Mapping Market Structure Evolution.

The paper develops a novel methodology for uncovering changes in firms' competitive positions in evolving market structure maps. A common element of market structure analysis is the spatial representation of firms' competitive positions on maps. Such maps typically capture static snapshots in time. Yet, competitive positions tend to change. Embedded in such changes are firms' trajectories, that is, the series of changes in firms' positions over time relative to all other firms in a market. Identifying these trajectories contributes to market structure analysis by providing a forward-looking perspective on competition, revealing firms' (re)positioning strategies and indicating strategy effectiveness. To unlock these insights, we propose EvoMap, a novel dynamic mapping framework that identifies firms' trajectories from high-frequency and potentially noisy data. We validate EvoMap via extensive simulations and apply it empirically to study the trajectories of more than 1,000 publicly listed firms over 20 years. We find substantial changes in several firms' positioning strategies, including Apple, Walmart, and Capital One. Because EvoMap accommodates a wide range of mapping methods, analysts can easily apply it in other empirical settings and to data from various sources. History: Olivier Toubia served as the senior editor and Carl Mela served as associate editor for this article. Funding: This work was supported by German Research Foundation [Grant SK 66/9-1]. Supplemental Material: Data and the online appendices are available at https://doi.org/10.1287/mksc.2022.1385. The Python implementation is available at https://github.com/mpmatthe/evomap. [ABSTRACT FROM AUTHOR]