Data envelopment analysis method based on a common set of normalized weights using bargaining game thought

The purpose of this study is to develop a new data envelopment analysis (DEA) method using a common set of normalized weights (CSNW) and the thought of the bargaining game. This method has a secondary objective model established to possibly solve the problem with the non-uniqueness of weights. The secondary objective is to minimize the sum of deviation between the self-evaluation efficiency and the peer-evaluation efficiency of each DMU. This method also involves the transformation of multiplier weights into normalized weights that are comparable and suitable for arithmetic operations and bargaining. The high consensus of CSNW is obtained after multiple bids among DMUs based on a bargaining procedure. The effectiveness of this method for DEA is finally illustrated using a case study.