Logit demand function with embedded neural network based utility function

Utility of product variants is a nonlinear function of product features. Such a utility function can be represented by a multi-layer perceptron and embedded into the classical logit demand function. However, the utility (which is the output of the multi-layer perceptron to be learned) is not explicitly known. This is why the backpropagation learning rule has been extended to fit the demand function directly to observed market shares. Forecasts of market shares on the German automobile market with the help of a perceptron-based and classical logit model are compared. The perceptron-based model leads to a significant improvement of the forecast quality