Treffer: Second-order cone programming approach to common set of weights in multiplicative network DEA model.

AbstractData Envelopment Analysis (DEA) is a data-driven approach employed to evaluate the efficiency of Decision-Making Units (DMUs). While DEA enables DMUs to determine the most favorable set of weights for optimizing their efficiency scores, this flexibility hinders direct comparison across all DMUs due to the absence of a common weighting scheme. This research proposes a model for analyzing Network DEA in multiplicative form and introduces a programming model aimed at finding a Common Set of Weights (CSW) that maximizes the efficiency of each stage concurrently. The proposed CSW model for multiplicative Network DEA is non-linear but can be converted into a Second-Order Cone Programming (SOCP) problem, a well-established convex optimization method capable of efficiently finding optimal solutions. This study disaggregates system efficiency into the product of efficiencies across each network stage, extends the analysis to include system-oriented, stage-oriented, and process-oriented cases. The rationality and robustness of the proposed model are validated through Monte Carlo simulation experiments and empirical two-stage dataset, further confirming its advantages in hierarchical discrimination and robustness. [ABSTRACT FROM AUTHOR]

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