EXPLORING THE FACTORS REGULATE GRASSROOTS FOOTBALL DEVELOPMENT IN ANHUI PROVINCE, CHINA WITH STRUCTURAL EQUATION MODELING

Bu Lusheng, Mohd Salleh Bin Aman, Lim Boon Hooi

Abstract


Against the background of the overall decline of Chinese football, grassroots football in Chinese schools has become an important position for the revitalization of Chinese football. What factors will affect the development of school grassroots football and how to avoid risks are issues that need to be solved urgently. Based on the theory of Sport success factors and taking Anhui Province as an example, this article constructs a model of factors influencing the development of grassroots football in Chinese schools, studies the support policies at the macro level, coach’s education and football competition at the meso level, and football at the micro level. The relationship between schools and football clubs and grassroots football sustainability. The empirical results show that government policies, education of grassroots football coaches, grassroots football competitions, football layout schools and social football clubs are the influencing factors of grassroots football development in China. In this regard, the article proposes targeted implication in four aspects: policy support for grassroots football development, competition management, coach training management and school-enterprise cooperation.


Keywords


Chinese Grassroots Football Development, Factors Regulate.

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References


Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.

Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.

Broom, E. (1991). Lifestyles of aspiring high performance athletes: A comparison of national models. Journal of comparative physical education and sport, 8(2), 24-54.

China teenage campus football work group office. (2018). National Youth Campus Football Development Report Beijing Sport University.

Churchill Jr, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of marketing research, 16(1), 64-73.

Clumpner, R. A. (1994). 21st century success in international competition. Sport in the global village, 298-303.

Cohen, J. (1988). Set correlation and contingency tables. Applied psychological measurement, 12(4), 425-434.

De Bosscher, V., De Knop, P., & Heyndels, B. (2003). Comparing relative sporting success among countries: Create equal opportunities in sport. Journal of comparative physical education and sport, 3(3), 109-120.

De Bosscher, V., De Knop, P., Van Bottenburg, M., & Shibli, S. (2006). A conceptual framework for analysing sports policy factors leading to international sporting success. European Sport Management Quarterly, 6(2), 185-215.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.

Geisser, S. (1974). A predictive approach to the random effect model. Biometrika, 61(1), 101-107.

Hair, J., Henseler, J., Dijkstra, T. K., & Sarstedt, M. (2014). Common beliefs and reality about partial least squares: comments on Rönkkö and Evermann.

Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). European business review.

Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing: Emerald Group Publishing Limited.

Hu, L.-t., & Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods, 3(4), 424.

Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1).

Larose, K., & Haggerty, T. (1996). Factors associated with national Olympic success: An exploratory study (Unpublished Master’s thesis). University of New Brunswick, Canada.

Myers, R. (1990). Detecting and combating multicollinearity. Classical and modern regression with applications, 368-423.

Nunnally, J. C., & Bernstein, I. (1994). Validity. Psychometric theory, 3, 99-132.

Pizam, A., Neumann, Y., & Reichel, A. (1978). Dimentions of tourist satisfaction with a destination area. Annals of tourism Research, 5(3), 314-322.

Seppänen, P. (1981). Olympic success: a cross-national perspective. Olympic success: a cross-national perspective., 93-116.

Stone, M. (1974). Cross‐validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society: Series B (Methodological), 36(2), 111-133.

Wong, K. K.-K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.

Yan, L., & Yongjin, J. (2007). Research on Sample Size of Customer Satisfaction Model. Statistical Research(07), 68-74.

Zhang, X. (2015). Research on the Development of Shanghai Campus Football League. (postgraduate). Shanghai Normal University, Available from Cnki


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