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The impact of artificial intelligence industry agglomeration on economic complexity

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  • Yang Shoufu
  • Ma Dan
  • Shen Zuiyi
  • Wen Lin
  • Dong Li

Abstract

Artificial intelligence (AI) is a fundamental driver of technological and economic growth. However, few studies have focused on the impact of AI industry agglomeration on economic complexity. This study uses a unique dataset of 2,503,795 AI enterprises in China collected through web crawlers to measure AI industrial agglomeration and examine the relationship between AI industry agglomeration and economic complexity in 194 Chinese cities based on Marshall industry agglomeration theory. The study’s results show that AI industry clustering increases economic complexity. The mechanism analysis indicates that people and knowledge are the channels through which it boosts economic complexity. Unexpectedly, AI industry agglomeration does not improve the economic complexity index (ECI) through the goods path. This study proposes three possible explanations for this result. First, AI industrial clustering may lead to excessive rivalry in China’s intermediate product market. Hence, sharing intermediate inputs has no increasing returns effect. Second, the city's high-end talent is not fairly distributed due to China's uneven development. Finally, policies drive the formation of China’s AI industrial agglomeration, which does not develop naturally. Consequently, China should implement a talent- and knowledge-driven AI agglomeration. To avoid overcrowding, policies must match regional development.

Suggested Citation

  • Yang Shoufu & Ma Dan & Shen Zuiyi & Wen Lin & Dong Li, 2023. "The impact of artificial intelligence industry agglomeration on economic complexity," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 36(1), pages 1420-1448, March.
    • Handle: RePEc:taf:reroxx:v:36:y:2023:i:1:p:1420-1448
    DOI: 10.1080/1331677X.2022.2089194
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    Cited by:

    1. Bonilla, George J.J. & Dietlmeier, Simon Frederic & Urmetzer, Florian, 2023. "Multi-Stakeholder Ecosystem for Standardization of AI in Industry," MPRA Paper 120619, University Library of Munich, Germany.

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