An inverse semi-oriented radial data envelopment analysis measure for dealing with negative data

The conventional inverse data envelopment analysis (DEA) model is only applicable to positive data, while negative data are commonly present in most real-world applications. This paper proposes a novel inverse DEA model that can handle negative data. The conventional inverse DEA model is a special case of our model as our model is more general in terms of returns-to-scale properties. The proposed model is used to evaluate the efficiency of the Chinese commercial banks after the global financial crisis, where negative outputs existed. We show that our model is feasible in the presence of negative data and generates empirical findings that are consistent with reality.