Network data envelopment analysis with common weights

Cheng-Feng Hu

Department of Applied Mathematics

National Chiayi University

cfhu@mail.ncyu.edu.tw

    Common weight models can combat the computational burden of data envelopment analysis (DEA) in the big data environment. This work considers studying a common-weights general network DEA model which is applicable to most network systems, except those with feedbacks and cycles. It shows that the general network DEA model with common weights can be reduced into an auxiliary fuzzy bi-objective mathematical programming problem by applying the basic principle of compromise of TOPSIS. The case of Taiwanese non-life insurance companies is utilized for illustration and comparison purposes. Our results show that the proposed common-weights network DEA model not only compares DMUs on a common base, but also produces reliable results in measuring efficiencies.