IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v26y2024i8d10.1007_s10668-023-04225-6.html
   My bibliography  Save this article

Does artificial intelligence technology enhance green transformation of enterprises: based on green innovation perspective

Author

Listed:
  • Peng Liang

    (Capital University of Economics and Business)

  • Xinhui Sun

    (University of International Business and Economics)

  • Luzhuang Qi

    (University of International Business and Economics)

Abstract

In the context of the rapid development of artificial intelligence, industrial robots, as an important manifestation of artificial intelligence technology application, provide enterprises with a “creative destruction” environment, and play a positive role in energy utilization and environmental governance. Therefore, academics have focused a lot of attention on the question of whether industrial robot application can successfully improve corporate green innovation (CGI), thus achieving green transformation, and upgrading the manufacturing industry. This paper builds a “Bartik instrument variable” to calculate the micro-enterprise robot penetration rate from 2007 to 2019, looks at the effect of industrial robot application on CGI using data from manufacturing listed companies, and discusses the mechanism, heterogeneity, and robustness of this effect. The research finds that industrial robot application significantly improve CGI, indicating that they can promote corporate green technology transformation. This effect not only enhances the scale of CGI but also strengthens the quality of CGI. In addition, the above conclusion still holds after a series of endogeneity and robustness tests. Mechanism research shows that industrial robot application contribute to CGI by improving production efficiency, human capital, and environmental governance levels. It has a good complementary optimization effect on CGI. Furthermore, heterogeneity research shows that industrial robot application has a more significant role in enhancing green innovation for enterprises that are labor-intensive, more intense market competitive, more serious environmental pollution, and have lower level of digital economy development. The research conclusion verifies the effect of artificial intelligence technology and explores its mechanism, which provides empirical references for improving corporate environmental performance and green transformation.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:endesu:v:26:y:2024:i:8:d:10.1007_s10668-023-04225-6
    DOI: 10.1007/s10668-023-04225-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-023-04225-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10668-023-04225-6?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. Jay Dixon & Bryan Hong & Lynn Wu, 2021. "The Robot Revolution: Managerial and Employment Consequences for Firms," Management Science, INFORMS, vol. 67(9), pages 5586-5605, September.
    2. 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.
    3. Karen Palmer & Wallace E. Oates & Paul R. Portney & Karen Palmer & Wallace E. Oates & Paul R. Portney, 2004. "Tightening Environmental Standards: The Benefit-Cost or the No-Cost Paradigm?," Chapters, in: Environmental Policy and Fiscal Federalism, chapter 3, pages 53-66, Edward Elgar Publishing.
    4. Sen, Suphi, 2015. "Corporate governance, environmental regulations, and technological change," European Economic Review, Elsevier, vol. 80(C), pages 36-61.
    5. 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.
    6. Li, Saiwei & Lopez, Rigoberto A. & Liu, Yumei, 2020. "Consumer preferences for sustainably produced milk in China," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304193, Agricultural and Applied Economics Association.
    7. Gray, Wayne B. & Shadbegian, Ronald J., 2003. "Plant vintage, technology, and environmental regulation," Journal of Environmental Economics and Management, Elsevier, vol. 46(3), pages 384-402, November.
    8. Jie Zhang & Shilong Li, 2023. "The Impact of Human Capital on Green Technology Innovation—Moderating Role of Environmental Regulations," IJERPH, MDPI, vol. 20(6), pages 1-19, March.
    9. Kong, Dongmin & Zhang, Bohui & Zhang, Jian, 2022. "Higher education and corporate innovation," Journal of Corporate Finance, Elsevier, vol. 72(C).
    10. 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.
    11. Allen Blackman & Zhengyan Li & Antung A. Liu, 2018. "Efficacy of Command-and-Control and Market-Based Environmental Regulation in Developing Countries," Annual Review of Resource Economics, Annual Reviews, vol. 10(1), pages 381-404, October.
    12. Hua-Hung (Robin) Weng & Ja-Shen Chen & Pei-Ching Chen, 2015. "Effects of Green Innovation on Environmental and Corporate Performance: A Stakeholder Perspective," Sustainability, MDPI, vol. 7(5), pages 1-30, April.
    13. Michael Greenstone & John A. List & Chad Syverson, 2011. "The Effects of Environmental Regulation on the Competiveness of U.S. Manufacturing," Working Papers 11-03, Center for Economic Studies, U.S. Census Bureau.
    14. Zou, Ran & Yang, Jun & Feng, Chao, 2023. "Does informatization alleviate energy poverty? A global perspective," Energy Economics, Elsevier, vol. 126(C).
