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Industry relatedness, FDI liberalization and the indigenous innovation process in China

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  • Anthony Howell

Abstract

This paper employs a structural innovation model to study the process of indigenous innovation in China and the role of industry relatedness. To better take into account China's transitioning economy context, it further tests to what extent the relationship between relatedness and firms’ innovation process is influenced by the relaxation of foreign ownership controls, an arguably exogenous shock. Controlling for selection, simultaneity and unobserved heterogeneity, the results show that firm research and development (R&D) boosts innovation output, which in turn enhances firm productivity. Relatedness economies are positively related to each phase of innovation, although the size of the effects depends on the type of firm and the stage of innovation. Foreign direct investment (FDI) liberalization encourages firms to rely more on relatedness economies: (1) to complement R&D spending that is required to adapt foreign technologies to local applications; (2) to recombine knowledge from related industries in order to bring forth new proprietary ideas, processes or concepts; and (3) to help solve process or organizational problems faced in related industries.

Suggested Citation

  • Anthony Howell, 2020. "Industry relatedness, FDI liberalization and the indigenous innovation process in China," Regional Studies, Taylor & Francis Journals, vol. 54(2), pages 229-243, February.
    • Handle: RePEc:taf:regstd:v:54:y:2020:i:2:p:229-243
    DOI: 10.1080/00343404.2019.1623871
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    Cited by:

    1. Chen, Yufeng & Zhang, Shun & Miao, Jiafeng, 2023. "The negative effects of the US-China trade war on innovation: Evidence from the Chinese ICT industry," Technovation, Elsevier, vol. 123(C).
    2. Yanwei Lyu & Jinning Zhang & Lingli Wang & Fei Yang & Yu Hao, 2022. "Towards a win‐win situation for innovation and sustainable development: The role of environmental regulation," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1703-1717, December.
    3. Zhangqi, Zhong & Zhuli, Chen & Lingyun, He, 2022. "Technological innovation, industrial structural change and carbon emission transferring via trade-------An agent-based modeling approach," Technovation, Elsevier, vol. 110(C).
    4. Kong, Dongmin & Tao, Yunqing & Wang, Yanan, 2020. "China's anti-corruption campaign and firm productivity: Evidence from a quasi-natural experiment," China Economic Review, Elsevier, vol. 63(C).
    5. Chanyuan Liu & Long Xin & Jinye Li & Huaping Sun, 2022. "The Impact of Renewable Energy Technology Innovation on Industrial Green Transformation and Upgrading: Beggar Thy Neighbor or Benefiting Thy Neighbor," Sustainability, MDPI, vol. 14(18), pages 1-28, September.
    6. Mao, Jie & Tang, Shiping & Xiao, Zhiguo & Zhi, Qiang, 2021. "Industrial policy intensity, technological change, and productivity growth: Evidence from China," Research Policy, Elsevier, vol. 50(7).
    7. Fubiao Zhu & Delin Zhuang & Shengwu Jin & Lingling Gao & Rui Chen, 2022. "Effects of air pollution on regional innovation and the mediator role of health: Evidence from China," Growth and Change, Wiley Blackwell, vol. 53(2), pages 628-650, June.
    8. Bai, Hanyu & Irfan, Muhammad & Hao, Yu, 2022. "How does industrial transfer affect environmental quality? Evidence from China," Journal of Asian Economics, Elsevier, vol. 82(C).
    9. Tianjian Yang & Minghui Han & Yilin Zhong & Junhao Zhong & Qinghua Zhang, 2023. "Relationship between financial development and intelligent transformation of manufacturing: evidence from 69 countries," Economic Change and Restructuring, Springer, vol. 56(5), pages 3437-3474, October.
    10. Bar-El, Raphael, 2023. "Reframing innovation: A case of split personality," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 111-122.
    11. Jurgita Bruneckiene & Robertas Jucevicius & Ineta Zykiene & Jonas Rapsikevicius & Mantas Lukauskas, 2019. "Assessment of Investment Attractiveness in European Countries by Artificial Neural Networks: What Competences are Needed to Make a Decision on Collective Well-Being?," Sustainability, MDPI, vol. 11(24), pages 1-23, December.
    12. Shuwaikh, Fatima & Dubocage, Emmanuelle, 2022. "Access to the Corporate Investors' Complementary Resources: A Leverage for Innovation in Biotech Venture Capital-Backed Companies," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    13. André Spithoven & Bruno Merlevede, 2023. "The productivity impact of R&D and FDI spillovers: characterising regional path development," The Journal of Technology Transfer, Springer, vol. 48(2), pages 560-590, April.
    14. Nicola Cortinovis & Zhiling Wang & Hengky Kurniawan, 2021. "Industrial Relatedness in MNE Spillovers over Geographical Space," Papers in Evolutionary Economic Geography (PEEG) 2111, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Mar 2021.
    15. Ruifa Hu & Changxin Yu & Yanhong Jin & Carl Pray & Haiyan Deng, 2022. "Impact of Government Policies on Research and Development (R&D) Investment, Innovation, and Productivity: Evidence from Pesticide Firms in China," Agriculture, MDPI, vol. 12(5), pages 1-16, May.

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