Applying cross-efficiency evaluation methods for multi-objective emergency relief supply chain network model

This paper studies a multi-objective emergency relief supply chain network (ERSCN) model, which would play a critical role in providing disaster relief items in time. Data envelopment analysis (DEA) method is applied to identify efficient ERSCN schemes among the proposed schemes. To overcome the weakness of the classical DEA method, a cross-efficiency (CE) evaluation method was proposed to improve DEA's poor discriminating power. But the original CE method also reveals its own weaknesses. So, the three CE methods, called as aggressive, benevolent, and neutral methods, are proposed to complement the shortcomings of the classical DEA and CE-DEA methods. This paper proposes a process of applying these CE evaluation methods in DEA for designing the ERSCN system. Through a case study, the applicability of the proposed procedure is demonstrated. We observe that it performs well regarding identifying the efficient ERSCN systems and can be used as an important tool to design various supply chain network schemes efficiently and effectively.