A research on the evolution of cooperative innovation network of new energy industry based on multi-dimensional proximities

Abstract

Abstract: The development of new energy industry is not only an important part of cultivating strategic emerging industries, but also an effective way to promote high-quality economic development and enhance China′s core competitiveness. However, the research on the Cooperative Innovation Network of China′s new energy industry from the perspective of multi-dimensional proximities needs to be strengthened. Therefore, based on the multi-dimensional perspective of proximity, through the social network analysis method, this paper deeply analyzes the evolution dynamics of China′s new Energy Industry Cooperative Innovation Network, explores its evolution law, and puts forward the corresponding countermeasures, it is expected to promote the development of new energy industry in China.
By manually searching the patent database of the State Intellectual Property Office, a sample of the patent data of the top 100 New Energy Enterprises from 1999 to 2018 was collected, with the help of UCINET6.0 software, the cooperative innovation network of each stage is visualized, and the related parameters of the Cooperative Innovation Network Atlas of new energy industry are analyzed. The performance of cooperative innovation is selected as the dependent variable, geographical proximity, technological proximity, organizational proximity and social proximity as the independent variables, and scale similarity and R&D experience similarity as the control variables, and carry on the standardization processing to these variable data. On this basis, the 1999-2018 period is divided into four stages, every five years for a stage, to establish a research model, using QAP multiple regression analysis, this paper explores the effects of geographical proximity, technological proximity, social proximity and organizational proximity on the evolution of cooperative innovation networks in new energy industries at different stages.
The results show that the influence of geographical proximity on the evolution of new energy industry cooperative innovation network is decreasing, and organizational proximity always plays a positive role in the evolution of new energy industry cooperative innovation network, the influence of technology proximity on the evolution of the innovation network is decreasing, and the social proximity is an important factor to promote the evolution of the Innovation Network, and its significance is always high.
In order to speed up the construction of a clean, low-carbon, safe and efficient modern new energy network in China and promote the sound development of the new energy industry, based on the results of the empirical study, this paper puts forward corresponding countermeasures and suggestions: firstly, to build an inter-regional new energy industry cooperation platform. Secondly, we will implement the technology-leading strategy, develop distinctive technological features, and establish a mechanism for regional mutual learning of new energy technologies and a mechanism for joint tackling complex technologies.
The contributions of this study are as follows: firstly, from the perspective of networking, a cooperative innovation network model of China′s new energy industry is constructed, this paper explores the law of cooperation and development of new energy industry in China, so as to find out the effective countermeasures to promote the cooperation and innovation of new energy industry. Secondly, through the multiple regression analysis of QAP, this paper investigates the influence degree of multi-dimensional proximities on the evolution of new energy industry cooperative innovation network, and puts forward the countermeasures to promote the good development of new energy industry.

Key words: multidimensional proximity, new energy industry, innovation network evolution, QAP analysis

Su Yi, Guo Jiaxing, Wang Wenjing. A research on the evolution of cooperative innovation network of new energy industry based on multi-dimensional proximities[J]. Science Research Management, 2021, 42(8): 67-74.

References

[1] 王朝阳, 陈宇峰, 金曦. 国际油价对中国新能源市场的传导效应研究[J]. 数量经济技术经济研究, 2018(4): 131-146.

Wang Chaoyang, Chen Yufeng, Jin Xi. Research on the effect of international oil prices pass-through on the China’s new energy market[J]. The Journal of Quantitative & Technical Economics, 2018(4): 131-146.

[2] Hairong Wang. Distribution efficiency evaluation of new energy industry based on microscopic graphics[J]. Acta Microscopica, 2019, 28(5): 1207-1218.

[3] 吴慧, 顾晓敏. 产学研合作创新绩效的社会网络分析[J]. 科学学研究, 2017, 35(10): 1578-1586.

Wu Hui, Gu Xiaomin. The social network analysis of cooperative innovation performance of industry-university-research institution[J]. Studies in Science of Science, 2017, 35(10): 1578-1586.

[4] 苏屹, 韩敏睿, 雷家骕. 基于社会网络分析的区域创新关联网络研究[J]. 科研管理, 2018, 39(12): 78-85.

Su Yi, Han Minrui, Lei Jiasu. An analysis of regional innovation correlation network in China based on social network analysis[J]. Science Research Management, 2018, 39(12): 78-85.

[5] 周灿, 曹贤忠, 曾刚. 中国电子信息产业创新的集群网络模式与演化路径[J]. 地理研究, 2019, 38(9): 2212-2225.

Zhou Can, Cao Xianzhong, Zeng Gang. Cluster networks and evolution path of China's electronic information industry innovation[J]. Geographical Research, 2019, 38(9): 2212-2225.

[6] 曹霞, 李传云, 林超然. 基于新能源汽车的专利合作网络演化研究[J]. 科研管理, 2019, 40(8): 179-188.

Cao Xia, Li Chuanyun, Lin Chaoran. A research on the evolution of patent cooperation networks based on new energy vehicles[J]. Science Research Management, 2019, 40(8): 179-188.

[7] 许冠南, 潘美娟, 周源. 基于QAP分析的国际知识流动影响要素研究——以光伏产业为例[J]. 科学学与科学技术管理, 2016, 37(10): 49-62.

Xu Guannan, Pan Meijuan, Zhou Yuan. A QAP-Based analysis of the key factors to the international knowledge flows: An empirical study of photovoltaic industry[J]. Science of Science and Management of S.& T., 2016, 37(10): 49-62.

[8] 任会明, 叶明确, 祝影. 基于教育网络的上海城市网络空间结构研究[J]. 经济地理, 2019, 39(8): 77-86.

Ren Huiming, Ye Mingque, Zhu Ying. The spatial structure of shanghai city network based on education network[J]. Economic Geography, 2019, 39(8): 77-86.

