Abstract
Complex Adaptive Systems (CAS) is an interdisciplinary and dynamic modelling approach for the study of today’s global challenges. It is used for the explanation, description, and prediction of behaviours of system components and the system at large. To understand and assess the quality of research in which CAS models are designed and used, a thorough understanding of the meanings of ‘validity’ from social science research methodology and ‘validation’ from simulation modelling is needed. In this paper, we first describe the modelling process. Then, we analyse the concepts ‘validity’ and ‘validation’ as used in a set of research methodology textbooks and a set of modelling textbooks. We present one single map that integrates validity as characteristic of the model input, the modelling process, model validation, and the validity of the model built. The map is illustrated by means of one example. The terminology proposed in the map allows to describe and distinguish between the validity of primary research used for input in the model, how the quality of the modelling depends on structural and behavioural validation, and, how the assessment of the validity of the model is informed by these types of validation plus research with independent data.
Highlights
Many of today’s global issues such as climate change, food security and social injustice, call for joint input of researchers from different scientific disciplines
The keyword validation referred to the evaluation of professional development programmes (B6). This analysis yielded three general classes of validity: measurement validity relating to the data obtained, internal validity relating to claims on relationships, and generalizability of research results
We identified three basic validities of primary studies from research methodology and two types of validation from computer modelling
Summary
Many of today’s global issues such as climate change, food security and social injustice, call for joint input of researchers from different scientific disciplines The complexity of these issues has promoted the development of interdisciplinary research and. Modelling is an important tool in the study of complex systems at the system level, and for the social sciences that study social actors and support decision makers. Modelling a CAS may serve many purposes but three are unambiguously related to an empirical reality and will be considered in this paper: explanation, description, and prediction of new (i.e. not yet known) behaviours (Edmonds et al 2019) For each of these purposes the modelling of a CAS builds on, and contributes to, different disciplines including the social sciences.
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