Journal Article

Task Decomposition and Newsvendor Decision Making

Lee, Yun Shin, Siemsen, Enno

2017

Overview

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 .

• Publisher: INFORMS,Institute for Operations Research and the Management Sciences
• Subject: attribute substitution / behavioral operations / Decision makers / Decision making / Decision making models / decision support / Decision support systems / Decomposition / Decomposition method / Efficacy / Experiments / loss function pull / Management science / newsvendor / Organizational effectiveness / Organizational structure / overconfidence / Production management / Purchasing / random judgment error / Set (Psychology) / Soliciting / task decomposition / Uncertainty