Trajectories in the Evolution of Technology: A Multi-Level Study of Competition in Formula 1 Racing

Abstract

This paper explores the trajectories of three key technologies in Formula One racing at the component, firm and system levels of analysis. The purpose is to understand the evolutionary forces that contribute to the emergence and survival of dominant designs. Based on archival data and contemporaneous accounts of the period from 1967-82, we develop a series of propositions specifying the evolutionary forces acting on technological trajectories within each level of analysis. The resulting framework leads to a set of predictions about relationships between technological transparency, coevolution, and the emergence of dominant designs. Specifically, we argue that when the costs and difficulty associated with transferring component knowledge between firms is low (technological transparency is high), technologies tend to coevolve across firms, leading to the development of complementary technologies and increasing the likelihood of industry dominance. Where transparency is low, however, technologies tend to coevolve across functions within firms, leading to the development of competing technologies across firms and increasing the likelihood of a technology's dominance within the firm. The data and argument suggests that the forces acting on these two types of technological trajectories are selfreinforcing, so that as momentum builds behind a trajectory, it becomes more likely that its evolutionary path will end in either firm-or system-level dominance.

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“…However that literature is crossdisciplinary, involving, for example, computational simulations of race results (Loiacono et al 2010, Bekker andLotz 2009), economic approaches that consider the importance of, and adaptability of, F1 teams as firms (Jenkins 2010, Jenkins andFloyd 2001), knowledge transfer between teams (Jenkins & Tallman, 2015) analyses of car design over time from an engineering perspective (Dominy andDominy 1984, Dominy 1992), analyses of specific tracks (Alnaser et al 2006) and their impacts on tourism (Henderson et al 2010), and historical approaches to the sport (Hassan 2012). There have been a few statistical analyses of race results, although these are often limited to a few races or seasons (Bekker andLotz 2009, Muehlbauer 2010).…”

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“…It is worth noting that various strategy scholars have recently extracted key theoretical insights from empirical studies in racing settings (e.g., Aversa et al 2015, Bothner et al 2007, Castellucci and Ertug 2010, Jenkins and Floyd 2001, Jenkins and Tallman 2010, Khanna et al 2003, Ross and Sharapov 2015.…”

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