[9] 张雅蕊, 马玎. 多维邻近性对创新绩效的影响——以钢铁产业为例[J]. 财会月刊, 2018(12): 121-128.

Zhang Yarui, Ma Ding. The impact of multidimensional proximity on innovation performance: A case study of the steel industry[J]. Finance and Accounting Monthly, 2018(12): 121-128.

[10] Knoben J, Oerlemans L A G. Proximity and inter-organizational collaboration: A literature review[J]. International Journal of Management Reviews, 2006, 8(2): 71-89.

[11] Rallet A, Torre A. Is geographical proximity necessary in the innovation networks in the era of global economy?[J]. Geo Journal. 1999, 49(4): 373-380.

[12] 余谦, 白梦平, 覃一冬. 多维邻近性能促进中国新能源汽车企业的合作创新吗?[J]. 研究与发展管理, 2018, 30(6): 67-74.

Yu Qian, Bai Mengping, Qin Yidong. Does multi-dimensional proximity promote innovation cooperation between new energy automobile enterprises in China?[J]. R&D Management, 2018, 30(6): 67-74.

[13] Hong Wei, Su Y-S. The effect of institutional proximity in non-local university-industry collaborations: An analysis based on Chinese patent data[J]. Research Policy, 2013, 42(2): 454-464.

[14] Jaffe A B. Technological opportunity and spillovers of R&D: Evidence from firms' patents, profits, and market value[J]. American Economic Review, 1986, 26(5): 1023-1046.

[15] 阮平南, 王文丽, 刘晓燕. 基于多维邻近性的技术创新网络演化动力研究——以OLED产业为例[J]. 研究与发展管理, 2018, 30(6): 59-66.

Ruan Pingnan, Wang Wenli, Liu Xiaoyan. Dynamic evolution of technological innovation network based on multi-dimensional proximity——based on OLED industry[J]. R&D Management, 2018, 30(6): 59-66.

[16] 夏丽娟, 谢富纪. 多维邻近性视角下的合作创新研究述评与未来展望[J]. 外国经济与管理, 2014, 36 (11): 45-54.

Xia Lijuan, Xie Fuji. A literature review of collaborative innovation from a perspective of multi-dimensional proximity[J]. Foreign Economics & Management, 2014, 36 (11): 45-54.

[17] 赵炎, 王琦. 联盟网络的小世界性对企业创新影响的实证研究——基于中国通信设备产业的分析[J]. 中国软科学, 2013(4): 108-116.

Zhao Yan, Wang Qi. The empirical study on the impact of alliance network's small-world characteristics on innovation:The case of Chinese communication equipment industry's strategic alliances[J]. China Soft Science, 2013(4): 108-116.

[18] 曹贤忠, 曾刚, 司月芳, 张海娜. 企业创新网络与多维邻近性关系研究述评[J]. 世界地理研究, 2019, 28(5): 165-171.

Cao Xianzhong, Zeng Gang, Si Yuefang, Zhang Haina. Research progress on firm innovation networks and multi-dimensional proximity from the perspective of economic geography[J]. World Regional Studies, 2019, 28(5): 165-171.

[19] 阮平南, 王文丽, 刘晓燕. 技术创新网络多维邻近性演化研究——基于IBM专利合作网络数据[J]. 科技进步与对策, 2018, 35(8): 1-7.

Ruan Pingnan, Wang Wenli, Liu Xiaoyan. Multidimensional proximities' evolution of technological innovation network——an analysis of IBM patent cooperation network data[J]. Science & Technology Progress and Policy, 2018, 35(8): 1-7.

[20] 刘雅琴, 余谦. 新能源汽车产业技术创新网络的时空演化与创新集聚[J]. 大连理工大学学报（社会科学版）, 2020, 41(6): 36-44.

Liu Yaqin, Yu Qian. Temporal-spatial evolution and innovation agglomeration of technological innovation network in new energy vehicle industry[J]. Journal of Dalian University of Technology(Social Sciences), 2020, 41(6): 36-44.

[21] Desrochers P. Geographical proximity and the transmission of tacit knowledge[J]. Review of Austrian Economics, 2001, 14(1): 25-46.

[22] 刘凤朝, 肖站旗, 马荣康. 多维邻近性对技术交易网络的动态影响研究[J]. 科学学研究, 2018, 36(12): 2205-2214.

Liu Fengchao, Xiao Zhanqi, Ma Rongkang. The dynamic impact of multidimensional proximities on technology transaction network[J]. Studies in Science of Science, 2018, 36(12): 2205-2214.

[23] 杨春白雪, 曹兴, 高远. 新兴技术合作创新网络演化及特征分析[J]. 科研管理, 2020, 41(7): 20-32.

Yang Chunbaixue, Cao Xing, Gao Yuan. A research on the evolution path and characteristics of the emerging technology cooperation innovation network[J]. Science Research Management, 2020, 41(7): 20-32.

[24] 石乘齐. 基于组织间依赖的创新网络演化模型及仿真研究[J]. 管理工程学报, 2019, 33(1): 12-22.

Shi Chengqi. Modeling and simulation of the innovation-network evolution: An inter-organizational dependence view[J]. Journal of Industrial Engineering and Engineering Management, 2019, 33(1): 12-22.

[25] 刘国巍, 邵云飞. 产业链创新视角下战略性新兴产业合作网络演化及协同测度——以新能源汽车产业为例[J]. 科学学与科学技术管理, 2020, 41(08): 43-62.

Liu Guowei, Shao Yunfei. Evolution and collaborative measurement of strategic emerging industry cooperation network from the perspective of industrial chain innovation: Taking the new energy vehicle industry as an example[J]. Science of Science and Management of S.& T., 2020, 41(08): 43-62.