IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i15p6700-d1707943.html

Study on Impact of Managerial Effectiveness and Digitalization on Green Total Factor Productivity of Enterprises: Sample of Listed Heavy-Polluting Enterprises in China

Author

Listed:
  • Jun Yan

    (School of Finance and Economics, Jiangsu University, Zhenjiang 212013, China)

  • Zexia Zhao

    (School of Management, Jiangsu University, Zhenjiang 212013, China)

Abstract

In the process of evaluating the quality of a company’s development, the issues related to production capacity and environmental pollution have emerged as significant concerns. Drawing on the methodologies employed in previous related research, this study utilizes the Data Envelopment Analysis with relaxation variables and the Global Malmquist–Luenberger index to measure the green total factor productivity of Chinese heavy-polluting enterprises. The main findings of this study are as follows: (1) It is clearly demonstrated that higher managerial effectiveness has a substantial positive impact on the improvement of a company’s green total factor productivity; (2) the digitalization progress within enterprises serves as a moderating factor in the relationship between managerial effectiveness and green total factor productivity; (3) the extent of financial constraints acts as a mediating variable, intervening in the relationship between managerial efficiency and green total factor productivity; and (4) a threshold effect is detected between managerial effectiveness and the debt repayment pressure faced by enterprises. When the threshold values of managerial effectiveness or the quick ratio are surpassed, the influence of managerial effectiveness on the green total factor productivity of enterprises will undergo a change.

