Collaborative Research: DAT and MOD: The Division of Innovative Labor

合作研究：DAT 和 MOD：创新劳动的分工

• 批准号: 0830248
• 负责人: John Walsh
• 金额: $ 5.77万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0830248&HistoricalAwards=false
• 关键词: Collaborative; Research; DAT; MOD; Division

Innovation is becoming more open, often involving multiple organizations in a division of innovative labor (DoIL). The division of innovative labor in the economy is conceived of as the distribution across firms and other organizations of the following steps in the innovation process: 1) research/idea generation; 2) development; and 3) commercialization. Despite its importance, there is little broad-based, systematic evidence on the extent or nature of the DoIL, nor on its impact on firm performance or the rate of technical advance. The project collects the first systematic data on the DoIL for the United States by surveying over 20,000 firms in manufacturing and selected service industries,. The collected data quantifies key features of the DoIL. It also provides the basis for developing and empirically testing models of the DoIL and its effects on innovative performance. The project addresses a number of important questions, such as the extent to which startups, as compared to established firms, are generators of new ideas, the importance of universities as sources of industrial innovation, and the extent to which firms' use of external knowledge inputs increases their innovative performance. Finally, the research advances the economics of innovation by generating formal models that capture the DoIL and testing those models empirically.Broader Impacts: This project is the first national effort to collect data on innovative activity generally, going beyond R&D and patenting. It is an important addition to the data infrastructure required for a science of science and innovation policy. By generating new data on innovative activity, creating new metrics, and developing new models of the innovation process, the research also informs both public policy and firm strategy. The research should contribute to deliberations on intellectual property policy and policies on standards and cooperative research and development agreements that potentially affect the growth of technology markets and the DoIL. By highlighting the role of small firms, startups, and universities in the innovation process, the findings should also help inform federal support to university research and new firm formation. The project findings should also contribute to the federal government's ongoing efforts to improve its collection of data on industrial R&D and innovation. The research also contributes to the management of innovation by highlighting the returns to extramural knowledge sourcing, or strategic alliances formed to develop or commercialize new technologies.

创新变得更加开放，通常涉及创新劳动分工 (DoIL) 中的多个组织。 经济中的创新劳动分工被认为是创新过程中以下步骤在企业和其他组织之间的分配：1）研究/创意生成； 2）开发； 3）商业化。 尽管它很重要，但关于 DoIL 的范围或性质，以及它对公司绩效或技术进步速度的影响，几乎没有广泛的、系统的证据。 该项目通过调查制造业和特定服务行业的 20,000 多家公司，收集了美国 DoIL 的第一个系统数据。 收集的数据量化了 DoIL 的关键特征。 它还为开发和实证测试 DoIL 模型及其对创新绩效的影响提供了基础。 该项目解决了许多重要问题，例如与老牌企业相比，初创企业在多大程度上产生新思想、大学作为工业创新来源的重要性以及企业利用外部知识的程度投入提高了他们的创新绩效。最后，该研究通过生成捕捉 DoIL 的正式模型并以实证方式测试这些模型来推进创新的经济学。 更广泛的影响：该项目是第一个全国范围内收集创新活动数据的项目，超越了研发和专利申请的范围。它是科学与创新政策所需的数据基础设施的重要补充。 通过生成有关创新活动的新数据、创建新指标以及开发创新过程的新模型，该研究还为公共政策和公司战略提供了信息。 该研究应有助于审议知识产权政策以及可能影响技术市场和 DoIL 增长的标准政策和合作研发协议。 通过强调小企业、初创企业和大学在创新过程中的作用，研究结果还应有助于为联邦对大学研究和新公司组建的支持提供信息。 该项目的研究结果还应有助于联邦政府不断努力改进其工业研发和创新数据的收集。 该研究还通过强调外部知识采购的回报或为开发或商业化新技术而形成的战略联盟，为创新管理做出贡献。