在“碳达峰，碳中和”战略背景下，新能源汽车取代传统燃油车已成为汽车行业未来的发展趋势。近年来，我国大力支持新能源汽车产业发展，其市场规模不断扩大，截至2020年，中国已连续6年位居全球新能源汽车产销第一大国。虽然我国新能源汽车产业已实现了经济总量的增长，但在技术创新方面仍与世界顶尖水平具有较大差距，存在核心技术短板、过度依赖政府补贴、自主创新能力弱等问题。基于此，研究我国新能源汽车产业技术创新效率及影响因素，对掌握新能源汽车产业技术创新发展态势、探索提升技术创新效率路径具有重要意义。

首先，本文在梳理国内外相关文献、界定相关概念和阐述相关理论的基础上，以2013-2019年39家新能源汽车上市企业作为研究样本，分别构建DEA模型和DEA-Malmquist指数模型对新能源汽车产业技术创新效率进行静态和动态的测度与评价。其次，以技术创新综合效率作为被解释变量，选取企业规模、企业性质、资本结构和政府补贴强度等指标作为解释变量，构建Tobit模型对新能源汽车产业影响因素进行实证分析，并运用面板门槛模型进一步探究与检验重要影响因素政府补贴强度与技术创新效率之间的门槛效应。研究发现：当前我国新能源汽车产业技术创新效率整体较为低下，且处于微弱衰退趋势，这主要是由纯技术效率较低和技术退步所导致的；盈利能力、成长能力、运营能力和政府补贴对技术创新效率产生显著的正向影响，企业规模对技术创新效率产生显著的负向影响，国有企业的技术创新效率更高；政府补贴强度与技术创新效率之间存在显著的双重门槛效应，只有当政府补贴处于最优区间内时，才会对技术创新效率产生正向激励作用。最后，基于上述实证研究结果，从企业和政府两个层面提出了加大企业研发投入、提高技术创新成果转化能力、加强新能源汽车产业市场推广、明确政府补贴方向、加强知识产权保护和完善补贴监管体系的政策建议。

Under the background of the "carbon peak, carbon neutral" strategy, the replacement of traditional fuel vehicles by new energy vehicles has become the future development trend of the automotive industry. In recent years, my country has vigorously supported the development of the new energy vehicle industry, and its market size has continued to expand. As of 2020, China has ranked first in the world in the production and sales of new energy vehicles for six consecutive years. Although my country's new energy vehicle industry has achieved economic growth, it still lags far behind the world's top level in terms of technological innovation. There are problems such as shortcomings in core technologies, excessive reliance on government subsidies, and weak independent innovation capabilities. Based on this, it is of great significance to study the technological innovation efficiency and influencing factors of my country's new energy automobile industry to grasp the technological innovation development trend of the new energy automobile industry and explore ways to improve the efficiency of technological innovation.

First of all, on the basis of sorting out relevant domestic and foreign literature, defining relevant concepts and expounding relevant theories, this paper takes 39 new energy vehicle listed companies from 2013 to 2019 as research samples, and builds DEA model and DEA–Malmquist index model respectively. Static and dynamic measurement and evaluation of the technological innovation efficiency of the automobile industry. Secondly, taking the comprehensive efficiency of technological innovation as the explained variable, selecting indicators such as enterprise scale, enterprise nature, capital structure and government subsidy intensity as explanatory variables, constructing a Tobit model to empirically analyze the influencing factors of the new energy vehicle industry, and using the panel threshold model Further explore and test the threshold effect between government subsidy intensity and technological innovation efficiency of important influencing factors. The research found that: the overall technological innovation efficiency of my country's new energy vehicle industry is relatively low, and it is in a weak decline trend, which is mainly caused by low pure technical efficiency and technological regression; profitability, growth ability, operational ability and government subsidies Technological innovation efficiency has a significant positive impact, enterprise scale has a significant negative impact on technological innovation efficiency, and state-owned enterprises have higher technological innovation efficiency; there is a significant double threshold effect between government subsidy intensity and technological innovation efficiency. Only when government subsidies are in the optimal range will they have a positive incentive effect on the efficiency of technological innovation. Finally, based on the above empirical research results, from both the enterprise and the government level, it is proposed to increase the R&D investment of enterprises, improve the transformation ability of technological innovation achievements, strengthen the market promotion of the new energy vehicle industry, clarify the direction of government subsidies, strengthen the protection of intellectual property rights and improve subsidies. Policy recommendations for the regulatory system.

