2006
DOI: 10.1007/s10588-006-8873-y
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Validation and verification of social processes within agent-based computational organization models

Abstract: The use of simulation modeling in computational analysis of organizations is becoming a prominent approach in social science research. However, relying on simulations to gain intuition about social phenomena has significant implications. While simulations may give rise to interesting macro-level phenomena, and sometimes even mimic empirical data, the underlying micro and macro level processes may be far from realistic. Yet, this realism may be important to infer results that are relevant to existing theories o… Show more

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Cited by 61 publications
(30 citation statements)
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“…If the chosen micro-level structure is able to generate the observed macro phenomena, the model provides a potential explanation for these phenomena. Models should base upon a sound theoretical foundation and use empirical data and expert knowledge to substantiate the model's micro-foundation (Boero and Squazzoni, 2005;Windrum et al, 2007;Yilmaz, 2006).…”
Section: Model Use For Understanding Transitionsmentioning
confidence: 99%
“…If the chosen micro-level structure is able to generate the observed macro phenomena, the model provides a potential explanation for these phenomena. Models should base upon a sound theoretical foundation and use empirical data and expert knowledge to substantiate the model's micro-foundation (Boero and Squazzoni, 2005;Windrum et al, 2007;Yilmaz, 2006).…”
Section: Model Use For Understanding Transitionsmentioning
confidence: 99%
“…In particular, a validation approach from (Yilmaz, 2006) distinguishes the validation phases similar to the ones considered in the paper (e.g., conceptual and operational validation); however, the precise elaboration of the phases is focused largely on social processes, which are not relevant for our work. Furthermore, examples of model validation are found in psychology, e.g.…”
Section: Discussionmentioning
confidence: 99%
“…ABS can have programming errors or might not adequately capture the essence of the target system. There are no standardized models that guarantee verification and validation in ABS, in spite of recent efforts (Yilmaz, 2006). Also, interpreting the results of an ABS is hard when they are counterintuitive or when there is stochasticity involved.…”
Section: Limitations Of Absmentioning
confidence: 99%