Performance measurement of humanitarian supply chains

In recent years, we have witnessed many unforeseen disasters. During disruptive events, governments and business organizations call for more effective and efficient humanitarian operations. Humanitarian supply chains (HSCs) play a vital role in helping businesses operate smoothly in such challenging situations. Simultaneously, the performance measurement of HSCs plays a strategic and key role in responding to unpredicted events. Despite the importance of measuring performance in HSCs, there are significant challenges with existing approaches in the literature. The objective of this paper is to develop a novel network data envelopment analysis (NDEA) model with unique features. The proposed model can calculate division and overall efficiency scores with high discriminatory power. Furthermore, the proposed NDEA model simultaneously takes into account integer data, ratio data, undesirable outputs, and fuzzy data. The model also addresses interval undesirable outputs. The proposed model demonstrates the capability to accurately rank HSCs. Additionally, a case study of Iranian natural disasters is provided to showcase the capabilities of the proposed model. Finally, the results of the numerical analysis are utilized to derive managerial implications for HSCs.