibrium are treated as distortions to the economy, implying most policy action is, by its nature, welfare decreasing (see also [29]) | Distinguishing between equilibrium and nonequilibrium economic modelling would be a useful criterion for not only understanding what drives model outputs but also assessing the models’ versatility in capturing the complex dynamics of energy-environment-economy interactions |
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| [30] | A broad discussion of sustainability modelling is classified into five groups: quantitative, pictorial, conceptual, physical, and standardising models. Following [31], from a policy-making perspective the most popular models are macro-econometric, economic (computable general) equilibrium models, optimisation models, system dynamic models, Bayesian network models, and multi-agent simulation models | Although conventional economic models have been particularly active in this area, “they have been poorly equipped to accommodate a holistic perspective, address the local-global perspective or acknowledge the need for stakeholders’ participation” ([30], p. 1401) |
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| [32] | A review of different types of formal or quantitative models tackling sustainability issues (agent-based, system dynamics, discrete event simulation) and the recent trend in hybrid simulation models | Researchers using simulation models must present their objectives clearly, state their assumptions explicitly, declare underlying the limitations of their studies, and articulate valuable insights gained |
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