基于两阶段价值链视角,将产学研知识流动分为知识研发和知识转化2个过程,探究长三角城市群产学研知识流动效率对先进制造业的影响机制,并分析空间溢出效应。结果表明：①2007—2020年长三角城市群知识流动效率整体呈现块状集聚特征,先进制造业发展水平由西北向东南递增;各城市间知识研发效率和知识转化效率的绝对差异分别表现出增大和减小趋势,而先进制造业的绝对差异逐渐减小。②知识流动效率对先进制造业的影响显著为正向,且知识转化效率对先进制造业的促进程度大于知识研发效率。③知识流动效率可以通过推动城市产业升级和技术扩散促进先进制造业发展,但这种作用机制存在差异。④知识研发效率和知识转化效率具有显著的正向空间溢出效应,对本地区及邻近地区先进制造业均产生促进作用。
Based on the two-stage value chain perspective, the knowledge flow of industry-university-research is divided into two stages: the stage of knowledge research and development and the stage of knowledge transformation. This study explores the impact mechanism of the knowledge flow efficiency of industry-university-research on the advanced manufacturing in the Yangtze River Delta urban agglomeration,and analyzes its spatial spillover effect. The results show that: 1) From 2007 to 2020,the overall efficiency of knowledge flow showed a blocky agglomeration feature in the Yangtze River Delta urban agglomeration,and the development level of advanced manufacturing gradually increased from the northwest to the southeast. The absolute differences in the knowledge research and development efficiency and the knowledge transformation efficiency among cities showed an increasing and decreasing trend respectively,while the absolute differences in advanced manufacturing gradually decreased. 2) The impact of knowledge flow efficiency on advanced manufacturing was significantly positive,and the promotion of knowledge transformation efficiency on advanced manufacturing was greater than that of knowledge research and development efficiency. 3) The efficiency of knowledge flow can promote the development of advanced manufacturing by promoting urban industrial upgrading and technological diffusion,but there are differences in the mechanism of this effect. 4) The efficiency of knowledge research and development and the efficiency of knowledge transformation have a significant positive spatial spillover effect,which has a promoting effect on the advanced manufacturing industry in the local and neighboring regions.
[1] 王晓红,张少鹏,张奔. 创新型城市试点政策与城市产学研知识流动——基于长三角城市群的空间DID模型分析[J]. 科学学研究,2021,39(9):1671-1682.
[2] 孙畅,吴芬. 中国高端服务业与先进制造业匹配发展的空间分异及收敛性[J]. 数量经济技术经济研究,2020,37(12):3-24.
[3] Díaz-Mora C,Gandoy R,Gonzalez-Diaz B.Strengthening the stability of exports through GVC participation:The who and how matters[J]. Journal of Economic Studies,2018,45(3):610-637.
[4] Schuh G,Scheuer T,Nick G,et al.A two-step digitalization level assessment approach for manufacturing companies[J]. Procedia Manufacturing,2021,54:25-30.
[5] Paschou T,Rapaccini M,Adrodegari F,et al.Digital servitization in manufacturing:A systematic literature review and research agenda[J]. Industrial Marketing Management,2020,89:278-292.
[6] 唐晓华,张欣珏,李阳. 中国制造业与生产性服务业动态协调发展实证研究[J]. 经济研究,2018,53(3):79-93.
[7] 王彬燕,王士君,田俊峰,等. 中国高技术产业及其细分行业发展时空演变特征[J]. 经济地理,2017,37(9):135-142.
[8] 冯峦叶,崔春莹,周昱岑,等. 国家制造业创新中心设立能否助推先进制造业发展——基于湖北省的准自然实验[J]. 科技进步与对策,2022,39(17):62-71.
[9] Bag S,Gupta S,Kumar S.Industry 4.0 adoption and 10R advance manufacturing capabilities for sustainable development[J]. International Journal of Production Economics,2021,231:107844.
[10] Garza-Reyes J A,Christopoulos C,Kumar A,et al. Deploying Kaizen events in the manufacturing industry:An investigation into managerial factors[J]. Production Planning & Control,2022,33(5):427-449.
[11] 汪芳,石鑫. 中国制造业高质量发展水平的测度及影响因素研究[J]. 中国软科学,2022(2):22-31.
