Human decision-making behavior and modeling effects
Previous research indicates that the human decision-making process is quite non-linear and that non-linear models would be more suitable than linear models for developing advanced decision-making models. In our study, we tested this generally held hypothesis by applying linear and non-linear models to experts' decision-making behavior and measuring the predictive accuracy (predictive validity) and valid non-linearity. As a result, we found that non-linearity in the decision-making process is positively related to the predictive validity of the decision. Secondly, in modeling the human decision-making process, we found that valid non-linearity is positively related to the predictive validity of non-linear models. Thirdly, we found that the more non-linearity is inherent in the decision-making process, the more non-linear models are effective. Therefore, we suggest that a preliminary analysis of the characteristics of expert decision-making is needed when knowledge-based models such as expert systems are being developed. We also verify that the lens model is effective in evaluating the predictive validity of human judgment and in analyzing the validity and non-linearity of the human decision-making process.
modeling effect predictive accuracy human judgment valid non-linearity and predictive validity in human decision-making behavior lens model analysis