Theoretical foundations of human decision-making in agent-based land use models - A review

By Jürgen Groeneveld, Birgit Müller, Carsten M. Buchmann, G. Dressler, C. Guo, N. Hase, Falk Hoffmann, F. John, Christian Klassert, T. Lauf and 6 more. Environmental Modelling & Software, 2017

309 citations recorded by the source corpus.

Recent reviews stated that the complex and context-dependent nature of human decision-making resulted in ad-hoc representations of human decision in agent-based land use change models (LUCC ABMs) and that these representations are often not explicitly grounded in theory. However, a systematic survey on the characteristics (e.g. uncertainty, adaptation, learning, interactions and heterogeneities of agents) of representing human decision-making in LUCC ABMs is missing. Therefore, the aim of this study is to inform this debate by reviewing 134 LUCC ABM papers. We show that most human decision sub-models are not explicitly based on a specific theory and if so they are mostly based on economic theories, such as the rational actor, and mainly ignoring other relevant disciplines. Consolidating and enlarging the theoretical basis for modelling human decision-making may be achieved by using a structural framework for modellers, re-using published decision models, learning from other disciplines and fostering collaboration with social scientists. Review on human decisions in agent-based models of land use change.Most human decision models are not based on theory.Used theories are mainly from economics and not from psychology.A framework to guide modellers how to implement human decision is needed.

Subfields: Economics and Econometrics, Global and Planetary Change, Transportation

View Paper: https://www.semanticscholar.org/paper/212b5d7ea7cc50642454d353d68d90b22a7605b9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. T. Konc
2. Tatiana Filatova
3. Daniel Müller
4. Ivan Savin
5. J. Bergh
6. K. Erb
7. Joël Foramitti
8. Eric F. Lambin

In Global and Planetary Change

1. Patrick Meyfroidt
2. Daniel Müller
3. Tobias Kuemmerle
4. R. R. Chowdhury
5. Peter H. Verburg
6. Peter Messerli
7. K. Erb
8. Eric F. Lambin

In Transportation

1. J. Bergh
2. Erle C. Ellis

Citations in the corpus

• Agent Based Modelling and Simulation tools: A review of the state-of-art software (2017, background): “A precise review of ABMS for the effective land use has been conducted in [41], thereby pinpointing the decision-making characteristics (e.”
• A review of agent‐based modeling of climate‐energy policy (2020, methodology): “…on climate adaptation or land-use issues (Arneth, Brown, & Rounsevell, 2014; Berger & Troost, 2014; Brown, Alexander, Holzhauer, & Rounsevell, 2017; Groeneveld et al., 2017), specific aspects of energy demand, energy efficiency or travel choice (e.g., Hansen, Liu, & Morrison, 2019; Hesselink &…”
• Middle-range theories of land system change (2018, background): “change, and social norms related to land use (Meyfroidt, 2013; Schlüter et al., 2017; Groeneveld et al., 2017; van Duinen et al., 2015).”