Application of Transformed Two-Stage Network DEA to Strategic Design of Biofuel Supply Chain Network

Abstract

This paper proposes an innovative procedure for designing efficient biomass-biofuel logistics networks (BBLNs). This procedure is based on the two-stage network data envelopment analysis (TSN-DEA) models that have been developed to provide specific process guidance for the managers to improve the efficiency of the decision-making unit (DMU) with the TSN process. The crucial issue of the TSN-DEA is that the overall efficiency score depends on the DMUs under evaluation. Thus, the rankings for the DMUs generated by the TSN-DEA model are inconsistent. As a result, the TSN-DEA-based ranking methods are limited. The TSN-DEA’s inconsistency frequently makes it difficult for decision-makers to select the top-rated DMUs. We develop the transformed TSN (T-TSN) DEA method by applying the multi-criteria DEA model to overcome this issue. The proposed method transforms the DMUs with any number of inputs, intermediate measures, and outputs in the TSN process, through the multi-objective programming model with a minimax objective approach, into the DMUs with two inputs and one output in the single-stage network (SSN) process. Then, the well-known DEA methods for the SSN, such as the cross-efficiency and super-efficiency DEA methods, can be applied to evaluate and rank the transformed DMUs more consistently. We exhibit the applicability of the proposed approach for the BBLN design problem. A case study of South Carolina in the USA demonstrates that the proposed method performs well in identifying efficient BBLN schemes more consistently than the traditional TSN-DEA.

Keywords

Biomass-biofuel logistics network / two-stage network / data envelopment analysis / efficiency score / decision-making unit / multiple criteria

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