The article examines how using Data Envelopment Analysis (DEA) to measure transport efficiency can lead to biased results if key specifications are not met. These specifications involve the relationships between inputs and outputs in the data sample. The researchers found that many studies on airlines, urban transit, and freight rail data often do not meet these specifications, leading to inaccurate efficiency scores. By identifying and correcting these errors, future transportation studies can avoid biased estimates.