IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i16p7509-d1728236.html
   My bibliography  Save this article

Effects of Supply Chain Digitization on Different Types of Corporate Green Innovation: Empirical Evidence from Double Machine Learning (DML)

Author

Listed:
  • Shaopeng Zhang

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Yuting Niu

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Jiong Zhang

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Jiyu Li

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Sihan Wang

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

  • Yangyang Guan

    (School of Economics and Management, Northeast Forestry University, Harbin 150040, China)

Abstract

Amid global resource shortage and severe climate problems, green innovation has become the key for enterprises to achieve sustainable development, and supply chain digitization brings a new opportunity to enhance the green innovation capability of enterprises. Therefore, this paper empirically investigates the differential effects of supply chain digitization (SCD) on two different green innovation strategies, namely substantive green innovation (SGI) and tactical green innovation (TGI), with 38,548 observations of Chinese listed companies in the 17-year period from 2007 to 2023 using an innovative double machine learning model. It is found that SCD can significantly enhance the substantive and tactical green innovation capabilities of enterprises, and the promotion effect on the former is more obvious. Mechanism analysis shows that SCD promotes substantive green innovation by improving the ESG (Environmental, Social, and Governance) performance of enterprises, and promotes tactical green innovation by improving the management efficiency of supply chain nodes. Heterogeneity analysis shows that SCD promotes green innovation more significantly for high-tech firms, firms with high degree of internal control and low financing constraints. Our paper can be informative in addressing this differential impact of supply chain digitization on different types of corporate green innovation.

