Super Efficiency DEA Evaluation Method with Anti-Entropy-Delphi Combined Weights Constraints Cone

In order to avoid the situation where the weight assignment value is zero in the data envelopment analysis, the weights of its input and output indexes should be restricted. In this paper, the objective weight determined by the anti-entropy method is combined with the subjective weight determined by the Delphi method, and then the combined weight is obtained according to the principle of minimum variance, which is added to the data envelopment analysis as a constraint condition to construct the super efficiency DEA model with anti-entropy-Delphi combined weights constrains cone. The new evaluation model with the constraint cone can not only reflect the objective impact of data on the index weight, but also integrate the subjective consciousness of experts, and achieve a complete ranking of the evaluation results. Finally, an empirical analysis of the innovation efficiency of basic research in Beijing from 2011 to 2020 is made based on panel data. The result shows that the new model has obvious advantages compared with the super-efficiency DEA model.