A 3-R principle for characterizing failure in relief supply chains’ response to natural disasters

The purpose of this paper is to introduce a 3R (right time, right place, and right material) principle for characterizing failure in humanitarian/relief supply chains’ response to natural disasters, and describes a Bayesian methodology of the failure odds with regard to external factors that may affect the disaster-relief outcome, and distinctive supply chain proneness to failure.

The suggested 3Rs combine simplicity and completeness, enclosing all aspects of the 7R principle popular within business logistics. A fixed effects logistic regression model is designed, with a Bayesian approach, to relate the supply chains’ odds for success in disaster-relief to potential environmental predictors, while accounting for distinctive supply chains’ proneness to failure.

Analysis of simulated data demonstrate the model’s ability to distinguish relief supply chains with regards to their disaster-relief failure odds, taking into account pertinent external factors and supply chain idiosyncrasies.

Due to the complex nature of natural disasters and the scarcity of subsequent data, the paper employs computer-simulated data to illustrate the implementation of the proposed methodology.

The 3R principle offers a simple and familiar basis for evaluating failure in relief supply chains’ response to natural disasters. Also, it brings the issues of customer orientation within humanitarian relief and supply operations to the fore, which had only been implicit within the humanitarian and relief supply chain literature.