A psychological approach to decision support systems
A psychological approach to decision support systems
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DOI：
10.1287/mnsc.42.1.51
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发表时间：
1996-01-01
影响因子：
5.4
通讯作者：
Schkade, DA
中科院分区：
文献类型：
--
作者：
Hoch, SJ;Schkade, DA
信息技术的快速发展给决策者带来了越来越多的容易获得的数据。决策支持系统（DSS）的设计者们一直把注意力集中在整合最新的技术上，而很少关注这些新系统是否与决策者的心理相容。我们的前提是，决策支持的设计应该利用决策者的独特能力，同时使用技术来弥补他们固有的弱点。在这项研究中，我们将这种方法应用于预测任务。我们发现，为了做出预测，决策者通常会从他们的经验中寻找与当前情况相似的情况，然后对之前的情况进行小幅调整。我们对这种直觉上吸引人的策略的理论模型表明，它在高度可预测的环境中表现得相当好，但在不可预测的环境中表现得相当差。实验结果证实了这些预测，并表明为决策者提供一个简单的线性模型，结合计算机化的历史案例数据库，可以显著提高绩效。最后，我们讨论了如何使用这些结果来帮助改进应用环境中的预测，例如零售杂货行业的促销预测。
Rapid advances in information technology have brought decision makers the mixed blessing of an increasingly vast amount of easily available data. Designers of decision support systems (DSS) have focused on incorporating the latest technology with little attention to whether these new systems are compatible with the psychology of decision makers. Our premise is that DSS should be designed to take advantage of the distinctive competencies of decision makers while using technology to compensate for their inherent weaknesses. In this study we apply this approach to a forecasting task. We find that to arrive at a forecast decision makers often search their experience for a situation similar to the one at hand and then make small adjustments to this previous situation. Our theoretical model of the performance of this intuitively appealing strategy shows that it performs reasonably well in highly predictable environments, but performs quite poorly in less predictable environments. Results from an experiment confirm these predictions and show that providing decision makers with a simple linear model in combination with a computerized database of historical cases improves performance significantly. We conclude by discussing how these results can be used to help improve forecasting in applied contexts, such as promotion forecasting in the retail grocery industry.