中国制造业转型升级政策的纵向协同性分析

科学学研究 ›› 2022, Vol. 40 ›› Issue (2): 237-246.

中国制造业转型升级政策的纵向协同性分析

胡志明¹,马辉民²,张金隆²,熊杰³,³,吴珊²,³

1. 华中科技大学
2. 华中科技大学管理学院
3.

收稿日期:2020-11-25 修回日期:2021-02-25 出版日期:2022-02-15 发布日期:2022-02-15
通讯作者: 张金隆
基金资助:
国家社会科学基金重大项目;国家自然科学基金

Vertical Coordination Analysis of Manufacturing Transformation and Upgrading Policy in China

Received:2020-11-25 Revised:2021-02-25 Online:2022-02-15 Published:2022-02-15
Contact: jinlong zhang

摘要/Abstract

摘要： 转型升级是当前制造业面临的核心议题，各级政府均将产业政策作为推动制造业高质量发展的重要选择。文章基于“政策目标-政策工具”分析框架对中央-河南-许昌三级政府的政策文本进行细粒度量化分析，解析中国制造业转型升级政策的纵向协同性问题。研究发现，制造业转型升级政策体系在纵向层级方面趋于耦合，其核心政策目标聚焦于信息化改造、创新能力提升，核心政策工具围绕着人才、资金、知识产权等领域；中央政府与地方政府在政策设计上存在一定差异，主要体现在政策目标的精细化以及政策工具的创新性方面；各级政府在政策工具选择上，已经形成相对一致的行为模式，即环境型政策工具、供给型政策工具、需求型政策工具的数量呈现阶梯式下降的差序格局。本文构建的研究方法为分析政策纵向协同性提供了参考，相关的对策建议对于政府部门优化政策设计具有一定启示意义。

Abstract: How to promote transform and upgrade becomes a challenge for all manufacturing firms. Industrial policy is of great significance to solve the bottleneck problem faced by manufacturing’s innovative development. This paper analyzes the industrial policy texts issued by Chinese government at central-provincial-municipal levels based on policy target-policy instrument patterns in order to identify the similarity characteristics between different levels of government. The results show that: (1)the policies pertaining to manufacturing transformation and upgrading show some similarities among all levels of government, their core policy targets focus on information transformation, innovation capabilities and their core policy instruments all include talent, capital, intellectual property; (2)the differences between central government local governments is obvious when it come to the operability of policy targets and the flexibility of policy instruments; (3) governments at all levels have formed a relatively stable behavior pattern regarding the choice of policy instruments, that is, the number of environmental policy instruments, supply-based policy instruments, and demand-based policy instruments has shown a stepwise decline. The research method provides reference for analyzing the vertical policy coordination, and the policy recommendations are beneficial to optimize the policy measures.

胡志明马辉民张金隆熊杰吴珊. 中国制造业转型升级政策的纵向协同性分析[J]. 科学学研究, 2022, 40(2): 237-246.

