Benchmarking evaluation of major North American Airports, 2017-2022: A study using Data Envelopment Analysis

The present article analyzes the technical efficiency of major airports in North America. This efficiency is related to the ability to generate the maximum amount of transported traffic units from a limited set of inputs. These inputs include the number and length of runways, the number of employees, airline contracts, and flight destinations. To conduct this evaluation, the Data Envelopment Analysis (DEA) methodology with variable returns to scale is used. The analysis period covers from 2017 to 2022. Techniques such as bootstrap, slacks, and benchmarking are also applied. Given the small and diverse sample size, the Bootstrap statistical technique is employed to obtain more reliable and accurate estimates. The article also includes an analysis of input excesses and output gaps in airports between actual and optimal transport capacity. It is also relevant to compare inefficient airports with those that performed better. It is noteworthy that the three main U.S. airports failed to meet the benchmark level, especially during the pandemic. Additionally, it is notable that cargo markets experienced significant growth in 2020-2022, driven by the distribution of vaccines, medical equipment,