Abstract
Although resources are scarce and outputs incorporate the potential to save human lives, efficiency measurement endeavors with data envelopment analysis (DEA) methods are not yet commonplace in the research and practice of non-government organizations (NGO) and states involved in humanitarian logistics. We present a boot-strapped DEA window analysis and Malmquist index application as a methodological state of the art for a multi-input and multi-output efficiency analysis and discuss specific adaptions to typical core challenges in humanitarian logistics. A characteristic feature of humanitarian operations is the fact that a multitude of organizations are involved on at least two levels, national and supra-national, as well as in two sectors, private NGO and government agencies. This is modeled and implemented in an international empirical analysis: First, a comprehensive dataset from the 34 least developed countries in Africa from 2002 to 2015 is applied for the first time in such a DEA Malmquist index efficiency analysis setting regarding the national state actor level. Second, an analysis of different sections in a Rohingya refugee camp in Bangladesh is analyzed based on a bootstrapped DEA with window analysis application for 2017, 2018, and 2019 quarter data regarding the private NGO level of operations in humanitarian logistics.
Highlights
Humanitarian logistics is an important field of general interest and research connected to the domain of public health [1,2,3]
The calculation results have been obtained for the presented input and output data in the timeframe of 2002 to 2015 while applying an output-oriented data envelopment analysis (DEA) model with the software BANXIA Frontier Analyst (Banxia Software, Highgate, UK) for the analyzed
In order to identify whether constant returns to scale (CRS) or variable returns to scale (VRS) has to be applied in the given setup, 14 application runs were conducted for a CCR DEA
Summary
Humanitarian logistics is an important field of general interest and research connected to the domain of public health [1,2,3]. As Doerner, Gutjahr, and van Wassenhove already described in 2011, operations research (OR) interest in humanitarian logistics has picked up since about 15 years ago due to major globally recognized disasters at this time and the awareness of worldwide interconnectedness of risks [4]. Few OR publications directly address humanitarian operations such as e.g., Noyan and Kahvecioglu, presenting a supply chain management (SCM) branch-and-cut algorithm for last mile distribution in disaster situations [14] As with these examples, there are no specific contributions regarding efficiency analysis for the strategic level of humanitarian operations, e.g., with the data envelopment method (DEA) proposed by Charnes, Cooper, and Rhodes [15] based on the works of Koopmanns [16] and Farrell [17]
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