The Impact of Innovation-Economic Development Metrics on Research Output in Artificial Intelligence and Economics

Nazira A. Gumar and Asan A. Satmurzaev
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Nazira A. Gumar: Almaty Technological University
Asan A. Satmurzaev: Turan University

Economic Consultant, 2026, issue 2, 4-21

Abstract: Introduction. Rising investments in digitalization demand a clear understanding of both AI achievements and the factors driving research activity and publication dynamics. This insight reveals how economic conditions and innovative environments fuel knowledge creation and dissemination. The study aims to quantify how innovation-economic development metrics drive publication trends among researchers working at the intersection of AI and economics. Materials and Methods. Data sources include peer-reviewed journal articles, monograph chapters, edited collections, and conference proceedings. The sample comprises 39 countries publishing over 30 AI papers. Methods include Pearson correlation analysis (r coefficients and p-values) and principal component analysis with Varimax rotation. Results. The volume of AI articles and total Scopus-indexed papers revealed the strongest association (r = 0.888, p is less than 0.001), followed by the relationship between AI articles and the number of Scopus-indexed journals (r = 0.786, p is less than 0.001). A distinct “science and economy” cluster emerged, linking human capital growth directly to scientific and economic outcomes. Conversely, the Global Innovation Index showed no positive association with the number of AI publications or other variables within the cluster. The United Kingdom generates a high volume of Scopus publications but maintains a moderate AI research output. China produces massive AI research but holds a smaller overall share of articles in Scopus. The Netherlands exhibits a mid-level volume of AI publications alongside a substantial number of Scopus-indexed articles. These discrepancies stem from Scopus indexing characteristics and language coverage rather than actual differences in AI research activity. Conclusion. The results demonstrate that the innovation-economic environment largely drives global research in artificial intelligence and economics. Advanced innovation infrastructure and robust R&D investments directly stimulate publication output and broaden research distribution. While this relationship spans across various countries, regional characteristics and scientific-institutional frameworks alter its intensity.

Keywords: innovationeconomic development; publication activity; artificial intelligence in economics (search for similar items in EconPapers)
JEL-codes: C8 D8 O3 O4 (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:ris:statec:022631

DOI: 10.46224/ecoc.2026.2.1

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