An approach for evaluating cleaner production performance in iron and steel enterprises involving competitive relationships

In recent years, many iron and steel enterprises (ISEs) have begun to implement cleaner production (CP) technologies in order to improve environmental performance and competitive advantage. We recognize that the evaluation of ISE CP performance is becoming more important than ever. It is for this reason that we propose an approach for evaluating such performance in this paper. Different from most of the traditional methods, our proposed approach directly involves the competitive relationship among ISEs in the context of the availability of big data today. On the basis of the evidential reasoning (ER) approach and the data envelopment analysis (DEA) cross-efficiency concept, we first construct a nonlinear programming model to portray the competitive relationship among ISEs, and obtain the optimal weight and the optimal utility value. Then, by applying the ER approach to the aggregate evaluation information, we obtain the ranking of the ISE CP performance. Finally, we use a numerical example to illustrate the detailed implementation process of the proposed approach and demonstrate its potential applications.