[1]李晓敏,刘毅然,杨娇娇.技术创新与新能源汽车销量:基于“创新引致需求理论”的经验检验[J/OL].大连理工大学学报(社会科学版):1-11[2022-06-05].

[2]田博文,高潇潇,姜伊朦.新能源汽车产业技术标准化如何发展——基于网络构建和创新价值链的标准文本分析[J].技术经济,2020,39(05):18-28.

[3]魏旭光,罗宜康,杨青松,张志颖.基于多维邻近性的新兴技术创新超网络演化研究——以新能源汽车产业为例[J].工业技术经济,2021,40(05):56-64.

[4]许秀瑞,田善武,王俊鹏.全球新能源汽车技术创新合作网络演化分析[J].工业技术经济,2020,39(10):65-73.

[5]陈开朗. CEO特征对专利产出的影响[D].山西大学,2015.

[6]王静宇.中国新能源汽车产业联盟发展现状及技术创新模式研究[J].科技管理研究,2016,36(22):162-171.

[7]熊勇清,范世伟,刘晓燕.新能源汽车财政补贴与制造商研发投入强度差异——制造商战略决策层面异质性视角[J].科学学与科学技术管理,2018,39(06):72-83.

[8]Pohl H , Yarime M . Integrating innovation system and management concepts: The development of electric and hybrid electric vehicles in Japan[J]. Technological Forecasting and Social Change, 2012, 79(8):1431-1446.

[9]Zhang J . R&D for Environmental Innovation and Supportive Policy: The Implications for New Energy Automobile Industry in China[J]. Energy Procedia, 2011, 5(1):1003-1007.

[10]Aigner Dennis,Lovell C.A.Knox,Schmidt Peter. Formulation and estimation of stochastic frontier production function models[J]. North-Holland,1977,6(1).

[11]Jin Hong et al. Do government grants promote innovation efficiency in China's high-tech industries?[J]. Technovation, 2016, 57-58 : 4-13.

[12]Eric C. Wang. R&D efficiency and economic performance: A cross-country analysis using the stochastic frontier approach[J]. North-Holland,2007,29(2):

[13]Oleksandr Movshuk. Restructuring, productivity and technical efficiency in China’s iron and steel industry, 1988–2000[J]. Journal of Asian Economics,2003,15(1):

[14]刘湘云,周铚翔.粤港澳大湾区技术创新效率评价研究——基于面板SFA随机前沿模型实证[J].科技管理研究,2020,40(07):67-74.

[15]方大春,张凡,芮明杰.我国高新技术产业创新效率及其影响因素实证研究——基于面板数据随机前沿模型[J].科技管理研究,2016,36(07):66-70+75.

[16]陈关聚.人力资本结构对重工企业技术效率的影响研究[J].技术经济与管理研究,2013(02):60-63.

[17]景保峰,周霞,吕健权.广东省高技术产业研发效率实证研究——基于随机前沿分析法[J].技术经济与管理研究,2011(10):96-100.

[18]Charnes A.,Cooper W.W.,Rhodes E.. Measuring the efficiency of decision making units[J]. North-Holland,1978,2(6).

[19]Ma Xiang,Liu Zhihui,Gao Yingfan,Liang Na. Innovation Efficiency Evaluation of Listed Companies Based on the DEA Method[J]. Procedia Computer Science,2020,174:

[20]Songbo Chen,Yuqiang Feng,Chaoran Lin,Changxiao Zhang. Innovation efficiency evaluation of new and high technology industries based on DEA-Malmquist index[J]. Journal of Interdisciplinary Mathematics,2017,20(6-7):

[21]Zhang W , Fang Q . Research on Technical Innovation Efficiency of Listed Company in Food Industry[J]. Advance Journal of Food Science & Technology, 2016, 11(11):759-764.