Suggested Citation

  • Jun Yan & Zexia Zhao, 2025. "Study on Impact of Managerial Effectiveness and Digitalization on Green Total Factor Productivity of Enterprises: Sample of Listed Heavy-Polluting Enterprises in China," Sustainability, MDPI, vol. 17(15), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:6700-:d:1707943
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/15/6700/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/15/6700/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liang Zhao & Liangyu Chen, 2022. "Research on the Impact of Government Environmental Information Disclosure on Green Total Factor Productivity: Empirical Experience from Chinese Province," IJERPH, MDPI, vol. 19(2), pages 1-20, January.
    2. Ludovic Halbert & John Henneberry & Fotis Mouzakis, 2014. "Finance, Business Property and Urban and Regional Development," Regional Studies, Taylor & Francis Journals, vol. 48(3), pages 421-424, March.
    3. Jinzhong Li & Daqing Gong, 2022. "Analysis on the Relationship between Financing Constraints and Research and Development from the Perspective of the Location of Top Management Network," Discrete Dynamics in Nature and Society, Hindawi, vol. 2022, pages 1-11, January.
    4. Tim Heubeck & Annina Ahrens, 2025. "Sustainable by Ideology? The Influence of CEO Political Ideology and Ivy League Education on ESG (Environmental, Social, and Governance) Performance," Business Strategy and the Environment, Wiley Blackwell, vol. 34(4), pages 4785-4810, May.
    5. Ke Mao & Pierre Failler, 2022. "Local Government Debt and Green Total Factor Productivity—Empirical Evidence from Chinese Cities," IJERPH, MDPI, vol. 19(19), pages 1-13, September.
    6. S. Trevis Certo & John R. Busenbark & Hyun‐soo Woo & Matthew Semadeni, 2016. "Sample selection bias and Heckman models in strategic management research," Strategic Management Journal, Wiley Blackwell, vol. 37(13), pages 2639-2657, December.
    7. Beaulieu, Martin & Bentahar, Omar, 2021. "Digitalization of the healthcare supply chain: A roadmap to generate benefits and effectively support healthcare delivery," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    8. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    9. 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.
    10. Martin Beaulieu & Omar Bentahar, 2021. "Digitalization of the healthcare supply chain: A roadmap to generate benefits and effectively support healthcare delivery," Post-Print hal-03208957, HAL.
    11. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    12. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    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. Tianqun Xu & Ping Gao & Qian Yu & Debin Fang, 2017. "An Improved Eco-Efficiency Analysis Framework Based on Slacks-Based Measure Method," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    2. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    3. Fukuyama, Hirofumi & Weber, William L., 2010. "A slacks-based inefficiency measure for a two-stage system with bad outputs," Omega, Elsevier, vol. 38(5), pages 398-409, October.
    4. Sebastián Lozano & Narges Soltani, 2020. "A modified discrete Raiffa approach for efficiency assessment and target setting," Annals of Operations Research, Springer, vol. 292(1), pages 71-95, September.
    5. Ning Geng & Zengjin Liu & Xuejiao Wang & Lin Meng & Jiayan Pan, 2022. "Measurement of Green Total Factor Productivity and Its Spatial Convergence Test on the Pig-Breeding Industry in China," Sustainability, MDPI, vol. 14(21), pages 1-19, October.
    6. Shih-Heng Yu & Ming Chen & Fu-Chiang Yang, 2025. "Corporate social responsibility, profitability and marketability in business performance evaluation: a directional network slacks-based measure approach," Annals of Operations Research, Springer, vol. 353(3), pages 1211-1237, October.
    7. Anh Ton Pham, 2026. "From efficiency measurement to spatial correlation: slacks-based directional distance function and Moran’s I study of Vietnam’s provincial development," Asia-Pacific Journal of Regional Science, Springer, vol. 10(1), pages 1-57, March.
    8. Zhenglin Sun & Jinyue Zhang, 2022. "Impact of Resource-Saving and Environment-Friendly Society Construction on Sustainability," Sustainability, MDPI, vol. 14(18), pages 1-25, September.
    9. Walter Briec, 2021. "Distance Functions and Generalized Means: Duality and Taxonomy," Papers 2112.09443, arXiv.org, revised Apr 2026.
    10. Gang Tian & Jian Shi & Licheng Sun & Xingle Long & Benhai Guo, 2017. "Dynamic changes in the energy–carbon performance of Chinese transportation sector: a meta-frontier non-radial directional distance function approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(2), pages 585-607, November.
    11. Song, Malin & Wang, Jianlin, 2018. "Environmental efficiency evaluation of thermal power generation in China based on a slack-based endogenous directional distance function model," Energy, Elsevier, vol. 161(C), pages 325-336.
    12. Manh D. Pham & Valentin Zelenyuk, 2018. "Slack-based directional distance function in the presence of bad outputs: theory and application to Vietnamese banking," Empirical Economics, Springer, vol. 54(1), pages 153-187, February.
    13. Deng, Zhongqi & Song, Shunfeng & Jiang, Nan & Pang, Ruizhi, 2023. "Sustainable development in China? A nonparametric decomposition of economic growth," China Economic Review, Elsevier, vol. 81(C).
    14. Laura Calzada-Infante & Ana María López-Narbona & Alberto Núñez-Elvira & Javier Orozco-Messana, 2020. "Assessing the Efficiency of Sustainable Cities Using an Empirical Approach," Sustainability, MDPI, vol. 12(7), pages 1-13, March.
    15. Fukuyama, Hirofumi & Matousek, Roman, 2011. "Efficiency of Turkish banking: Two-stage network system. Variable returns to scale model," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(1), pages 75-91, February.
    16. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    17. Zelenyuk, Valentin & Zhao, Shirong, 2024. "Russell and slack-based measures of efficiency: A unifying framework," European Journal of Operational Research, Elsevier, vol. 318(3), pages 867-876.
    18. Yang, Jun & Zhang, Tengfei & Sheng, Pengfei & Shackman, Joshua D., 2016. "Carbon dioxide emissions and interregional economic convergence in China," Economic Modelling, Elsevier, vol. 52(PB), pages 672-680.
    19. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    20. Kounetas, Konstantinos & Zervopoulos, Panagiotis D., 2019. "A cross-country evaluation of environmental performance: Is there a convergence-divergence pattern in technology gaps?," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1136-1148.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:gam:jsusta:v:17:y:2025:i:15:p:6700-:d:1707943. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.