Applications of technology that contribute to managing decision-making teams for their objectives benefit from an explicit account of microprocessing in the information exchange of team members. While negative evaluations are well recognized as a key information type in this exchange, the micro-processing that underlies its exchange has not been well defined. Negative evaluations will be proposed to differ from other information types because of their dual properties as information and affect. We propose dynamics that are implied by the duality in negative evaluations we cite and report empirical studies that test abstract generalizations on the proposed dynamics. We then give an explicit form to exchange of negative evaluations in a numerical model of information exchange and use the model in exercises that directly demonstrate the proposed properties of negative evaluations in information exchange. Finally, we review contributions that the discourse offers to the design of AI-supported GDSSs for managerial objectives in the exchange of information in ill-structured decision making and introduce architecture of a prototype GDSS that implements quality-maximizing information exchange. Directions for subsequent study are discussed.

有助于管理决策团队实现其目标的技术应用受益于团队成员信息交换中对微处理的明确说明。虽然负面评价已被公认为这种交换中的关键信息类型，但对其交换基础的微处理却尚未明确定义。负面评价将被提议与其他信息类型不同，因为它们具有信息和影响的双重属性。我们提出了负面引用中双重性所隐含的动力学，并引用了经验研究来测试对所提出的动力学的抽象概括。然后，我们为信息交换的数值模型中的负面评价的交换提供了一种明确的形式，并在练习中使用了该模型，该练习直接证明了负面评价在信息交换中的拟议性质。最后，我们回顾了该论述对在结构错误的决策中信息交换中为管理目标提供AI支持的GDSS设计的贡献，并介绍了实现质量最大化信息交换的GDSS原型体系结构。讨论了后续研究的方向。我们回顾了该论述对在结构不良的决策中信息交换中为管理目标的AI支持的GDSS设计提供的贡献，并介绍了实现质量最大化的信息交换的GDSS原型体系结构。讨论了后续研究的方向。我们回顾了该论述对在结构不良的决策中信息交换中为管理目标的AI支持的GDSS设计提供的贡献，并介绍了实现质量最大化的信息交换的GDSS原型体系结构。讨论了后续研究的方向。