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Examining the Factors Influencing the
      Propensity of Highly Compensated
    Athletes to Contribute to Social Change

   By Jonathan A. Jensen, Kristy L. McCray &
Brian A. Turner, PhD (The Ohio State University)
Introduction


  “You make a living by what you get; you make a life by
          what you give.” –Winston Churchill


•Charitable giving and foundations growing
   • 97,941 foundations in 2010
   • 2008: $307.65 billion in charitable giving; 13% from
     foundations ($41.21 billion)
   • 2011: $46.9 billion from foundations
Introduction


• Growing trend of philanthropy and activism in sports
  world
• Athletes have growing power in society
   • “Professional athletes today, for better or for worse,
     have substantial impact on society. These individuals
     have agency, power and influence they did not have
     decades ago” (Babiak et al., 2012, p. 172)
Purpose


• The purpose of this study was to explore the potential
  factors that may influence the propensity of highly
  compensated athletes to contribute to social change.
Literature Review


• Demographics have been explored in connection with
  general charitable giving and philanthropy
• Growing academic interest in athlete social
  responsibility (charitable giving, community outreach,
  cause-related marketing, etc.)
Literature Review


• Babiak, et al. (2012) explored professional athletes and
  factors influencing their charitable giving
   • Identified athletes in 4 major North American
     professional leagues (NBA, NFL, MLB, NHL)
   • 36 interviews, including 10 athletes, foundation
     directors, league/team executives, sport agent
   • Findings indicate that antecedents to foundation
     creation include attitudes of altruism and self-
     interest, perceived behavior control, subjective
     norms, and moral obligations
Method


• The dataset utilized for the study was Forbes’ list of
  the world’s 100 highest-paid athletes (Badenhausen,
  2012)
• Utilized binary logistic regression featuring a
  dichotomous variable indicating whether the athlete
  has established a non-profit foundation as the
  dependent variable
• Factors investigated include the athlete’s earnings,
  whether the athlete plays an individual or team
  sport, nationality and age
Descriptives

• Top Americans on list were Tiger Woods ($114m),
  LeBron James ($93.0m), Phil Mickelson ($90.8m),
  Floyd Mayweather ($85.0m) & Kobe Bryant ($84.3m)
• Top international athletes were Roger Federer
  ($97.7m), David Beckham ($83.0m), Manny Pacquiao
  ($68m) & Cristiano Ronaldo ($64.5m)
                                Descriptive Statistics

                          N         Minimum       Maximum       Mean         Std. Deviation



     SPORT                100          0             1           .22             .416

     NATLTY               100          0             1           .65             .479

     EARN (MIL)           100        16.7          114.4        32.864         19.6762

     AGE                  100         23            44          31.13            4.733

     Valid N (listwise)   100                                             
Examination of Assumptions


                                    Collinearity Statistics
                                            Tolerance       VIF      
                                 EARN           .843       1.186     
                                  AGE           .908       1.101     
                                  NATLTY        .860       1.162     
                                  SPORT         .706       1.416     
                                 



                                           Correlations
                                    ENDORSE CHARITY                SALARY       SPORT     NATLTY     AGE

                      EARN                  -.420        .012           1.000     -.052       .270    -.027
                      SPORT                  .397        .238           -.052     1.000      -.369     .283
Pearson Correlation
                      NATLTY                -.242        .121            .270     -.369      1.000    -.051
                      AGE                    .207        .132           -.027      .283      -.051    1.000
Results


• Good model fit was evidenced by non-significant
  results on the Hosmer-Lemeshow test (p = .371)
• Whether a highly-compensated athlete plays an
  individual or team sport (p = .012) and his or her
  nationality (p = .018) were found to be significant
  predictors of his or her propensity to establish a
  charitable foundation
• Individual athletes were 6.6 times more likely and
  Americans 3.5 times more likely to have established
  a charitable foundation.
Results

                                      Hosmer and Lemeshow Test

                        Step           Chi-square            df                  Sig.

                        1                         8.674               8                 .371



                                            Variables in the Equation

                            B        S.E.        Wald       df            Sig.          Exp(B)        95% C.I.for EXP(B)

                                                                                                       Lower         Upper

             EARN            .018      .016        1.267          1         .260          1.018           .987        1.050

             SPORT          1.890      .757        6.241          1         .012          6.621          1.503       29.171
Step 1   a

             NATLTY         1.252      .530        5.571          1         .018          3.498          1.237        9.893
                                                                                                                  
             Constant       -1.068     .688        2.409          1         .121           .344
a. Variable(s) entered on step 1: EARN, SPORT, NATLTY.
Discussion


• Interestingly, earnings and age were not found to be
  significant predictors
• These results contrast with the findings of Babiak et
  al. (2012)
• Not surprising that individual athletes were much
  more likely to establish a non-profit foundation, but
  interesting that American athletes had a much
  higher propensity to establish a non-profit
  foundation
Limitations


• Results only generalizable to highly compensated
  athletes (M = $32.86 million in earnings)
• Athlete’s propensity to contribute to social change
  operationalized based on whether they have
  established a foundation or not
   • Some athletes are very active without having
     their own foundation
   • Some foundations do not contribute to social
     change (i.e. Alex Rodriguez)
Future Research


