How the Allocation of Scientific and Technological Resources Promote the Growth of TFP in High-Tech Industries:An fsQCA Analysis Based on 29 Provincial Cases
Du Baogui,Yang Bangxing
(School of Humanities and Law, Northeastern University, Shenyang 110169, China)
杜宝贵,杨帮兴. 科技资源配置何以促进高技术产业TFP增长——基于29个省域案例的fsQCA分析[J]. 科技进步与对策, 2022, 39(23): 65-75.
Du Baogui,Yang Bangxing. How the Allocation of Scientific and Technological Resources Promote the Growth of TFP in High-Tech Industries:An fsQCA Analysis Based on 29 Provincial Cases. SCIENCE & TECHNOLOGY PROGRESS AND POLICY, 2022, 39(23): 65-75.
[1] QU C, ZHAO X. Total factor productivity analysis of high-tech industries for supply-side structural reform[C]. 13th International Conference on Advanced Computational Intelligence (ICACI),2021.[2] SONG Y, YU C, HAO L, et al. Path for China's high-tech industry to participate in the reconstruction of global value chains[J]. Technology in Society, 2021, 65(5):101486.[3] MCLAUGHLIN P. Measuring productivity[J]. Management Services, 2014, 58(4):31-37.[4] PENG J Y, XIE R, MA C, et al. Market-based environmental regulation and total factor productivity: evidence from Chinese enterprises[J]. Economic Modelling, 2021, 95: 394-407.[5] 胡亚茹,陈丹丹.中国高技术产业的全要素生产率增长率分解——兼对“结构红利假说”再检验[J].中国工业经济,2019,33(2):136-154.[6] 陈燕儿,蒋伏心,白俊红.中国高技术产业发展的质量检验——基于全要素生产率的视角[J].研究与发展管理,2018,30(6):117-127.[7] 卜洪运,陶玲玲,赵琳皓.高技术产业集群竞争力与全要素生产率关系研究——以京津冀为例[J].商业研究,2016,40(11):53-60.[8] 姜彤彤.高技术产业研发创新全要素生产率研究——基于价值链的视角[J].北京理工大学学报(社会科学版),2013,15(4):58-62,68.[9] 董会忠,张仁杰.中国高技术产业创新效率的空间格局及演变特征[J].统计与决策, 2021,37(3):106-111.[10] WAN Q C, CHEN J ,YAO Z ,et al. Preferential tax policy and R&D personnel flow for technological innovation efficiency of China's high-tech industry in an emerging economy[J]. Technological Forecasting and Social Change, 2022, 174: 121228.[11] ZHANG B, YUAN L, YUNG-HO C. Efficiency evaluation of China's high-tech industry with a multi-activity network data envelopment analysis approach[J]. Socio-Economic Planning Sciences, 2019, 66: 2-9.[12] 尹向飞.中国高技术产业全要素生产率测算及其分解研究:基于生产要素的视角[J].商学研究,2020,27(6):96-109.[13] 李沙沙,邹涛.政府干预、资本市场扭曲与全要素生产率——基于高技术产业的实证研究[J].东北财经大学学报,2017,19(2):24-32.[14] 汪浩瀚,徐建军,吕博.空间视角下要素市场扭曲与高技术产业TFP增长——基于电子及通信设备制造业的实证检验[J].经济地理,2019,39(9):129-137.[15] 万宜超,刘廷廷.融资结构对全要素生产率增长率影响的实证研究——以高技术产业为例[J].特区经济,2019,35(1):96-98.[16] 杨奕,赵洪进,岳碧霄.风险投资与高技术产业R&D全要素生产率增长——基于中国数据的实证[J].世界科技研究与发展,2013,35(6):749-755.[17] 汪泉.R&D投入、技术引进对高技术产业全要素生产率影响研究[J].企业科技与发展,2021,28(7):6-8.[18] 郑丽升,李若曦.技术创新投入对高技术产业TFP增长的影响研究[J].北京邮电大学学报(社会科学版),2019,21(2):60-67.[19] 艾育红,彭迪云.自主创新、对外开放和高技术产业全要素生产率——基于吸收能力视角的研究[J].金融与经济,2021,36(9):68-75.[20] 李若曦,赵宏中.技术活动、空间外溢与高技术产业TFP[J].科学学研究,2018,36(2):264-271,323.[21] 魏新颖,王宏伟.信息化对高技术产业全要素生产率的影响分析——基于面板门限回归模型的实证研究[J].统计与信息论坛,2017,32(12):34-41.[22] 冯志军,康鑫.知识产权保护、FDI与研发创新全要素生产率——基于中国区域高技术产业的实证研究[J].工业技术经济,2015,34(3):98-105.[23] 于世海.