潜在Dirichlet分配
可追溯性
供应链
块链
主题模型
计算机科学
数据科学
供应链管理
钥匙(锁)
云计算
可扩展性
过程管理
SWOT分析
仿制品
知识管理
业务
数据库
营销
软件工程
人工智能
操作系统
法学
计算机安全
政治学
作者
Truong Van Nguyen,Hiep Pham,Minh Nhat Nguyen,Li Zhou,Mohammadreza Akbari
标识
DOI:10.1080/00207543.2023.2165190
摘要
Blockchain (BC) applications in supply chain management (SCM) have recently received extensive attention. It is important to synthesise the extant literature on the field to identify key research themes and navigate potential future directions. This study thus develops an efficient, scalable data-driven review approach that uses text mining and Latent Dirichlet Allocation (LDA)-based topic modelling for automatic content analysis of full-text documents. Our method overcomes the drawbacks of traditional systematic literature reviews using either manual coding or bibliographic analysis for article classifications, which are highly time-consuming and biased when dealing with large amounts of text. 108 papers published between 2017 and 2022 were analysed which identified 10 key research themes, including revenue management, sustainability, traceability, manufacturing system, scheduling in cloud manufacturing, healthcare SCM, anti-counterfeit system, logistics and transportation, system architecture development, and food & agriculture SC. Five future directions are then suggested, including (1) integration of BC and other emerging technologies for global and scalable SCM, (2) crypto-X applications in SCM, (3) BC-enabled closed-loop SCM, (4) the environmental and social impacts of BC-based SCM and (5) decentralised autonomous organisations in SCM.
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