Inter-governmental cooperation mechanism of science and technology innovation policy based on multi-level networks

Abstract

Abstract: The diversification of innovation subjects and the increasing span of innovation fields make the governance of collaborative innovation more difficult. How to promote innovation policy coordination through intergovernmental cooperation and provide institutional guarantee for collaborative innovation becomes particularly important. As the premise of optimizing resource allocation and realizing intergovernmental coordination, intergovernmental cooperation can provide an important guarantee for the effective and orderly operation of public affairs management and the realization of public interests. However, inter-governmental cooperation not only has the impetus but also faces heavy resistance in the process of policy formulation and implementation due to the complex environment of public governance, the pursuit of the interests of government departments and the institutional constraints outside government departments. Current scholars have analyzed the impetus and resistance of intergovernmental cooperation from the perspective of governance environment and the relationship between policy subjects. The research methods mainly focus on qualitative analysis such as theoretical deduction and grounded theory, but lack quantitative research. The research content explores the power and resistance of inter-governmental cooperation from the public governance environment and the relationship among policy subjects at the same level, and there is a lack of cross-level research. However, the policy network is a complex relationship network formed by multiple subjects in the process of policy formulation and implementation. It is not only dynamic but also hierarchical. The policy network includes horizontal cooperation among central policy subjects or local policy subjects, as well as vertical central-local relations. Different levels of networks are interdependent and influence mutually. Therefore, this paper explores the mechanism of inter-governmental cooperation from a cross-level perspective.
This research constructs a multi-level network model of intergovernmental cooperation by using the cooperation and citation relationship among the policy subjects presented in the policy texts promulgated by the Central Government and Beijing from 2012 to 2017. The method of Multilevel Exponential Random Graph Models is used in the model construction. The purpose of the research is to break through the limitation of the traditional single-level intergovernmental cooperation in theory. Placing the central and local governments in the same framework is conducive to enrich the quantitative study of inter-governmental cooperation. It is beneficial to the optimization of cooperation relations at the same level and the governance of cross-level policy response relations, thus improving the comprehensiveness and effectiveness of policy formulation and promoting the smooth implementation of policies in terms of application. The research is mainly based on four dimensions: the characteristics of central policy subject and the cooperation of central policy subjects, the characteristics of policy diffusion of central policy subject and the cooperation of central policy subjects, the characteristics of policy response of local policy subject and the cooperation of local policy subjects, as well as the relational characteristics of central policy subjects and the cooperation of local policy subjects.
The study points out that the number of partners, the history of cooperation and the common partners play an important role in promoting cooperation among central policy subjects (Hypothesis H1, H2, H3). In terms of the characteristics of the policy diffusion of the central policy subjects, the smaller administrative influence promotes the cooperation of the central policy subjects (Hypothesis H4). However, the common target of policy diffusion will hinder the cooperation of central policy subjects (Hypothesis H5). In terms of the characteristics of policy response of local policy subjects, policy response and different policy respondents hinder the cooperation of local policy subjects (Hypothesis H6, H7b). However, the common policy respondents will promote the cooperation of local policy subjects (Hypothesis H7a). In terms of the relational characteristics of central policy subjects, the cooperation of central policy subjects promotes the cooperation of local policy subjects (Hypothesis H8), while the number of partners of the central policy subjects hinders the cooperation of the local policy subjects (Hypothesis H9).
Subsequently, this paper uses the method of Multilevel Exponential Random Graph Models to construct a multi-level network model of inter-governmental cooperation based on the central and local levels and carries out the empirical analysis. The empirical results show that the proposed multi-level network model of inter-governmental cooperation can reflect the real observation network. They also show that Hypothesis H7b is rejected, Hypothesis H8 is not significant, and other hypotheses are tested. It follows that the policy subjects with more partners and cooperation history are more likely to attract other policy subjects to cooperate with them for the central policy subjects. Policy subjects with great influence on policy diffusion have a promoting effect on the cooperation of policy subjects at the same level. It is easier to form cooperative relations between central policy subjects with common partners and different policy diffusion objects. As far as local policy subjects are concerned, policy similarity promotes cooperation among local policy subjects at the same level. When the response of local policy subjects to the central policy can meet the needs of heterogeneous resource accumulation to overcome their own limitations, cooperation with policy subjects at the same level will be reduced. The number of partners of central policy subjects will inhibit the cooperation of local policy subjects at the same level. However, the promotion effect of cooperation among central policy subjects on cooperation among local policy subjects is not significant.
According to the research results, combined with policy formulation and implementation practice, the study puts forward the following countermeasures and suggestions. First, the cooperation among central policy subjects should be strengthened, and the coordinating role of the policy subjects with strong policy effectiveness and high policy similarity in the cooperation among the central policy subjects should be paid attention to in policy formulation. Secondly, the central policy subjects should clarify the characteristics of its policy diffusion, find its own shortcomings and improve itself to increase the scientific and effectiveness of policy formulation in the process of policy implementation. Finally, local policy subjects should strengthen cooperation with policymakers at the same level and respond to the central policy subjects at the same time.
The multi-level network analysis model of intergovernmental relations based on Multilevel Exponential Random Graph Models can be further extended to the policy network of prefecture-level cities, county-level cities and other administrative levels to explore more inter-governmental cooperation mechanisms. This can provide a powerful reference for optimizing and governing inter-governmental relations.

