VOSS: Teams Emerging from the Crowd: Virtual Team Structure as a Predictor of Idea Goodness in Online Innovation Communities

创新是美国经济的核心驱动力。组织不断寻求用更少的资源实现更大的创新。先进的信息和通信技术使组织能够从用户群体的各种建议中提取出关于产品、服务和政策的好想法，这是在不增加资源支出的情况下增加创新的一种方式。但是，将创意产生工作外包给非专业人士，增加了创意的质量和适用性的差异，同时也削弱了组织对所有建议给予同等关注的能力。本研究的目的是探索组织如何更有效地利用“人群的力量”，在海量的贡献中发现和识别最有前途的想法。最近，对团队设计的大量研究表明，团队的结构组成可以解释团队产生好想法的能力的变化。将众包投票人的集体概念化为“紧急虚拟团队”，可以让我们探索一些假设，即由具有特定结构的紧急虚拟团队投票选出的“好”想法，实际上是组织应该花费其有限的注意力资源的想法。在这个为期两年的项目中，我们收集和分析了三个社区创新论坛中用户提交和投票的想法，开发了一种算法，可以高效有效地从坏想法中筛选出好想法，并在其他社区创新论坛上测试算法的预测能力。

Innovation is a core driver of the U.S. economy. Organizations are constantly seeking to be more innovative with fewer resources. Advanced information and communication technologies that allow organizations to extract good ideas for products, services, and policies from the diverse suggestions of user communities represent one way to increase innovation without a concomitant increase in resource expenditures. But the outsourcing of idea generation to non-specialists increases the variance in the quality and applicability of the ideas that are generated and, concordantly, strains an organization's ability to give equal attention to all suggestions. The goal of this study is to explore how organizations might more effectively harness "the power of the crowd" to find and recognize the most promising ideas within a sea of contributions.Recently, a good deal of research into team design has shown that the structural composition of a team can explain variations in the team's ability to generate good ideas. Conceptualizing a collective of crowd-soucing voters as an "emergent virtual team" allows us to explore a number of hypotheses about when the ideas that are voted to be "good" by emergent virtual teams with particular structures will, in fact, be the ideas upon which an organization should spend its limited resources of attention. In this two-year project, we collect and analyze ideas submitted and voted on by users in three community-based innovation forums, develop an algorithm for efficiently and effectively filtering good ideas from bad, and test the predictive power of the algorithm on other community-based innovation forums.