China Safety Science Journal ›› 2021, Vol. 31 ›› Issue (12): 144-152.doi: 10.16265/j.cnki.issn 1003-3033.2021.12.019

• Emergency technology and management • Previous Articles     Next Articles

Research prospects and hotspot comparison for emergency logistics in China and foreign countries

JI Xiaofeng1,2,3, YANG Chunli1,2,3, HAO Jingjing1,2,3, QIN Wenwen1,2,3   

  1. 1 Faculty of Traffic Engineering, Kunming University of Science and Technology, Kunming Yunnan 650504, China;
    2 Yunnan Integrated Transport Development and Regional Logistics Management Think Tank, Kunming University of Science and Technology, Kunming Yunnan 650504, China;
    3 Yunnan Engineering Research Center of Modern Logistics, Kunming Yunnan 650504, China
  • Received:2021-09-14 Revised:2021-11-12 Online:2021-12-28 Published:2022-06-28

Abstract: In order to get an access to research status and developing trend of emergency logistics under influence of major emergencies, 992 related papers from CNKI and Web of Science databases for nearly 23 years (1997-2020) were used as samples, method of bibliometric analysis was utilized to analyze comparatively development context and characteristics of emergency logistics in China and overseas. The results show that research on this area has experienced a periodic change in three stages: infancy stage (before 2003), rising stage (2003-2013) and steady development stage (2014-2020). Construction of optimized model for emergency logistics in a specific situation is a research hotspot at home and abroad. Natural disaster events, with earthquake as a major one, are the main research objects. And more importantly, the model can be divided into three categories: routing optimization model, facility location model and location-routing combination model according to research differences. Uncertainty is a key influential factor that affects modeling precision, which is also a problem for emergency logistics optimization.

Key words: emergency logistics, research hot spots, comparative analysis, emergencies, multi-objective optimization

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