Collaborative Research: Industries of Ideas: A prototype system for measuring the effects of research investments on regional firms and jobs

协作研究：创意产业：衡量研究投资对区域企业和就业影响的原型系统

• 批准号: 2332572
• 负责人: Bruce Weinberg
• 金额: $ 166.32万
• 依托单位: Ohio State University
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2332572&HistoricalAwards=false
• 关键词: Collaborative; Research; Industries; Ideas; prototype

The Industries of Ideas: A prototype system for measuring the effects of research investments on regional firms and jobs proposes to test a first of its kind end-to-end data-driven pilot framework for assessing the impact of research investment in specific technology areas on corresponding regional firms and jobs. The CHIPS and Science Act supports investments in key technologies to drive innovation, create jobs, and establish technology hubs across the United States. Understanding the impacts of such investments in the ten technology areas described in the CHIPS and Science Act can be challenging given current data and methods because new technologies such as AI, quantum computing, biomanufacturing and others are difficult to map to specific sectors and are also quickly evolving. There are no current means to systematically identify all the industries, employers, and workers which those technologies might affect. To address these challenges the Industries of Ideas project will engage with various stakeholders through outreach and community engagement, create a prototype dashboard for effective accessible visualization and communication of relevant information, and develop metrics for effectiveness of the outcomes. The initial focus of this project is on the State of Ohio — a large, diverse state with much of the requisite data infrastructure already in place and with two rapidly emerging technology areas, viz., Artificial Intelligence (AI) and Electric Vehicles (EV). The project will establish plans and partnerships for scaling this effort from a single state to the national level. The tracking of investment impacts is challenging in multiple ways. Identifying investments in rapidly evolving, trans-disciplinary technology areas that do not align with existing classification systems is difficult. Existing methods and data also cannot identify the companies, jobs, and individuals affected by research investments in emerging technologies a priori, rendering traditional sample survey methods inadequate. Reporting at the regional level can be challenging due to data limitations and privacy requirements. Requirements for timely reporting are also hindered by the current state of relevant data sources which exhibit significant time lags in producing the data. The project addresses these challenges by using a framework based on data linkage and inductive, iterative expansion of inclusion restrictions to take advantage of established network effects. Core to the approach is the idea that research funding enables the work of innovators, which generates valuable ideas and skilled people who then contribute to the economy through networks created by the mobility of knowledge-workers. The proposed novel approach categorizes firms into "idea industries" based on: (1) the research-trained individuals employed by those firms and (2) the research projects to which they supply inputs. This is achieved by linking together close to real-time bibliometric/textual data, university administrative records, and state workforce data, and using a “snowball” logic to identify industry and workforce effects of scientific investments that are difficult to measure otherwise. The project builds upon existing, proven platforms with which the project team has significant experience. The novelty of the work is in its integrative, scalable, iterative nature. The project will engage the regional community and create measures, plans and support for expansion to other regions of the country. The project will develop a prototype dashboard that can be improved and expanded upon iteratively over time. The work will also develop methods and templates for system building that can be integrated with other analysis efforts, allowing for triangulation across multiple data sources and approaches. The framework is designed to be expanded in three ways: (1) by including more technology areas and additional states; (2) by incorporating additional data sources like information on post-secondary certificate and degree recipients; and (3) by transitioning from prototype development to a software platform and data production system suitable for a wealth of use cases. The project will collaborate closely with three major stakeholder groups, viz., university leaders, regional innovation ecosystem leaders, and state agency leaders to help inform the design of the system, develop metrics for success, and make improvements to the system. The outreach and engagement with the stakeholder community will help secure the broadest possible use of the prototype and build support and momentum for planned future expansions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

创意产业：用于衡量研究投资对区域企业和就业的影响的原型系统建议测试第一个端到端数据驱动的试点框架，以评估特定技术领域的研究投资对区域企业和就业的影响。 《CHIPS 和科学法案》支持对关键技术的投资，以推动创新、创造就业机会并在美国各地建立技术中心。了解此类投资对《CHIPS 和科学法案》所述的十个技术领域的影响。考虑到当前的数据和方法，这可能具有挑战性，因为诸如此类的新技术由于人工智能、量子计算、生物制造等很难映射到特定行业，而且也在快速发展，目前还没有方法可以系统地识别这些技术可能影响的所有行业、雇主和工人，以应对这些行业的挑战。 of Ideas 项目将通过外展和社区参与与各个利益相关者进行接触，创建一个原型仪表板，以实现有效的可视化和相关信息的交流，并制定成果有效性的指标。该项目的最初重点是俄亥俄州。一个庞大、多元化的国家，拥有许多必要的条件该项目将建立计划和合作伙伴关系，将这一工作从单一州扩展到国家层面。识别与现有分类系统不符的快速发展的跨学科技术领域的投资影响在很多方面都具有挑战性，现有的方法和数据也无法识别受研究投资影响的公司、工作和个人。新兴技术先验，渲染传统抽样调查由于数据限制和隐私要求，及时报告的要求也受到相关数据源现状的阻碍，这些数据源在生成数据方面存在显着的时间滞后。使用基于数据链接和包容性限制的归纳、迭代扩展的框架来利用已建立的网络效应，该方法的核心理念是研究资金支持创新者的工作，从而产生有价值的想法和技术人员，然后为之做出贡献。通过网络经济所提出的新方法根据以下因素将公司分为“创意产业”：（1）这些公司雇用的受过研究培训的人员以及（2）他们提供投入的研究项目。该项目通过将实时文献计量/文本数据、大学行政记录和州劳动力数据紧密联系在一起，并使用“滚雪球”逻辑来识别科学投资对行业和劳动力的影响来实现，而这些影响是难以通过其他方式衡量的。该项目使用现有的、经过验证的平台该项目的新颖性在于其综合性、可扩展性和迭代性，并为扩展到该国其他地区制定措施、计划和支持。随着时间的推移，这项工作还将开发可与其他分析工作集成的系统构建方法和模板，从而允许跨多个数据源和方法进行三角测量。方式： (1) 纳入更多技术领域和更多状态；(2) 纳入更多数据源，例如关于高等教育证书和学位获得者的信息；(3) 从原型开发过渡到适合的软件平台和数据生产系统；该项目将与三个主要利益相关者群体（即大学领导者、区域创新生态系统领导者和国家机构领导者）密切合作，帮助为系统设计提供信息、制定成功指标并做出改进。与利益相关者社区的外展和参与将。帮助确保原型得到最广泛的使用，并为计划中的未来扩展建立支持和动力。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。