文献速递—建模技术创新：科学、工程和行业方法如何结合

中文题目：建模技术创新：科学、工程和行业方法如何结合以产生有益的社会经济影响

英文题目：Modeling technology innovation: How science, engineering, and industry methods can combine to generate beneficial socioeconomic impacts

摘要：

背景：政府资助的科学、技术和创新（STI）项目除了扩大知识库外，还支持公共政策的社会经济方面。例如，有益的医疗服务和设备预计将来自研发项目的投资，这些项目与商业创新存在因果关系。这些项目越来越多地被要求对影响证据负责，即研发活动产生的创新商品和服务。然而，由于缺乏全面的模型和指标，证据收集倾向于关于研究产出（已发表的发现）的文献计量学，较少关注关于发展产出（专利原型）的转移指标，几乎没有关注与生产产出（商业创新）相关的计量经济学。由于最后一类产出产生了最可衡量的社会经济效益，因此这种差异对于此类项目的明确意图而言尤其成问题。

方法：本文提出了一个概念框架，将所有三种知识生成方法整合到一个逻辑模型中，有助于规划、获取和测量通过在实践中实施知识而产生的预期有益影响。此外，环境输入过程产品（CIPP）评估模型的集成在保持严谨性的同时，积极地将相关性构建到STI政策和计划中。

结果：生成的逻辑模型框架明确跟踪了知识从输入到三个知识生成过程及其各自的知识输出（发现、发明、创新）的进展，因为它产生了预期的社会效益影响。它是一种用于产生基于技术的创新的混合模型，其中新产品开发的最佳实践与广泛接受的知识翻译方法相融合。鉴于对医疗卫生领域循证实践的重视以及对知识转移的“从工作台到床边”期望，赞助者和受赠者都应该发现该模型对规划、实施和评估创新过程有用。

结论：医疗保健等高成本/高风险行业需要在市场上部署基于技术的创新，以改善全球经济中的国内社会。研究、开发和生产中相关性和严谨性的适当平衡对于优化此类项目的公共投资回报至关重要。技术创新过程需要一个全面的运作模式，以有效地分配公共资金，从而有意识地、系统地实现社会经济效益。

Abstract:

Background: Government-sponsored science, technology, and innovation (STI) programs support the socioeconomic aspects of public policies, in addition to expanding the knowledge base. For example, beneficial healthcare services and devices are expected to result from investments in research and development (R&D) programs, which assume a causal link to commercial innovation. Such programs are increasingly held accountable for evidence of impact-that is, innovative goods and services resulting from R&D activity. However, the absence of comprehensive models and metrics skews evidence gathering toward bibliometrics about research outputs (published discoveries), with less focus on transfer metrics about development outputs (patented prototypes) and almost none on econometrics related to production outputs (commercial innovations). This disparity is particularly problematic for the expressed intent of such programs, as most measurable socioeconomic benefits result from the last category of outputs.

Methods: This paper proposes a conceptual framework integrating all three knowledge-generating methods into a logic model, useful for planning, obtaining, and measuring the intended beneficial impacts through the implementation of knowledge in practice. Additionally, the integration of the Context-Input-Process-Product (CIPP) model of evaluation proactively builds relevance into STI policies and programs while sustaining rigor.

Results: The resulting logic model framework explicitly traces the progress of knowledge from inputs, following it through the three knowledge-generating processes and their respective knowledge outputs (discovery, invention, innovation), as it generates the intended socio-beneficial impacts. It is a hybrid model for generating technology-based innovations, where best practices in new product development merge with a widely accepted knowledge-translation approach. Given the emphasis on evidence-based practice in the medical and health fields and "bench to bedside" expectations for knowledge transfer, sponsors and grantees alike should find the model useful for planning, implementing, and evaluating innovation processes.

Conclusions: High-cost/high-risk industries like healthcare require the market deployment of technology-based innovations to improve domestic society in a global economy. An appropriate balance of relevance and rigor in research, development, and production is crucial to optimize the return on public investment in such programs. The technology-innovation process needs a comprehensive operational model to effectively allocate public funds and thereby deliberately and systematically accomplish socioeconomic benefits.

来源期刊：IMPLEMENTATION SCIENCE，2012年

参考文献格式：Stone, Vathsala I.&Lane, Joseph P..Modeling technology innovation: How science, engineering, and industrymethods can combine to generate beneficial socioeconomic impacts[J].IMPLEMENTATION SCIENCE,2012,7(期号):起始页-结束页