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

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:
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
项目状态:
已结题
起止时间:
2009-09-15 至 2012-08-31

项目摘要

项目成果

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中文摘要
翻译
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、解释并预测这些现象的不同层面的假设;以及一旦假设能够预测它成为理论,检验这些假设的能力。创新政策科学必须建立在允许制定和测试关键假设的平台上。建立这样一个平台在社会科学中通常是一项挑战,因为通常没有能力像物理科学那样进行实验,即在实验室中进行实验。这个项目开发了一种方法,通过在内部创建一个计算实验室来检验假设和理论,假设进化和假设检验可以发生。智力价值目前创新政策科学的研究主要集中在收集实证数据上。令人惊讶的是,可检验的模型和理论非常缺乏。模型可以来自两个方向:经验观察或基于对一个领域的定性理解的推理。熊彼特在他对资本主义成功的分析中,提出了一种最具解释性的定性创新理论--创造性破坏。这一创新理论对产品和过程的演变采取了拉马克式的观点,但它尚未得到正式的建模和测试。本研究的贡献在于推进熊彼特创造性破坏的建模和检验。在这样做的过程中,项目创建了一个实验室,然后可以更广泛地使用。该实验室旨在综合创新理论、创造性生产、计算社会学、社会多智能体系统、情境认知、涌现和数据挖掘等不同领域的概念。实验室及其产生的结果都为创新政策科学奠定了基础:这是一门能够产生可检验结果的科学,也是一门可以检验假设的科学。该实验室使用计算社会学作为建模工具,这是一种基于社会多智能体系统的技术,允许出现行为。代理商是产品的生产者和接收者。并采用新奇、有用和意想不到的产品。整个系统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输入与输出联系起来,因此不同类型的创新政策的效果可以在实验室中进行测试。广泛影响这项研究的更广泛影响在于多个维度。该项目将邀请博士生参与,并让其他学生体验这种综合研究。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。该项目的结果最初提供给乔治梅森大学的设计和创新教育工作者作为反馈,然后通过示范提供给其他大学的设计和创新教育工作者。该项目的成果通过会议论文、期刊论文和网站传播。该实验室向公众开放,以便其他人可以通过网站进行实验。
英文摘要
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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