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| Is Urban Innovation and Entrepreneurship Ecosystem Conducive to the Improvement of Enterprise Innovation Efficiency：Evidence from Listed Companies on STAR Market Board |
| Li Zhiguang,Li Yaokuang |
| (School of Management, Hefei University of Technology, Hefei 230009, China) |
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Abstract The establishment of a dual circulation development pattern in which domestic economic cycle plays a leading role while international economic cycle remains its extension and supplement is a major strategic measure for China to respond to the continuous spread of the COVID-19 pandemic and the resurgence of anti-globalization. Over the past two decades, China has achieved many innovations, but a large part of it is based on the huge demographic dividends, and the pursuit of hard technology innovation still requires continuous and unremitting efforts. Only by relying on independent innovation and breaking through the technical bottleneck issues can the domestic economic cycle be truly unblocked without being controlled by the U.S.. Therefore, how to actively mobilize and make use of the capital market, stabilize social and economic development, and promote continuous innovation of small and medium-sized enterprises is the key to China's sustainable economic growth.#br#This paper aims to measure the innovation efficiency of 65 Chinese enterprises registered on the STAR Market, and summarize the feasible efficiency improvement plans. The three-stage DEA method is used to calculate the innovation efficiency of the listed enterprises on the STAR Market and fsQCA is used for configuration analysis of determinants affecting innovation efficiency. We find the overall performance of innovation efficiency of listed enterprises is poor. The external environment for innovation and entrepreneurship, like policy environment, talent environment and financial support, can promote the improvement of enterprise innovation efficiency. While the regional GDP, financial subsidies and R&D are not conducive. The industrial environment and intermediary market are uncertain for the improvement of enterprise innovation efficiency. The realization paths of innovation efficiency of listed enterprises on STAR Market is composed of policy environment leading and intermediary market leading. The imbalance of urban innovation environment and lack of industrial environment and financial supports are the main reasons for low enterprise innovation efficiency. This study systematically analyzes the influences of the external institutional environment on the listed enterprises' innovation efficiency, and explains the internal logic and path for the enterprises to achieve the innovation efficiency from the perspective of configuration. These configurations are verified by the cases of existing listed companies, which can provide practical references for improving the innovation efficiency of scientific and technological enterprises.#br#Our theoretical contributions are mainly shown in the following two aspects. Firstly, we measure the innovation efficiency of listed companies on the STAR Market for the first time, taking full account of the influence of external environment to make the measurement results more accurate. Secondly, in view of the high degree of uncertainty and nonlinearity of causality in the process of enterprise innovation, we make the research results more convincing and explanatory from the perspective of configuration, which makes a certain contribution to the development of enterprise external environment theory.