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Physics Maths Engineering

AI technology specialization and national competitiveness

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Youngsam Chun,

Youngsam Chun


Jisoo Hur,

Jisoo Hur


Junseok Hwang

Junseok Hwang


  Peer Reviewed

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© attribution CC-BY

  • 0

rating
377 Views

Added on

2024-10-20

Doi: http://dx.doi.org/10.1371/journal.pone.0301091

Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology

Abstract

This study investigates the factors influencing specialization in artificial intelligence (AI) technology, a critical element of national competitiveness. We utilized a revealed comparative advantage matrix to evaluate technological specialization across countries and employed a three-way fixed-effect panel logit model to examine the relationship between AI specialization and its determinants. The results indicate that the development of AI technology is strongly contingent on a nation’s pre-existing technological capabilities, which significantly affect AI specialization in emerging domains. Additionally, this study reveals that scientific knowledge has a positive impact on technological specialization, highlighting the necessity of integrating scientific advancements with technological sectors. Although complex technologies positively influence AI specialization, their effect is less pronounced than that of scientific knowledge. This suggests that in rapidly advancing fields, such as AI, incorporating new scientific knowledge into related industries may be more advantageous than simply advancing existing technologies to outpace competitors. This insight points nations toward enhancing AI competitiveness in new areas, emphasizing the vital importance of both scientific and technological capabilities, and the integration of novel AI knowledge with established sectors. This research offers critical guidance for policymakers in less technologically and economically developed countries, as these nations may not have the technological infrastructure required to foster AI specialization through increased technical complexity.

Key Questions

1. What factors influence a nation's specialization in AI technology?

The study identifies that a nation's pre-existing technological capabilities and scientific knowledge significantly impact its specialization in AI technology.

2. How do pre-existing technological capabilities affect AI specialization?

The research indicates that nations with strong technological foundations are better positioned to specialize in emerging domains like AI, leveraging their existing infrastructure and expertise.

3. What role does scientific knowledge play in technological specialization?

The study reveals that scientific knowledge positively impacts technological specialization, highlighting the necessity of integrating scientific advancements with technological sectors.

4. How do complex technologies influence AI specialization?

While complex technologies positively influence AI specialization, their effect is less pronounced than that of scientific knowledge. This suggests that in rapidly advancing fields like AI, incorporating new scientific knowledge into related industries may be more advantageous than simply advancing existing technologies.

Summary

Chun, Hur, and Hwang's study emphasizes that a nation's specialization in AI technology is strongly influenced by its pre-existing technological capabilities and scientific knowledge. The findings suggest that integrating scientific advancements into technological sectors is crucial for enhancing national competitiveness in AI. Additionally, while complex technologies contribute to AI specialization, the impact of scientific knowledge is more significant, indicating the importance of fostering scientific research and its application in technological development.

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ARTICLE USAGE


Article usage: Oct-2024 to May-2025
Show by month Manuscript Video Summary
2025 May 38 38
2025 April 57 57
2025 March 63 63
2025 February 44 44
2025 January 50 50
2024 December 55 55
2024 November 45 45
2024 October 25 25
Total 377 377
Show by month Manuscript Video Summary
2025 May 38 38
2025 April 57 57
2025 March 63 63
2025 February 44 44
2025 January 50 50
2024 December 55 55
2024 November 45 45
2024 October 25 25
Total 377 377
Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology
copyright icon

© attribution CC-BY

  • 0

rating
377 Views

Added on

2024-10-20

Doi: http://dx.doi.org/10.1371/journal.pone.0301091

Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology

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