Using DEA and AHP for hierarchical structures of data

Abstract

In this paper, we propose an integrated data envelopment analysis (DEA) and analytic hierarchy process (AHP) methodology in which the information about the hierarchical structures of input-output data can be reflected in the performance assessment of decision making units (DMUs). Firstly, this can be implemented by extending a traditional DEA model to a three-level DEA model. Secondly, weight bounds, using AHP, can be incorporated in the three-level DEA model. Finally, the effects of incorporating weight bounds can be analyzed by developing a parametric distance model. Increasing the value of a parameter in a domain of efficiency loss, we explore the various systems of weights. This may lead to various ranking positions for each DMU in comparison to the other DMUs. An illustrative example of road safety performance for a set of 19 European countries highlights the usefulness of the proposed approach.