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The Impact of Government Role on High-Quality Innovation Development in Mainland China

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  • Xuanzhi Yang

    (Business School, Hohai University, Nanjing 211100, China)

  • Zhaofang Zhang

    (Business School, Hohai University, Nanjing 211100, China)

  • Wei Luo

    (Business School, Henan University, Kaifeng 475004, China)

  • Zhen Tang

    (Business School, Hohai University, Nanjing 211100, China)

  • Xin Gao

    (Business School, Hohai University, Nanjing 211100, China)

  • Zhongchi Wan

    (College of Economics & Management, China Three Gorges University, Yichang 443002, China)

  • Xin Zhang

    (Business School, Hohai University, Nanjing 211100, China
    International Economic &Technical Cooperation and Exchange Center, Ministry of Water Resources, Beijing 100038, China)

Abstract

Innovation serves as the first impetus for high-quality development. The role of government in promoting high-quality innovation development has become a chief driving force. Therefore, based on role theory, this paper will discuss the effect of different government roles on high-quality innovation development and regional alienation, providing policy recommendations for China. In this paper, firstly, a super-efficiency DEA model is introduced to measure the high-quality innovation development level among 30 provinces and municipalities in mainland China from 2010 to 2017. Secondly, a Tobit model is used to analyze the impact of different government roles on high-quality innovation development. The following conclusions are drawn through a super-efficiency DEA model: (1) From the holistic perspective, the high-quality innovation development in mainland China shows a fluctuating growth trend, but its level still needs improvement. (2) From the regional perspective, there is a patchwork pattern of ‘the eastern region ranks highest, followed by the western region and the middle region that stays at the lowest’. In addition, the three regions’ average of total factor productivity of high-quality innovation development has shown a smooth upward trend over the years. Then, the results of Tobit regression analysis are as follows: (1) Apart from the role in supporting talent, roles in constructing innovation platforms, cultivating the innovation environment, and coordinating social resources all pass the significance test. (2) Demands of different government roles vary significantly in different regions from the regional perspective. For the betterment of an innovation society, this paper puts forward suggestions according to different regional development statuses, such as shifting our focus from quantity to quality, strengthening cooperation among provinces and municipalities, and formulating appropriate governance role strategies.