    15. Jana Stoever & John P. Weche, 2018. "Environmental Regulation and Sustainable Competitiveness: Evaluating the Role of Firm-Level Green Investments in the Context of the Porter Hypothesis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 70(2), pages 429-455, June.
    16. 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.
    17. Ariel T. Burstein & Alexander Monge-Naranjo, 2009. "Foreign Know-How, Firm Control, and the Income of Developing Countries," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(1), pages 149-195.
    18. Xu, Le & Yang, Lili & Li, Ding & Shao, Shuai, 2023. "Asymmetric effects of heterogeneous environmental standards on green technology innovation: Evidence from China," Energy Economics, Elsevier, vol. 117(C).
    19. repec:ags:aaea22:335879 is not listed on IDEAS
    20. Kim, Incheol & Pantzalis, Christos & Zhang, Zhengyi, 2021. "Multinationality and the value of green innovation," Journal of Corporate Finance, Elsevier, vol. 69(C).
    21. Dincer, Ibrahim & Acar, Canan, 2017. "Smart energy systems for a sustainable future," Applied Energy, Elsevier, vol. 194(C), pages 225-235.
    22. Remco H. Oostendorp, 2009. "Globalization and the Gender Wage Gap," The World Bank Economic Review, World Bank, vol. 23(1), pages 141-161, January.
    23. Philippe Aghion & Stefan Bechtold & Lea Cassar & Holger Herz, 2018. "The Causal Effects of Competition on Innovation: Experimental Evidence," The Journal of Law, Economics, and Organization, Oxford University Press, vol. 34(2), pages 162-195.
    24. Xiaofeng Quan & Yun Ke & Yuting Qian & Yao Zhang, 2023. "CEO Foreign Experience and Green Innovation: Evidence from China," Journal of Business Ethics, Springer, vol. 182(2), pages 535-557, January.
    25. 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.
    26. Huang, Geng & He, Ling-Yun & Lin, Xi, 2022. "Robot adoption and energy performance: Evidence from Chinese industrial firms," Energy Economics, Elsevier, vol. 107(C).
    27. Caglar, Abdullah Emre & Askin, Bekir Emre, 2023. "A path towards green revolution: How do competitive industrial performance and renewable energy consumption influence environmental quality indicators?," Renewable Energy, Elsevier, vol. 205(C), pages 273-280.
    28. Faber, Marius, 2020. "Robots and reshoring: Evidence from Mexican labor markets," Journal of International Economics, Elsevier, vol. 127(C).
    29. Xu, Jia & Zeng, Shu & Qi, Shaozhou & Cui, Jingbo, 2023. "Do institutional investors facilitate corporate environmental innovation?," Energy Economics, Elsevier, vol. 117(C).
    30. Amore, Mario Daniele & Bennedsen, Morten, 2016. "Corporate governance and green innovation," Journal of Environmental Economics and Management, Elsevier, vol. 75(C), pages 54-72.
    31. Singh, Sanjay Kumar & Giudice, Manlio Del & Chierici, Roberto & Graziano, Domenico, 2020. "Green innovation and environmental performance: The role of green transformational leadership and green human resource management," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    32. Yousaf, Umair Bin & Ullah, Irfan & Jiang, Junchen & Wang, Man, 2022. "The role of board capital in driving green innovation: Evidence from China," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    33. 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).
    34. Klaus Rennings & Christian Rammer, 2011. "The Impact of Regulation-Driven Environmental Innovation on Innovation Success and Firm Performance," Industry and Innovation, Taylor & Francis Journals, vol. 18(3), pages 255-283.
    35. Feng Zhang & Lei Zhu, 2019. "Enhancing corporate sustainable development: Stakeholder pressures, organizational learning, and green innovation," Business Strategy and the Environment, Wiley Blackwell, vol. 28(6), pages 1012-1026, September.
    36. Wolfgang Gerstlberger & Mette Præst Knudsen & Ian Stampe, 2014. "Sustainable Development Strategies for Product Innovation and Energy Efficiency," Business Strategy and the Environment, Wiley Blackwell, vol. 23(2), pages 131-144, February.
    37. Böhringer, Christoph & Moslener, Ulf & Oberndorfer, Ulrich & Ziegler, Andreas, 2012. "Clean and productive? Empirical evidence from the German manufacturing industry," Research Policy, Elsevier, vol. 41(2), pages 442-451.
    38. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    39. McCullough, Ellen B., 2017. "Labor productivity and employment gaps in Sub-Saharan Africa," Food Policy, Elsevier, vol. 67(C), pages 133-152.
    40. He, Feng & Yan, Yulin & Hao, Jing & Wu, Ji (George), 2022. "Retail investor attention and corporate green innovation: Evidence from China," Energy Economics, Elsevier, vol. 115(C).
    41. 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.
    42. Gan, Jiawu & Liu, Lihua & Qiao, Gang & Zhang, Qin, 2023. "The role of robot adoption in green innovation: Evidence from China," Economic Modelling, Elsevier, vol. 119(C).
    43. Won‐Moo Hur & Yeonshin Kim & Kyungdo Park, 2013. "Assessing the Effects of Perceived Value and Satisfaction on Customer Loyalty: A ‘Green’ Perspective," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 20(3), pages 146-156, May.