[22]罗良文,梁圣蓉.中国区域工业企业绿色技术创新效率及因素分解[J].中国人·资源与环境,2016,26(09):149-157.

[23]常广庶,朱利利.国有及国有控股高技术制造业技术创新效率评价[J].财会月刊,2020(20):70-77.

[24]方磊,赵紫剑.财政补贴政策对区域技术创新的门槛效应研究[J].经济问题,2020(09):54-61.

[25]白露珍,邱玉莲.长江经济带工业企业技术创新效率测度与时空演变[J].财会通讯,2021(18):85-88.

[26]吴传清,黄磊,文传浩.长江经济带技术创新效率及其影响因素研究[J].中国软科学,2017(05):160-170.

[27]吴士健,张洁,权英.基于两阶段串联DEA模型的工业企业技术创新效率及影响因素[J].科技管理研究,2018,38(04):181-189.

[28]王雅丽,黄永春.长江经济带科技创新效率测度及影响因素分析[J].统计与决策,2021,37(15):104-108.

[29]黄金枝,郝全,黄祎,刘锦志.环境约束下中国工业企业创新效率评价及影响因素研究[J].工业技术经济,2017,36(06):55-62.

[30]储姗姗,汪涛,夏四友,杨雪梅,陈静.创新价值链视角下企业创新效率差异及影响因素分析——基于江苏省国家高新区企业的验证[J].长江流域资源与环境,2021,30(02):269-279.

[31]朱慧明,张中青扬,吴昊,邹凯.创新价值链视角下制造业技术创新效率测度及影响因素研究[J].湖南大学学报(社会科学版),2021,35(06)

[32]楼旭明,徐聪聪.智能制造企业技术创新效率及其影响因素研究[J].科技管理研究,2020,40(04):1-7.

[33]Paige D , Bombach G . A Comparison of National Output and Productivity in the United Kingdom and the United States[J]. International Affa , 1959, 36(3).

[34]Anthony Howell. ‘Indigenous’ innovation with heterogeneous risk and new firm survival in a transitioning Chinese economy[J]. Research Policy,2015,44(10):

[35]Marshall S. Jiang,Oana Branzei,Jun Xia. DIY: How internationalization shifts the locus of indigenous innovation for Chinese firms[J]. Journal of World Business,2016,51(5):

[36]Szczygielski K , Grabowski W , Pamukcu M T , et al. Does government support for private innovation matter? Firm-level evidence from two catching-up countries[J]. Research Policy, 2017, 46(1):219-237.

[37]Zhenji Jin,Yue Shang,Jian Xu. The Impact of Government Subsidies on Private R&D and Firm Performance: Does Ownership Matter in China’s Manufacturing Industry?[J]. Sustainability,2018,10(7).

[38]于潇宇,庄芹芹.政府补贴对中国高技术企业创新的影响——以信息技术产业上市公司为例[J].技术经济,2019,38(04):15-22.

[39]Jin Hong et al. Do government grants promote innovation efficiency in China's high-tech industries?[J]. Technovation, 2016, 57-58 : 4-13.

[40]安同良,周绍东,皮建才.R&D补贴对中国企业自主创新的激励效应[J].经济研究,2009,44(10):87-98+120.

[41]Austan Goolsbee. Does Government R&D Policy Mainly Benefit Scientists and Engineers?[J]. The American Economic Review,1998,88(2).

[42]吴剑峰,杨震宁.政府补贴、两权分离与企业技术创新[J].科研管理,2014,35(12):54-61.

[43]陈庆江.政府科技投入能否提高企业技术创新效率?[J].经济管理,2017,39(02):6-19.

[44]张帆,孙薇.政府创新补贴效率的微观机理:激励效应和挤出效应的叠加效应——理论解释与检验[J].财政研究,2018(04):48-60.

