Modelling Schumpeter's Theory of Innovation as a Basis for Innovation Policy: An Experimental Approach

将熊彼特的创新理论建模为创新政策的基础：实验方法

• 批准号: 0915482
• 负责人: John Gero
• 金额: $ 37.37万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915482&HistoricalAwards=false
• 关键词: Modelling; Schumpeter; Theory; Innovation; Basis

Any science requires the following elements: phenomena; empirical data that describe those phenomena; hypotheses at various levels to connect, explain and then predict those phenomena; and the ability to test those hypotheses, Once a hypothesis is able to predict it becomes a theory.The science of innovation policy must be based on a platform that permits the formulation and testing of key hypotheses. Constructing such a platform is typically a challenge in the social sciences as there is often no ability to carry out experiments in the same way that the physical sciences can, i.e, in a laboratory. This project develops an approach to test hypotheses and theories by creating a computational laboratory within with hypothesis evolution and hypothesis testing can take place.Intellectual MeritMuch of the current research in the science of innovation policy is focused on collecting empirical data. There is a surprising paucity of testable models and theories. There are two directions from which models can come: empirical observation or inference based on a qualitative understanding of a field. Schumpeter, in his analysis of the success of capitalism, has produced one of the most explanatory qualitative theories of innovation known as ?creative destruction?. This theory of innovation takes a Lamarckian view of the evolution of products and processes, but it has yet to be formally modeled and tested. The contribution of this research is to advance the modeling and testing of Schumpeterian creative destruction. In doing so the project creates a laboratory, which can then be used more generally. The laboratory is designed to synthesize concepts from the disparate fields of: innovation theory; creative production; computational sociology; social multi-agent systems; situated cognition; emergence; and data mining. Both the laboratory and the results it produces provide the foundations for a science of innovation policy: science that produces testable results, and one that can test hypotheses. The laboratory uses computational sociology, a technology based on social multi-agent systems that allow for emergent behavior, as the modeling tool. Agents are generators and receivers of ?products? and take up novel, useful and unexpected products. The overall system behavior is structured to be emergent and is captured using data mining techniques. Because the system connects inputs to outputs at the overall system level, the effects of different types of innovation policies can then be tested in the laboratory.Broader ImpactThe broader impacts of this research lie in multiple dimensions. The project will involve PhD students and give other students experience with this kind of integrative research. It will make connections to computer science, cognitive science, social science and design science. The results from this project provide as feedback to design and innovation educators initially at George Mason University and then to design and innovation educators at other universities through the use of demonstrations. The results from this project are disseminated via conference papers, journal papers and a website. The laboratory is publicly available publicly so that others can experiment with it through the website.

任何科学都需要以下要素：现象;描述这些现象的经验数据;连接、解释和预测这些现象的各个层次的假设;以及检验这些假设的能力。一旦假设能够预测，它就成为理论。在社会科学中，构建这样一个平台通常是一个挑战，因为通常没有能力像物理科学那样在实验室中进行实验。本项目开发了一种方法来测试假设和理论，通过创建一个计算实验室内的假设进化和假设检验可以发生。智力MeritMost目前的研究在创新政策的科学是集中在收集经验数据。令人惊讶的是，缺乏可检验的模型和理论。模型可以从两个方向产生：经验观察或基于对一个领域的定性理解的推断。熊彼特在他对资本主义成功的分析中，提出了一个最具解释性的创新定性理论，称为？创造性破坏？这种创新理论采用拉马克的观点来看待产品和流程的演变，但它还没有被正式建模和测试。 这项研究的贡献是推进熊彼特创造性破坏的建模和测试。在这样做的过程中，该项目创建了一个实验室，然后可以更普遍地使用。该实验室旨在综合来自不同领域的概念：创新理论;创造性生产;计算社会学;社会多智能体系统;情境认知;涌现;和数据挖掘。实验室及其产生的结果为创新政策科学提供了基础：产生可检验结果的科学，以及可以检验假设的科学。该实验室使用计算社会学，一种基于社会多代理系统的技术，允许紧急行为，作为建模工具。代理人是生成器和接收器？产品？并采用新颖、有用和意想不到的产品。整个系统的行为被构造为紧急的，并使用数据挖掘技术捕获。由于该系统在整个系统层面上将投入与产出联系起来，因此可以在实验室中测试不同类型的创新政策的效果。更广泛的影响本研究的更广泛的影响在于多个维度。该项目将涉及博士生，并为其他学生提供这种综合研究的经验。它将与计算机科学，认知科学，社会科学和设计科学联系起来。从这个项目的结果提供反馈，最初在乔治梅森大学的设计和创新教育工作者，然后在其他大学的设计和创新教育工作者通过使用示范。该项目的成果通过会议论文、期刊论文和网站传播。该实验室是公开的，以便其他人可以通过网站进行实验。