#br#In order to further optimize the allocation of innovation resources and improve innovation efficiency, this paper puts forward the following countermeasures and suggestions. Firstly, for enterprises dominated by external policy, in-depth research should be made on human resources to accelerate the training of new employees. Secondly, for enterprises dominated by intermediary market, the establishment of a trinity financing system with government support, multi-level capital market and bank interconnection is one of the ways to solve the financing needs of enterprises' innovative development. Thirdly, it is urgent to optimize industrial policies and talent policies for enterprises with unbalanced urban innovation environment, among which tax incentives and talent subsidies are one of the effective ways. Fourthly, for enterprises lacking industrial environment and financial support, the society should strengthen the protection of intellectual property rights, improve the transformation mechanism of high-tech achievements, and provide more policy support to scientific and technological enterprises.#br#
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Received: 03 December 2020
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| [1] 李倩.外部知识获取与企业创新绩效关系研究 :一个链式中介模型[D].长春:吉林大学,2019.[2] 邵传林.制度环境、财政补贴与企业创新绩效:基于中国工业企业微观数据的实证研究[J].软科学,2015,29(9):34-37,42.[3] 湛正群,杨华.外部环境、内部能力与高新技术企业创新绩效关系实证研究[J].科技管理研究,2016,36(15):136-142.[4] 赵阳,王芳.地方政府创新激励政策与企业创新绩效:来自党报与工业企业的经验证据[J].湖南科技大学学报(社会科学版),2018,21(2):61-68.[5] 张志华,陈向东.创新环境与企业协同创新绩效关系的实证研究[J].北京航空航天大学学报(社会科学版),2019,32(1):84-90.[6] 尚炜伦.营商环境对民营企业创新绩效的影响[J].国际经济合作,2020,36(5):127-134.[7] 孙泽宇,齐保垒.非正式制度的有限激励作用:基于地区信任环境对企业创新影响的实证研究[J].山西财经大学学报,2020,42(3):31-46.[8] 徐辉,周孝华.制度环境、产融结合对企业创新绩效的影响研究[J].科学学研究,2020,38(1):158-168.[9] 张振刚,易欢,陈雪瑶.创新网络资源整合、双元创新对制造企业创新绩效的影响:环境不确定性的调节作用[J].技术经济,2020,39(3):58-65,73.[10] 许骞.创新开放度、知识吸收能力对企业创新绩效的影响机制研究:基于环境动态性视角[J].预测,2020,39(5):9-15.[11] FRIED H O,LOVELL C A K,SCHMIDT S S,et al.Accounting for environmental effects and statistical noise in data envelopment analysis[J].Journal of Productivity Analysis,2002,17(1-2):157-174.[12] 李永周,黄薇,刘旸.高新技术企业研发人员工作嵌入对创新绩效的影响:以创新能力为中介变量[J].科学学与科学技术管理,2014,35(3):135-143.[13] 赵振宇.研发费用投入对企业价值影响的实证研究 :基于我国中小板市场的数据[D].呼和浩特:内蒙古财经大学,2014.[14] 赵旭梅.知识产权、无形资产与企业创新力的新解构[J].社会科学战线,2017(9):71-76.[15] 冯宗宪,王青,侯晓辉.政府投入、市场化程度与中国工业企业的技术创新效率[J].数量经济技术经济研究,2011,28(4):3-17,33.[16] 钱丽,王文平,肖仁桥.产权差异视角下我国区域高技术企业创新效率研究[J].管理工程学报,2019,33(2):99-109.[17] 余明桂,范蕊,钟慧洁.中国产业政策与企业技术创新[J].中国工业经济,2016,33 (12):5-22.[18] 刘满凤,李圣宏.基于三阶段DEA模型的我国高新技术开发区创新效率研究[J].管理评论,2016,28(1):42-52,155.[19] 徐书彬,叶晗堃.跨境电商上市企业经营效率评价:基于三阶段DEA模型[J].技术经济与管理研究,2019,40(10):75-81.[20] 吴雪.地域科技投入产出的DEA模型构建与分析[J].统计与决策,2014,30(3):109-112.[21] 赵文,李月娇,赵会会.政府研发补贴有助于企业创新效率提升吗:基于模糊集定性比较分析(fsQCA)的研究[J].研究与发展管理,2020,32(2):37-47.[22] 陈升,王京雷,谭亮.基于三阶段DEA的我国创新型产业集群投入产出效率研究[J].经济问题探索,2019,40(9):148-157.[23] 任跃文.政府补贴有利于企业创新效率提升吗:基于门槛模型的实证检验[J].科技进步与对策,2019,36(24):18-26.[24] 王钊,王良虎.税收优惠政策对高技术产业创新效率的影响:基于断点回归分析[J].科技进步与对策,2019,36(11):109-116.[25] 黄庆华,胡江峰,陈习定.环境规制与绿色全要素生产率:两难还是双赢[J].中国人口·资源与环境,2018,28(11):140-149.[26] 侯鹏,刘思明,建兰宁.创新环境对中国区域创新能力的影响及地区差异研究[J].经济问题探索,2014,35(11):73-80.[27] 聂鲲.产业集群、产业共享、人力资本互动研究 :以硅谷和中关村为例[D].长春:吉林大学,2017.[28] 张立杰,梁锦凯.我国丝绸之路经济带沿线省(市、区)高技术产业创新效率研究:基于DEA-Malmquist-Tobit方法[J].科技进步与对策,2019,36(13):68-75.[29] 清华大学启迪创新研究院.2015中国城市创新创业环境评价研究报告[M].北京:清华大学,2016.[30] 杜运周,贾良定.组态视角与定性比较分析(QCA):管理学研究的一条新道路[J].管理世界,2017,33(6):155-167.[31] LI Z G,ZHANG W Y,KONG A J,et al.Configuration analysis of influencing factors of technical efficiency based on DEA and fsQCA:evidence from China's medical and health institutions[J].Risk Management and Healthcare Policy,2021,14:49-65.[32] RAGIN C C.How to lure analytic social science out of the doldrums[J].International Sociology,2006,21(5):633-646.[33] CODURAS A,CLEMENTE J A,RUIZ J.A novel application of fuzzy-set qualitative comparative analysis to GEM data[J].Journal of Business Research,2016,69(4):1265-1270.[34] 张明,杜运周.组织与管理研究中QCA方法的应用:定位、策略和方向[J].管理学报,2019,16(9):1312-1323.[35] 袁红林,陈小锋.我国中小企业政策与中小企业成长环境的相关性:基于384家中小企业的实证[J].企业经济,2012,31(2):176-180.[36] 张鹏,于伟.金融集聚与城市发展效率的空间交互溢出作用:基于地级及以上城市空间联立方程的实证研究[J].山西财经大学学报,2019,41(4):1-16.[37] 陈明华,刘玉鑫,王山,等.金融发展对城市经济差距的影响效应及传导路径:基于长三角地区产业分解的经验考察[J].城市问题,2020,39(3):57-67.[38] 朱磊,徐晓彤,王春燕.产业环境、管理者任期与企业双元创新投资:来自创业板的经验数据[J].证券市场导报,2017,17(6):4-11,19. |
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