Agent decision-making

The Elephant in the Room - Enabling the justification of decision model fit in social-ecological models

Journal Article (2023)
Authors

Nanda Wijermans (Stockholm Resilience Centre, Institute For Future Studies)

G. Scholz (TU Delft - Energy and Industry)

Émile J.L. Chappin (TU Delft - Energy and Industry)

Alison Heppenstall (University Glasgow)

T. Filatova (TU Delft - Policy Analysis)

Gary Polhill (The James Hutton Institute)

Christina Semeniuk (University of Windsor)

Frithjof Stöppler (Stockholm University)

Research Group
Energy and Industry
Copyright
© 2023 Nanda Wijermans, G. Scholz, E.J.L. Chappin, Alison Heppenstall, T. Filatova, J. Gareth Polhill, Christina Semeniuk, Frithjof Stöppler
To reference this document use:
https://doi.org/10.1016/j.envsoft.2023.105850
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 Nanda Wijermans, G. Scholz, E.J.L. Chappin, Alison Heppenstall, T. Filatova, J. Gareth Polhill, Christina Semeniuk, Frithjof Stöppler
Research Group
Energy and Industry
Volume number
170
DOI:
https://doi.org/10.1016/j.envsoft.2023.105850
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Abstract

Agent-based models are particularly suitable to reflect the dynamics of humans, nature, and their interactions, making them a crucial approach for understanding social-ecological systems. The formalisations of human decision-making are central to resulting model behaviours. Despite awareness of the complexity of human behaviour in social-ecological systems research, scholars tend to represent human decision-makers as simplified, perfectly informed rational optimisers, without explicitly considering the fit with decision context. Key reasons are a lacking uptake of social theories and insights. To advance, we need a practice of reflecting, sharing, and inquiring on the justification of the decision model fit with its context. This paper stimulates this practice by 1) supporting the justification of decision model (DM) fit by describing the DM landscape and providing guiding questions; and 2) by supporting researchers in considering alternative DMs through a survey-based impression of modeller practices, and through highlighting DM frontiers as inspiration for future research.