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Artificial Intelligence Adoption and Digital Innovation: How Does Digital Resilience Act as a Mediator and Training Protocols as a Moderator?

Author

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  • Xiaochun Zeng

    (School of Economics and Management, Xi’an University of Technology, Xi’an 710048, China)

  • Suicheng Li

    (School of Economics and Management, Xi’an University of Technology, Xi’an 710048, China)

  • Zahid Yousaf

    (Higher Education Department, Government College of Management Sciences, Mansehra 23100, Pakistan)

Abstract

This study aims to discover how technology firms accomplish digital innovation through AI adoption. The current research also investigated digital resilience’s role as a mediator and training protocol’s role as a moderator between AI adoption and digital innovation links. The data collection and analysis were conducted using a quantitative method. To examine the research hypotheses, we chose technology firms that face problems regarding the enhancement of digital innovation. The findings confirmed that the digital innovation of technology firms is forecasted through AI adoption. The results proved that digital resilience plays a mediating role between AI adoption and digital innovation links. Technology firms play a key role in the advancement of digital technology. This research study adds to the existing knowledge by offering a digital innovation model with the combined influence of AI adoption, digital resilience, and training protocol. This study will be helpful for top management by showing when, why, and how AI adoption helps firms in their achievement of digital innovation. Moreover, digital resilience’s role is also important in the current digitalized world; thus, we used digital resilience as mediator in this research.

Suggested Citation

  • Xiaochun Zeng & Suicheng Li & Zahid Yousaf, 2022. "Artificial Intelligence Adoption and Digital Innovation: How Does Digital Resilience Act as a Mediator and Training Protocols as a Moderator?," Sustainability, MDPI, vol. 14(14), pages 1-14, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8286-:d:857049
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    References listed on IDEAS

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    Cited by:

    1. Li, Chengming & Xu, Yang & Zheng, Hao & Wang, Zeyu & Han, Haiting & Zeng, Liangen, 2023. "Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China's listed companies," Resources Policy, Elsevier, vol. 81(C).
    2. Abdelmohsen A. Nassani & Asad Javed & Joanna Rosak-Szyrocka & Ladislav Pilar & Zahid Yousaf & Mohamed Haffar, 2023. "Major Determinants of Innovation Performance in the Context of Healthcare Sector," IJERPH, MDPI, vol. 20(6), pages 1-14, March.

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