|
|
|
| Flowof Innovation Elements and Urban Green Innovation Development:The Spatial Moderating Effect ofData Elements' Flow Environment |
| Peng Ying,Li Shimei |
| (School of Economics, Jilin University, Changchun 130012, China) |
|
|
|
|
Abstract In the high-quality development stage of China's economy,green innovation is the fundamental driving force for green growth and green welfare which are the ultimate goals of green innovation. Strategies ofgreen sustainable development and innovative development are inevitable choices for China's high-quality economic development. It is also a must to realize the domestic cycle to promote the free flow of innovation elements in the construction of a unified national market. In addition, a good sharing and circulation environment of data element can not only promote the effective flow of data elements anddeeply tap the potential of data elements and fully release the dividends of data elements, but also guide the orderly flow and precise matching of innovative elements such as talents and capital. Then does innovation elements mobility promote urban green innovation development? What exactly is the role of the flow environment of data elements in the development of urban green innovation? An in-depth exploration of the above two issues provides an empirical reference for the formulation of policies related to the synergistic development of "innovation" and "green" in cities in the digital economyto fully explore the potential value of data elements and enable the development of urban green innovation.#br#This study uses the panel data of 280 prefecture-level cities in China from 2004 to 2019,and employs the gravity model to measure the flow of innovation elements and the environment index of data-flow. Then it measures the development efficiency of urban green innovation by the SBM-undesirable model, and uses the spatial Durbin model to empirically analyze the spatial impact of the flow of innovation elements on the development of urban green innovation, and explore the mitigation effect of innovation element mismatch in the flow environment of data elements, as well as its spatial adjustment effect on the development of urban green innovation.#br#The research finds that firstly, the flow of innovation elements only promotes the development of local green innovation by improving the efficiency of green technology, but also inhibits the development of green innovation in neighboring areas. Secondly, the flow environment of data elements can ensure the free flow of talents and capital innovation elements in an orderly manner, and improve the matching efficiency of urban talents and capital innovation elements, and there is an effect of mitigating the mismatch of innovation elements. Thirdly, under the spatial adjustment effect of the flow of data elements, from the perspective of local effects, the flow of talent innovation elements promotes the development of urban green innovation by affecting the efficiency of green technology and the progress of green technology, showing the characteristics of "dual-track drive"; while the element flow of capital innovation only improves green technological efficiency and the level of urban green innovation and development, showing the characteristics of "single-track drive". From the spatial spillover effect, the flow environment of data element can reasonably regulate the spatial flow of talent and capital innovation, generate mismatch mitigation effect ofinnovation elements and a positive spatial spillover effect on green innovation development in neighboring regions through improving green technology efficiency and enhance green technology progress. Thus, under the spatial regulation of flow environment of data elements, the driving characteristic of innovation elements flow to urban green innovation development is changed from being "single-track driven" to "double-track driven", and innovation elements flow has a strong positive spatial spillover effect on urban green innovation development.