Using worker personality and demographic information to improve system performance prediction
研究在系统性能仿真模型中纳入工人个性和人口统计信息的效果，发现不同建模方法会导致显著差异，对招聘、团队组建和任务分配有实际意义。
Abstract This paper presents an approach to modeling workers where human performance has a significant impact on system productivity. Highly technical industries such as semiconductor manufacturing and service industries like banking are relying on fewer but more skilled workers. In these systems, productivity depends on worker availability and organization; therefore, modeling system performance may require accurate representations of individual worker behavior. This paper examines the tradeoffs in including information about the demographics and personalities of workers in system performance simulation models. A series of actual and simulated experiments in which personality and demographic data are used in different ways to model the performance of a team of workers is reported. Significant differences are found in predicted system performance demonstrating that model validity depends on the methodology used for modeling workers. These results have practical implication for the managerial processes of recruiting and selecting individual workers, as well as organizing teams of workers and assigning them to tasks.