On Price Recognition and Computational Complexity in a Monopolistic Model

Abstract

A single seller of an indivisible good operates in a market with many consumers who differ in their ability to process information. The consumers' constraints are modeled in two submodels: the first in terms of the limits on the number of sets in the partition of the price space, and the second in terms of the limits on the complexity of the operation he can use to process a price offer. For the construction of the second submodel, the tool of a "perceptron" is borrowed from the parallel computation literature. Assuming a negative correlation between the seller's cost of supply of the good and the consumer's ability to process information, I demonstrate that the heterogeneity of consumer's abilities can be used by the seller to profitably discriminate among them.