IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v10y2023i1d10.1057_s41599-023-02061-7.html
   My bibliography  Save this article

How does industry-university-research collaborative innovation affect energy intensity in China: a novel explanation based on political turnover

Author

Listed:
  • Guanglei Yang

    (Lanzhou University)

  • Dongqin Cao

    (Lanzhou University)

  • Guoxing Zhang

    (Lanzhou University)

Abstract

As a form of integrating knowledge resources and promoting technological innovation, industry-university-research (IUR) collaborative innovation is thought to influence energy intensity reduction. However, the boundary conditions of IUR collaborative innovation affecting energy intensity have yet to be discussed. To fill this gap, we explore the impact of IUR collaborative innovation on energy intensity and the role of political turnover in its influencing mechanism, using a panel dataset of 30 Chinese provinces from 2010 to 2018. IUR collaborative innovation inhibits energy intensity, but this effect is only significant in the eastern region. Interestingly, political turnover positively moderates the inhibitory effect of IUR collaborative innovation on energy intensity. However, this moderating effect is only significant in the central and western regions. Moreover, the robustness tests provide abundant evidence to support the above findings. Finally, some policy implications are suggested.

Suggested Citation

  • Guanglei Yang & Dongqin Cao & Guoxing Zhang, 2023. "How does industry-university-research collaborative innovation affect energy intensity in China: a novel explanation based on political turnover," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-12, December.
  • Handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-02061-7
    DOI: 10.1057/s41599-023-02061-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-023-02061-7
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-023-02061-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Glaeser, Edward L. & Kahn, Matthew E., 2010. "The greenness of cities: Carbon dioxide emissions and urban development," Journal of Urban Economics, Elsevier, vol. 67(3), pages 404-418, May.
    2. Rafiq, Shuddhasattwa & Salim, Ruhul & Nielsen, Ingrid, 2016. "Urbanization, openness, emissions, and energy intensity: A study of increasingly urbanized emerging economies," Energy Economics, Elsevier, vol. 56(C), pages 20-28.
    3. Tian, Zhihua & Hu, An & Chen, Yang & Shao, Shuai, 2023. "Local officials’ tenure and CO2 emissions in China," Energy Policy, Elsevier, vol. 173(C).
    4. Samargandi, Nahla, 2019. "Energy intensity and its determinants in OPEC countries," Energy, Elsevier, vol. 186(C).
    5. Richard Blundell & Stephen Bond & Frank Windmeijer, 2000. "Estimation in dynamic panel data models: improving on the performance of the standard GMM estimator," IFS Working Papers W00/12, Institute for Fiscal Studies.
    6. Szücs, Florian, 2018. "Research subsidies, industry–university cooperation and innovation," Research Policy, Elsevier, vol. 47(7), pages 1256-1266.
    7. Sidorkin, Oleg & Vorobyev, Dmitriy, 2018. "Political cycles and corruption in Russian regions," European Journal of Political Economy, Elsevier, vol. 52(C), pages 55-74.
    8. Wolfgang Keller, 2004. "International Technology Diffusion," Journal of Economic Literature, American Economic Association, vol. 42(3), pages 752-782, September.
    9. Li, Hongbin & Zhou, Li-An, 2005. "Political turnover and economic performance: the incentive role of personnel control in China," Journal of Public Economics, Elsevier, vol. 89(9-10), pages 1743-1762, September.
    10. Thursby, Jerry G. & Kemp, Sukanya, 2002. "Growth and productive efficiency of university intellectual property licensing," Research Policy, Elsevier, vol. 31(1), pages 109-124, January.
    11. Santiago, Renato & Fuinhas, José Alberto & Marques, António Cardoso, 2020. "An analysis of the energy intensity of Latin American and Caribbean countries: Empirical evidence on the role of public and private capital stock," Energy, Elsevier, vol. 211(C).
    12. Chen, Guanghua & Yang, Guoliang & He, Feng & Chen, Kaihua, 2019. "Exploring the effect of political borders on university-industry collaborative research performance: Evidence from China’s Guangdong province," Technovation, Elsevier, vol. 82, pages 58-69.
    13. Georg Man, 2016. "Political competition and growth in global perspective: Evidence from panel data," Journal of Applied Economics, Universidad del CEMA, vol. 19, pages 363-382, November.
