IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i5p1822-d1596327.html
   My bibliography  Save this article

How Do Robot Applications Affect Corporate Sustainability?—An Analysis Based on Environmental, Social, and Governance Performance

Author

Listed:
  • Yuefeng Xie

    (School of Economics and Trade, Hunan University, Changsha 410006, China)

  • Luman Zhao

    (School of Economics and Trade, Hunan University, Changsha 410006, China)

  • Yabin Zhang

    (School of Economics and Trade, Hunan University, Changsha 410006, China)

  • Zhenguo Wang

    (School of Economics and Trade, Hunan University, Changsha 410006, China)

Abstract

Can the application of robots promote corporate sustainability? This study constructs micro-data based on robot data provided by the IFR and annual reports of China’s A-share listed companies from 2010 to 2018. By employing a multidimensional fixed effects model for empirical analysis, we arrive at the following conclusions. Firstly, the implementation of robotic technologies substantially improves the environmental, social, and governance (ESG) performance of corporations, which remains robust following a series of robustness tests (including the implementation of instrumental variables, the Heckman two-stage model, and placebo tests). Secondly, a decomposition effect analysis shows that robots positively influence the E, S, and G aspects of ESG; in addition, robotic applications primarily promote corporate ESG performance by promoting green technology innovation, boosting corporate goodwill, and enhancing internal control effectiveness. Thirdly, a heterogeneity analysis reveals that the positive effects of robotic applications on corporate ESG performance are predominantly observed in state-owned, large-scale, and technology-intensive enterprises. Additionally, the promoting effect is strongest in enterprises located in central regions, followed by the eastern regions, while the effect in the western regions is insignificant. Furthermore, the results of the quantile regression analysis reveal that robotics exerts a greater impact on firms with higher initial levels of ESG performance. These findings offer researchers a framework to identify and measure the effects of robots on corporate sustainability, thus enhancing the understanding of the relationship between robotics and corporate sustainability.

