Collaborative Research: MOD and TLS: A Predictive Simulation Model of Competitive Dynamics in Innovation

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。竞争如何影响创新？该项目采用了一种独特的方法来理解这个问题：它开发了一个基于证据的模拟平台，以了解竞争动态如何影响创新。这种方法为技术战略提供了新的知识，并为科学和技术政策提供了一种变革性的新工具。学术贡献：主要贡献有三点。首先，一个计算多智能体搜索理论的开发和评估的环境与复杂的相互作用的竞争代理。结果有助于了解搜索创新时，多个代理同时搜索，并开发计算representations it. Second，定性观察创新和竞争是通过结构化访谈在一个真实的技术为基础的行业。我们的目标是为技术战略中一个长期存在的问题提供理论上的答案：在竞争市场中，什么是最有效的公司层面的创新搜索策略？第三，软件研究工具ASaP是通过整合该项目的计算和战略组件的见解。该仿真工具可以对行业数据进行“实时”仿真，类似于工程中的物理仿真。学者和公共政策制定者可以利用这一工具了解他们的建议可能发挥作用的方式，从而帮助设计有效的政策，以管理竞争并同时促进创新。该项目的结果不仅可用于学术界严格分析竞争和创新，也可用于商业和政策分析，以提高企业和行业的创新能力，从而最终提高经济生产力。为了促进这种进展，通过一个网站向学者和从业人员公开提供ASaP工具，从而降低了一般计算分析的进入门槛，特别是对商业数据的预测分析。在当前的经济困难时期，保持创新比以往任何时候都更加重要，既可以抵御更深的衰退，也可以使我们以技术为基础的经济回到增长轨道。ASaP工具充当数据的实时模型，因此可用于识别生成数据的事件序列，并进行修改以找出如果某些因素（例如支持某些参与者的生计）会发生什么行业中的其他人）不同。从本质上讲，ASaP使人们有可能在实验室般的实验中交互式地研究档案数据，因此，它可以导致对科学和技术政策的见解，这是不可能获得的。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). How does competition influence innovation? This project takes a unique approach to understand this question: It develops an evidence-based simulation platform to understand how competitive dynamics influences innovation. This approach contributes new knowledge to technology strategy and a transformative new tool for science and technology policy. Intellectual Merit: There are three main contributions. First, a computational multi-agent search theory is developed and evaluated for environments with complex interactions of competing agents. The results help understand search for innovation when multiple agents search simultaneously, and develop computational representations of it. Second, qualitative observations on innovation and competition are made through structured interviews in a real technology-based industry. The goal is to provide theoretically informed answers to an enduring question in technology strategy: What are the most effective firm-level innovation search strategies in competitive markets? Third, a software research tool called ASaP is developed by integrating insights from the computational and strategy components of this project. This simulation tool makes it possible to perform "live" simulations of industry data, similar to physical simulations in engineering. Scholars and public policy makers can use this tool to understand the ways in which their recommendations are likely to play out and therefore help design effective policies to manage competition and simultaneously promote innovation.Broader Impacts: The results of the project can be used not only by academics to analyze competition and innovation rigorously but also by business and policy analysts to improve innovativeness of firms and industries, and thus ultimately advance economic productivity. To foster such progress, the ASaP tool is made publicly available to scholars and practitioners through a website, thus lowering the barrier of entry to computational analysis in general, and predictive analysis of business data in particular. During the current difficult economic times, it is more important than ever to remain innovative, both to resist deeper downturn and to bring our technology-based economy back to a growth trajectory. The ASaP tool serves as a live model of the data, and thus can be used to identify the sequence of events that generated the data, and modified to find out what would have happened if some factors (such as supporting the livelihood of certain players in the industry over others) had been different. In essence, ASaP makes it possible to study the archival data interactively in laboratory-like experiments, and it can therefore lead to insights on science and technology policy that are not possible to obtain otherwise.