    44. Ma, Dan & Zhu, Qing, 2022. "Innovation in emerging economies: Research on the digital economy driving high-quality green development," Journal of Business Research, Elsevier, vol. 145(C), pages 801-813.
    45. DeCanio, Stephen J., 2016. "Robots and humans – complements or substitutes?," Journal of Macroeconomics, Elsevier, vol. 49(C), pages 280-291.
    46. Balsmeier, Benjamin & Woerter, Martin, 2019. "Is this time different? How digitalization influences job creation and destruction," Research Policy, Elsevier, vol. 48(8), pages 1-1.
    47. Andrew D. Foster & Emilio Gutierrez, 2013. "The Informational Role of Voluntary Certification: Evidence from the Mexican Clean Industry Program," American Economic Review, American Economic Association, vol. 103(3), pages 303-308, May.
    48. Horbach, Jens, 2008. "Determinants of environmental innovation--New evidence from German panel data sources," Research Policy, Elsevier, vol. 37(1), pages 163-173, February.
    49. Chan, Hing Kai & Yee, Rachel W.Y. & Dai, Jing & Lim, Ming K., 2016. "The moderating effect of environmental dynamism on green product innovation and performance," International Journal of Production Economics, Elsevier, vol. 181(PB), pages 384-391.
    50. Ching-Hsun Chang, 2011. "The Influence of Corporate Environmental Ethics on Competitive Advantage: The Mediation Role of Green Innovation," Journal of Business Ethics, Springer, vol. 104(3), pages 361-370, December.
    51. Daron Acemoglu, 1996. "A Microfoundation for Social Increasing Returns in Human Capital Accumulation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(3), pages 779-804.
    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. Peng Liang & Xinhui Sun, 2024. "Does digital transformation promote the green innovation of China’s listed companies?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(9), pages 22199-22235, September.
    2. Gan, Jiawu & Liu, Lihua & Qiao, Gang & Zhang, Qin, 2023. "The role of robot adoption in green innovation: Evidence from China," Economic Modelling, Elsevier, vol. 119(C).
    3. Lin, Boqiang & Xu, Chongchong, 2024. "Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities," Applied Energy, Elsevier, vol. 365(C).
    4. He, Feng & Yan, Yulin & Hao, Jing & Wu, Ji (George), 2022. "Retail investor attention and corporate green innovation: Evidence from China," Energy Economics, Elsevier, vol. 115(C).
    5. Li, Jianjun & Wu, Zhouyi & Yu, Kaijia & Zhao, Wei, 2024. "The effect of industrial robot adoption on firm value: Evidence from China," Finance Research Letters, Elsevier, vol. 60(C).
    6. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    7. Zhang, Yi & Wang, Ting & Liu, Chun, 2024. "Beyond the modern productivity paradox: The effect of robotics technology on firm-level total factor productivity in China," Journal of Asian Economics, Elsevier, vol. 90(C).
    8. Shi, Xuanyi & Lin, Yongjia & Wang, Yizhi, 2024. "Institutional investor heterogeneity and green innovation in China: Does digital transformation matter?," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 994-1014.
    9. 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).
    10. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    11. Zhou, Zhongsheng & Li, Zhuo & Du, Shanzhong & Cao, June, 2024. "Robot adoption and enterprise R&D manipulation: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    12. Xinwei Li & Wenjuan Zeng & Mao Xu, 2022. "The Moderating Role of IT Capability on Green Innovation and Ambidexterity: Towards a Corporate Sustainable Development," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
    13. Murtaza Hussain & Shaohua Yang & Umer Sahil Maqsood & R. M. Ammar Zahid, 2024. "Tapping into the green potential: The power of artificial intelligence adoption in corporate green innovation drive," Business Strategy and the Environment, Wiley Blackwell, vol. 33(5), pages 4375-4396, July.
    14. Valeria Cirillo & Andrea Mina & Andrea Ricci, 2024. "Digital Technologies, Labor market flows and Training: Evidence from Italian employer-employee data," LEM Papers Series 2024/22, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    15. Tariq, Adeel & Badir, Yuosre F. & Tariq, Waqas & Bhutta, Umair Saeed, 2017. "Drivers and consequences of green product and process innovation: A systematic review, conceptual framework, and future outlook," Technology in Society, Elsevier, vol. 51(C), pages 8-23.
    16. 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.
    17. 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.
    18. 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).
    19. Davide Dottori, 2021. "Robots and employment: evidence from Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 739-795, July.
    20. Cui, Huijie & Liang, Shangkun & Xu, Canyu & Junli, Yu, 2024. "Robots and analyst forecast precision: Evidence from Chinese manufacturing," International Review of Financial Analysis, Elsevier, vol. 94(C).

    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:spr:endesu:v:26:y:2024:i:8:d:10.1007_s10668-023-04225-6. 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: http://www.springer.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.