Post on 06-May-2015
transcript
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
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
• 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)
Examination of Assumptions
Correlations ENDORSE CHARITY SALARY SPORT NATLTY AGE
Pearson Correlation
EARN -.420 .012 1.000 -.052 .270 -.027SPORT .397 .238 -.052 1.000 -.369 .283NATLTY -.242 .121 .270 -.369 1.000 -.051AGE .207 .132 -.027 .283 -.051 1.000
Collinearity Statistics Tolerance VIF EARN .843 1.186
AGE .908 1.101 NATLTY .860 1.162 SPORT .706 1.416
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
Variables in the Equation
B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B)
Lower Upper
Step 1a
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
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.
Hosmer and Lemeshow Test
Step Chi-square df Sig.
1 8.674 8 .371
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