• Female athletes and foundation creation and/or
  charitable giving
• Examination of other types of charitable giving
• Further examination of individual athletes
• Study of less highly paid athletes
• Connection between player’s career and foundation
  creation (age, established career, “brand”)
• Sustainability of foundations established by athletes

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Jansen & McCray - Athletes for social change

  • 1. Examining the Factors Influencing the Propensity of Highly Compensated Athletes to Contribute to Social Change By Jonathan A. Jensen, Kristy L. McCray & Brian A. Turner, PhD (The Ohio State University)
  • 2. Introduction “You make a living by what you get; you make a life by what you give.” –Winston Churchill •Charitable giving and foundations growing • 97,941 foundations in 2010 • 2008: $307.65 billion in charitable giving; 13% from foundations ($41.21 billion) • 2011: $46.9 billion from foundations
  • 3. Introduction • Growing trend of philanthropy and activism in sports world • Athletes have growing power in society • “Professional athletes today, for better or for worse, have substantial impact on society. These individuals have agency, power and influence they did not have decades ago” (Babiak et al., 2012, p. 172)
  • 4. Purpose • The purpose of this study was to explore the potential factors that may influence the propensity of highly compensated athletes to contribute to social change.
  • 5. Literature Review • Demographics have been explored in connection with general charitable giving and philanthropy • Growing academic interest in athlete social responsibility (charitable giving, community outreach, cause-related marketing, etc.)
  • 6. Literature Review • Babiak, et al. (2012) explored professional athletes and factors influencing their charitable giving • Identified athletes in 4 major North American professional leagues (NBA, NFL, MLB, NHL) • 36 interviews, including 10 athletes, foundation directors, league/team executives, sport agent • Findings indicate that antecedents to foundation creation include attitudes of altruism and self- interest, perceived behavior control, subjective norms, and moral obligations
  • 7. Method • The dataset utilized for the study was Forbes’ list of the world’s 100 highest-paid athletes (Badenhausen, 2012) • Utilized binary logistic regression featuring a dichotomous variable indicating whether the athlete has established a non-profit foundation as the dependent variable • Factors investigated include the athlete’s earnings, whether the athlete plays an individual or team sport, nationality and age
  • 8. Descriptives • Top Americans on list were Tiger Woods ($114m), LeBron James ($93.0m), Phil Mickelson ($90.8m), Floyd Mayweather ($85.0m) & Kobe Bryant ($84.3m) • Top international athletes were Roger Federer ($97.7m), David Beckham ($83.0m), Manny Pacquiao ($68m) & Cristiano Ronaldo ($64.5m) Descriptive Statistics   N Minimum Maximum Mean Std. Deviation SPORT 100 0 1 .22 .416 NATLTY 100 0 1 .65 .479 EARN (MIL) 100 16.7 114.4 32.864 19.6762 AGE 100 23 44 31.13 4.733 Valid N (listwise) 100        
  • 9. Examination of Assumptions Collinearity Statistics   Tolerance VIF     EARN .843 1.186   AGE .908 1.101   NATLTY .860 1.162   SPORT .706 1.416     Correlations   ENDORSE CHARITY SALARY SPORT NATLTY AGE EARN -.420 .012 1.000 -.052 .270 -.027 SPORT .397 .238 -.052 1.000 -.369 .283 Pearson Correlation NATLTY -.242 .121 .270 -.369 1.000 -.051 AGE .207 .132 -.027 .283 -.051 1.000
  • 10. Results • Good model fit was evidenced by non-significant results on the Hosmer-Lemeshow test (p = .371) • Whether a highly-compensated athlete plays an individual or team sport (p = .012) and his or her nationality (p = .018) were found to be significant predictors of his or her propensity to establish a charitable foundation • Individual athletes were 6.6 times more likely and Americans 3.5 times more likely to have established a charitable foundation.
  • 11. Results Hosmer and Lemeshow Test Step Chi-square df Sig. 1 8.674 8 .371 Variables in the Equation   B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper EARN .018 .016 1.267 1 .260 1.018 .987 1.050 SPORT 1.890 .757 6.241 1 .012 6.621 1.503 29.171 Step 1 a NATLTY 1.252 .530 5.571 1 .018 3.498 1.237 9.893     Constant -1.068 .688 2.409 1 .121 .344 a. Variable(s) entered on step 1: EARN, SPORT, NATLTY.
  • 12. Discussion • Interestingly, earnings and age were not found to be significant predictors • These results contrast with the findings of Babiak et al. (2012) • Not surprising that individual athletes were much more likely to establish a non-profit foundation, but interesting that American athletes had a much higher propensity to establish a non-profit foundation
  • 13. Limitations • Results only generalizable to highly compensated athletes (M = $32.86 million in earnings) • Athlete’s propensity to contribute to social change operationalized based on whether they have established a foundation or not • Some athletes are very active without having their own foundation • Some foundations do not contribute to social change (i.e. Alex Rodriguez)
  • 14. Future Research • Female athletes and foundation creation and/or charitable giving • Examination of other types of charitable giving • Further examination of individual athletes • Study of less highly paid athletes • Connection between player’s career and foundation creation (age, established career, “brand”) • Sustainability of foundations established by athletes