<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>With the continuous expansion of the scale of colleges and universities and the rapid development of network technology, the management of college sports events is facing more and more challenges. This study first constructs a collaborative management model for college sports events based on the SFIC model. It selects teachers and students from M school as the research object and presents relevant hypotheses. Factor analysis is used to verify the effectiveness of college sports event management, and multiple regression analysis is employed to analyze the factors. The results show that the four public factors extracted have been able to cumulatively summarize 71.408% of the original indicators of information starting conditions, catalytic leadership, institutional design, and synergistic process that can explain the management effect. Furthermore, the correlation coefficients between the variables and management effects are greater than 0.96, indicating a significant correlation. According to the study, there is potential for optimizing the management system of university sports events in terms of management power, management capacity, administrative duties, system improvement, management cooperation, transparency, and openness.</p>
</abstract>

With the continuous expansion of the scale of colleges and universities and the rapid development of network technology, the management of college sports events is facing more and more challenges. This study first constructs a collaborative management model for college sports events based on the SFIC model. It selects teachers and students from M school as the research object and presents relevant hypotheses. Factor analysis is used to verify the effectiveness of college sports event management, and multiple regression analysis is employed to analyze the factors. The results show that the four public factors extracted have been able to cumulatively summarize 71.408% of the original indicators of information starting conditions, catalytic leadership, institutional design, and synergistic process that can explain the management effect. Furthermore, the correlation coefficients between the variables and management effects are greater than 0.96, indicating a significant correlation. According to the study, there is potential for optimizing the management system of university sports events in terms of management power, management capacity, administrative duties, system improvement, management cooperation, transparency, and openness.

Research on the framework of sports event management system of colleges and universities based on big data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

With the continuous expansion of the scale of colleges and universities and the rapid development of network technology, the management of college sports...

Research on the framework of sports event management system of colleges and universities based on big data

Publié en ligne: 15 mai 2024

Pages: -

Reçu: 05 févr. 2024

Accepté: 13 avr. 2024

DOI: https://doi.org/10.2478/amns-2024-1131

Mots clés
SFIC model, Factor analysis, Multiple regression analysis, Sports event management

© 2024 Yi Xie, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the framework of sports event management system of colleges and universities based on big data

Publié en ligne: 15 mai 2024

Pages: -

Reçu: 05 févr. 2024

Accepté: 13 avr. 2024

DOI: https://doi.org/10.2478/amns-2024-1131

Mots clésSFIC model, Factor analysis, Multiple regression analysis, Sports event management

© 2024 Yi Xie, et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
SFIC model, Factor analysis, Multiple regression analysis, Sports event management