Data Envelopment Analysis based on opportunity losses (DEA-OPLO): A new approach for Performance Evaluation

Performance evaluation is a critical tool for organizations seeking to enhance competitiveness through continuous improvement. Assessing systems with multiple inputs and outputs requires advanced analytical methods. This study introduces Data Envelopment Analysis based on Opportunity Loss (DEA-OPLO) , a novel approach for evaluating Decision-Making Units (DMUs). This method transforms inputs and outputs into ratio-based metrics, evaluating units through opportunity loss calculated via polar coordinate distance. The optimal unit (with minimal opportunity losses) is positioned on the x-axis, while a newly proposed Reference Axis quantifies the distance of other units from this benchmark. A numerical validation involving six units with two inputs and two outputs demonstrated DEA-OPLO’s alignment with conventional models and its superior accuracy in identifying inefficiencies. Comparative analyses further highlighted its enhanced precision over existing methodologies. The results underscore DEA-OPLO’s potential as a robust framework for performance assessment, offering refined insights into inefficiencies within complex multi-input/output systems.