#br#The conclusions of this paper enrich the research on the relationship between the flow of innovation elements, the flow environment of data elements and the development of green innovation. Different from the previous literature, this study innovatively uses the gravity model to measure the flow environment indicators of urban data elements, and selects the number of employees in the ICT industry as the core variable. It takes the urban market environment, communication environment, and Internet environment as attractive variables, and uses the spatial Durbin model to test the spatial correlation and technology transmissions path related to the flow of innovation elements, the flow environment of data elements, and the development of green innovation. The research conclusions provide policy support for guiding the free flow of innovation elements in an orderly manner, fully releasing the dividends of data elements, and realizing the development of urban green innovation.#br#
|
|
Received: 09 March 2022
|
|
|
|
|
|
| [1] 陶长琪,徐茉.经济高质量发展视阈下中国创新要素配置水平的测度[J].数量经济技术经济研究,2021,38(3):3-22.[2] 孔艳芳,刘建旭,赵忠秀.数据要素市场化配置研究:内涵解构、运行机理与实践路径[J].经济学家,2021，33(11):24-32.[3] 杨艳, 王理, 廖祖君. 数据要素：倍增效应与人均产出影响——基于数据要素流动环境的视角[J].经济问题探索,2021，42(12):118-135.[4] 戴魁早,刘友金.要素市场扭曲与创新效率——对中国高技术产业发展的经验分析[J].经济研究,2016,51(7):72-86.[5] 白俊红,卞元超.要素市场扭曲与中国创新生产的效率损失[J].中国工业经济,2016,34(11):39-55.[6] 董直庆,胡晟明.创新要素空间错配及其创新效率损失:模型分解与中国证据[J].华东师范大学学报(哲学社会科学版),2020,52(1):162-178，200.[7] 李涛,刘国燕.时空压缩下研发要素流动是否提升了区域绿色创新效率[J].科技进步与对策,2021,38(19):37-46.[8] 海本禄,常鹏宇,张秀峰.创新要素流动与黄河流域高质量发展——基于地级市面板数据的空间计量研究[J].河南师范大学学报(自然科学版),2022,50(1):36-47.[9] 卓乘风,邓峰.创新要素区际流动与产业结构升级[J].经济问题探索,2018,39（5）:70-79.[10] 周叔莲,王伟光.科技创新与产业结构优化升级[J].管理世界,2001,17（5）:70-78，89-216.[11] ZHAO S L,CACCIOLATTI,LEE S H,et al. Regional collaborations and indigenous innovation capabilities in China: a multivariate method for the analysis of regional innovation systems[J]. Technological Forecasting and Social Change,2015,94(1):202-220.[12] 严成樑,龚六堂.熊彼特增长理论:一个文献综述[J].经济学(季刊),2009,8(3):1163-1196.[13] 李政,杨思莹.科技创新、产业升级与经济增长:互动机理与实证检验[J].吉林大学社会科学学报,2017,57(3):41-52，204-205.[14] SACCONE D, VALLI V. Structural change and economic development in China and India[J]. European Journal of Comparative Economics,2009,8:101-129.[15] 周杰文,张云,蒋正云.创新要素集聚对绿色经济效率的影响——基于空间计量模型的实证分析[J].生态经济,2018,34(6):57-62.[16] KLENOW H P J. Misallocation and manufacturing TFP in China and India[J]. Quarterly Journal of Economics, 2009, 4(4):1403-1448.[17] 王建冬,童楠楠.数字经济背景下数据与其他生产要素的协同联动机制研究[J].电子政务,2020,17(3):22-31.[18] 蔡跃洲,马文君.数据要素对高质量发展影响与数据流动制约[J].数量经济技术经济研究,2021,38(3):64-83.[19] 金环,于立宏.数字经济、城市创新与区域收敛[J].南方经济,2021,39(12):21-36.[20] 李士梅,彭影.区域制度环境对创新人才集聚的空间影响研究——基于人口老龄化的视角[J].吉林大学社会科学学报,2020,60(5):82-91,237.[21] 周亮,车磊,周成虎.中国城市绿色发展效率时空演变特征及影响因素[J].地理学报,2019,74(10):2027-2044.[22] 董会忠,李旋,张仁杰.粤港澳大湾区绿色创新效率时空特征及驱动因素分析[J].经济地理,2021,41(5):134-144.[23] 曹莉,邓峰,卓乘风.产业转移一定能提升绿色创新效率吗[J].生态经济,2022,38(4):53-59.[24] 张军,吴桂英,张吉鹏.中国省际物质资本存量估算:1952-2000[J].经济研究,2004,50(10):35-44.[25] 吴延兵.R&D存量、知识函数与生产效率[J].经济学(季刊),2006,164(3):1129-1156.[26] HALL B H, MAIRESSE J. Exploring the relationship between R&D and productivity in French manufacturing firms[J]. Journal of Econometrics, 1995,65(1)263-293.[27] 白俊红,王钺,蒋伏心,等.研发要素流动、空间知识溢出与经济增长[J].经济研究,2017,52(7):109-123.[28] 余奕杉,卫平.中国城市绿色全要素生产率测度研究[J].生态经济,2021,37(3):43-52.[29] 安虎森,颜银根,朴银哲.城市高房价和户籍制度:促进或抑制城乡收入差距扩大——中国劳动力流动和收入差距扩大悖论的一个解释[J].世界经济文汇,2011,55（4）:41-54.[30] 卞元超,吴利华,白俊红.财政科技支出竞争是否促进了区域创新绩效提升——基于研发要素流动的视角[J].财政研究,2020,41（1）:45-58.[31] 王欣亮,汪晓燕,刘飞.税收竞争有利于提升区域创新绩效吗——基于创新要素流动的空间机制分析[J].财贸研究,2021,32(6):98-110.[32] 王钺,刘秉镰.创新要素的流动为何如此重要——基于全要素生产率的视角[J].中国软科学,2017,32（8）:91-101.[33] AOKI S. A simple accounting framework for the effect of resource misallocation on aggregate productivity[J]. Journal of the Japanese and International Economies, 2012, 26(4):473-494. |
|
|
|
