Task Decomposition and Newsvendor Decision Making
通过三个行为实验，比较了直接订货与分解式订货（先预测需求、估计不确定性、设定服务水平再订货）的效果，发现分解式订货在临界比率低于50%或需求不确定性过高时效果不佳，但配合决策支持则普遍更优。
We conduct three behavioral laboratory experiments to compare newsvendor order decisions placed directly to order decisions submitted in a decomposed way by soliciting point forecasts, uncertainty estimates, and service-level decisions. Decomposing order decisions in such a way often follows from organizational structure and can lead to performance improvements compared with ordering directly. However, we also demonstrate that if the critical ratio is below 50%, or if the underlying demand uncertainty is too high, task decomposition may not be preferred to direct ordering. Under such conditions, decision makers are prone to set service levels too high or to suffer from excessive random judgment error, which reduces the efficacy of task decomposition. We further demonstrate that if accompanied by decision support in the form of suggested quantities, task decomposition becomes the better-performing approach to newsvendor decision making more generally. Decision support and task decomposition therefore appear as complementary methods to improve decision performance in the newsvendor context. This paper was accepted by Serguei Netessine, operations management.