Dynamic DEA with Common Weights: A Case Study of Iranian Airlines

Abstract

The traditional data envelopment analysis (DEA) models allow each decision-making unit (DMU) to designate the most advantageous weights to maximize its relative efficiency score. Furthermore, for evaluating the performance of DMUs with consecutive processes during specified periods, dynamic data envelopment analysis (DDEA) has received considerable attention from researchers. Considering the dynamic effects, this paper develops a novel dynamic DEA approach based on the analysis of weight restrictions to achieve a common set of weights in dynamic structures. Essentially, the contribution of this research is fourfold: (1) Generating strictly positive weights. (2) Evaluating overall and periodic efficiencies simultaneously. (3) Preventing weight dissimilarity using the proposed Model. (4) Simplifying the comparison and ranking of each unit in a dynamic network nature. To elucidate the details of the proposed approach, the real data set of fourteen Iranian airlines is used to analyze their dynamic performance levels during the period 2018–2020. The results highlight that Iran Air Tour has had the best total efficiency in the years under evaluation. The findings further demonstrate the superiority and applicability of the proposed method in analyzing the dynamic structures with the carryover flows that link the consecutive periods.