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Explore success factors that impact artificial intelligence adoption on telecom industry in China

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  • Hong Chen
  • Ling Li
  • Yong Chen

Abstract

As the core driving force of the new round of informatization development and industrial revolution, the disruptive achievements of artificial intelligence (AI) are rapidly and comprehensively infiltrating into various fields of human activities. Although technologies and applications of AI have been widely studied and factors that affect AI adoption are identified in existing literature, the impact of success factors on AI adoption remains unknown. Accordingly, this paper proposes a framework to explore the impacts of success factors on AI adoption in telecom industry by integrating the technology, organization, and environment (TOE) framework and diffusion of innovation (DOI) theory. Particularly, this framework consists of factors regarding external environment, organizational capabilities, and innovation attributes of AI. The framework is empirically tested with data collected by surveying telecom companies in China. Structural equation modeling is applied to analyze the data. The study provides support for firms’ decision-making and resource allocation regarding AI adoption.

Suggested Citation

  • Hong Chen & Ling Li & Yong Chen, 2021. "Explore success factors that impact artificial intelligence adoption on telecom industry in China," Journal of Management Analytics, Taylor & Francis Journals, vol. 8(1), pages 36-68, January.
    • Handle: RePEc:taf:tjmaxx:v:8:y:2021:i:1:p:36-68
    DOI: 10.1080/23270012.2020.1852895
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    14. Gupta, Somya & Ghardallou, Wafa & Pandey, Dharen Kumar & Sahu, Ganesh P., 2022. "Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework," Research in International Business and Finance, Elsevier, vol. 63(C).
    15. Yu Sun & Xiaobo Xu & Haiqing Yu & Hecheng Wang, 2022. "Impact of value co‐creation in the artificial intelligence innovation ecosystem on competitive advantage and innovation intelligibility," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 474-488, May.
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    17. Jing Liu & Mengbo Wang & Xiaoling Kang & Xia Zhang & Xing Chen, 2022. "Seizing the opportunity window of artificial intelligence in China: Towards an innovation policy mix framework for emerging technologies from an evolution perspective," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 397-414, May.
    18. Ghobakhloo, Morteza & Asadi, Shahla & Iranmanesh, Mohammad & Foroughi, Behzad & Mubarak, Muhammad Faraz & Yadegaridehkordi, Elaheh, 2023. "Intelligent automation implementation and corporate sustainability performance: The enabling role of corporate social responsibility strategy," Technology in Society, Elsevier, vol. 74(C).
    19. Baoshan Ge & Liyi Zhao, 2022. "The impact of the integration of opportunity and resources of new ventures on entrepreneurial performance: The moderating role of BDAC‐AI," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 440-461, May.
    20. Dahlke, Johannes & Beck, Mathias & Kinne, Jan & Lenz, David & Dehghan, Robert & Wörter, Martin & Ebersberger, Bernd, 2024. "Epidemic effects in the diffusion of emerging digital technologies: evidence from artificial intelligence adoption," Research Policy, Elsevier, vol. 53(2).
    21. Ming-Ching Hsu, 2023. "The Construction of Critical Factors for Successfully Introducing Chatbots into Mental Health Services in the Army: Using a Hybrid MCDM Approach," Sustainability, MDPI, vol. 15(10), pages 1-22, May.
    22. Weifeng Jia & Shuo Wang & Yongping Xie & Zifeng Chen & Kaixin Gong, 2022. "Disruptive technology identification of intelligent logistics robots in AIoT industry: Based on attributes and functions analysis," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 557-568, May.

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