Modeling the Driving Factors of the Value Added in the Chinese Sports Industry: A Ridge Regression

Abstract

The development of a high-quality sports industry is crucial to China’s economic growth. This research quantitatively analyzed factors influencing the development of the sports industry for the period 2010–2019. The study selected variables pertaining to the gross national income per capita (X1 ), household final consumption expenditure per capita (X2 ), sports population (X3 ), number of fitness venues and facilities (X4 ), number of sporting events (X5 ), and number of sports-related business registrations (X6 ) and analyzed their relationship with the value added to the sports industry. By developing a ridge regression model, it can be determined that correlations (Pearson’s r) between six factors and the value added to the sports industry were all greater than 0.90, and that each factor had a positive impact on the industry (p < 0.05). After standardizing the ridge regression model with the z-score method, it was determined that the degree of influence of the six factors varied: X2 (βridge = 0.156), X3 (βridge = 0.153) and X5 (βridge = 0.153), X1 (βridge = 0.151), X4 (βridge = 0.136), and X6 (βridge = 0.121). The ridge regression model can give a reference model for predicting and optimizing the sustainable development of the sports industry in China.