A compact common weight data envelopment analysis model for efficiency measurement

This paper proposes a novel common-weight DEA model that combines multi-objective linear fractional programming and goal programming to determine a set of common-weights for evaluating decision-making units (DMUs). The model formulates a single linear program (LP) without requiring iterative procedures, thereby enhancing computational efficiency. To validate the model’s effectiveness, we compare the proposed method with a satisfaction degree–based model, a distance-based model, and a credibility-based common-weight method. Our model demonstrates competitive efficiency scores and a high degree of discrimination among DMUs, while maintaining a lower computational time complexity. This research contributes by offering a practical and computationally efficient alternative to existing models.