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| Analysis of the Influence Mechanism and Opportunities for the Convergence of Artificial Intelligence Technology and Traditional Industries from the Perspective of Multilayer Networks |
| Wang Tao1,2, Wang Jiajie1,2, Kang Lele1,2 |
1.Laboratory of Data Intelligence and Interdisciplinary Innovation, Nanjing University, Nanjing 210023
2.School of Information Management, Nanjing University, Nanjing 210023 |
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Abstract Exploring the influence mechanism and potential convergence opportunities of artificial intelligence technology and traditional industries is important for promoting the construction of modernized industrial systems and the convergence development of digital and real economies. Based on patent data in the field of convergence of artificial intelligence technology and traditional industries after in-depth screening, this study constructs a multilayer network of organizational technology and measures relevant indices, takes the field of unmanned aerial vehicles as a sample, and utilizes the exponential random graph model to empirically explore the influence mechanism of the convergence of artificial intelligence technology and traditional industries. It further identifies and analyzes the convergence opportunities based on the probability of connecting the edges of the fitted results of the model. The results of the study show that (1) the formation of a convergence network between AI technology and traditional industries is jointly driven by organizational cooperation and technological fusion, and the contribution of organizational cooperation may be effective only for innovation-advantageous organizations; (2) the mediating effect has a significant negative impact on the formation of convergence networks between AI technology and traditional industries; and (3) the probabilistic prediction method based on the results of the exponential stochastic graph model fitting can effectively identify convergence opportunities, specifically including the three technical themes of precision agriculture, intelligent inspection, and special operations. This study provides a reference for the construction of a convergent innovation ecology of artificial intelligence technology and traditional industries.
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Received: 24 January 2025
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