Spatial and Social Networks in Organizational Innovation

组织创新中的空间和社交网络

• 批准号: 0724675
• 负责人: Jean Wineman
• 金额: --
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0724675&HistoricalAwards=false
• 关键词: Spatial; Social; Networks; Organizational; Innovation

Research on what enables innovation tends to focus on either social factors or spatial ones, but not both. This is an interdisciplinary study examining links among spatial layout, social networks, and innovation in a set of highly innovative organizations. The results should have value for those who design spaces for organizations that seek to be innovative as well as for those who manage them. The research team includes experts in architecture, organization sciences, and sociology. As built space structures patterns of circulation, co-presence, co-awareness and encounter in an organization, these interrelationships become fundamental to the development of social networks, especially those networks critical to the innovation process. This study will include an in-depth analysis of space, including its geometric and topological qualities. It will also examine user perceptions of the environmental qualities of space as they relate to innovation. It will also employ theories and methods related to social network analysis to examine the formation and maintenance of crucial social links. The study will include development and testing of new metrics for describing spatial variables pertinent to social phenomena. These will be valuable for other researchers who would like to explore questions related to links among people, spaces, and performance.

关于创新的研究往往集中于社会因素或空间因素，但不会同时关注两者。 这是一项跨学科研究，探讨了一组高度创新组织中的空间布局、社交网络和创新之间的联系。结果应该对那些为寻求创新的组织设计空间的人和管理这些组织的人有价值。 研究团队包括建筑学、组织科学和社会学方面的专家。 随着组织中循环、共存、共同意识和相遇的空间结构模式的建立，这些相互关系成为社交网络发展的基础，特别是那些对创新过程至关重要的网络。这项研究将包括对空间的深入分析，包括其几何和拓扑性质。它还将研究用户对与创新相关的空间环境质量的看法。它还将采用与社交网络分析相关的理论和方法来研究重要社会联系的形成和维持。 该研究将包括开发和测试用于描述与社会现象相关的空间变量的新指标。这些对于其他想要探索与人、空间和性能之间的联系相关的问题的研究人员来说是有价值的。