The diffusion dynamics of choice: From durable goods markets to fashion first names

TL;DR

This paper introduces a predictive diffusion model for fashion, specifically applied to first names, validated across multiple countries, enabling forecasts of popularity trends and distinguishing between popularity and fashion influences.

Contribution

It presents the first diffusion-based framework for modeling fashion dynamics in first names, validated with large-scale international data, and highlights the distinction between popularity and fashion effects.

Findings

Validated model accurately forecasts first name popularity trends.

Uncovered that less popular names can also be driven by fashion.

Model applies across French, Dutch, and US datasets.

Abstract

Goods, styles, ideologies are adopted by society through various mechanisms. In particular, adoption driven by innovation is extensively studied by marketing economics. Mathematical models are currently used to forecast the sales of innovative goods. Inspired by the theory of diffusion processes developed for marketing economics, we propose, for the first time, a predictive framework for the mechanism of fashion, which we apply to first names. Analyses of French, Dutch and US national databases validate our modelling approach for thousands of first names, covering, on average, more than 50% of the yearly incidence in each database. In these cases, it is thus possible to forecast how popular the first names will become and when they will run out of fashion. Furthermore, we uncover a clear distinction between popularity and fashion: less popular names, typically not included in studies of fashion, may be driven by fashion, as well.