IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0318619.html
   My bibliography  Save this article

Pathways to sustainability: Higher education and green productivity

Author

Listed:
  • Yongchun Sun

Abstract

The research conducted theoretical analysis and empirical testing on the relationship between higher education and regional green productivity based on panel data from 30 Chinese provinces from 2003 to 2021. The study’s findings demonstrate that higher education can have a major impact on local green production. In order to determine whether industrial structure upgrading and the digital economy work together to promote the development of green productivity, higher education is added to these factors at the same time as the new economic growth mode transformation in the digital economy era. The research hypothesis aligns with the results, suggesting that higher education and the digital economy collaborate to enhance green productivity levels. Higher education has a more significant impact on green productivity the greater the level of regional economic growth, according to a further nonlinear test utilizing the partial linear function coefficient (PLFC) model. Higher education’s influence on green production varies by place and period, becoming more pronounced as time passes and the degree of regional economic growth rises. In order to fully utilize higher education’s capacity for scientific research, innovation, and talent, as well as to increase the direct contribution of its scientific and technological innovations to the advancement of national industry and production promotion, it is imperative that people actively promote the new type of industrialization, develop the digital economy, and work in tandem with higher education.

Suggested Citation

  • Yongchun Sun, 2025. "Pathways to sustainability: Higher education and green productivity," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-25, February.
    • Handle: RePEc:plo:pone00:0318619
    DOI: 10.1371/journal.pone.0318619
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0318619
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0318619&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0318619?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
    ---><---

    References listed on IDEAS

    as
    1. Di Liberto, Adriana, 2008. "Education and Italian regional development," Economics of Education Review, Elsevier, vol. 27(1), pages 94-107, February.
    2. Li, Quan & Chen, Huimin & Chen, Yang & Xiao, Tong & Wang, Li, 2023. "Digital economy, financing constraints, and corporate innovation," Pacific-Basin Finance Journal, Elsevier, vol. 80(C).
    3. 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).
    4. Fare, Rolf, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    5. Wang, Mei & Xu, Mi & Ma, Shaojun, 2021. "The effect of the spatial heterogeneity of human capital structure on regional green total factor productivity," Structural Change and Economic Dynamics, Elsevier, vol. 59(C), pages 427-441.
    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. Lin, Boqiang & Xu, Chongchong, 2024. "Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities," Applied Energy, Elsevier, vol. 365(C).
    2. Peng Liang & Xinhui Sun & Luzhuang Qi, 2024. "Does artificial intelligence technology enhance green transformation of enterprises: based on green innovation perspective," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(8), pages 21651-21687, August.
    3. Lee, Chien-Chiang & He, Zhi-Wen & Yuan, Zihao, 2023. "A pathway to sustainable development: Digitization and green productivity," Energy Economics, Elsevier, vol. 124(C).
    4. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.
    5. Mika Kortelainen & Timo Kuosmanen, 2007. "Eco-efficiency analysis of consumer durables using absolute shadow prices," Journal of Productivity Analysis, Springer, vol. 28(1), pages 57-69, October.
    6. Zanella, Andreia & Camanho, Ana S. & Dias, Teresa G., 2015. "Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(2), pages 517-530.
    7. Arik Levinson, 2009. "Technology, International Trade, and Pollution from US Manufacturing," American Economic Review, American Economic Association, vol. 99(5), pages 2177-2192, December.
    8. Valadkhani, Abbas & Roshdi, Israfil & Smyth, Russell, 2016. "A multiplicative environmental DEA approach to measure efficiency changes in the world's major polluters," Energy Economics, Elsevier, vol. 54(C), pages 363-375.
    9. D’Inverno, Giovanna & Carosi, Laura & Romano, Giulia & Guerrini, Andrea, 2018. "Water pollution in wastewater treatment plants: An efficiency analysis with undesirable output," European Journal of Operational Research, Elsevier, vol. 269(1), pages 24-34.
    10. Lei, Hao & Gao, Renyuan & Ning, Chutong & Sun, Guanglin, 2025. "Green finance and corporate green innovation," Finance Research Letters, Elsevier, vol. 72(C).
    11. Mohammad Tavassoli & Mahsa Ghandehari & Masoud Taherinia, 2023. "Rang-adjusted measure: modelling and computational aspects from internal and external perspectives for network DEA," Operational Research, Springer, vol. 23(4), pages 1-34, December.
    12. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    13. Atkinson, Scott E. & Tsionas, Mike G., 2021. "Generalized estimation of productivity with multiple bad outputs: The importance of materials balance constraints," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1165-1186.
    14. Tao, Miaomiao, 2024. "Dynamics between electric vehicle uptake and green development: Understanding the role of local government competition," Transport Policy, Elsevier, vol. 146(C), pages 227-240.
    15. Xiaohui Xin & Ruoyu Zhu & Guoli Ou, 2025. "Does the opening of high-speed rail speed up the development of urban digital economy?," Economic Change and Restructuring, Springer, vol. 58(2), pages 1-24, April.
    16. Maciej Jagódka & Małgorzata Snarska, 2021. "The State of Human Capital and Innovativeness of Polish Voivodships in 2004–2018," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    17. Soledad Moya & Jordi Perramon & Anselm Constans, 2005. "IFRS Adoption in Europe: The Case of Germany," Working Papers 0501, Departament Empresa, Universitat Autònoma de Barcelona, revised Feb 2005.
    18. Manca, Fabio, 2011. "Education, Catch-up and Growth in Spain," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 20, pages 5-28.
    19. Abad, A. & Ravelojaona, P., 2025. "An unified framework for measuring environmentally-adjusted productivity change: Theoretical basis and empirical illustration," European Journal of Operational Research, Elsevier, vol. 320(3), pages 642-654.
    20. Muhammad, Tufail & Ni, Guohua & Chen, Zhenling & Mallek, Sabrine & Dudek, Marek & Mentel, Grzegorz, 2024. "Addressing resource curse: How mineral resources influence industrial structure dynamics of the BRI 57 oil-exporting countries," Resources Policy, Elsevier, vol. 99(C).

    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:plo:pone00:0318619. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.