国家自主创新示范区产业转型升级水平测度及其影响因素研究

MeasurementSofSIndustrialSTransformationSandSUpgradingSLevelSofSNationalSInnovationSDemonstrationSZoneSandSitsSInfluencingSFactors

摘要:

国家自主创新示范区测度产业转型升级的发展水平和探析各影响因素,对于推动国家自主创新示范区的产业可持续发展、更好发挥国家自主创新示范区的高质量区域经济引领作用,意义重大。研究联合体通过产业共性技术研发带动区域产业向价值链上游转移,为研究国家自主创新示范区的产业转型升级提供了新视角。选取2014-2019年我国21个国家自主创新示范区的面板数据,基于研究联合体的视角构建涵括产业结构水平、创新驱动水平、数智赋能水平和绿色发展水平四个维度的国家自主创新示范区产业转型升级水平测度体系,利用熵权TOPSIS模型评价国家自主创新示范区产业转型升级发展水平,并运用固定效应模型寻找其发展水平的影响因素。实证分析结果显示：示范区产业转型升级平均水平为0.470,处于中等水平；水平最高的深圳与最低的乌昌石之间的差为0.545,差距较大；东部示范区整体发展水平高于中西部；南方示范区产业转型升级平均水平为0.519远高于北方的0.3932,南北方差距明显。进一步分析影响因素表明：示范区研发创新能力与产业转型升级呈正相关,研发创新通过知识发现和技术创造带动示范区产业向价值链上游转移；人才支撑能力与示范区产业转型升级呈正相关,示范区通过提升人才存量进而引发“知识外溢”效应带动产业转型升级；创新服务能力与示范区产业转型升级呈正相关,示范区通过搭建良好的企业经营环境提供完善的保障服务促进产业转型升级；经济牵引能力对产业转型升级呈正相关,示范区通过吸引资源要素聚集促进产业转型升级；示范区开放合作能力未通过显著性检验,表明整体而言开放合作跟示范区产业转型升级的关系不大。鉴于此,示范区应搭建完善的研发创新环境、打造致力产业共性技术研究的研发平台、构建研发人才体系、探索差异化的产业转型升级路径。

Abstract:

It is significant to measure the development level of industrial transformation and upgrading and to explore the various influencing factors in the National Innovation Demonstration Zone (NIDZ), in order to promote the sustainable development of industries in the NIDZ and to better play the leading role of the NIDZ in high-quality regional economy. RJVs provides a new perspective for studying the industrial transformation and upgrading of NIDZ by driving regional industries to the upstream of the value chain through industrial common technology R D. The panel data of 21 national autonomous innovation demonstration zones in China from 2014 to 2019 are selected to construct a measurement system of industrial transformation and upgrading level of national autonomous innovation demonstration zones covering four dimensions: industrial structure level, innovation-driven level, digital intelligence empowerment level and green development level based on the perspective of RJVs, and first evaluate the industrial transformation and upgrading level of national innovation demonstration zones using the entropy TOPSIS model, and then the fixed-effect model is used to explore the influencing factors of its industrial transformation and upgrading. The results of empirical analysis show that: the average level of industrial transformation and upgrading in demonstration zones is 0.470, which is at a medium level; the difference between Shenzhen, which has the highest level, and Wuchang Shi, which has the lowest level, is 0.545, with a large gap; the overall development level of eastern demonstration zones is higher than that of central and western zones; the average level of industrial transformation and upgrading in southern demonstration zones is 0.519, which is much higher than that of 0.3932 in the north, with an obvious gap. Further analysis of the influencing factors shows that: The R D innovation capacity of demonstration areas is positively related to industrial transformation and upgrading, and R D innovation drives the industries in demonstration areas to move upstream of the value chain through knowledge discovery and technology creation; The talent support capacity is positively related to industrial transformation and upgrading of demonstration areas trigger “knowledge spillover” by enhancing the stock of talents; The innovation service capability is positively related to the industrial transformation and upgrading of the demonstration area, and the demonstration area promotes industrial transformation and upgrading by building a good business environment and providing perfect guarantee services; The economic traction capability is positively related to the industrial transformation and upgrading, and the demonstration area promotes industrial transformation and upgrading by attracting the gathering of resource elements; The open cooperation capability of the demonstration area does not pass the significance test, indicating that the overall relationship between open cooperation and industrial transformation and upgrading of the demonstration area is not significant. In view of this, the demonstration zones should build a perfect R D innovation environment, create R D platforms dedicated to research on common industrial technologies, construct R D talent system, and explore differentiated industrial transformation and upgrading paths.