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A bibliometric analysis of inventory management research based on knowledge mapping

机译：基于知识图谱的库存管理研究文献计量分析

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Purpose The research mainly aims at the hotspot of inventory management by knowledge mapping and provides a visualization reference in this research field.Design/methodology/approach First, inventory management journals during 1986 to 2017 were selected as the research object and text formatting in the Web of Science (WOS) database is exported. Then inventory management knowledge mapping is done and clustering keywords are extracted by using CiteSpace and VOSviewer software. Based on co-word analysis, the three special clusters are exported: inventory optimization strategy, inventory pricing and inventory technology. Besides, the clustering structure and time evolution are analysed. Finally, bibliographic item co-occurrence matrix builder (BICOMB) was used to extract the journal and researchers keywords in the inventory management research fields. Setting three parameters such as the cited half-life, centrality, frequency and keywords for data mining, it can infer the trend keywords of future research.Findings Results showed that inventory management research has been abundant in literature over the past 30 years and has experienced a change from focusing on inventory optimization strategy to inventory pricing and inventory technology in process. It shows that inventory management research focused on the classic topics and includes economic order quantity, dynamic pricing, design and technology, and the new topics include channel coordination, hierarchical price and simulation.Research limitations/implications Based on knowledge mapping, this study is still relatively macro and cannot cover all areas of inventory management. This study only investigated the state of correlational research in WOS and Google Trends and not additional databases.Originality/value The current research mainly builds on knowledge mapping for the research hotspot of inventory management and provides visual references for future research in this field.
机译：目的研究主要针对通过知识图谱进行库存管理的热点问题，并为该研究领域提供可视化参考。设计/方法/方法首先，选择1986年至2017年间的库存管理期刊作为研究对象，并在Web上设置文本格式。科学（WOS）数据库已导出。然后使用CiteSpace和VOSviewer软件完成库存管理知识映射并提取聚类关键字。基于共词分析，导出了三个特殊类：库存优化策略，库存定价和库存技术。此外，分析了聚类结构和时间演化。最后，书目项目共现矩阵构建器（BICOMB）用于提取库存管理研究领域中的期刊和研究人员关键字。设置引用的半衰期，中心性，频率和关键词三个参数进行数据挖掘，可以推断出未来研究的趋势关键词。结果表明，库存管理研究在过去的30年中已有丰富的文献，并且经验丰富。从专注于库存优化策略到库存定价和库存技术的转变。它表明库存管理研究集中在经典主题上，包括经济订单数量，动态定价，设计和技术，新主题包括渠道协调，分层价格和模拟。相对宏，无法涵盖库存管理的所有领域。这项研究仅调查了WOS和Google趋势中的相关研究状态，未调查其他数据库。原始内容/价值当前的研究主要建立在库存管理研究热点的知识映射上，并为该领域的未来研究提供可视参考。

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