An analysis of the determinants of sport expenditure in sports centers in spain

The European health and fitness sector serves 62.2 million consumers who generate 27,200 million euros in income and frequent 61,984 sports installations. With an increase in market share of 1.2% of income and 4.6% more sports centers than the previous financial year, Europe has emerged as the world’s leading market in terms of health and fitness. Of the total income, 65% of the sector is attributable to Germany, the UK, Italy, France, and Spain.

This topic is what the scientific publication that we analyze today talks about, which is written by Amal Elasri Ejjaberi, member of Management and e-Learning (MeL) research group, together with Pilar Aparicio Chueca and Xavier M. Triadó-Ivern. The article was published in Sustainability in 2020.

Objectives and Methodology

The objectives of the research included identifying key variables predicting sport expenditure, examining the influence of factors like time of participation, federation membership, income, age, and educational level on expenditure patterns, and understanding the relationship between sociodemographic characteristics and sport spending behavior.

The methodology involved non-probabilistic snowball sampling to recruit participants, with data collected through online questionnaires distributed via sports clubs. The study utilized a quantitative approach, analyzing eight variables including sport expenditure, income, educational level, loyalty duration, federation membership, participation time, age, and gender.

Results and Conclusions

Having reviewed different research works with respect to the determinants of sport expenditure, three variables that help to predict this variable were identified: time of participation, federation membership, and income. This study also shows that variables like age and educational level explain significant differences in sport expenditure among its different categories. The two age ranges at the extremes spend more money on sports, while the group with a higher educational level also shows differences in sport expenditure.

The regression model could be an efficient simulation tool for people who spend smaller amounts of money on sports. The model is efficient when classifying people who spend less than 45 EUR per month.

The present study demonstrates the importance of knowing sports center users’ behavior regarding sport expenditure as an essential element in the future strategy of the sector. With sports centers either closed or limiting the number of users at any one time, it is essential for managers that new products and services suited to the characteristics of their users are found, both at the level of doing sports and at the sociodemographic level.

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