The article discusses using artificial neural networks to estimate binary choice models without making restrictive assumptions. The researchers show that these networks can be interpreted as logistic regression with more flexibility. They applied this method to a study on willingness-to-pay and found it to be a promising alternative to traditional models like binary logit and probit.