How to conduct more systematic reviews of agent-based models and foster theory development - Taking stock and looking ahead
AuthorAchter, Sebastian; Borit, Melania; Cottineau, Clémentine; Polhill, J. Gareth; Radchuk, Viktoriia; Meyer, Matthias
Agent-based models (ABMs) are increasingly utilized in ecology and related fields, yet concerns persist regarding the lack of consideration for lessons learned from previous models. This study explores the potential of systematically conducted ABM reviews to contribute to cumulative science and theory development by synthesizing individual ABM findings more effectively. We are conducting a meta-review of ABM reviews to assess current practices, compare them to systematic literature review (SLR) literature recommendations, and evaluate their engagement with theory and theory development. Our analysis of the ecology and social science sample reveals that many reviews are not conducted systematically and lack transparency. The analysis step of SLRs holds significant potential to advance theory development. Reviews primarily focus on model design, while other avenues of theory development receive less attention. Our findings suggest ways to improve current practices and may guide future ABM reviews via benchmarks for methodological decisions and dimensions for advancing theory development.
CitationAchter S, Borit M, Cottineau, Polhill JG, Radchuk V, Meyer M. How to conduct more systematic reviews of agent-based models and foster theory development - Taking stock and looking ahead. Environmental Modelling & Software. 2023;173
MetadataShow full item record
Copyright 2023 The Author(s)