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

VOSS：从人群中脱颖而出的团队：虚拟团队结构作为在线创新社区中创意的预测因素

• 批准号: 1322103
• 负责人: Paul Leonardi
• 金额: $ 22.99万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1322103&HistoricalAwards=false
• 关键词: VOSS; Teams; Emerging; Crowd; Virtual

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.

创新是美国经济的核心驱动力。组织不断寻求以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社区的不同建议中提取产品、服务和政策的好创意，这是在不随之增加资源支出的情况下增加创新的一种方式。但是，将想法生成外包给非专家会增加所生成想法的质量和适用性的差异，并且相应地会限制组织对所有建议给予同等关注的能力。这项研究的目的是探索组织如何更有效地利用“群体的力量”来发现和识别海量贡献中最有前途的想法。最近，大量关于团队设计的研究表明，结构团队的组成可以解释团队产生好创意的能力的差异。 将众包选民的集体概念化为“新兴虚拟团队”，使我们能够探索多种假设，即具有特定结构的新兴虚拟团队投票为“好”的想法实际上何时会成为想法一个组织应该将其有限的注意力资源花在这个问题上。在这个为期两年的项目中，我们收集并分析了用户在三个基于社区的创新论坛中提交和投票的想法，开发了一种算法，用于高效、有效地从坏想法中过滤好想法，并测试该算法对其他社区的预测能力基于创新的论坛。