Products combine function and form. This paper focuses on product form. We combine state-of-the-art clustering techniques with experimental validation to identify styles (groupings of new product designs of similar form) among the more than 350,000 U.S. design patents granted from 1977 through 2010. Thus we compile, for the first time, a rich data set of styles that can serve as an empirical platform for a rigorous study of the role played by product form in new product development. Building on this platform, we analyze the determinants of “style turbulence”—the year-to-year unpredictability of changes in a style’s prevalence. We find that (i) style turbulence follows a U-shaped relationship with respect to function turbulence (the turbulence of product functions associated with a given style), and (ii) style turbulence increases over time. We discuss the implications of these findings for managing design in new product development.
Product design (or the form of a product) is an important aspect of new product development. Using design patent data granted from 1977-2010, we categorized over 350,000 designs into over 9,000 styles (or categories of designs that are perceived to be visually similar).
Attached is the pseudocode if you wish to identify styles on a dataset of designs. If you use the data or would propose improvements / alternatives to our approach, please also let us know and we are happy to improve the approach over time, and acknowledge your work.
Given a similarity matrix between designs S
1The approach relies on the Ng-Jordan-Weiss (2002) algorithm (NJW), which approximately partitions a group of objects into two groups by minimizing conductance (a graph measure of heterogeneity). The evaluate step stops the algorithm corresponding to a post-hoc identified Δ value of about 0.002, at which point a sharp increase in conductance is observed. (The NJW algorithm is popular and you can find ready implementations online, e.g., from MATLAB central).