| 跨区域协同创新系统绩效测度与优化研究 |
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| 引用本文： | 吴卫红,冯兴奎,张爱美,唐方成.跨区域协同创新系统绩效测度与优化研究[J].科研管理,2022,43(7):29-36. |
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| 作者姓名： | 吴卫红 冯兴奎 张爱美 唐方成 |
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| 作者单位： | 北京化工大学经济管理学院，北京100029 |
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| 基金项目： | 北京市自然科学基金面上项目(9212013,2021.01—2023.12)；;教育部人文社会科学规划基金项目(17YJA630111,2017.03—2020.03)；;国家自然科学基金重点项目(71532003,2016.01—2020.12)； |
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| 摘 要： | 现有研究较少从跨区域维度考察协同创新，且在进行协同创新绩效测度的过程中往往忽视了参与各方的协同联系。本研究在明晰跨区域协同创新绩效内涵的基础上，构建跨区域协同创新复合系统，测算区域间协同投入和协同产出，进而采用DEA-Tobit两阶段模型对2013年-2016年间长三角地区和京津冀地区的跨区域协同创新绩效及其关键影响因素进行了实证研究，结果发现：（1）长三角内部各区域间协同创新绩效水平呈阶梯状多元化分布，其中江浙沪各自与皖的协同创新绩效水平高于江浙沪彼此间的协同创新绩效水平，并因地理邻近性表现出一定的差异；（2）京津冀内部各区域间协同创新绩效水平呈极端化分布，京津和京冀协同创新绩效达到很高的水平，而津冀协同创新绩效水平则较低；（3）长三角地区整体协同创新绩效水平高于京津冀地区，无论是技术效率还是和规模效率，京津冀地区相比长三角地区均有较大差距；（4）区域间协同度对于跨区域协同创新绩效具有显著正向影响，地理邻近性也能在一定程度上对跨区域协同创新绩效具有促进作用，而区域间经济发展差距则对跨区域协同创新绩效影响较小。最后提出了提升绩效的优化建议。
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| 关 键 词： | 跨区域协同创新绩效 区域协调发展 京津冀 长三角 |
| 收稿时间： | 2019-09-25 |
| 修稿时间： | 2020-03-04 |
Research on performance measurement and optimization of cross-regional collaborative innovation system |
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| Wu Weihong,Feng Xingkui,Zhang Aimei,Tang Fangcheng.Research on performance measurement and optimization of cross-regional collaborative innovation system[J].Science Research Management,2022,43(7):29-36. |
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| Authors: | Wu Weihong Feng Xingkui Zhang Aimei Tang Fangcheng |
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| Institution: | School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China |
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| Abstract: | The existing research seldom examines collaborative innovation from a cross-regional perspective, and in the process of measuring collaborative innovation performance, it is often overlooked that the collaborative connection of all parties involved, resulting in a certain deviation between the measured collaborative innovation performance and the actual situation, which is difficult to truly reflect the current situation and existing problems of the cross-regional collaborative innovation performance. Cross-regional collaborative innovation can realize the free flow of innovation elements among innovation subjects in different regions and produce a "1+1>2" system synergy effect. And cross-regional collaborative innovation can also provide endogenous motivation for regional coordinated development and plays an important driving role in the implementation of regional coordinated development strategy. Therefore, it is necessary to accurately measure the performance of cross-regional collaborative innovation and deeply explore the constraints of performance improvement.
Before measuring the cross-regional collaborative innovation performance, it is necessary to clarify the connotation of collaborative innovation performance. And previous studies have studied the collaborative innovation performance of innovation subjects such as industries, universities and research institutes from the dimensions of collaborative input and collaborative output. But in their process of researching, the independent innovation inputs and innovation outputs of the subjects were used to represent the collaborative inputs and the collaborative outputs between the subjects. That is, the collaborative innovation performance is understood as the sum of the respective innovation performance of the innovation subjects participating in the collaboration. However, the essence of collaborative innovation is the organic integration of innovation elements and the free flow of innovation elements among all the parties in the synergy. But the organic integration of innovation elements is not a simple summary of innovation resources of all parties, but through the integration of complementary resources, the complementary advantages of all parties can be realized, resulting in "1+1>2" synergy effect. The cross-border flow of innovation elements establishes synergy link between the parties. However, simply taking the innovation input and output of each party as the collaborative input and output of each other not only cuts off the synergistic connection between the parties, but also hardly reflects the synergy effect produced by the parties′ collaborative innovation. Collaborative innovation across regions is the organic integration and dynamic flow of innovative elements such as capital and manpower across regional boundaries and organizational boundaries among innovative entities in different regions, which results in a systematic superposition of non-linear effect and ultimately promotes regional collaborative development. Therefore, this study believes that the performance of cross-regional collaborative innovation is the performance of multi-innovation subjects in different regions cooperating with each other to jointly carry out scientific and technological innovation activities. And the key to accurately measure the performance of cross-regional collaborative innovation lies in the reasonable measurement of inter-regional collaborative inputs and collaborative outputs.
