Measuring the degree of congestion in two-stage DEA: A case of Chinese textile, wearing apparel, and accessories industry

Abstract

Abstract This paper develops a method to identify congestion and measure the degree of congestion in two-stage data envelopment analysis (DEA). First, the congestion in the two-stage DEA is defined. Next, based on the definition, a slack-based method is proposed to identify congestion and measure the degree of congestion in the two-stage DEA. We compare our method with the congestion identification method in one-stage DEA and find that the two-stage DEA can provide more accurate congestion information than treating the production process as a black box. The method we propose is used to assess congestion in the Chinese textile, wearing apparel, and accessories industry. The empirical results show that the degree of congestion in the Chinese textile, wearing apparel, and accessories is getting worse, although it has been weakening from 2013–2014. The information can be used to support the corresponding policymaking for the managers of both government and enterprises.