    14. Tang, Chor Foon & Tan, Eu Chye, 2013. "Exploring the nexus of electricity consumption, economic growth, energy prices and technology innovation in Malaysia," Applied Energy, Elsevier, vol. 104(C), pages 297-305.
    15. Pertuze, Julio A. & Reyes, Tomas & Vassolo, Roberto S. & Olivares, Nicolas, 2019. "Political uncertainty and innovation: The relative effects of national leaders’ education levels and regime systems on firm-level patent applications," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    16. Jaeho Shin & Changhee Kim & Hongsuk Yang, 2019. "Does Reduction of Material and Energy Consumption Affect to Innovation Efficiency? The Case of Manufacturing Industry in South Korea," Energies, MDPI, vol. 12(6), pages 1-14, March.
    17. Chen, Xiude & Qin, Quande & Wei, Y.-M., 2016. "Energy productivity and Chinese local officials’ promotions: Evidence from provincial governors," Energy Policy, Elsevier, vol. 95(C), pages 103-112.
    18. Sohag, Kazi & Begum, Rawshan Ara & Abdullah, Sharifah Mastura Syed & Jaafar, Mokhtar, 2015. "Dynamics of energy use, technological innovation, economic growth and trade openness in Malaysia," Energy, Elsevier, vol. 90(P2), pages 1497-1507.
    19. Herrerias, M.J. & Cuadros, A. & Orts, V., 2013. "Energy intensity and investment ownership across Chinese provinces," Energy Economics, Elsevier, vol. 36(C), pages 286-298.
    20. Aalbers, Rob & Shestalova, Victoria & Kocsis, Viktória, 2013. "Innovation policy for directing technical change in the power sector," Energy Policy, Elsevier, vol. 63(C), pages 1240-1250.
    21. Cao, Chunfang & Dong, Yizhe & Hou, Wenxuan & Liu, Yue & Qian, Xianhang, 2019. "Provincial official turnover and bank loans," Pacific-Basin Finance Journal, Elsevier, vol. 57(C).
    22. Eom, Boo-Young & Lee, Keun, 2010. "Determinants of industry-academy linkages and, their impact on firm performance: The case of Korea as a latecomer in knowledge industrialization," Research Policy, Elsevier, vol. 39(5), pages 625-639, June.
    23. Gardner, Douglas T. & Elkhafif, Mahmoud A. T., 1998. "Understanding industrial energy use: structural and energy intensity changes in Ontario industry," Energy Economics, Elsevier, vol. 20(1), pages 29-41, February.
    24. Motohashi, Kazuyuki & Yun, Xiao, 2007. "China's innovation system reform and growing industry and science linkages," Research Policy, Elsevier, vol. 36(8), pages 1251-1260, October.
    25. Negassi, S., 2004. "R&D co-operation and innovation a microeconometric study on French firms," Research Policy, Elsevier, vol. 33(3), pages 365-384, April.
    26. Choi, Seong-jin & Liu, Huilong & Yin, Jun & Qi, Yunfei & Lee, Jeoung Yul, 2021. "The effect of political turnover on firms’ strategic change in the emerging economies: The moderating role of political connections and financial resources," Journal of Business Research, Elsevier, vol. 137(C), pages 255-266.
    27. Arvind K. Jain, 2001. "Corruption: A Review," Journal of Economic Surveys, Wiley Blackwell, vol. 15(1), pages 71-121, February.
    28. Mitra Akhtari & Diana Moreira & Laura Trucco, 2022. "Political Turnover, Bureaucratic Turnover, and the Quality of Public Services," American Economic Review, American Economic Association, vol. 112(2), pages 442-493, February.
    29. Fiaz, Muhammad, 2013. "An empirical study of university–industry R&D collaboration in China: Implications for technology in society," Technology in Society, Elsevier, vol. 35(3), pages 191-202.
    30. Kong, Gaowen & Ji, Mianmian & Guo, Yuemei, 2021. "Political promotion events and energy conservation decisions: Evidence from China," Energy Economics, Elsevier, vol. 95(C).
    31. Farajzadeh, Zakariya & Nematollahi, Mohammad Amin, 2018. "Energy intensity and its components in Iran: Determinants and trends," Energy Economics, Elsevier, vol. 73(C), pages 161-177.
    32. Lin, Boqiang & Wang, Miao, 2021. "What drives energy intensity fall in China? Evidence from a meta-frontier approach," Applied Energy, Elsevier, vol. 281(C).
    33. Kafouros, Mario & Wang, Chengqi & Piperopoulos, Panagiotis & Zhang, Mingshen, 2015. "Academic collaborations and firm innovation performance in China: The role of region-specific institutions," Research Policy, Elsevier, vol. 44(3), pages 803-817.
    34. Cornillie, Jan & Fankhauser, Samuel, 2004. "The energy intensity of transition countries," Energy Economics, Elsevier, vol. 26(3), pages 283-295, May.
    35. Chakraborty, Saptorshee Kanto & Mazzanti, Massimiliano, 2020. "Energy intensity and green energy innovation: Checking heterogeneous country effects in the OECD," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 328-343.
