Research Article

Gangless cross-evaluation in DEA: an application to stock selection

¹ Faculty of Business, University of New Brunswick at Saint John, E2L 4L5 Saint John, NB, Canada
² Department of Operations Management and Business Statistics, College of Economics and Political Science, Sultan Qaboos University, Muscat, Oman

^* Corresponding author: gamin@unb.ca

Received: 26 April 2017
Accepted: 7 July 2018

Abstract

This paper discusses the impact of ganging decision making units (DMUs) on the cross-efficiency evaluation in data envelopment analysis (DEA). A group of DMUs are said to be ganging-together if the minimum and the maximum cross-efficiency scores they give to all other DMUs are identical. This study demonstrates that the ganging phenomenon can significantly influence the cross-efficiency evaluation in favour of some DMUs. To overcome this shortcoming, we propose a gangless cross-efficiency evaluation approach. The suggested method reduces the effect of ganging and generates a more diversified list of top performing units. An application to the Tehran stock market is used to show the benefits of gangless cross-evaluation.