A systematic literature review on humanitarian logistics using network analysis and topic modeling - Jin Ju Kim; Hyunmi Jang; Saeyeon Roh (Asian Journal of Shipping and Logistics (AJSL), 2022)
The aim of this paper is to conduct a systematic literature review to understand the research trends, identify area of improvements and recommend the future research direction in humanitarian relief logistics (HRL). Using Netminer 4.0, keyword network analysis, keyword frequency analysis, and topic modeling analysis were undertaken. As a result, it has been identified that the number of studies on HRL continuously increased since it mounted in the mid-2010s, with the main issues changing by period. Keyword network analysis and keyword frequency analysis discovered that establishment of the HRL identity and disaster response, preparation and recovery were the main issues from 2005 to 2009. Whereas followed by education and practical logistics flow (2010 - 2014) and provision and coordination (2015 - 2019) to be the main focused area of research. Through topic modeling analysis, nine topics (preparation, coordination, stakeholders, sustainable development, facilities location, recovery, supplying and sourcing, emergent response, transportation, supplying and sourcing) were extracted. Facilities location was the most frequent topic that studied in the number of papers. Meanwhile, recovery, preparation, stakeholders, and emergent response showed downward trends but facilities location, coordination, and supplying and sourcing showing upward. This study is significant in the sense that it suggests research trends in different approach using keyword network analysis, keyword frequency analysis, network analysis and topic modeling which are one of the first attempts in research trend analysis in HRL field. This study will support HRL studies by understanding macroscopic and comprehensive way and set as a steppingstone for future research direction.
Keywords: 650; Humanitarian logistics; Keyword network analysis; Systematic literature review; Topic modeling