Matrix-based network data envelopment analysis: A common set of weights approach

Performance measurement of decision-making units (DMUs) with network structure is one of the main challenges in data envelopment analysis (DEA) field. The main purpose of this paper is to propose a novel network data envelopment analysis (NDEA) approach based on matrix of efficiency, common set of weights (CSW), multiobjective programming (MOP), and goal programming (GP) technique for performance measurement of peer DMUs in two-stage network structure. The advantages of the proposed NDEA approach can be summarized as follows: comparing all DMUs and sub-DMUs on the same base, considering all internal structures and relations and capability to extending this for all network structures, linearity of the proposed models, unique efficiency decomposing without any need to consider multiplicative, additive or leader-follower relations between overall and stages efficiency. To illustrate the usefulness and applicability of the proposed approach we applied it to a real application of non-life insurance companies in Taiwan.