Social network analysis in humanitarian logistics research

Purpose – The purpose of this paper is to promote social network analysis (SNA) methodology within the humanitarian research community, surveying its current state of the art and demonstrating its utility in analyzing humanitarian operations. Design/methodology/approach – A comprehensive survey of t...

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Main Authors: Zhasmina Tacheva, Natalie Simpson
Format: Article
Language:English
Published: Emerald Publishing 2019-12-01
Series:Journal of Humanitarian Logistics and Supply Chain Management
Subjects:
Online Access:https://www.emerald.com/insight/content/doi/10.1108/JHLSCM-06-2018-0047/full/pdf
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author Zhasmina Tacheva
Natalie Simpson
author_facet Zhasmina Tacheva
Natalie Simpson
author_sort Zhasmina Tacheva
collection DOAJ
description Purpose – The purpose of this paper is to promote social network analysis (SNA) methodology within the humanitarian research community, surveying its current state of the art and demonstrating its utility in analyzing humanitarian operations. Design/methodology/approach – A comprehensive survey of the related literature motivates a proposed agenda for interested researchers. Analysis of two humanitarian networks in Afghanistan demonstrates the use and utility of SNA, based on secondary data. In the second case study, the use of random graphs to detect network motifs is demonstrated using Monte Carlo simulation to create the benchmark null sets. Findings – SNA is an adaptable and highly useful methodology in humanitarian research, quantifying patterns of community structure and collaboration among humanitarian organizations. Network motifs suggesting distinct affinity between particular agencies within humanitarian clusters are observed. Research limitations/implications – The authors summarize common challenges of using SNA in humanitarian research and discuss ways to alleviate them. Practical implications – Practitioners can use SNA as readily as researchers, to visualize existing networks, identify areas of concern and better communicate observations. Social implications – By making SNA more accessible to a humanitarian research audience, the authors hope its ability to capture complex, dynamic relationships will advance understanding of effective humanitarian relief systems. Originality/value – To the best of knowledge, it is the first study to conduct a systematic analysis of the application of SNA in empirical humanitarian research and outline a concrete SNA-based research agenda. This is also a currently rare instance of a humanitarian study using random graphs to assess observed SNA measures.
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spelling doaj-art-89f8efb35b224b3f82bf326e1b2fc60d2025-08-20T02:11:55ZengEmerald PublishingJournal of Humanitarian Logistics and Supply Chain Management2042-67472019-12-019349251410.1108/JHLSCM-06-2018-0047Social network analysis in humanitarian logistics researchZhasmina Tacheva0Natalie Simpson1State University of New York, Buffalo, New York, USAState University of New York, Buffalo, New York, USAPurpose – The purpose of this paper is to promote social network analysis (SNA) methodology within the humanitarian research community, surveying its current state of the art and demonstrating its utility in analyzing humanitarian operations. Design/methodology/approach – A comprehensive survey of the related literature motivates a proposed agenda for interested researchers. Analysis of two humanitarian networks in Afghanistan demonstrates the use and utility of SNA, based on secondary data. In the second case study, the use of random graphs to detect network motifs is demonstrated using Monte Carlo simulation to create the benchmark null sets. Findings – SNA is an adaptable and highly useful methodology in humanitarian research, quantifying patterns of community structure and collaboration among humanitarian organizations. Network motifs suggesting distinct affinity between particular agencies within humanitarian clusters are observed. Research limitations/implications – The authors summarize common challenges of using SNA in humanitarian research and discuss ways to alleviate them. Practical implications – Practitioners can use SNA as readily as researchers, to visualize existing networks, identify areas of concern and better communicate observations. Social implications – By making SNA more accessible to a humanitarian research audience, the authors hope its ability to capture complex, dynamic relationships will advance understanding of effective humanitarian relief systems. Originality/value – To the best of knowledge, it is the first study to conduct a systematic analysis of the application of SNA in empirical humanitarian research and outline a concrete SNA-based research agenda. This is also a currently rare instance of a humanitarian study using random graphs to assess observed SNA measures.https://www.emerald.com/insight/content/doi/10.1108/JHLSCM-06-2018-0047/full/pdfHumanitarian logisticsResearch methodologySocial network analysis
spellingShingle Zhasmina Tacheva
Natalie Simpson
Social network analysis in humanitarian logistics research
Journal of Humanitarian Logistics and Supply Chain Management
Humanitarian logistics
Research methodology
Social network analysis
title Social network analysis in humanitarian logistics research
title_full Social network analysis in humanitarian logistics research
title_fullStr Social network analysis in humanitarian logistics research
title_full_unstemmed Social network analysis in humanitarian logistics research
title_short Social network analysis in humanitarian logistics research
title_sort social network analysis in humanitarian logistics research
topic Humanitarian logistics
Research methodology
Social network analysis
url https://www.emerald.com/insight/content/doi/10.1108/JHLSCM-06-2018-0047/full/pdf
work_keys_str_mv AT zhasminatacheva socialnetworkanalysisinhumanitarianlogisticsresearch
AT nataliesimpson socialnetworkanalysisinhumanitarianlogisticsresearch