Suggested Citation

  • Yuefeng Xie & Luman Zhao & Yabin Zhang & Zhenguo Wang, 2025. "How Do Robot Applications Affect Corporate Sustainability?—An Analysis Based on Environmental, Social, and Governance Performance," Sustainability, MDPI, vol. 17(5), pages 1-29, February.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:1822-:d:1596327
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/5/1822/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/5/1822/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    2. Gihleb, Rania & Giuntella, Osea & Stella, Luca & Wang, Tianyi, 2022. "Industrial robots, Workers’ safety, and health," Labour Economics, Elsevier, vol. 78(C).
    3. Luo, Wei & Tang, Lixin & Yang, Yaxin & Zou, Xianqiang, 2025. "Robots as guardians: Industrial automation and workplace safety in China," Journal of Development Economics, Elsevier, vol. 172(C).
    4. Gutiérrez, Emilio & Teshima, Kensuke, 2018. "Abatement expenditures, technology choice, and environmental performance: Evidence from firm responses to import competition in Mexico," Journal of Development Economics, Elsevier, vol. 133(C), pages 264-274.
    5. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    6. Hui Huang & Jing Yang & Changman Ren, 2024. "Unlocking ESG Performance Through Intelligent Manufacturing: The Roles of Transparency, Green Innovation, and Supply Chain Collaboration," Sustainability, MDPI, vol. 16(23), pages 1-26, December.
    7. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    8. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue Nov.
    9. Huang, Geng & He, Ling-Yun & Lin, Xi, 2022. "Robot adoption and energy performance: Evidence from Chinese industrial firms," Energy Economics, Elsevier, vol. 107(C).
    10. Gene M. Grossman & Alan B. Krueger, 1995. "Economic Growth and the Environment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(2), pages 353-377.
    11. Joseph S. Shapiro & Reed Walker, 2018. "Why Is Pollution from US Manufacturing Declining? The Roles of Environmental Regulation, Productivity, and Trade," American Economic Review, American Economic Association, vol. 108(12), pages 3814-3854, December.
    12. Timothy J. Bartik, 1991. "Who Benefits from State and Local Economic Development Policies?," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number wbsle.
    13. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    14. Fang, Mingyue & Nie, Huihua & Shen, Xinyi, 2023. "Can enterprise digitization improve ESG performance?," Economic Modelling, Elsevier, vol. 118(C).
    15. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    16. Kong, Dongmin & Shu, Yijia & Wang, Yanan, 2021. "Corruption and corporate social responsibility: Evidence from a quasi-natural experiment in China⋆," Journal of Asian Economics, Elsevier, vol. 75(C).
    17. Daron Acemoglu & Pascual Restrepo, 2018. "The Race between Man and Machine: Implications of Technology for Growth, Factor Shares, and Employment," American Economic Review, American Economic Association, vol. 108(6), pages 1488-1542, June.
    18. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    19. Wang, Zongrun & Zhang, Taiyu & Ren, Xiaohang & Shi, Yukun, 2024. "AI adoption rate and corporate green innovation efficiency: Evidence from Chinese energy companies," Energy Economics, Elsevier, vol. 132(C).
    20. Forslid, Rikard & Okubo, Toshihiro & Ulltveit-Moe, Karen Helene, 2018. "Why are firms that export cleaner? International trade, abatement and environmental emissions," Journal of Environmental Economics and Management, Elsevier, vol. 91(C), pages 166-183.
    21. Shihong Zeng & Gen Li & Shaomin Wu & Zhanfeng Dong, 2022. "The Impact of Green Technology Innovation on Carbon Emissions in the Context of Carbon Neutrality in China: Evidence from Spatial Spillover and Nonlinear Effect Analysis," IJERPH, MDPI, vol. 19(2), pages 1-25, January.
    22. Wolfgang Dauth & Sebastian Findeisen & Jens Suedekum & Nicole Woessner, 2018. "Adjusting to Robots: Worker-Level Evidence," Opportunity and Inclusive Growth Institute Working Papers 13, Federal Reserve Bank of Minneapolis.
    23. Zhang, Guiling & Wang, Linjiang & Guo, Fei & Yang, Guochao, 2021. "Does corporate internationalization affect corporate social responsibility? Evidence from China," Emerging Markets Review, Elsevier, vol. 46(C).
    24. Christian Gunadi & Hanbyul Ryu, 2021. "Does the rise of robotic technology make people healthier?," Health Economics, John Wiley & Sons, Ltd., vol. 30(9), pages 2047-2062, September.
    25. Chen, Yi-Chun & Hung, Mingyi & Wang, Yongxiang, 2018. "The effect of mandatory CSR disclosure on firm profitability and social externalities: Evidence from China," Journal of Accounting and Economics, Elsevier, vol. 65(1), pages 169-190.
    26. Song, Yanwu & Niu, Niu & Song, Xinyi & Zhang, Bin, 2024. "Decoding the influence of servitization on green transformation in manufacturing firms: The moderating effect of artificial intelligence," Energy Economics, Elsevier, vol. 139(C).
    27. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2018. "Introduction to "The Economics of Artificial Intelligence: An Agenda"," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 1-19, National Bureau of Economic Research, Inc.
    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. Zhang, Zhenhua & Zhang, Yunpeng & Wu, Huangbin & Song, Shunfeng & Pan, Yuxi & Feng, Yanchao, 2024. "Dual effects of automation on economy and environment: Evidence from A-share listed enterprises in China," China Economic Review, Elsevier, vol. 88(C).
    2. Gries, Thomas & Naudé, Wim, 2020. "Artificial Intelligence, Income Distribution and Economic Growth," IZA Discussion Papers 13606, Institute of Labor Economics (IZA).
    3. Łukasz Arendt & Eugeniusz Kwiatkowski, 2023. "Kontrowersje wokół wpływu nowoczesnych technologii na zatrudnienie i bezrobocie," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 2, pages 195-216.
    4. Chen, Yang & Cheng, Liang & Lee, Chien-Chiang, 2022. "How does the use of industrial robots affect the ecological footprint? International evidence," Ecological Economics, Elsevier, vol. 198(C).
    5. He, Xiaogang & Teng, Ruifeng & Feng, Dawei & Gai, Jiahui, 2024. "Industrial robots and pollution: Evidence from Chinese enterprises," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 629-650.
    6. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    7. Fernández-Macías, Enrique & Klenert, David & Antón, José-Ignacio, 2021. "Not so disruptive yet? Characteristics, distribution and determinants of robots in Europe," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 76-89.
    8. Clément Bosquet & Paul Maarek & Elliot Moiteaux, 2021. "Routine-biased technological change and wages by education level: Occupational downgrading and displacement effects," Working Papers hal-03270715, HAL.
    9. Gregory, Terry & Salomons, Anna & Zierahn, Ulrich, 2016. "Racing With or Against the Machine? Evidence from Europe," VfS Annual Conference 2016 (Augsburg): Demographic Change 145843, Verein für Socialpolitik / German Economic Association.
    10. Jasmine Mondolo, 2022. "The composite link between technological change and employment: A survey of the literature," Journal of Economic Surveys, Wiley Blackwell, vol. 36(4), pages 1027-1068, September.
    11. Fierro, Luca Eduardo & Caiani, Alessandro & Russo, Alberto, 2022. "Automation, Job Polarisation, and Structural Change," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 499-535.
    12. Zhang, Xinchun & Sun, Murong & Liu, Jianxu & Xu, Aijia, 2024. "The nexus between industrial robot and employment in China: The effects of technology substitution and technology creation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    13. FU, Yunyun & SHEN, Yongchang & SONG, Malin & WANG, Weiyu, 2024. "Does artificial intelligence reduce corporate energy consumption? New evidence from China," Economic Analysis and Policy, Elsevier, vol. 83(C), pages 548-561.
    14. Nikolova, Milena & Cnossen, Femke & Nikolaev, Boris, 2024. "Robots, meaning, and self-determination," Research Policy, Elsevier, vol. 53(5).
    15. Du, Longzheng & Lin, Weifen, 2022. "Does the application of industrial robots overcome the Solow paradox? Evidence from China," Technology in Society, Elsevier, vol. 68(C).
    16. Oscar Afonso & Tiago Sequeira & Derick Almeida, 2023. "Technological knowledge and wages: from skill premium to wage polarization," Journal of Economics, Springer, vol. 140(2), pages 93-119, October.
    17. Roberto Antonietti & Luca Cattani & Francesca Gambarotto & Giulio Pedrini, 2021. "Education, routine, and complexity-biased Knowledge Enabling Technologies: Evidence from Emilia-Romagna, Italy," Discussion Paper series in Regional Science & Economic Geography 2021-07, Gran Sasso Science Institute, Social Sciences, revised May 2021.
    18. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the Digital Divide: Workers' Exposure to Digitalization and Its Consequences for Individual Employment," IZA Discussion Papers 14649, Institute of Labor Economics (IZA).
    19. Parteka, Aleksandra & Wolszczak-Derlacz, Joanna & Nikulin, Dagmara, 2024. "How digital technology affects working conditions in globally fragmented production chains: Evidence from Europe," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    20. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2021. "Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics," GLO Discussion Paper Series 802, Global Labor Organization (GLO).

    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:5:p:1822-:d:1596327. 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.