Results indicate a highly significant model (F = 113.5, p < .001) that explains close to half the variance in team points (adjusted R-squared = 0.45). All five independent variables are significant predictors (each p < .01). Interpreting the coefficients, the control variables indicate that F1 teams historically earn 10 points in the current season for each past drivers’ championship won by the team, and teams competing after 2009 can expect to earn 114 more points than teams competing in 2009 and prior (due to the institutional change in the points system that occurred in 2010). Regarding the sponsor variables of interest, operational sponsors had the most surprising effect: each operational sponsor was associated with 4.7 less team points earned. However, this negative effect of operational sponsors somewhat supports the findings of Cobbs and colleagues (in press), where such sponsors had no discernible influence on team survival. Conversely, both performance and financial sponsors produced positive effects to team points. For each performance-based sponsor, teams earned 2.1 additional points. For each financial sponsor, teams earned 3.6 additional points.

1. Does Sponsorship Enhance Sport
Organizational Performance?
Joe Cobbs, Northern Kentucky University
Jonathan A. Jensen, University of North Carolina at Chapel Hill
B. David Tyler, Western Carolina University

2. Sponsorship Exchange
“Provision of assistance either financial or in kind to
an activity by a commercial organization for the
purpose of achieving commercial objectives” –
Meenaghan, 1983
Sponsoring
firm/brand
Popular [sports]
enterprise
$ VIK
Benefits
Cornwell; Gwinner; O’Reilly;
Olson & Thjømøe; Wakefield;
Speed & Thompson;
Farrelly & Quester
?

3. Sponsorship as Resource
• Strategic Alliance: mechanism for interorganizational exchange to
enhance competitive position (Bergmann Lichtenstein & Brush, 2001)
• Resource-based View (RBV): asymmetric distribution of heterogeneous
resources (Barney, 1991; Cui & O’Connor, 2012; Grant, 1991)
• Resource utility based on competitive context (Cobbs et al., 2017)
• Performance (e.g., tires, lubricants, brakes, high technology firms)
• Operational (e.g., accounting, banking, logistics, office furniture)
• Financial (e.g., food and beverages, fashion, movies and television)

4. Data
• 1967-2015
• 687 team years
• Team points (M = 43.2, SD = 85.5)
• Performance sponsors (M = 5.2, SD = 5.7)
• Operational sponsors (M = 2.1, SD = 3.2)
• Financial sponsors (M = 2.7, SD = 3.2)
• Drivers’ Championships (M = 2.1, SD = 3.4)
• Era 0/1, change in point system 2010+

5. Model Results
Regression Statistics
R Square 0.455
Adjusted R Square 0.451
Observations 687
ANOVA
df F Sig. F
Regression 5 113.53 3.27E-87
Residual 681
Total 686
Ind. Variables Coefficient t Stat P-value
Intercept 0.05 0.01 0.989
Performance Sponsors 2.10 2.89 0.004
Operations Sponsors -4.70 -3.52 0.000
Financial Sponsors 3.60 2.78 0.006
Cum Drivers Champs 10.06 12.96 0.000
Era 2010 113.97 12.24 0.000

6. Model Interpretation
Control variables
• each past drivers’
championship = 10 points
in current season
• teams competing after
2009 can expect 114 more
points than prior
Primary variables
• each operational sponsor,
4.7 less team points
• each performance sponsor,
2.1 additional points
• each financial sponsor,
3.6 additional points

7. Era 1967-1995 Results
Regression Statistics
R Square 0.314
Adj R Sq 0.308
Observations 468
ANOVA
df F Sig F
Regression 4 52.963 0.000
Residual 463
Total 467
Coefficient t Stat P-value
Intercept 1.42 0.64 0.522
Performance Sponsors 2.61 3.76 0.000
Operations Sponsors 3.96 1.99 0.048
Financial Sponsors 4.78 3.75 0.000
Cum Drivers Champs 5.59 10.11 0.000

8. Era 1995-2009 Results
Regression Statistics
R Square 0.542
Adj R Sq 0.529
Observations 151
ANOVA
df F Sig F
Regression 4 43.198 0.000
Residual 146
Total 150
Coefficient t Stat P-value
Intercept 14.37 1.65 0.101
Performance Sponsors 2.25 3.39 0.001
Operations Sponsors -1.70 -1.46 0.146
Financial Sponsors -1.70 -1.37 0.172
Cum Drivers Champs 9.12 11.04 0.000

9. Era 2010-2015 Results
Regression Statistics
R Square 0.313
Adj R Sq 0.269
Observations 68
ANOVA
df F Sig F
Regression 4 7.164 0.000
Residual 63
Total 67
Coefficient t Stat P-value
Intercept 10.28 0.15 0.883
Performance Sponsors 2.29 0.43 0.668
Operations Sponsors -12.98 -1.75 0.086
Financial Sponsors 20.02 2.63 0.011
Cum Drivers Champs 19.05 4.29 0.000

10. Era Interpretation
Evolution in F1 sponsorship
• early sponsorship era (1967-1995), all sponsors influenced
points
• performance-based era (1996-2009), teams discerned how
to utilize certain sponsors to improve performance
• modern era (2010-2015/present), technology highly
developed and now an arms race to bankroll equipment
needed to compete on the track.

11. Discussion
• Aligns with Cobbs et al., 2017 regarding sponsorship
priority
• Performance, Financial prioritized
• Cautious of Operational (management capacity)
• Monitor institutional change
• Sport governance, resource distribution
• Toward Win-Win Cycle in sponsorship research
• Team performance  sponsorship ROI (Jensen & Cobbs,
2015)
• Sponsorship  team survival (Cobbs et al., 2017)
• Sponsorship  team performance