系统管理学报

系统管理学报 ›› 2024, Vol. 33 ›› Issue (2): 279-296.DOI: 10.3969/j.issn.1005-2542.2024.02.001

• 决策科学与运营管理 •    下一篇

基于大数据的血液供应链管理研究综述及展望

郭心雨1，陈旭2   

  1. 1.中北大学经济与管理学院，太原 030051；2.电子科技大学经济与管理学院，成都 611731
  • 收稿日期:2023-03-24 修回日期:2023-06-12 出版日期:2024-03-28 发布日期:2024-04-02
  • 基金资助:

    国家自然科学基金重大研究计划培育项目（91646109）

Review and Prospect of Blood Supply Chain Management Based on Big Data

GUO Xinyu1，CHEN Xu2   

  1. 1.School of Economics and Management,North University of China, Taiyuan 030051, China; 2.School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, China
  • Received:2023-03-24 Revised:2023-06-12 Online:2024-03-28 Published:2024-04-02

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摘要：

血液供应链相关综述论文多聚焦于研究问题、方法、趋势和挑战等方面，缺少从数据应用角度探讨血液供应链管理的综述性研究。利用文献计量方法回顾了116篇学术论文，可视化地展示了基于大数据的血液供应链管理相关研究合作和热点。在此基础上，从大数据视角探讨血液采集管理、血液库存与分配管理以及血液供应链网络设计3个方面的研究热点。最后，提出基于大数据的血液供应链管理PAGE框架阐述未来研究方向。研究成果有助于学界更准确地追踪和聚焦血液供应链管理中大数据的应用研究前沿和主题，为业界利用大数据管理血液供应链提供重要指导方向。

关键词:

医疗与健康管理, 大数据, 血液供应链, 研究综述, 知识图谱

Abstract:

At present, most of the review papers related to blood supply chain mainly focus on research issues, methods, trends, and challenges, lacking comprehensive research on blood supply chain management from the perspective of data application. Therefore, in this paper, 116 academic papers were reviewed using bibliometric methods to visually display the cooperation and hot spots related to blood supply chain management based on big data, based on which, the research hotspots of blood collection management, blood inventory and distribution management, and blood supply chain network design were explored from the perspective of big data. In addition, a PAGE framework was proposed for blood supply chain management based on big data to elaborate future research directions. This paper will help scholars more accurately track and focus on the research frontiers and topics of big data application in blood supply chain management, and provide important guidance for the industry to manage blood supply chain utilizing big data methods.

Key words:

healthcare management, big data, blood supply chain, review, knowledge graph

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