对外直接投资、空间溢出与中国高技术产业全要素生产率——基于空间杜宾面板模型的实证分析[J].广西社会科学,2018,34(8):86-91.[24] 李洪伟,任娜,陶敏,等.我国高技术产业全要素生产率分析——基于三阶段Malmquist指数方法[J].技术经济与管理研究,2013,20(8):41-46.[25] 李明智,王娅莉.我国高技术产业TFP及其影响因素的定量分析[J].科技管理研究,2005,25(6):34-38.[26] 徐一鸣,王宏.我国高技术产业全要素生产率测算及影响因素分析[J].市场研究,2020,27(2):27-29.[27] 苗玉宁,杨冬英.基于综合评价方法的中部地区科技资源配置效率分析[J].中国软科学,2020,35(3):134-149.[28] HONG J, FENG B, WU R Y, et al. Do government grants promote innovation efficiency in China's high-tech industries[J]. Technovation, 2016, 57:4-13.[29] YU L, LIU X, FUNG H G, et al. Size and value effects in high-tech industries: the role of R&D investment[J]. The North American Journal of Economics and Finance, 2018, 51:100853.[30] 田喜洲,郭新宇,杨光坤.要素集聚对高技术产业创新能力发展的影响研究[J].科研管理, 2021,42(9):61-70.[31] 盛亚,冯媛媛,施宇.政府科研机构科技资源配置效率影响因素组态分析[J].科技进步与对策,2022,39(8):1-9.[32] 段忠贤,吴鹏.科技资源配置效率影响因素组态与路径研究——基于中国内地30个省市的QCA分析[J].科技进步与对策, 2021,38(22):11-18.[33] 张曼,菅利荣.高技术产业产学研协同创新效率研究——基于行业的动态分析[J].当代经济管理,2021,43(3):25-33.[34] LI L B, LIU B L, LIU W L, et al. Efficiency evaluation of the regional high-tech industry in China: a new framework based on meta-frontier dynamic DEA analysis[J]. Socio-Economic Planning Sciences, 2017, 60: 24-33.[35] 张子珍,杜甜,于佳伟.科技资源配置效率影响因素测度及其优化分析[J].经济问题,2020,42(8):20-27.[36] CHEN X Q, LIU X W, ZHU Q W. Comparative analysis of total factor productivity in China's high-tech industries[J].Technological Forecasting and Social Change, 2022,175:121332.[37] CHEN X Q, LIU X W, GONG Z W, et al. Three-stage super-efficiency DEA models based on the cooperative game and its application on the R&D green innovation of the Chinese high-tech industry[J]. Computers & Industrial Engineering, 2021,156:107234.[38] CHEN K, SONG Y Y, PAN J F, et al. Measuring destocking performance of the Chinese real estate industry: a DEA-Malmquist approach[J]. Socio-Economic Planning Sciences, 2020, 69:100691.[39] MALMQUIST S.Index numbers and indifference surfaces[J]. Trabajos De Estadistica, 1953, 4(2):209-242.[40] RAGIN C C.Redesigning social inquiry : fuzzy sets and be-yond[M]. Chicago:University of Chicago Press ,2008.[41] FISS P C.Building better causal theories: a fuzzy set approach to typologies in organization research[J]. Academy of Management Journal,2011,54(2):393-420.[42] 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.[43] PARK Y K, FISS P C, SAWY O A E.Theorizing the multiplicity of digital phenomena: the ecology of configurations, causal recipes, and guidelines for applying QCA[J]. MIS Quarterly, 2020, 44(4):1493-1520.[44] SCHNEIDER C Q, WAGEMANN C. Set-theoretic methods for the social sciences: a guide to qualitative comparative analysis[M]. Cambridge: Cambridge University Press,2012.[45] CAMPBELL J T, SIRMON D G, SCHIJVEN M. Fuzzy logic and the market: a configurational approach to investor perceptions of acquisition announcements[J].Academy of Management Journal,2016,59(1):163-187.