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Research on Impact of Artificial Intelligence Orientation on Enterprise Green Innovation

Received: 13 January 2023     Accepted: 4 February 2023     Published: 14 February 2023
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Abstract

As the core technology to lead the digital future and promote the industrial revolution, artificial intelligence (AI) technology can empower the whole chain of manufacturing enterprises, accelerate the fundamental transformation of production mode and enterprise form, guide enterprises to integrate artificial intelligence with green innovative technology, and improve energy efficiency. Based on the background of green transformation faced by the manufacturing industry, we discuss the mechanism of artificial intelligence to realize green innovation of enterprises through dynamic capabilities. AI orientation refers to the tendency and strategy of enterprises in introducing and applying AI technology. Based on the strategic management theory and the resource-based view, a questionnaire survey for manufacturing enterprises was conducted. Using regression analysis method to conduct empirical research on 204 valid questionnaire data, to test the hypothesis. The result shows that AI has a significant positive effect on the green innovation of enterprises. Both strategic sensing capacity and timely decision-making capacity positively affect the green innovation of enterprises. Strategic sensing capacity and timely decision-making capacity play a partial mediating role between AI and green innovation. AI gives the light to enterprise development to clarify the direction of progress of the production technology. Enterprises need to establish AI-orientated strategies in many aspects to realize green innovation and improve environmental performance.

Published in International Journal of Business and Economics Research (Volume 12, Issue 1)
DOI 10.11648/j.ijber.20231201.16
Page(s) 40-45
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

AI Orientation, Strategic Sensing Capacity, Timely Decision-Making Capacity, Green Innovation

References
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[5] Wang, Y., Tian, Q., Li, X., & Xiao, X.,“Different roles, different strokes: How to leverage two types of digital platform capabilities to fuel service innovation,” Journal of Business Research, 2022, 144, 1121-1128.
[6] Duan, Y., Edwards, J. S. & Dwivedi Y. K,“Artificial Intelligence for Decision Making in the Era of Big Data-Evolution, Challenges and Research Agenda,” International Journal of Information Management, 2019, 48 (2): 63-71.
[7] Abbas, A., Luo, X., Wattoo, M. U., & Hu, R., “Organizational Behavior in Green Supply Chain Integration: Nexus Between Information Technology Capability, Green Innovation, and Organizational Performance,” Frontiers in Psychology, 2022, 13, 1-11.
[8] Li W., “Research on the Impact of strategic Orientation Balance on Product Innovation and Business Performance,” Science Research Management, 2015 (1): 1-9.
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Cite This Article
  • APA Style

    Can Tian, Jiangang Wu, Yu Xiao. (2023). Research on Impact of Artificial Intelligence Orientation on Enterprise Green Innovation. International Journal of Business and Economics Research, 12(1), 40-45. https://doi.org/10.11648/j.ijber.20231201.16

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    ACS Style

    Can Tian; Jiangang Wu; Yu Xiao. Research on Impact of Artificial Intelligence Orientation on Enterprise Green Innovation. Int. J. Bus. Econ. Res. 2023, 12(1), 40-45. doi: 10.11648/j.ijber.20231201.16

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    AMA Style

    Can Tian, Jiangang Wu, Yu Xiao. Research on Impact of Artificial Intelligence Orientation on Enterprise Green Innovation. Int J Bus Econ Res. 2023;12(1):40-45. doi: 10.11648/j.ijber.20231201.16

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  • @article{10.11648/j.ijber.20231201.16,
      author = {Can Tian and Jiangang Wu and Yu Xiao},
      title = {Research on Impact of Artificial Intelligence Orientation on Enterprise Green Innovation},
      journal = {International Journal of Business and Economics Research},
      volume = {12},
      number = {1},
      pages = {40-45},
      doi = {10.11648/j.ijber.20231201.16},
      url = {https://doi.org/10.11648/j.ijber.20231201.16},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20231201.16},
      abstract = {As the core technology to lead the digital future and promote the industrial revolution, artificial intelligence (AI) technology can empower the whole chain of manufacturing enterprises, accelerate the fundamental transformation of production mode and enterprise form, guide enterprises to integrate artificial intelligence with green innovative technology, and improve energy efficiency. Based on the background of green transformation faced by the manufacturing industry, we discuss the mechanism of artificial intelligence to realize green innovation of enterprises through dynamic capabilities. AI orientation refers to the tendency and strategy of enterprises in introducing and applying AI technology. Based on the strategic management theory and the resource-based view, a questionnaire survey for manufacturing enterprises was conducted. Using regression analysis method to conduct empirical research on 204 valid questionnaire data, to test the hypothesis. The result shows that AI has a significant positive effect on the green innovation of enterprises. Both strategic sensing capacity and timely decision-making capacity positively affect the green innovation of enterprises. Strategic sensing capacity and timely decision-making capacity play a partial mediating role between AI and green innovation. AI gives the light to enterprise development to clarify the direction of progress of the production technology. Enterprises need to establish AI-orientated strategies in many aspects to realize green innovation and improve environmental performance.},
     year = {2023}
    }
    

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  • TY  - JOUR
    T1  - Research on Impact of Artificial Intelligence Orientation on Enterprise Green Innovation
    AU  - Can Tian
    AU  - Jiangang Wu
    AU  - Yu Xiao
    Y1  - 2023/02/14
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    DO  - 10.11648/j.ijber.20231201.16
    T2  - International Journal of Business and Economics Research
    JF  - International Journal of Business and Economics Research
    JO  - International Journal of Business and Economics Research
    SP  - 40
    EP  - 45
    PB  - Science Publishing Group
    SN  - 2328-756X
    UR  - https://doi.org/10.11648/j.ijber.20231201.16
    AB  - As the core technology to lead the digital future and promote the industrial revolution, artificial intelligence (AI) technology can empower the whole chain of manufacturing enterprises, accelerate the fundamental transformation of production mode and enterprise form, guide enterprises to integrate artificial intelligence with green innovative technology, and improve energy efficiency. Based on the background of green transformation faced by the manufacturing industry, we discuss the mechanism of artificial intelligence to realize green innovation of enterprises through dynamic capabilities. AI orientation refers to the tendency and strategy of enterprises in introducing and applying AI technology. Based on the strategic management theory and the resource-based view, a questionnaire survey for manufacturing enterprises was conducted. Using regression analysis method to conduct empirical research on 204 valid questionnaire data, to test the hypothesis. The result shows that AI has a significant positive effect on the green innovation of enterprises. Both strategic sensing capacity and timely decision-making capacity positively affect the green innovation of enterprises. Strategic sensing capacity and timely decision-making capacity play a partial mediating role between AI and green innovation. AI gives the light to enterprise development to clarify the direction of progress of the production technology. Enterprises need to establish AI-orientated strategies in many aspects to realize green innovation and improve environmental performance.
    VL  - 12
    IS  - 1
    ER  - 

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Author Information
  • School of Business Administration, Guizhou University of Finance and Economics, Guiyang, China

  • School of Business Administration, Guizhou University of Finance and Economics, Guiyang, China

  • School of Business Administration, Guizhou University of Finance and Economics, Guiyang, China

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