A meta-analysis of humanitarian logistics research

Nathan Kunz, Gerald Reiner

Publication: Scientific journalJournal articlepeer-review


Purpose - This paper gives an up-to-date and structured insight into the most recent literature on hu-manitarian logistics, and suggests trends for future research based on the gaps identified through structured content analysis.

Design/methodology/approach - We use a quantitative and qualitative content analysis process to analyse the characteristics of the existing literature. We identify the most studied topics in six structural dimensions, and present gaps and recommendations for further research.

Findings - We found that existing humanitarian logistics research shows too little interest in continuous humanitarian aid operations, in slow onset disasters and man-made catastrophes. While several papers address different phases of disasters, very few focus particularly on the reconstruction following a disaster. Empirical research is underrepresented in the existing literature as well.

Research limitations/implications - While five of our structural dimensions are inspired by previous reviews, our sixth dimension (situational factors) is derived from a theoretical framework we developed and which has never been tested before. The validity of our study could therefore be increased by testing this framework.

Originality/value - We analyse the broadest set of papers (174) ever covered in previous literature reviews on humanitarian logistics. We conduct a quantitative analysis of the papers in order to analyse the situational factors which have mostly been studied so far in literature. This paper is also the first in humanitarian logistics to use content analysis as the main methodology to analyse literature in a structured way, which is of particular value to the academic community as well as practitioners.

Outstanding Paper Award 2013 winner (Emerald)
Original languageEnglish
Pages (from-to)116 - 147
JournalJournal of Humanitarian Logistics and Supply Chain Management
Issue number2
Publication statusPublished - 2012

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102009 Computer simulation
  • 502052 Business administration
  • 502012 Industrial management
  • 211
  • 502017 Logistics
  • 502032 Quality management

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