Open Access
Publication Frequency:Continuously
Blockchain is a revolutionary promising practical technology. At present, it is in the process of accelerating evolution and development, from its initial application in digital cash to its present extension to digital finance, internet of things, intelligent manufacturing, supply chain management, digital asset transactions, metaverse and other fields. Even though blockchain and intelligent computing have highly different developing parties and applications, researchers have been discussing and exploring their combination. It goes without saying that each technology has its own individual degree of complexity, but both blockchain and intelligent computing are in situations where they can benefit from each other, and help one another. Journal of Blockchain and Intelligent Computing aims to gather researchers and industry practitioners in blockchain and intelligent computing, focuses on studying and understanding the algorithms, techniques, theories, applications and security issues can be adopted or modified to extend and enrich computer science, and enrich the understanding and control in society and in individual human beings.
Open Access
REVIEW
Journal of Blockchain and Intelligent Computing, Vol.2, pp. 1-26, 2026, DOI:10.32604/jbic.2026.077106 - 11 March 2026
Abstract This study conducts a systematic bibliometric investigation of scholarly research on game-theoretic applications in blockchain ecosystems over the period 2014–2024, based on 554 publications retrieved from the Web of Science and Scopus databases. Using citation analysis, co-citation analysis, bibliographic coupling, and keyword co-occurrence mapping implemented through VOSviewer, the study quantitatively reveals the intellectual structure, thematic evolution, and collaborative architecture of this interdisciplinary research domain. The results demonstrate an exponential growth in publications after 2020, corresponding with the rapid expansion of decentralized finance (DeFi) and Web3 ecosystems. Five dominant research clusters are identified: consensus mechanisms, token… More >
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