Influence of technology partners in the history of sport organizations: The case of F1 Racing
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Among the study’s initial findings is that technology partners, in the form of technology-based sponsor relationships, have a positive, statistically significant influence on the survival of F1 teams. From a managerial perspective, this result provides organizations with the knowledge that while monetary resources provided by sponsors are important, the technological expertise available via such partners is also essential to survival in the technologically advanced world of F1 motor racing.
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Influence of technology partners in the history of sport organizations: The case of F1 Racing
- 1. Influence of technology partners in the history of sport organizations: The case of F1 Racing Joe Cobbs, Jonathan A. Jensen, & B. David Tyler
- 2. Research Question INTRODUCTION 2 Formula One (F1) teams did not survive 2014 season • Caterham and Marussia entered administration • Sport of F1 racing generates over US$1 billion revenue (Knight & Torre, 2013) • Team operating budgets exceed US$300 million (Sylt & Reid, 2008) Sponsorships represent primary resource acquisition method • Resources not homogeneous (Barney, 1991; Grant, 1991) Which resources most conducive to team survival?
- 3. Intense corporate involvement F1 RACING • 41 of Interbrand’s Top 100 global brands • Annual corporate commitments over US $100M • Considerable involvement beyond monetary investments, including technological, logistical and operational expertise (Castellucci & Ertug, 2010; Jenkins & Floyd, 2001)
- 4. Survival Analysis METHOD & DATA • DV: Hazard of team dissolution based on proportion of teams at risk with given level of experience • Age-based hazard function representing chronological probability of team failure • Independent variables predict probability of dissolution (i.e., hazard rate) • Type of sponsor: technology, monetary, business operations • Controls: team and sponsor F1 experience, team points, drivers’ championships, pre1996 dummy, GDP growth • Requires longitudinal data 40 years, 124 F1 teams, 1,077 sponsors
- 5. F1 Team Hazard of Dissolution RESULTS 0 .05 .1 .15 .2 0 10 20 30 Analysis Time (Years) 95% CI Smoothed hazard function Smoothed Hazard Estimate - Survival of F1 Teams
- 6. Hazard function based on technology sponsor RESULTS 0 .01 .02 .03 .04 .05 5 10 15 20 25 Analysis Time Performance Sponsorship No Performance Sponsors Cox Model: Differentials Based on Performance Sponsorship Technology Sponsorship No Technology Sponsors
- 7. Predicted Failure Functions Based on Resources DISCUSSION Technology Sponsorship Monetary Sponsorship Years No Yes No Yes 5 .134 .062 .104 .060 10 .276 .133 .218 .130 15 .312 .152 .248 .149 20 .312 .152 .248 .149 25 .440 .225 .357 .222 30 .734 .442 .636 .436 35 .734 .442 .636 .436 40 .734 .442 .636 .436 • Monetary resources are important but technology resources are just as vital
Notas do Editor
- Sponsorship accounts for 70% of team budgets
- Ferrari with and without Marlboro branding. [Altria group, owns Phillip Morris, decided not to run Marlboro branding at any race in ’09] Not necessarily directly relevant to what we’re investigating here, but shows the assumed power of branding building in the F1 context. Also visible on the car: Shell, AMD, Alice, Acer, Bridgestone
- A total of 84.03% of cases featured at least one performance sponsor (15.97% did not), compared to 72.94% with a financial sponsor (27.06% without). Finally, only 45.21% of cases featured an operational sponsor, with the majority (54.29%) of cases without an operations sponsor.
- Dating back to 1967, the overall hazard function for F1 teams is .1169, defined as the conditional probability that a F1 team may fail at any given time (11.69%). For example, in year one of a F1 team’s experience, the hazard for dissolution is .2892. This result can be interpreted as the conditional probability that a F1 team will fail after only one year of existence is 28.92%. As one might expect, the hazard decreases to 26.79% after the second year, 15.0% after the third, and to only 5.26% after the fourth.
- As depicted in the table, the model predicts that after five years 13.4% of F1 teams without a technology sponsor would be predicted to fail, compared to only 6.2% of those with a technology sponsor. After 20 years, 31.2% of teams without such sponsors would be predicted to fail, with only 15.2% of teams sponsored by technology sponsors. After 30 years, the failure function stabilizes, predicting that 73.4% of teams without technology sponsors will have failed, compared to only 44.2% of those with technology sponsors.