中国衡量创新的方法和挑战

Yuxin Li, Jiang Yang, Chris Warhurst
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引用次数: 0

摘要

在中国和其他地方,创新作为经济发展的关键驱动力在政府政策中占有重要地位。因此,能够衡量创新绩效非常重要。本文分析了中国衡量国家创新绩效的方法。在这样做并使用文献分析的过程中,它评估了支撑和支持该测量的概念化和数据收集。研究结果表明,中国注重用科学技术方法来衡量创新。指出了这种方法的弱点:首先,概念范围过于狭窄,因为它排除了非技术创新;第二,相对而言,数据收集在数量和质量上对创新类型的覆盖有限;第三,样本总体是有偏见的,排除了大量的公司和员工。这些弱点削弱了对中国创新绩效的理解。在此基础上,本文首次对中国创新的概念和测量进行了评价,并在此基础上提出了解决这些问题和改进创新绩效测量的建议,这些建议具有一定的适用性。对于中国和其他国家,如经合组织和欧盟成员国,本文提供的证据表明,迫切需要采用这种更广泛的政策方法,并通过制定适当的措施和数据收集来支持它。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The approach to and challenges in measuring innovation in China
In China and elsewhere, innovation features strongly in government policy as a key driver of economic development. Being able to measure innovation performance is therefore important. This paper analyses China’s approach to measuring the country’s innovation performance. In doing so and using documentary analysis, it evaluates the conceptualisation and data collection that underpin and support that measurement. The findings show that China focuses on a science and technology approach to measuring innovation. The weaknesses of this approach are identified: first, the conceptual scope is too narrow due to its exclusion of non-technological innovation; second, relatedly, data gathering is limited quantitatively and qualitatively in its coverage of types of innovation; and, third, the sample population is biased, acting to excluding a significant number of firms and employees. These weaknesses undermine understanding of innovation performance in China. With this analysis, this paper provides the first evaluation of China’s innovation conceptualization and measurement and, based on the findings, provides suggestions to address these weaknesses and improve the measurement of innovation performance and which have applicability beyond China. For China and other countries such as those which are members of the OECD and EU, the evidence provided in this paper suggest that there is a pressing need to adopt this broader policy approach and support it through the development of appropriate measures and data collection.
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