Key words: inter-governmental cooperation, science and technology innovation policy, multi-level network, policy network

Liu Xiaoyan, Hou Wenshuang, Shan Xiaohong. Inter-governmental cooperation mechanism of science and technology innovation policy based on multi-level networks[J]. Science Research Management, 2021, 42(3): 97-108.

References

[1] 何精华.府际合作治理：生成逻辑、理论涵义与政策工具[J].上海师范大学学报(哲学社会科学版)，2011，40（6）：41-48.

He Jinghua. Inter-governmental cooperative governance:Formation logic,theoretical concept and policy tools[J]. Journal of Shanghai Normal University( Philosophy&Social Sciences Edition), 2011,40(6): 41-48.

[2] 任维德. “一带一路”战略下的府际合作创新研究[J].内蒙古社会科学(汉文版)，2016，37（1）：1-6.

Ren Weide. Research on inter governmental cooperation and innovation under the "the belt and road initiatives" strategy[J]. Inner Mongolia Social Sciences, 2016,37(1): 1-6.

[3] 栾文敬，郭少云，王恩见，等.府际合作治理视域下医养结合部门协同研究[J].西北大学学报(哲学社会科学版)，2018，48（3）：64-73.

Ruan Wenjing, Guo Shaoyun, Wang Enjian, et al. An study on the departments collaborationin the context of intergovernmental cooperation governance[J]. Journal of Northwest University( Philosophy and Social Sciences Edition), 2018,48(3): 64-73.

[4] Christopoulos S, Demir C, Kull M. Cross-sectoral coordination for sustainable solutions in Croatia: The (meta) governance of energy efficiency[J]. Energy Policy, 2016,99: 57-87.

[5] Trencher G P, Yarime M, Kharrazi A. Co-creating sustainability: cross-sector university collaborations for driving sustainable urban transformations[J]. Journal of Cleaner Production, 2013,50(6): 40-55.

[6] 黄萃，任弢，李江，等.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（12）：68-81.

Huang Cui, Ren Tao, Li Jiang, et al. Responsibility and interest:Evolution of intergovernmental cooperation in China's science and technology innovation policy based on quantitative analysis of policy documents[J]. Management World, 2015(12): 68-81.

[7] Allison G T. Essence of decision[M]. Boston Little:Addison-Wesley Educational Publishers, 1999.

[8] Ulybina O. Interaction, cooperation and governance in the Russian forest sector[J]. Journal of Rural Studies, 2014,34(2): 246-253.

[9] Gerke A, Babiak K, Dickson G, et al. Developmental processes and motivations for linkages in cross-sectoral sport clusters[J]. Sport Management Review, 2017,21(2): 133-146.

[10] 罗若愚，范利君，2006—2014年我国创新政策制定主体协同问题研究[J].中州学刊，2016（12）：28-32.

Luo Ruoyu, Fan Lijun. Study on the characteristics and problems of cooperative evolvement

of innovative policy－makers in china from 2006 to 2014[J]. Academic Journal of Zhongzhou, 2016(12): 28-32.

[11] Alonso J M,Andrews R.Governance by targets and the performance of Cross-Sector partnerships: Do partner diversity and partnership capabilities matter?[J]. Strategic Management Journal, 2018.

[12] Heuer M. Ecosystem cross-sector collaboration: Conceptualizing an adaptive approach to sustainability governance[J]. Business Strategy & the Environment, 2011,20(4): 211-221.

[13] 徐晨光，王海峰.中央与地方关系视阈下地方政府治理模式重塑的政治逻辑[J].政治学研究，2013（4）：30-39.

Xu Chenguang,Wang Haifeng. Political logic of reshaping the governance model of local government from the perspective of central and local relations[J]. CASS Journal of Political Science, 2013(4): 30-39.

[14] 谢庆奎.中国政府的府际关系研究[J].北京大学学报:哲学社会科学版，2000（1）：26-34.

Xie Qingkui. Intergovernmental relations in china[J]. Journal Of Peking University ( Humanities and Social Sciences), 2000(1): 26-34.

[15] 孙秀林，周飞舟.土地财政与分税制：一个实证解释[J].中国社会科学，2013（4）：40-59+205.

Sun Xiulin, Zhou Feizhou. Land finance and the tax-sharing system: An empirical explanation [J]. Social Sciences in China, 2013(4): 40-59+205.

[16] 文宏，崔铁. 矩阵式结构、网格化管理与多机制保障—运动式治理中的纵向府际合作实现[J].四川大学学报(哲学社会科学版)，2015（3）：121-128.

