The compensation incentive effect of athletes: A structural equation model

Examining the incentive effects of athlete compensation: a combined analysis using SEM and fsQCA

In the context of competitive sports, the evaluation of compensation incentive effectiveness is key to the optimization of compensation systems for athletes. This study creates a model of the athlete compensation incentive effect from single and multinomial grouping perspectives, combining empirical research (SEM) with fuzzy-set qualitative comparative analysis (fsQCA) based on a sample of 352 validated data. The results lead to two findings. First, athletes' direct economic compensation, direct non-economic compensation, and indirect non-economic compensation have a significant positive effect on the incentive effect of compensation. Second, that the incentive effect of high compensation has two configurations, namely "economic value" and "economic environmental value." It seems that the effective combination of compensation factors can enhance the motivation effect in a "different way."

Mixed methods research on satisfaction with athletes' compensation

This study explores the factors influencing athletes' compensation satisfaction and their configuration effects. A mixed research approach that combines regression analysis and fuzzy-set qualitative comparative analysis (fsQCA) was applied to process the survey data of 352 athletes from six provinces. The regression analysis results demonstrate that economic compensation, the compensation system, the external environment, and compensation fairness all have a significant positive effect on athletes' compensation satisfaction. Accordingly, the fsQCA approach was applied to explore the combined effects of the factors influencing athletes' compensation satisfaction, which verifies the conclusions drawn from regression analysis and provides improvement paths for increasing athletes' compensation satisfaction.

The attitude of online fans: perceived value, expectation, and identification on VAR satisfaction

This study explores online fan satisfaction with the Video Assistant Referee (VAR) during the FIFA World Cup Qatar 2022. A structural equation model comprising perceived value, fan expectation, fan identification, and fan satisfaction was run. The online questionnaires were distributed among Chinese football fans. A total of 224 valid responses were received. Using indicators like Cronbach's alpha coefficient, Kaiser-Meyer-Olkin (KMO) statistic, and Bartlett's test of sphericity, the results were assessed for reliability, validity, and suitability. From the statistical results, the overall satisfaction of fans with VAR is the middle. Both fan expectation and perceived value positively affect satisfaction (p < 0.01); the path coefficients were 0.26 and 0.57. Contrastingly, fan identification exerts no significant effect on fan satisfaction (p > 0.05); and fan expectation indirectly affects fan satisfaction through perceived value (p < 0.01); the path coefficient was 0.29. The highest effect value for fan satisfaction is perceived value, followed by fan expectation. Consequently, to improve online fan satisfaction with VAR, researchers should focus on perceived value. This research contributes to a greater more comprehensive of Chinese online fans' preference towards VAR at the FIFA World Cup Qatar 2022.