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

Geert J. Groeneveld, B. Müller, C.M. Buchmann, Gunnar Dressler, C. Guo, N. Hase, F. Hoffmann, F. John, C. Klassert, T. Lauf, V. Liebelt, H. Nolzen, N. Pannicke, J. Schulze, H. Weise, N. Schwarz

Research output: Contribution to journalArticleAcademicpeer-review

145 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)39-48
Number of pages10
JournalEnvironmental modelling & software
Publication statusPublished - 1 Jan 2017


  • Adaptation
  • Heterogeneity
  • Human behaviour
  • Learning
  • Multi-agent systems
  • ODD+D
  • Uncertainty


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