Combining the priority rankings of DEA and AHP methodologies: a case study on an ICT industry

Abstract

This article presents a case study on how data envelopment analysis (DEA) and analytic hierarchy process (AHP) could be combined to produce priority rankings for a set of companies. The shortcomings of each method, when exclusively used to deal with multiple criteria decision analysis (MCDA) problems, are also analysed. The dataset of this study, arising from the European Union (EU) Industrial R&D Investment Scoreboard (European Commission, 2009), consists of the top EU companies activating in the telecommunications equipment industry, which is one of the most representative information and communications technology (ICT) industries. Five criteria, namely, R&D investment, number of employees, capital expenditure, net sales, and operating profit, are used for defining priority rankings of these companies. The application of the case study indicates that the super-efficiency DEA model could be employed for ranking the companies at an initial stage; following that, ranking of the efficient companies could be attained through AHP.