The article discusses a method to make complex choice models easier to estimate when there are many options to choose from, like in transportation decisions. By using a combination of Principal Component Analysis and Cluster Analysis on real data, the researchers found that selecting a subset of alternatives can improve the accuracy of the estimates. This approach was demonstrated in a case study on destination choice modeling, showing that it can enhance the efficiency of the analysis.