| 要素集聚对高技术产业创新能力发展的影响研究 |
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| 引用本文： | 田喜洲,郭新宇,杨光坤.要素集聚对高技术产业创新能力发展的影响研究[J].科研管理,2021,42(9):61-70. |
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| 作者姓名： | 田喜洲 郭新宇 杨光坤 |
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| 作者单位： | 1.重庆工商大学 工商管理学院，重庆400067；
2.重庆工商大学 经济学院，重庆400067；
3.重庆工商大学 长江上游经济研究中心，重庆400067 |
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| 摘 要： | 基于1996年至2016年的我国省际面板数据，本文聚焦产业要素集聚视角研究高技术产业创新能力的来源，利用莫兰指数(Moran′s I)进行空间相关检验，通过LM等系列检验确定本研究采用空间杜宾模型。结论指出：（1）总体来看我国高技术产业创新能力具有显著的空间集聚特点，创新能力存在区域间的空间正相关；（2）劳动、技术、人才、规模等要素集聚及税收优惠政策都对地区内高技术产业各阶段创新能力发展具有积极作用，资本集聚对产业创新转化存在逆向作用；（3）FDI和政策支持都对我国高技术产业总体创新能力存在约束，原因是FDI与政府资金目的导向差异性所致。
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| 关 键 词： | 产业要素集聚 高技术产业 创新能力 空间SDM模型 |
| 收稿时间： | 2018-09-29 |
| 修稿时间： | 2019-05-20 |
A research on the influence of factor agglomeration on the development of high-tech industry innovation ability |
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| Tian Xizhou,Guo Xinyu,Yang Guangkun.A research on the influence of factor agglomeration on the development of high-tech industry innovation ability[J].Science Research Management,2021,42(9):61-70. |
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| Authors: | Tian Xizhou Guo Xinyu Yang Guangkun |
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| Institution: | 1. School of Business Management, Chongqing Technology and Business University, Chongqing 400067, China;
2. School of Economics, Chongqing Technology and Business University, Chongqing 400067, China;
3. Research Center for Economy of Upper Reaches of the Yangtze River, Chongqing Technology and Business University, Chongqing 400067, China; |
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| Abstract: | Under the background of "the new normal" of China′s economy, the traditional growth model can no longer solve China′s main contradictions of development. Therefore, China implements an innovation-driven development strategy and attempts to shift the driving force of economic development from factor-driven to innovation-driven. High-tech industry forms a critical sector in our national innovation-driven plans. Particularly after USA took trade war against Chinese technological enterprises exampled as ZTE and Huawei, great attentions have given to the creativity and promotion of Chinese high-tech sectors. Nowadays, the overall creativity of China′s high-tech sector is poor, the shortage of critical technology, and the imbalance of industrial development influenced a lot the promotion of Chinese industry, even Chinese whole economy. So, development of high-tech sectors to uplift independent creativity relies on Chinese innovation-driven development plans. In addition, with the development of cluster economy, the agglomeration effect formed by industrial agglomeration is closely related to industrial innovation and development, and industrial innovation is inseparable from the development of cluster economy.
First, by going through extant literatures both home and abroad from the perspective of factor agglomeration, the theoretical mechanism concerning the impact of factor agglomeration on the creativity of high-tech industries is integrated, and the gaps in the extant related fields are found as following: (1) Most literatures are not complete in the collection of innovation-driven elements, focusing on the impact of one aspect, and ignoring the differences between industrial innovation regions, and less research on spatial distribution and spatial spillover effects, especially the influence of innovation factors in local areas on local innovation activities; (2) In the field of industrial innovation activities, most of the research focuses on the overall activities of innovation, ignoring the different stages of industrial innovation ability; (3) In terms of methods, the existing literature is largely using OLS, SLM and SEM for spatial analysis, the phenomenon of multiple cases is not taken into consideration, resulting in deviations in the model results. Based on these analyses, we put forward the first hypothesis: factor agglomeration influences the creativity of high-tech industry; second, the creativity of high-tech industry consists of three stages, which is input, output and transformation; third, the growth states of each agglomeration factor include time and space respectively. At the level of analysis, 11 indicators including innovation input, innovation output, innovation transformation, capital agglomeration, policy support, foreign direct investment, labor agglomeration, talent agglomeration, technology agglomeration, tax incentives and scale agglomeration were selected. Then, the spatial correlation of the elements and the innovation ability is tested by the spatial correlation Moran index. Conclusions show that the innovation ability from strong to weak can be divided into three regions in space, and the coastal region has economic and geographical advantages. Secondly, the central region has good innovation and development conditions such as manpower, capital and transportation, and its innovation ability is strong too; finally, the remote western and northern cold regions have a bad innovation environment and are not easy to generate innovation. Then through the correlation test of LM, Wald, LR and so on, the spatial Dubin model (SDM) is found the best model.
An empirical research is carried out according to the research hypothesis, and results are shown as follows: (1) Each stage of innovation capability of China′s high-tech industry presents the characteristics of resource scarcity in terms of spatial impact. There is a negative impact for input, but both output and transformation have positive impacts. There is a long period of innovation activity, and the spatial correlation of each stage is different, and the industry is affected by the degree of industrial agglomeration. The stage of innovation activities is different; (2) Talent, technology, scale, and policy orientation are the main sources of innovation capability of China′s high-tech industries. The agglomerations of labour, scale, talent, technology and tax incentives have positive impacts on the development of high-tech industry innovation capabilities in different regions. The agglomeration of capital imposes a constraining impact on change of high-tech industry innovation and; (3) High-tech industry Innovation and development are often subject to the nature of funding. Policy support has a negative impact on all stages of China′s high-tech industry innovation. Local foreign direct investment agglomeration has a negative impact on China′s high-tech industry innovation input and output, but it has a positive effect on innovation transformation because funding differs from the purpose of FDI, with the former relying on basic application-based R&D and the latter relying on interest-based R&D.
Lastly, some recommendations for promoting the creativity of high-tech industries are provided according to the findings above: (1) Optimizing the constructure of R&D capital investment, reducing R&D costs, and improving innovation efficiency. When developing local high-tech industry innovations, all regions should rationally allocate resources and plan industrial layout according to the stage of industrial innovation and development in the local and surrounding areas, so as to avoid causing errors in industrial innovation development and waste of resources. (2) Paying attention to the stage of industrial development and rationally plan the industrial layout. When improving the innovation capability of local high-tech industries, all regions should pay attention to whether the agglomeration factors owned by local and neighboring regions match the resources required in the stage of industrial innovation development, so as to avoid the inconsistency between innovation and development goals and actual development, resulting in waste of resources. (3) Setting up an innovation platform for high-tech industry, lifting scale effects, and promoting the core competence of high-tech industries. In developing high-tech industry innovations, local governments should clarify the capital composition and innovative development direction of local high-tech industry pillar enterprises. When attracting funds in each stage of innovation, local governments should distinguish and control the sources of funds. For example, a corresponding intermediary institution can be established to compare and screen projects such as capital source, whether to carry technology, and whether there is an industry-university research channel. In this way, we can improve the innovation efficiency and innovation ability of China′s high-tech industries. |
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| Keywords: | industrial factor agglomeration high-tech industry innovation capability spatial SDM model |
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