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

Please note this paper has been re-typeset by Taylor & Francis from the manuscript originally provided to the previous publisher.

Abstract

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, ɛ, is a key concept in DEA models. Nevertheless, it is known that some computational difficulties arise when using ɛ 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 ɛ or estimating the same.

Keywords:

• Data envelopment analysis
• directional distance function
• non-Archimedean

JEL ClassificationS:

• C02
• C61

Acknowledgements

The authors would like to thank both the editors and five anonymous reviewers for their constructive comments on the previous version of this short communication.

Notes

Please note this paper has been re-typeset by Taylor & Francis from the manuscript originally provided to the previous publisher.