Wen Hong, Cui Tie.Matrix structure,grid management and multi-mechanism protection—The achievement of vertical intergovernmental cooperation in campaign-style governance [J]. Journal of Sichuan University ( Social Science Edition), 2015(3): 121-128.

[17] 刘凤朝，徐茜.中国科技政策主体合作网络演化研究[J].科学学研究，2012，30（2）：241-248.

Liu Fengchao, Xu Qian. Research on the evolution of Chinese S&T policy makers cooperation networks[J]. Studies in Science of Science, 2012,30(2): 241-248.

[18] 孙涛，温雪梅.动态演化视角下区域环境治理的府际合作网络研究—以京津冀大气治理为例[J].中国行政管理，2018（5）：83-89.

Sun Tao, Wen Xuemei. Network analysis of regional environmental governance under inter-government cooperation: An example of the regional air governance in beijing-tianjin-hebei area[J]. Chinese Public Administration, 2018(5): 83-89.

[19] Rhodes R A W. How to manage your policy network[J]. ResearchGate, 2013,10: 1-23.

[20] Lazega E, Snijders T. Multilevel network analysis for the social sciences[M]. Springer, 2015.

[21] Wang P, Robins G, Matous P.Multilevel network analysis using ERGM and Its extension[M]. Multilevel Network Analysis for the Social Sciences. Springer International Publishing, 2016.

[22] Sun Y, Cao C. The evolving relations between government agencies of innovation policymaking in emerging economies: A policy network approach and its application to the Chinese case[J]. Research Policy, 2018,47(3): 592-605.

[23] Lee Y, Lee I W, Feiock R C. Interorganizational collaboration networks in economic development policy: An exponential random graph model analysis[J]. Policy Studies Journal, 2012,40(3): 547–573.

[24] 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.

Wu Bin, Yang Yimin, Lou Chengwu. Quantitative research on the policy documents based on literature measurement and content analysis: A case study on China's marine engineering equipment manufacturing industry[J].Journal of Intelligence, 2017,36(8): 131-137.

[25] 郑登攀，党兴华.网络嵌入性对企业选择合作技术创新伙伴的影响[J].科研管理，2012，33（1）：154-160.

Zheng Dengpan, Dang Xinghua. The impact of network embeddedness on the partner selection of cooperative technological innovation[J]. Science Research Management, 2012, 33(1): 154-160.

[26] Kim D Y. Understanding supplier structural embeddedness: A social network perspective[J]. Journal of Operations Management, 2014,32(5): 219-231.

[27] Charles R S, Craig Volden. Policy Diffusion: Seven Lessons for Scholars and Practitioners[J]. Public Administration Review, 2012,72(6): 788–796.

[28] 张剑，黄萃，叶选挺，等.中国公共政策扩散的文献量化研究—以科技成果转化政策为例[J].中国软科学，2016（2）：145-155.

Zhang Jian, Huang Cui, Ye Xuanting, et al. Study on China’s public policy diffusion based on the quantitative analysis of policy documents: A case study on policies promoting commercialization of scientific and technological achievements[J]. China Soft Science, 2016(2): 145-155.

[29] Guan J C, Yan Y. Technological proximity and recombinative innovation in the alternative energy field[J]. Research Policy, 2016,45(7): 1460-1473.

[30] Klijn E H. Analyzing and managing policy processes in complex networks: A theoretical examination of the concept policy network and its problems[J]. Administration & Society, 1996, 28(1): 90-119.

[31] 朱旭峰，赵慧.自下而上的政策学习—中国三项养老保险政策的比较案例研究[J].南京社会科学，2015（6）：68-75.

Zhu Xufeng, Zhao Hui. Bottom-up policy learning: A comparative case study on three china's pension policies[J]. Nanjing Journal of Social Sciences, 2015(6): 68-75.

[32] Gulati, Ranjay, Gargiulo, et al. Where do interorganizational networks come from?[J]. American Journal of Sociology, 1999,104(5): 1439-1438.

[33] Wang P, Robins G, Pattison P, et al. Exponential random graph models for multilevel networks[J]. Social Networks, 2013,35(1): 96-115.

[34] Wang P, Robins G, Pattison P, et al. Social selection models for multilevel networks[J]. Social Networks, 2015,44: 346-362.

[35] Lusher D, Koskinen J, Robins G. Exponential random graph models for social networks: Theory,methods and applications[J]. Contemporary Sociology, 2014,43(4): 552-553.

[36] Gondal N. Duality of departmental specializations and PhD exchange:A Weberian analysis of status in interaction using multilevel exponential random graph models (mERGM)[J]. Social Networks, 2018,55: 202-212.

[37] 刘晓燕，侯文爽，单晓红，等.多层级视角下京津冀科技创新政策府际关系研究[J].科技进步与对策，2019，36（08）：115-123.

Liu Xiaoyan, Hou Wenshuang, Shan Xiaohong, et al. Research on the inter-governmental relations of the technology and innovation policies of jing-jin-ji under multi-level perspective[J]. Science & Technology Progress and Policy, 2019,36(08): 115-123.