Activity: Talk or presentation types › Oral presentation
Description
Robust Data Envelopment Analysis (RDEA) adopts a conservative approach to deal with inherent uncertainties, ensuring robust and reliable performance evaluation. RDEA models in the literature utilise robust optimisation techniques within conventional DEA frameworks to seek robust efficiency measures. Notably, RDEA models under budgeted uncertainty have gained attention for achieving a balance between optimality and feasibility in the presence of uncertainty. However, an often overlooked drawback is the potential for excessively conservative efficiency measures, especially with high levels of uncertainty, which could diminish the practical utility of this approach. This paper aims to address this concern by examining existing robust DEA models and introducing two new variants using variable budgeted uncertainty and proportion-based uncertainty, thereby extending and refining the existing robust DEA models.