Efficiency decomposition in a three-stage network structure: Cooperative DEA, Nash bargaining game models and conic relaxations

The objective of this study is to find out how airlines can reduce their inputs and provide appropriate passenger and cargo capacity, thereby increasing passenger and cargo traffic and reducing CO2 emissions. A network data envelopment analysis (DEA)–based Nash bargaining model is developed incorporating intermediate products and weakly disposable undesirable outputs and is applied to a dataset of 33 airline companies to obtain the bargaining solution. According to the results, airlines that are weak efficient or inefficient could establish their targets to attain efficiency through a fair and logical negotiation among the inputs, intermediate products, good outputs and bad output. Appropriate policies need to be implemented that would improve the airlines’ performance in terms of improvement in not only the efficiency of inputs and desirable outputs along with intermediate products but also with regard to environmental performance. This would ensure sustainable growth in airlines’ performance.

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Additive Slack-Based Measure for a Two-Stage Structure with Shared Inputs and Undesirable Feedback

Salahi

Jamalian

Shakouri

et al. 2022

Advances in Operations Research

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The two-stage data envelopment analysis models are among the widely used mathematical programming approaches to evaluate the performance of two-stage structures. In this paper, a two-stage structure with shared inputs and feedback is studied. To reduce undesirable outputs, an additive slack-based measure model is proposed to evaluate the stages and overall efficiencies, while undesirable outputs are weakly disposable. As it does not require determining the weights for combining stages’ efficiencies, all Pareto optimal stages’ efficiencies can be gained. In addition, the proposed approach can identify desirable outputs from undesirable outputs, thereby avoiding the need for weighting. This advantage from the aspect of multiobjective programming helps internal evaluation of the network model to match priorities of managers. The proposed nonlinear model is reformulated as a second-order cone program, which is a convex optimization problem that can be solved to global optimality. This is a computational improvement over the parametric models in the literature. Furthermore, the proposed model is applied for country-wise and area-wise performance evaluations of a real industrial application dataset in mainland China. Results show that the efficiency of the overall system relies between the efficiencies of the two stages and for all DMUs, the first stage’s efficiency scores are always higher than the second stage ones in both evaluations. Also, the Pearson correlation coefficient test results show that the overall efficiency is more correlated with the waste disposal stage. Finally, to show the effect of the decision maker’s preference, a detailed sensitivity analysis is performed.

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Efficiency decomposition in a three-stage network structure: Cooperative DEA, Nash bargaining game models and conic relaxations

Cited by 3 publications

References 44 publications

An SOCP approach to a two-stage network DEA with feedbacks and shared resources

An SOCP approach to a two-stage network DEA with feedbacks and shared resources

Target setting for airlines: A DEA bargaining approach with network structure

Additive Slack-Based Measure for a Two-Stage Structure with Shared Inputs and Undesirable Feedback

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