Shapes as Product Differentiation: Neural Network Embedding in the Analysis of Markets for Fonts

arXiv:2107.02739v2 Announce Type: replace-cross
Abstract: Many differentiated products have key attributes that are unstructured and thus high-dimensional (e.g., design, text). Instead of treating unstructured attributes as unobservables in economic models, quantifying them can be important to answer interesting economic questions. To propose an analytical framework for these types of products, this paper considers one of the simplest design products-fonts-and investigates merger and product differentiation using an original dataset from the world's largest online marketplace for fonts. We quantify font shapes …

abstract analysis arxiv cs.cv design differentiation econ.em economic embedding framework key markets network neural network product products questions text them type unstructured