Rausser Gordon, Choi Elliot, Bayen Alexandre
University of California, Rausser College of Natural Resources, Berkeley, CA 94720.
University of California, College of Engineering, Berkeley, CA 94720.
Proc Natl Acad Sci U S A. 2023 Oct 24;120(43):e2222013120. doi: 10.1073/pnas.2222013120. Epub 2023 Oct 16.
As public and private institutions recognize the role of space exploration as a catalyst for economic growth, various areas of innovation are expected to emerge as drivers of the space economy. These include space transportation, in-space manufacturing, bioproduction, in-space agriculture, nuclear launch, and propulsion systems, as well as satellite services and their maintenance. However, the current nature of space as an open-access resource and global commons presents a systemic risk for exuberant competition for space goods and services, which may result in a "tragedy of the commons" dilemma. In the race among countries to capture the value of space exploration, NASA, American research universities, and private companies can avoid any coordination failures by collaborating in a public-private research and development partnership (PPRDP) structure. We present such a structure founded upon the principles of polycentric autonomous governance, which incorporate a decentralized autonomous organization framework and specialized research clusters. By advancing an alignment of incentives among the specified participatory members, PPRDPs can play a pivotal role in stimulating open-source research by creating positive knowledge spillover effects and agglomeration externalities as well as embracing the nonlinear decomposition paradigm that may blur the distinction between basic and applied research.
随着公共和私人机构认识到太空探索作为经济增长催化剂的作用，预计各种创新领域将成为太空经济的驱动力。这些领域包括太空运输、太空制造、生物生产、太空农业、核发射和推进系统，以及卫星服务及其维护。然而，太空目前作为一种开放获取资源和全球公域的性质，给太空货物和服务的过度竞争带来了系统性风险，这可能导致“公地悲剧”困境。在各国争夺太空探索价值的竞赛中，美国国家航空航天局（NASA）、美国研究型大学和私营公司可以通过公私研发伙伴关系（PPRDP）结构进行合作，避免任何协调失败。我们提出了一种基于多中心自主治理原则的结构，该结构纳入了去中心化自主组织框架和专门的研究集群。通过促进指定参与成员之间的激励一致，PPRDP可以通过创造积极的知识溢出效应和集聚外部性，以及采用可能模糊基础研究和应用研究之间区别的非线性分解范式，在刺激开源研究方面发挥关键作用。