On the basis of clarifying the connotation of cross-regional collaborative innovation performance, this study built a composite system of cross-regional collaborative innovation. It measured the collaborative input and output of different regions to characterize the synergistic relationship between different regional innovation subjects, and then the DEA-Tobit two-stage model was used to measure the cross-regional collaborative innovation performance in the Yangtze River Delta region and Beijing-Tianjin-Hebei region from 2013 to 2016. Combined with the new economic geography, it analyzed the measurement results of cross-regional collaborative innovation performance, and the key influencing factors of cross-regional collaborative innovation performance were further identified and verified.
The research results found that: (1) The level of collaborative innovation performance among various regions within the Yangtze River Delta is distributed in a ladder-like and diversified manner. Among them, the level of collaborative innovation performance of Zhejiang-Anhui, Jiangsu-Zhejiang belong to the first echelon, Shanghai-Anhui, Jiangsu-Zhejiang belong to the second echelon, and Shanghai-Zhejiang and Shanghai-Jiangsu belong to the third echelon. The level of collaborative innovation performances of Jiangsu- Anhui, Zhejiang- Anhui and Shanghai- Anhui are higher than that between Jiangsu-Zhejiang, Zhejiang-Shanghai and Jiangsu-Shanghai, and shows a certain difference due to their geographical proximity. (2) The level of collaborative innovation performance among regions within Beijing, Tianjin and Hebei is extremely distributed. The collaborative innovation performances of Beijing-Tianjin and Beijing-Hebei all have reached a very high level, while the level of collaborative innovation performance of Tianjin-Hebei is far lower than that of Beijing-Tianjin and Beijing-Hebei due to the limitation of the insufficient scale of collaborative innovation, low technical efficiency and the inhibitory effect of similar resources advantages. (3) The overall collaborative innovation performance level in Yangtze River Delta is higher than that in Beijing, Tianjin and Hebei. Regardless of overall efficiency or technical efficiency and scale efficiency, there is a large gap between the Beijing-Tianjin-Hebei region and the Yangtze River Delta region. (4) The degree of inter-regional synergy has a significant positive impact on the performance of cross-regional collaborative innovation. Geographical proximity can also promote the performance of cross-regional collaborative innovation to a certain extent, while the gap of inter-regional economic development has a weak impact on the performance of cross-regional collaborative innovation.
Finally, two optimization suggestions for improving performance are put forward：(1) For the Yangtze River Delta region, it is necessary to clarify the core position of each region′s development, promote the rational transfer of innovative resources, and continuously improve the level of regional coordinated development. Jiangsu, Zhejiang and Shanghai should reasonably transfer the innovative resources that are excessively concentrated according to the current situation of regional economic and social development. Anhui should make reasonable use of its "value depression" and its geographical proximity advantages to sequentially undertake the innovative resource elements overflowing from Jiangsu, Zhejiang and Shanghai. (2) For the Beijing-Tianjin-Hebei region, while giving full play to the leading role of Beijing′s "core" in promoting the "two wings" of Tianjin and Hebei, attention should also be paid to strengthening the collaborative innovation links between the "two wings" and constantly seeking the joint points of Tianjin and Hebei′s collaborative innovation, such as setting up a collaborative innovation center according to the related industries of the two places, so as to promote the promotion of synergy between Tianjin and Hebei. |
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| Keywords: | cross-regional collaborative innovation performance coordinated regional development Beijing-Tianjin-Hebei Yangtze River Delta |
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