A directional distance function approach to void the non-Archimedean in DEA

Over the past years, the data envelopment analysis (DEA) methodology has registered widespread use among researchers from many fields. Furthermore, it is important to note that the non-Archimedean infinitesimal, ϵ, is a key concept in DEA models. Nevertheless, it is known that some computational difficulties arise when using ϵ in DEA. In this short communication, we show how the non-Archimedean may be voided using a directional distance function approach. Thus, our approach avoids choosing a real number (10-5 or 10-6) as a value for ϵ or estimating the same.