[45]郑玉.政府补贴的创新效应——兼论不同类型创新的最适补贴区间[J].经济经纬,2020,37(04):142-149.

[46]Dominique Guellec,Bruno Van Pottelsberghe De La Potterie. THE IMPACT OF PUBLIC R&D EXPENDITURE ON BUSINESS R&D[J]. Economics of Innovation and New Technology,2003,12(3)

[47]罗雪婷.政府补助对高技术企业技术创新效率的影响研究——基于东中西区域的门槛分析[J].调研世界,2020(10):33-41.

[48]李茜,王昊,葛鹏.中国新能源汽车发展历程回顾及未来展望[J].汽车实用技术,2020(09):285-288.

[49]约瑟夫熊彼特.经济发展理论[M].北京:商务印书馆,2000:73-74页．

[50]王雅彬.创新理论研究发展、现状及趋势分析[J].现代商业,2022(03):11-13..

[51]李瑛,张兴恒.制度创新理论的研究探索[J].现代经济(现代物业下半月刊),2009,8(01):6-7

[52]Koopmans T C . An Analysis of Production as an Efficient Combination of Activities[J]. Analysis of Production and Allocation, 1951.

[53]Leibenstein H . Allocative efficiency and X-efficiency[J]. American Economic Review, 1966, 56.

[54]Afriat S N , Review I E , Cole H L . Efficiency Estimation of Production Function[J]. International Economic Review, 1972, 13(3):568-598.

[55]Fritsch M, Slavtchev V. How does industry specialization affect the efficiency of regional innovation systems?[J]. Annals of Regional Science, 2010, 45(1):87-108.

[56]柳卸林.企业技术创新管理[M].北京:科学技术文献出版社, 1997.

[57]吕海萍,池仁勇.基于产业波及效应视角的浙江省战略性新兴产业技术创新效率研究[J].科技管理研究,2016,36(21):91-97+122.

[58]王婧仪. 中部地区高技术产业技术创新效率及影响因素研究[D].哈尔滨商业大学,2021.

[59]韩振海,李国平.国家创新系统理论的演变评述[J].科学管理研究,2004(02):24-26+71.

[60]Farrell M J . The Measurement of Productive Efficiency[J]. Journal of the Royal Statistical Society, 1957, 120(3):253-290.

[61]Hansen M T, Birkinshaw J. The innovation value chain[J]. Harvard Business Review, 2007, 85(6):121.

[62]汪文生,考晓璇.高质量发展视角下环渤海地区物流效率测度研究——基于三阶段DEA模型[J].商业研究,2021(04):75-84.

[63]R. Färe,S. Grosskopf,B. Lindgren,P. Roos. Productivity changes in Swedish pharamacies 1980–1989: A non-parametric Malmquist approach[J]. Journal of Productivity Analysis,1992,3(1-2).

[64]方正起,张宝承,秦杰.创新价值链视角下我国上市军工企业技术创新效率评价研究[J].经济与管理评论,2019,35(06):37-48.

[65]李爽.R&D强度、政府支持度与新能源企业的技术创新效率[J].软科学,2016,30(03):11-14

[66]彭雯婷. 新能源汽车上市企业技术创新效率及影响因素研究[D].湖北大学,2016.

[67]Tobin, James. Estimation of Relationships for Limited Dependent Variables[J]. Econometrica, 1958, 26(1):24-36.

[68]申俊喜,刘元雏.战略性新兴产业产能利用率及影响因素——以新一代信息技术产业为例[J].中国科技论坛,2019(03):61-70+91. Bruce E. Hansen. Threshold effects in non-dynamic panels: Estimation, testing, and inference[J]. Journal of Econometrics,1999,93(2).

[69]Bruce E. Hansen. Threshold effects in non-dynamic panels: Estimation, testing, and inference[J]. Journal of Econometrics,1999,93(2).

[70]吴剑峰,杨震宁.政府补贴、两权分离与企业技术创新[J].科研管理,2014,35(12):54-61.