Data Envelopment Analysis (DEA)

Data envelopment analysis (DEA) is a non-parametric, deterministic method for evaluating performance. DEA estimates best practice production frontiers and measures the relative efficiency of peer entities. These entities are called decision-making units (DMUs) and are assumed to be homogeneous. This assumption implies that all DMUs (e.g., hotels, Airbnb listings, destinations) pursue the same or at least similar goals (e.g., increasing occupancy rate, increasing guest satisfaction). Then, their performances are evaluated. DEA has been successfully used in various contexts, with continuous applications across disciplines and sectors as diverse as agriculture, Airbnb listings, banking, education, hospitals, hotels, transportation and travel agencies. The literature also highlights the method’s superior benchmarking abilities over other operations research techniques. This characteristic alone makes DEA interesting to decision makers. It gives them an opportunity to improve the performance of their DMUs. Benchmarking is all about improvement.