Synergy of blockchain technologies and artificial intelligence in supply chain management with an emphasis on the theory of complex networks

Abstract

This article examines the synergy of blockchain technologies and artificial intelligence in supply chain management using approaches from the theory of complex networks. The purpose of the study is to analyze the potential of integrating distributed registries that ensure transparency and immutability of data with artificial intelligence algorithms capable of analyzing large amounts of information and optimizing logistical processes. The relevance of the topic is due to the increasing complexity of global supply chains, the need to increase the efficiency of decision-making and ensure the security of transactions. The methodological basis of the research is based on a combined approach that includes modeling supply chain management processes using tools from the theory of complex networks. An integrated model has been developed in which blockchain technologies are used to record and verify data, and artificial intelligence is used to analyze, predict and make operational management decisions. For empirical verification of the model, computer modeling and simulation experiment methods were used, which made it possible to assess the stability and adaptability of the system in the context of dynamic changes in supply chain parameters. The results obtained demonstrate a significant increase in the efficiency of supply chain management: blockchain integration minimizes the risks of data forgery and increases trust between participants, while artificial intelligence algorithms help to quickly identify bottlenecks and optimize logistics routes. The analysis of the network structure revealed the presence of critical nodes that determine the overall stability of the system, which allows us to suggest ways for further optimization. The discussion of the results focuses on the potential of the proposed integrated system for the transformation of traditional supply chain management models. The main challenges are highlighted, including issues of scalability, data security, and the need to adapt to rapidly changing environmental conditions. The presented conclusions serve as the basis for further research aimed at developing integrated solutions in the field of logistics and digital business transformation.