    36. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cao, Dongqin & Peng, Can & Yang, Guanglei, 2022. "The pressure of political promotion and renewable energy technological innovation: A spatial econometric analysis from China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    2. Bai, Xue-Jie & Li, Zhen-Yang & Zeng, Jin, 2020. "Performance evaluation of China's innovation during the industry-university-research collaboration process—an analysis basis on the dynamic network slacks-based measurement model," Technology in Society, Elsevier, vol. 62(C).
    3. Cornelia Storz & Tobias ten Brink & Na Zou, 2022. "Innovation in emerging economies: How do university-industry linkages and public procurement matter for small businesses?," Asia Pacific Journal of Management, Springer, vol. 39(4), pages 1439-1480, December.
    4. Pan, Xiongfeng & Uddin, Md. Kamal & Saima, Umme & Jiao, Zhiming & Han, Cuicui, 2019. "How do industrialization and trade openness influence energy intensity? Evidence from a path model in case of Bangladesh," Energy Policy, Elsevier, vol. 133(C).
    5. Yi Zhang & Kaihua Chen & Guilong Zhu & Richard C. M. Yam & Jiancheng Guan, 2016. "Inter-organizational scientific collaborations and policy effects: an ego-network evolutionary perspective of the Chinese Academy of Sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1383-1415, September.
    6. Jin, Taeyoung, 2022. "Impact of heat and electricity consumption on energy intensity: A panel data analysis," Energy, Elsevier, vol. 239(PA).
    7. Ji, Xiaoqing & Liu, Shuai & Lang, Jingyi, 2022. "Assessing the impact of officials' turnover on urban economic efficiency: From the perspective of political promotion incentive and power rent-seeking incentive," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    8. Cong Khai Dinh & Quang Thanh Ngo & Trung Thanh Nguyen, 2021. "Medium- and High-Tech Export and Renewable Energy Consumption: Non-Linear Evidence from the ASEAN Countries," Energies, MDPI, vol. 14(15), pages 1-16, July.
    9. Hiroyuki Okamuro & Junichi Nishimura, 2013. "Impact of university intellectual property policy on the performance of university-industry research collaboration," The Journal of Technology Transfer, Springer, vol. 38(3), pages 273-301, June.
    10. Lei Jin & Keran Duan & Xu Tang, 2018. "What Is the Relationship between Technological Innovation and Energy Consumption? Empirical Analysis Based on Provincial Panel Data from China," Sustainability, MDPI, vol. 10(1), pages 1-13, January.
    11. Dias, Joilson & McDermott, John, 2006. "Institutions, education, and development: The role of entrepreneurs," Journal of Development Economics, Elsevier, vol. 80(2), pages 299-328, August.
    12. Shi, Xing & Wu, Yanrui & Fu, Dahai, 2020. "Does University-Industry collaboration improve innovation efficiency? Evidence from Chinese Firms⋄," Economic Modelling, Elsevier, vol. 86(C), pages 39-53.
    13. Trinh, Hai Hong & Sharma, Gagan Deep & Tiwari, Aviral Kumar & Vo, Diem Thi Hong, 2022. "Examining the heterogeneity of financial development in the energy-environment nexus in the era of climate change: Novel evidence around the world," Energy Economics, Elsevier, vol. 116(C).
    14. Wang, En-Ze & Lee, Chien-Chiang & Li, Yaya, 2022. "Assessing the impact of industrial robots on manufacturing energy intensity in 38 countries," Energy Economics, Elsevier, vol. 105(C).
    15. Chen, Wenhui & Lei, Yalin, 2018. "The impacts of renewable energy and technological innovation on environment-energy-growth nexus: New evidence from a panel quantile regression," Renewable Energy, Elsevier, vol. 123(C), pages 1-14.
    16. Richard Frensch & Jan Hanousek & Evžen Kocenda, 2012. "Incomplete Specialization and Offshoring across Europe," CESifo Working Paper Series 3809, CESifo.
    17. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    18. Yongli Tang & Kazuyuki Motohashi & Xinyue Hu & Angeles Montoro-Sanchez, 2020. "University-industry interaction and product innovation performance of Guangdong manufacturing firms: the roles of regional proximity and research quality of universities," The Journal of Technology Transfer, Springer, vol. 45(2), pages 578-618, April.
    19. Huang, Junbing & Hao, Yu & Lei, Hongyan, 2018. "Indigenous versus foreign innovation and energy intensity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1721-1729.
    20. Huang, Junbing & Du, Dan & Tao, Qizhi, 2017. "An analysis of technological factors and energy intensity in China," Energy Policy, Elsevier, vol. 109(C), pages 1-9.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-02061-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.