参考文献

[1] 彭纪生,仲为国,孙文祥.政策测量、政策协同演变与经济绩效:基于创新政策的实证研究[J].管理世界,2008,24(9):25-36. [2] 周志忍,蒋敏娟.整体政府下的政策协同:理论与发达国家的当代实践[J].国家行政学院学报,2010(6):28-33. [3] 吴宾,杨一民,娄成武.基于文献计量与内容分析的政策文献综合量化研究——以中国海洋工程装备制造业政策为例[J].情报杂志,2017,36(8):131-137. [4] Kivimaa P, Kern F. Creative destruction or mere niche support? Innovation policy mixes for sustainability transitions[J]. Research Policy, 2016, 45(1): 205-217. [5] Li L, Wang J, Gallachóir B ó, et al. Energy-intensive manufacturing sectors in China: policy priorities for achieving climate mitigation and energy conservation targets[J]. Climate Policy, 2019, 19(5): 598-610. [6] Bonvillian W B. Advanced manufacturing policies and paradigms for innovation[J]. Science, 2013, 342(6163): 1173-1175. [7] 李晨光,张永安.区域创新政策对企业创新效率影响的实证研究[J].科研管理,2014,35(9):25-35. [8] Yang Y, Hong J, Song G, et al. Technology policy, technology strategy and innovation performance: evidence from Chinese aircraft and spacecraft manufacturing[J]. Science and Public Policy, 2017, 44(5): 620-630. [9] Xiong Y, Yang X, Song M. Analysis on the effects of China's fiscal and taxation policy on exporting products of photovoltaic and high-end equipment manufacturing industries[J]. Journal of Renewable and Sustainable Energy, 2018, 10(1): 015906. [10] Guo Y, Guo X, Tian J, et al. Study of reciprocal effects between mandatory pollutant emissions reduction policy and structural change within the manufacturing sector in a Chinese coastal area[J]. Environmental science & technology, 2015, 49(21): 12840-12850. [11] 戴亦舒,叶丽莎,董小英,胡燕妮.CPS与未来制造业的发展:中德美政策与能力构建的比较研究[J].中国软科学,2018(2):11-20. [12] 贾根良,楚珊珊.中国制造愿景与美国制造业创新中的政府干预[J].政治经济学评论,2019,10(4):88-107. [13] Li L. China's manufacturing locus in 2025: With a comparison of “Made-in-China 2025” and “Industry 4.0”[J]. Technological Forecasting and Social Change, 2018, 135: 66-74. [14] Müller J M, Voigt K I. Sustainable industrial value creation in SMEs: A comparison between industry 4.0 and made in China 2025[J]. International Journal of Precision Engineering and Manufacturing-Green Technology, 2018, 5(5): 659-670. [15] Meijers E, Stead D. Policy integration: what does it mean and how can it be achieved? A multi-disciplinary review[C]//Berlin Conference on the Human Dimensions of Global Environmental Change: Greening of Policies-Interlinkages and Policy Integration. Berlin. 2004. [16] OECD. Government Coherence: The Role of the Centre of Government[R], Public Management Service/Public Management Committee, 2000. [17] Lambin E F, Meyfroidt P, Rueda X, et al. Effectiveness and synergies of policy instruments for land use governance in tropical regions[J]. Global Environmental Change, 2014, 28(1): 129-140. [18] Huang C, Su J, Xie X, et al. A bibliometric study of China’s science and technology policies: 1949–2010[J]. Scientometrics, 2015, 102(2): 1521-1539. [19] 张国兴,叶亚琼,管欣,尹江河,吕绚丽.京津冀节能减排政策措施的差异与协同研究[J].管理科学学报,2018,21(5):111-126. [20] 王浦劬,赖先进.中国公共政策扩散的模式与机制分析[J].北京大学学报(哲学社会科学版),2013,50(6):14-23. [21] Trichet J. International policy coordination in the Euro area: Toward an economic and fiscal federation by exception[J]. Journal of Policy Modeling, 2013, 35(3): 473-481. [22] 魏娜,孟庆国.大气污染跨域协同治理的机制考察与制度逻辑——基于京津冀的协同实践[J].中国软科学,2018(10):79-92. [23] 黄萃,任弢,李江,赵培强,苏竣.责任与利益:基于政策文献量化分析的中国科技创新政策府际合作关系演进研究[J].管理世界,2015,31(12):68-81. [24] Zhang L, Qin Q, Wei Y, et al. China's distributed energy policies: Evolution, instruments and recommendation[J]. Energy Policy, 2019: 55-64. [25] Yang C. Government policy change and evolution of regional innovation systems in China: evidence from strategic emerging industries in Shenzhen:[J]. Environment and Planning C-government and Policy, 2015, 33(3): 661-682. [26] 芈凌云,杨洁.中国居民生活节能引导政策的效力与效果评估——基于中国1996-2015年政策文本的量化分析[J].资源科学,2017,39(4):651-663. [27] Rio P D. On evaluating success in complex policy mixes: The case of renewable energy support schemes[J]. Policy Sciences, 2014, 47(3): 267-287. [28] 李景海.智能制造转型的产业政策选择[J].财经科学,2019(3):119-132. [29] Perry B. The Multi-level Governance of Science Policy in England[J]. Regional Studies, 2007, 41(8): 1051-1067. [30] Rothwell R, Zegveld W. Reindustrialization and Technology [M]. Longman:M.E.Sharpe,1985. [31] 范梓腾,谭海波.地方政府大数据发展政策的文献量化研究——基于政策“目标-工具”匹配的视角[J].中国行政管理,2017(12):46-53. [32] Huang C, Yang C, Su J. Policy change analysis based on “policy target–policy instrument” patterns: a case study of China’s nuclear energy policy[J]. Scientometrics, 2018, 117(2): 1081-1114. [33] Zhang G, Deng N, Mou H, et al. The impact of the policy and behavior of public participation on environmental governance performance: Empirical analysis based on provincial panel data in China[J]. Energy Policy, 2019: 1347-1354. [34] Guerzoni M, Raiteri E. Demand-side vs. supply-side technology policies: Hidden treatment and new empirical evidence on the policy mix[J]. Research Policy, 2015, 44(3): 726-747.