Information Sampling During Group Performance

在解决问题或做出决定时，拥有能够提供多种知识和见解的成员可能会使小团体受益。然而，之前的研究表明，这一决定是正确的。组成小组（即被要求做出判断的小组）常常不能考虑单个成员所掌握的信息。观。事实上，非结构化的讨论侧重于所有成员已经知道的信息，因此，群体经常忽略他们的集体知识所青睐的选项。拟议的研究将检验这种现象在多大程度上推广到用明显正确答案解决问题的群体。此外，该研究将审查战略组成的少数派别在促进小组讨论期间更有效的信息交流方面的作用。通过跟踪讨论过程中信息的流动和影响，本研究还将提供完善群体决策的讨论模型所需的数据。该模型模拟了在群体决策过程中面对面讨论过程中信息的采样和使用。它提供了一种方便的方法来表示群体相互作用的复杂性，并检查群体组成（例如，规模和派系表示）和任务需求（例如，决策选项或可能解决方案的数量和信息负载）变化的含义。

When solving a problem or making a decision, small groups can potentially benefit from having members who can contribute a diversity of knowledge and insights. Previous research suggests, however, that decision.making groups (i.e., groups asked to make a judgment) often fail to consider information that is held by single members. Face.to.face, unstructured discussion focuses on information that all members already know, and, as a result, groups frequently overlook an option that is favored by their collective knowledge. The proposed research will examine the extent to which this phenomenon generalizes to groups that are solving a problem with a demonstratably correct answer. Additionally, the research will examine the role of strategically composed minority factions in facilitating more effective information exchange during group discussion. By tracking the flow and impact of information during discussion, the research will also provide data needed to refine the DISCUSS model of group decision making. This model simulates the sampling and use of information during face.to.face discussion en route to a group decision. It provides a convenient way of representing the complexities of group interaction and of examining the implications of changes in group composition (e.g., size and factional representation) and task demands (e.g., number of decision options or possible solutions and information load).