[12] 余子鹏,田璐. 要素禀赋、产业环境与我国制造业发展质量[J]. 科研管理,2020,41(12):103-111.
[13] Damijan J,Haller S A,Kaitila V,et al.The performance of trading firms in the services sectors-comparable evidence from four EU countries[J]. The World Economy,2015,38(12):1809-1849.
[14] 吴继英,李琪. 长三角地区先进制造业与现代服务业融合的时空演变及影响因素[J]. 科技管理研究,2023,43(10):98-107.
[15] 袁荣,曹贤忠,曾刚. 国家重点实验室知识网络空间结构特征及影响因素[J]. 经济地理,2022,42(6):113-120,78.
[16] 邹琳,曾刚,朱贻文,等. 长江经济带装备工业知识空间网络特征及优化路径[J]. 经济地理,2019,39(11):113-122.
[17] 原毅军,孙大明. 合作研发影响制造业技术升级的机理及实证研究[J]. 经济学家,2017(8):49-55.
[18] 单勤琴. 空间关联视角下协同创新对装备制造业产业结构升级的影响[J]. 系统工程,2020,38(3):17-26.
[19] 张彭. 绿色技术创新对制造业全球价值链攀升的影响研究[J]. 经济体制改革,2023(1):135-144.
[20] 单春霞,李倩,丁琳. 知识产权保护、创新驱动与制造业高质量发展——有调节的中介效应分析[J]. 经济问题,2023 (2):51-59.
[21] 马茜,张红兵,廖甍. 数字基础设施建设、知识流动与城市高质量发展——准自然实验与空间溢出的经验证据[J]. 产业经济研究,2022(6):114-128.
[22] 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.
[23] 孙大明,原毅军. 空间外溢视角下的协同创新与区域产业升级[J]. 统计研究,2019,36(10):100-114.
[24] 吴松强,黄盼盼,蔡文洁,等. 知识溢出与先进制造业集群成长——企业创新关联的中介效应研究[J]. 科学学研究,2022,40(3):516-524.
[25] Bourreau M,Verdier M.Cooperative and noncooperative R&D in two-sided markets[J]. Review of Network Economics,2014,13(2):175-190.
[26] 李春梅. 中国制造业发展质量的评价及其影响因素分析——来自制造业行业面板数据的实证[J]. 经济问题,2019(8):44-53.
[27] 庄毓敏,储青青. 金融集聚、产学研合作与区域创新[J]. 财贸经济,2021,42(11):68-84.
[28] 方刚,谈佳馨. 互联网环境下产学研协同创新的知识增值研究[J]. 科学学研究,2020,38(7):1325-1337.
[29] 刘成坤,林明裕. 制造业高质量发展水平的统计测度及时空演变特征研究[J]. 当代经济管理,2023,45(8):56-68.
[30] 江艇. 因果推断经验研究中的中介效应与调节效应[J]. 中国工业经济,2022(5):100-120.
[31] Lesage J,Pace R K.Introduction to Spatial Econometrics[M]. Chapman and Hall/CRC,2009.
[32] 张虎,韩爱华. 制造业与生产性服务业耦合能否促进空间协调——基于285个城市数据的检验[J]. 统计研究,2019,36(1):39-50.
[33] 王欢芳,彭琼,傅贻忙,等. 先进制造业与生产性服务业融合水平测度及驱动因素研究[J]. 财经理论与实践,2023,44(1):114-121.
[34] 范德成,李盛楠. 考虑空间效应的高技术产业技术创新效率研究[J]. 科学学研究,2018,36(5):901-912.
[35] 王默,魏先彪,彭小宝,等. 国家创新型城市效率评价研究——基于两阶段DEA模型[J]. 北京理工大学学报:社会科学版,2018,20(6):65-74.
[36] 付明卫,王鹤. 行政边界、技术扩散与共同富裕[J]. 经济学动态,2023(5):55-71.
[37] Arellano M,Bond S.Some tests of specification for panel data:Monte Carlo evidence and an application to employment equations[J]. The Review of Economic Studies,1991,58(2):277-297.
[38] Elhorst J P.Matlab software for spatial panels[J]. International Regional Science Review,2014,37(3):389-405.
