Artificial Intelligence and Economic Development: An Evolutionary Investigation and Systematic Review

Yong Qin, Zeshui Xu, Xinxin Wang and Marinko Skare
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Yong Qin: Sichuan University
Zeshui Xu: Sichuan University
Xinxin Wang: Sichuan University

Journal of the Knowledge Economy, 2024, vol. 15, issue 1, No 69, 1736-1770

Abstract: Abstract In today’s environment of the rapid rise of artificial intelligence (AI), debate continues about whether it has beneficial effects on economic development. However, there is only a fragmented perception of what role and place AI technology actually plays in economic development (ED). In this paper, we pioneer the research by focusing our detective work and discussion on the intersection of AI and economic development. Specifically, we adopt a two-step methodology. At the first step, we analyze 2211 documents in the AI&ED field using the bibliometric tool Bibliometrix, presenting the internal structure and external characteristics of the field through different metrics and algorithms. In the second step, a qualitative content analysis of clusters calculated from the bibliographic coupling algorithm is conducted, detailing the content directions of recently distributed topics in the AI&ED field from different perspectives. The results of the bibliometric analysis suggest that the number of publications in the field has grown exponentially in recent years, and the most relevant source is the “Sustainability” journal. In addition, deep learning and data mining-related research are the key directions for the future. On the whole, scholars dedicated to the field have developed close cooperation and communication across the board. On the other hand, the content analysis demonstrates that most of the research is centered on the five facets of intelligent decision-making, social governance, labor and capital, Industry 4.0, and innovation. The results provide a forward-looking guide for scholars to grasp the current state and potential knowledge gaps in the AI&ED field.

Keywords: Artificial intelligence; Economic development; Bibliometrix; Content analysis; Bibliographic coupling (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13132-023-01183-2

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