Suggested Citation

  • Xuanzhi Yang & Zhaofang Zhang & Wei Luo & Zhen Tang & Xin Gao & Zhongchi Wan & Xin Zhang, 2019. "The Impact of Government Role on High-Quality Innovation Development in Mainland China," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:20:p:5780-:d:277866
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    as
    1. Wu, Yunna & Ke, Yiming & Zhang, Ting & Liu, Fangtong & Wang, Jing, 2018. "Performance efficiency assessment of photovoltaic poverty alleviation projects in China: A three-phase data envelopment analysis model," Energy, Elsevier, vol. 159(C), pages 599-610.
    2. Leonid Kogan & Dimitris Papanikolaou & Amit Seru & Noah Stoffman, 2017. "Technological Innovation, Resource Allocation, and Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(2), pages 665-712.
    3. Alexander Cotte, Poveda, 2011. "Economic development and growth in Colombia: An empirical analysis with super-efficiency DEA and panel data models," Socio-Economic Planning Sciences, Elsevier, vol. 45(4), pages 154-164, December.
    4. Kirjavainen, Tanja & Loikkanent, Heikki A., 1998. "Efficiency differences of finnish senior secondary schools: An application of DEA and Tobit analysis," Economics of Education Review, Elsevier, vol. 17(4), pages 377-394, October.
    5. Junhong Bai, 2013. "On Regional Innovation Efficiency: Evidence from Panel Data of China's Different Provinces," Regional Studies, Taylor & Francis Journals, vol. 47(5), pages 773-788, May.
    6. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    7. Yishan Wu & Yuntao Pan & Yuhua Zhang & Zheng Ma & Jingan Pang & Hong Guo & Bo Xu & Zhiqing Yang, 2004. "China Scientific and Technical Papers and Citations (CSTPC): History, impact and outlook," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 385-397, August.
    8. Avkiran, Necmi K., 2011. "Association of DEA super-efficiency estimates with financial ratios: Investigating the case for Chinese banks," Omega, Elsevier, vol. 39(3), pages 323-334, June.
    9. Munshi Naser Ibne Afzal, 2014. "An empirical investigation of the National Innovation System (NIS) using Data Envelopment Analysis (DEA) and the TOBIT model," International Review of Applied Economics, Taylor & Francis Journals, vol. 28(4), pages 507-523, July.
    10. Yang, Chao & Lee, Lung-fei & Qu, Xi, 2018. "Tobit models with social interactions: Complete vs incomplete information," Regional Science and Urban Economics, Elsevier, vol. 73(C), pages 30-50.
    11. Anglin, Aaron H. & Wolfe, Marcus T. & Short, Jeremy C. & McKenny, Aaron F. & Pidduck, Robert J., 2018. "Narcissistic rhetoric and crowdfunding performance: A social role theory perspective," Journal of Business Venturing, Elsevier, vol. 33(6), pages 780-812.
    12. Xin Gao & Juqin Shen & Weijun He & Fuhua Sun & Zhaofang Zhang & Xin Zhang & Liang Yuan & Min An, 2019. "Multilevel Governments’ Decision-Making Process and Its Influencing Factors in Watershed Ecological Compensation," Sustainability, MDPI, vol. 11(7), pages 1-28, April.
    13. Prakashan Veettil & Stijn Speelman & Guido Huylenbroeck, 2013. "Estimating the Impact of Water Pricing on Water Use Efficiency in Semi-arid Cropping System: An Application of Probabilistically Constrained Nonparametric Efficiency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(1), pages 55-73, January.
    14. Rosegrant, Mark W. & Evenson, Robert E., 1995. "Total factor productivity and sources of long-term growth in Indian agriculture:," EPTD discussion papers 7, International Food Policy Research Institute (IFPRI).
    15. Alwyn Young, 1995. "The Tyranny of Numbers: Confronting the Statistical Realities of the East Asian Growth Experience," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(3), pages 641-680.
    16. Held, Benjamin & Rodenhäuser, Dorothee & Diefenbacher, Hans & Zieschank, Roland, 2018. "The National and Regional Welfare Index (NWI/RWI): Redefining Progress in Germany," Ecological Economics, Elsevier, vol. 145(C), pages 391-400.
    17. Stefan Felder & Horst Schmitt, 2004. "Data envelopment analysis based bonus payments," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 5(4), pages 357-364, November.
    18. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    19. Chien-Hsun Chen & Hui-Tzu Shih, 2005. "High-Tech Industries in China," Books, Edward Elgar Publishing, number 3710.
    20. Zhimin Dai & Lu Guo & Zhengyi Jiang, 2016. "Study on the industrial Eco-Efficiency in East China based on the Super Efficiency DEA Model: an example of the 2003–2013 panel data," Applied Economics, Taylor & Francis Journals, vol. 48(59), pages 5779-5785, December.
    21. Wang, H. & Ang, B.W. & Wang, Q.W. & Zhou, P., 2017. "Measuring energy performance with sectoral heterogeneity: A non-parametric frontier approach," Energy Economics, Elsevier, vol. 62(C), pages 70-78.
    22. Galambos, Louis & Amatori, Franco, 2016. "The Entrepreneurial Multiplier Effect," Enterprise & Society, Cambridge University Press, vol. 17(4), pages 763-808, December.
    23. David Doloreux & Igone Porto Gomez, 2017. "A review of (almost) 20 years of regional innovation systems research," European Planning Studies, Taylor & Francis Journals, vol. 25(3), pages 371-387, March.
    24. Song, ChiUng & Oh, Wankeun, 2015. "Determinants of innovation in energy intensive industry and implications for energy policy," Energy Policy, Elsevier, vol. 81(C), pages 122-130.
    25. Bisma Mannan & Abid Haleem, 2017. "Understanding major dimensions and determinants that help in diffusion & adoption of product innovation: using AHP approach," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 7(1), pages 1-24, December.
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    2. Li, Yunjian & Chen, Jiawen & Li, Li & Huang, Xiaojun, 2024. "Government innovation awards, innovation funds acquisition and enterprise innovation," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 846-864.
    3. Hongwei Liu & Ronglu Yang & Zhixiang Zhou & Dacheng Huang, 2020. "Regional Green Eco-Efficiency in China: Considering Energy Saving, Pollution Treatment, and External Environmental Heterogeneity," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    4. Zhe Cheng & Anni Tang & Jianming Cai & Tao Song, 2022. "Exploring the High-Quality County-Level Development and Governance Response for Farming–Pastoral Ecotone in China: A Case Study of Kulun," Agriculture, MDPI, vol. 12(12), pages 1-18, November.
    5. Shuai Liu & Xiao-Yu Xu & Kai Zhao & Li-Ming Xiao & Qi Li, 2021. "Understanding the Complexity of Regional Innovation Capacity Dynamics in China: From the Perspective of Hidden Markov Model," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    6. Fen Zhang & Xiaonan Qin & Lina Liu, 2020. "The Interaction Effect between ESG and Green Innovation and Its Impact on Firm Value from the Perspective of Information Disclosure," Sustainability, MDPI, vol. 12(5), pages 1-18, March.
    7. Zhu, Jun & Xu, Haokun & Zhang, Yue, 2022. "Local government debt and firm productivity: Evidence from China," Research in International Business and Finance, Elsevier, vol. 63(C).
    8. Ruifeng Xu & E Guan, 2023. "Can blockchain innovation promote total factor productivity? Evidence from Chinese-listed firms," Applied Economics, Taylor & Francis Journals, vol. 55(6), pages 653-670, February.

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