Crowdsourcing Mental Models using DESIM (Descriptive to Executable Simulation Modeling)

This paper describes the DESIM (Descriptive to Executable Simulation Modeling) process for transforming causal descriptive models into computer simulation models based on information obtained from crowdsourcing. Feedback obtained from crowdsourcing is used to quantify the strength of causal relationships between variables in descriptive models to provide consistent and less-biased distributions of estimated weights for each causal relationship and thereby enable mathematical processing of the descriptive models on a computer. The approach employs fuzzy cognitive modeling methods to elicit and structure the models and the analytic hierarchy process to compute the distribution of weights between variables. The output of this process produces a decision space, which is visualized with a novel decision space visualization tool. An experimental application of this process is presented and discussed, with implications for future research.