Identification of Key Drivers for Performance Measurement in Sustainable Humanitarian Relief Logistics: An Integrated Fuzzy Delphi-DEMATEL Approach

Abstract

Sustainable humanitarian relief logistics (SHRL) is gaining attention due to increased disasters, unpredictable demand, large volumes, high delivery stakes, and limited resources, evaluated through adaptable performance drivers. This study presents a novel hybrid framework for SHRL, combining the Fuzzy Delphi Method (FDM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). Initially, FDM is utilized to reach a consensus among experts concerning key performance indicators (KPIs) for humanitarian logistics and supply chains. By incorporating the inherent uncertainty and vagueness in expert judgments, FDM refines the list of key performance indicators that reflect the real-life conditions and constraints in disaster operations. Finally, the fuzzy DEMATEL approach was used to analyze the interrelationships among factors, identifying cause-and-effect behavior and ranking them, forming a robust theoretical framework. Based on the acquired results, the KPIs attached to the Quality (P1) aspect of the proposed framework have gained significant importance and are the main cause in a cause-and-effect relationship which impacts and is helpful to improve the performance of humanitarian organizations in all phases of disaster management. The KPIs prompt delivery (D1), and delivery accuracy (D2) are more significant, while capacity building and training (D19) and delivery compliance (D15) are least significant in SHRL scenarios. This research is expected to support humanitarian organizations in enhancing their capabilities, thereby improving the effectiveness and efficiency of aid delivery in disaster-stricken areas.