Statistical Model of the Growth in Artificial Intelligence Utilization for Enhancing Supply Chain Resilience

Abstract

Supply chain resilience refers to organizations’ ability to maintain stability and respond effectively to crises and sudden disruptions. As supply chains become increasingly complex, artificial intelligence (AI) has emerged as a highly efficient analytical tool. Through data analysis, pattern prediction, and risk identification, AI enables companies to respond promptly and optimally to critical conditions. This study systematically reviews and performs a bibliometric analysis of 238 review articles published between 2000 and 2024, examining the growth trends and thematic structure of research in the field of "artificial intelligence and supply chain resilience." Findings indicate that over 65% of the articles were published in the past five years (2019–2023), with the primary research focus centered on "artificial intelligence and machine learning." Keyword co-occurrence network analysis using scientometric indices reveals that the phrase “Internet of Things” holds the highest centrality score and is positioned at the center of the network. On average, each frequently used keyword is linked to more than 15 other concepts, with the network’s average degree estimated between 8 and 12. Thematic clustering of the research corpus reveals the formation of seven prominent research clusters, including "smart agriculture," "cold chain logistics," and "energy management." Among these, the cluster of "artificial intelligence and machine learning" has the highest share, indicating a strong research focus in recent years. The publication bias test yielded a Z-value of 1.614 (less than the critical value of 2.39 at the 0.05 significance level), indicating no significant bias in the data and thus affirming the validity of the current analysis. Moreover, based on practical study results, the implementation of AI algorithms has led to an average reduction of approximately 18% in operational supply chain costs and an increase of up to 25% in recovery speed following disruptions. These numerical and structural findings demonstrate that artificial intelligence—especially in interaction with the Internet of Things and machine learning—has played a pivotal and catalytic role in research related to supply chain resilience and is expected to continue to do so in the future. The clustered studies in the domain of supply chain resilience using artificial intelligence identified seven main clusters with significant differences in participation and growth trends. The largest cluster, “artificial intelligence and machine learning,” accounts for approximately 35% of all articles and has experienced a remarkable growth surge, particularly since 2019.