Suggested Citation

  • Shaopeng Zhang & Yuting Niu & Jiong Zhang & Jiyu Li & Sihan Wang & Yangyang Guan, 2025. "Effects of Supply Chain Digitization on Different Types of Corporate Green Innovation: Empirical Evidence from Double Machine Learning (DML)," Sustainability, MDPI, vol. 17(16), pages 1-23, August.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7509-:d:1728236
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/16/7509/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/16/7509/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lee, Chien-Chiang & He, Zhi-Wen & Yuan, Zihao, 2023. "A pathway to sustainable development: Digitization and green productivity," Energy Economics, Elsevier, vol. 124(C).
    2. Schniederjans, Dara G. & Curado, Carla & Khalajhedayati, Mehrnaz, 2020. "Supply chain digitisation trends: An integration of knowledge management," International Journal of Production Economics, Elsevier, vol. 220(C).
    3. Victor Chernozhukov & Denis Chetverikov & Mert Demirer & Esther Duflo & Christian Hansen & Whitney Newey & James Robins, 2018. "Double/debiased machine learning for treatment and structural parameters," Econometrics Journal, Royal Economic Society, vol. 21(1), pages 1-68, February.
    4. 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).
    5. Chao Hung Wang & Wei‐Jr Juo, 2021. "An environmental policy of green intellectual capital: Green innovation strategy for performance sustainability," Business Strategy and the Environment, Wiley Blackwell, vol. 30(7), pages 3241-3254, November.
    6. Li, Feng & Srinivasan, Suraj, 2011. "Corporate governance when founders are directors," Journal of Financial Economics, Elsevier, vol. 102(2), pages 454-469.
    7. Petrovic, Dobrila, 2001. "Simulation of supply chain behaviour and performance in an uncertain environment," International Journal of Production Economics, Elsevier, vol. 71(1-3), pages 429-438, May.
    8. Guiso, Luigi & Sapienza, Paola & Zingales, Luigi, 2015. "The value of corporate culture," Journal of Financial Economics, Elsevier, vol. 117(1), pages 60-76.
    9. Zhou, Yue, 2024. "Natural resources and green economic growth: A pathway to innovation and digital transformation in the mining industry," Resources Policy, Elsevier, vol. 90(C).
    10. Wang, Xiong & Li, Jingyao & Ren, Xiaohang & Bu, Ruijun & Jawadi, Fredj, 2023. "Economic policy uncertainty and dynamic correlations in energy markets: Assessment and solutions," Energy Economics, Elsevier, vol. 117(C).
    11. Susanne Arvidsson & John Dumay, 2022. "Corporate ESG reporting quantity, quality and performance: Where to now for environmental policy and practice?," Business Strategy and the Environment, Wiley Blackwell, vol. 31(3), pages 1091-1110, March.
    12. Luo, Shuangcheng & Xiong, Zhiqiao & Liu, Jianjiang, 2024. "How does supply chain digitization affect green innovation? Evidence from a quasi-natural experiment in China," Energy Economics, Elsevier, vol. 136(C).
    13. Liu, Ying & Huang, Hongyun & Mbanyele, William & Li, Xin & Balezentis, Tomas, 2025. "Harnessing supply chain digital innovation for enhanced corporate environmental practices and sustainable growth," Energy Economics, Elsevier, vol. 142(C).
    14. Rena Kondo & Yuki Kinoshita & Tetsuo Yamada, 2019. "Green Procurement Decisions with Carbon Leakage by Global Suppliers and Order Quantities under Different Carbon Tax," Sustainability, MDPI, vol. 11(13), pages 1-19, July.
    15. Smith, Jared D., 2016. "US political corruption and firm financial policies," Journal of Financial Economics, Elsevier, vol. 121(2), pages 350-367.
    16. Li, Zhiyi & Hu, Boqiang & Bao, Yifei & Wang, Yifei, 2025. "Supply chain digitalization, green technology innovation and corporate energy efficiency," Energy Economics, Elsevier, vol. 142(C).
    17. Gunasekaran, A. & Patel, C. & McGaughey, Ronald E., 2004. "A framework for supply chain performance measurement," International Journal of Production Economics, Elsevier, vol. 87(3), pages 333-347, February.
    18. Xu, Jingru & Yang, Baochen & Yuan, Chunlai, 2025. "The impact of supply chain digitalization on urban resilience: Do industrial chain resilience, green total factor productivity and innovation matter?," Energy Economics, Elsevier, vol. 145(C).
    19. Liao, Feimei & Hu, Yaoyao & Chen, Mengjie & Xu, Shulin, 2024. "Digital transformation and corporate green supply chain efficiency: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 81(C), pages 195-207.
    20. Shaoxing Sun & Tao Guo & Shaopeng Zhang, 2025. "Guiding corporate green sustainable development: insights from green public procurement," Economic Change and Restructuring, Springer, vol. 58(4), pages 1-22, August.
    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. Yang, Ping & Lv, Yanqin & Chen, Jing & Shen, Hebin & Xu, Yang, 2025. "Can the digitization of supply chains promote the low-carbon transformation of enterprises? A case study of listed companies in China," Energy Economics, Elsevier, vol. 143(C).
    2. Li, Zhiyi & Hu, Boqiang & Bao, Yifei & Wang, Yifei, 2025. "Supply chain digitalization, green technology innovation and corporate energy efficiency," Energy Economics, Elsevier, vol. 142(C).
    3. Malik, Mahfuja & Mamun, Khawaja & Osman, Syed Muhammad Ishraque, 2025. "Does corruption control enhance ESG-induced firm value? Insights from machine learning analysis," Finance Research Letters, Elsevier, vol. 72(C).
    4. Yiying Wang & Derek D. Wang, 2025. "The Dual Path of the Impact of Digital Technology Adoption on ESG Performance," Sustainability, MDPI, vol. 17(6), pages 1-24, March.
    5. Robin Chen & Chia‐Wei Huang & Chih‐Yung Lin, 2022. "Board corruption and loan contracts," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(9-10), pages 1929-1956, October.
    6. Quentin Dupont & Jonathan M. Karpoff, 2020. "The Trust Triangle: Laws, Reputation, and Culture in Empirical Finance Research," Journal of Business Ethics, Springer, vol. 163(2), pages 217-238, May.
    7. Gu, Jiafeng, 2025. "Did supply chain digitization contribute to corporate green energy innovation? The mediating role of asset receivable management and policy spillovers," Energy Economics, Elsevier, vol. 143(C).
    8. Huang, Wei & Yang, Fan & Zhu, Yixin, 2025. "Digital economy and entrusted loans: Evidence from shadow banking," Finance Research Letters, Elsevier, vol. 73(C).
    9. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-dimensional econometrics and regularized GMM," CeMMAP working papers CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    10. Marta Szczepańczyk & Paweł Nowodziński & Adam Sikorski, 2023. "ESG Strategy and Financial Aspects Using the Example of an Oil and Gas Midstream Company: The UNIMOT Group," Sustainability, MDPI, vol. 15(18), pages 1-24, September.
    11. Asanov, Anastasiya-Mariya & Asanov, Igor & Buenstorf, Guido, 2024. "A low-cost digital first aid tool to reduce psychological distress in refugees: A multi-country randomized controlled trial of self-help online in the first months after the invasion of Ukraine," Social Science & Medicine, Elsevier, vol. 362(C).
    12. Justin Whitehouse & Morgane Austern & Vasilis Syrgkanis, 2025. "Inference on Optimal Policy Values and Other Irregular Functionals via Smoothing," Papers 2507.11780, arXiv.org.
    13. Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
    14. Kyle Colangelo & Ying-Ying Lee, 2019. "Double debiased machine learning nonparametric inference with continuous treatments," CeMMAP working papers CWP72/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    15. Leon Zolotoy & Don O’Sullivan & Keke Song, 2021. "The Role of Ethical Standards in the Relationship Between Religious Social Norms and M&A Announcement Returns," Journal of Business Ethics, Springer, vol. 170(4), pages 721-742, May.
    16. Sant’Anna, Pedro H.C. & Zhao, Jun, 2020. "Doubly robust difference-in-differences estimators," Journal of Econometrics, Elsevier, vol. 219(1), pages 101-122.
    17. Ruoxuan Xiong & Allison Koenecke & Michael Powell & Zhu Shen & Joshua T. Vogelstein & Susan Athey, 2021. "Federated Causal Inference in Heterogeneous Observational Data," Papers 2107.11732, arXiv.org, revised Apr 2023.
    18. Sophie Brana & Dalila Chenaf-Nicet & Delphine Lahet, 2023. "Drivers of cross-border bank claims: The role of foreign-owned banks in emerging countries," Working Papers 2023.06, International Network for Economic Research - INFER.
    19. Boubaker, Sabri & Liu, Pei-Zhi & Ren, Yi-Shuai & Ma, Chao-Qun, 2024. "Do anti-corruption campaigns affect corporate environmental responsibility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 91(C).
    20. Arne Henningsen & Guy Low & David Wuepper & Tobias Dalhaus & Hugo Storm & Dagim Belay & Stefan Hirsch, 2024. "Estimating Causal Effects with Observational Data: Guidelines for Agricultural and Applied Economists," IFRO Working Paper 2024/03, University of Copenhagen, Department of Food and Resource Economics.

    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:16:p:7509-:d:1728236. 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.