The influence of geographical distance on motivations for social media engagement and its influence on fan loyalty: a comparison of local and international satellite fans
Bibliographic record
Abstract
Professional sports teams and leagues that play at a superior level and have sporting success on an international level nowadays have a large number of geographically distant fans. These fans are labelled in the literature as satellite fans (Kerr & Gladden, 2008). The emergence of the internet, especially social media, allows these satellite fans to stay in constant contact with their favourite team (Kerr & Emery, 2011; Li et al., 2019). However, little is known about the use of social media by satellite fans and its consequences for their fandom. Therefore, this study investigates the motivations for social media engagement with team-related content and the impact of this social media engagement on fan loyalty of satellite fans and compares them to local fans. In particular, this research focuses on NHL fans in Germany (satellite fans), USA and Canada (local fans) that use Instagram to follow their team’s official account and/or other related accounts. The local fans reside within 100 miles (160 km) of their NHL team’s home stadium (Collins et al., 2016; Richelieu & Pons, 2009). This comparison reveals how geographical distance from a favourite sports team affects social media use and its offline impact on fan loyalty. \n \nUses and gratifications theory was applied to examine the relationship between motivations for media use (entertainment, integration and social interaction, personal identity, information, remuneration, and empowerment) and consumers’ online brand-related activity levels (consumption, contribution, and creation). In addition, the relationship between these three online engagement levels and attitudinal and behavioural fan loyalty was investigated. An online questionnaire was conducted and disseminated via social media for data collection. A local fan sample (n = 472) and a satellite fan sample (n = 465) were collected. Quantitative methods using confirmatory factor analysis and structural equation modeling were applied to confirm the conceptual model. The chi-square difference test was used to compare the local and satellite fan samples and identify differences. \n \nThe analysis revealed seven paths in the conceptual model that showed statistically significant differences between the two fan groups. Further differences were found at a descriptive level. The results showed that local fans have a smaller set of motivations to engage in social media compared to satellite fans. In addition, social media engagement with team-related content has a greater and usually stronger impact on fan loyalty among satellite fans than among local fans. These results underline that satellite fans have a higher dependence on social media than local fans. It also demonstrates that local and satellite fans are two distinct fan groups in terms of their motivations for social media engagement with team-related content and its influence on their fan loyalty. Furthermore, the study shows that social media can be used as a strategic tool to influence the loyalty of both local and satellite fans. Implications are made on how to address these groups collectively and individually via social media.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".