The Effect of Corporate Social Responsibility on Fans’ Engagement: Evidence and Implications for a Professional Soccer Club
Bibliographic record
Abstract
Corporate social responsibility (CSR) has become increasingly prevalent in the sport industry. Indeed, sport organizations have been launching various CSR initiatives because, presumably, they create value for their stakeholders. Nevertheless, little research has been done to attempt to better comprehend the benefits of CSR on sport organizations’ stakeholders, particularly concerning fan engagement. The research question on which this study is based is: what is the effect of CSR on fan engagement behavior among a sample of fans of a professional soccer club? To address this query and understand the CSR/fan engagement relationship, the following research hypotheses are examined: 1) when a soccer club adopts CSR, it creates a significant difference in the overall fan engagement behavior in terms of intention or any of its attributes (sport consumption, experience sharing, fan involvement, and match attendance); 2) there is a relationship between CSR and non-transactional fan engagement behavior intention or any of its non-transactional attributes (sport consumption, experience sharing and fan involvement); and 3) there is an association between CSR and the probability of the highest transactional fan engagement intention (match attendance). The first statistical method used in this study is the Mann-Whitney test used in order to uncover the significant differences by comparing the probability of the dependent variable distributional change when exposed to an independent variable in two different samples. The independent variable is the CSR which is the summation of its three bottom-line variables (social, economic and environmental). The dependent variable embodies a non-transactional fan engagement index or any of its attributes (sport consumption, experience sharing and fan involvement), and transactional connection represented by match attendance. The second statistical method used is linear regression which examines the relationship between non-transactional fan engagement or its attributes and CSR. Finally, the third method applied is ordinal regression in relation to the ordinal variable (transactional fan engagement) to support the association between CSR and the probability of being a season ticket holder. The target population of this study is the fans of a professional soccer club in Major League Soccer (MLS): The Montreal Impact. A random independent sample (control group N1=920) of ticket buyers receiving a control survey is compared to another independent sample (study group N2=920) of ticket buyers receiving the same survey with the exception of including a section containing CSR questions. The result of this study resolved that significant differences neither materialized on the overall nor on the non-transactional and transactional fan engagement. Nevertheless, the regression analysis attested the existence of positive association between CSR and non-transactional fan engagement, all its attributes (sport consumption, experience sharing and fan involvement) and transactional engagement. Essentially, on one hand, the absence of significant difference variation into non-transactional fan engagement is better explained by the fact that fan engagement is multifactorial construct that cannot be explained by one motivator such as CSR. In fact, fan engagement is individually and collectively perceived by fans and taken into account during the engagement decision-making process. Likewise, the non-significant change into the transactional characteristic is more rationalized through the causations nexus as well as economic and personal restraints. On the other hand, the regression’s positive association proves that when sport consumers are CSR stakeholders concurrently, they converge toward a synergy concerning the decision-making process permitting an enhancement of their engagement. Undeniably, fan engagement appears to be a process which is partially rationalized and reshaped by CSR which formats the social setting in which fans support and cooperate with their team.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".