Global Growth in International Sport: A Niche Portfolio Strategy

As described by Porter (1980), a niche marketing strategy concentrates on serving a particular market niche – defined by geographic boundaries, type of customer, segment of the product line, or a combination of these three elements. Yet focus on a single niche can entail risks of instability and collapse, which can be countered by the market flexibility offered by a niche portfolio that includes multiple targeted niches (Hamlin et al. 2012). Where firms define targeted niches geographically, building a diversified niche portfolio involves difficult decisions concerning international market expansion. Our study addresses this challenge empirically by utilizing the context of Formula One (F1) motor racing to advance the study of a niche-based growth strategy. Specifically, we develop and test a model that examines the importance of native resources to the success of an international expansion strategy featuring a portfolio of geographically-defined niches.

Our study builds on the theoretical foundation of Milne et al. (1996), who applied niche marketing strategy to the sport industry. Similar to any organization, sport teams, leagues, and events need to secure certain resources for continued survival (Smart and Wolfe 2000). To develop our hypotheses in the sport context, we rely on the resource categorization of Milne et al. (1996) as participants, spectators, sponsors and media attention.

In order to approximate the demand for the sport of F1 (dependent variable) across numerous countries, we utilize hierarchical regression with a data set that features the advertising rates for standard commercial time during the broadcast of every F1 grand prix from 2007 to 2010 in 19 different countries across five continents. H1 is fully supported as all three participant-based resource variables yield significant coefficients and the change in R ² from a base model with controls for year is also significant (p < .01). In support of H2, the incremental change in R ² is again significant (p < .05), but only the Population variable coefficient is significant (GNI nonsignificant). Likewise, the incremental variance in ad rates explained by the sponsor-resource variables (H3) is significant (p < .01), but only one of the variable coefficients is positive and significant (SponsorSpend). Finally, media-based resources (H4) do not explain a significant amount of additional variance in ad rates. In conclusion, we have applied a niche-based resource categorization specific to sports to the international context of F1 racing to explain variance in demand across countries as relevant to geographic expansion decisions.