This study analyses the determinants of cycling expenditure by means of a Tobit regression analysis, based on a dataset of 5,157 cyclists. Using a heterodox economic framework, 23 different variables are combined into two commonly used variable groups (socio-demographics, sports intensity variables) and two rarely investigated variables groups (socio-economic cycling capital, psychographics). With all variables included in the Tobit regression, gender, trip duration, frequency, number of cycling variants practiced, visiting cycling websites, and practicing road-cycling or mountain bike are positive determinants of cycling expenditure. A negative association is found with competitive riding and cycling drop out. Marketeers of cycling services and cycling apparel should meet the cyclists need for identification instead of focusing solely on socio-demographic factors.
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Given the recent economic crisis and the risen poverty rates, sports managers need to get insight in the effect of income and other socio-economic determinants on the household time and money that is spent on sports participation. By means of a Tobit regression, this study analyses the magnitude of the income effect for the thirteen most practiced sports by households in Flanders (the Dutch speaking part of Belgium), which are soccer, swimming, dance, cycling, running, fitness, tennis, horse riding, winter sports, martial arts, volleyball, walking and basketball. The results demonstrate that income has a positive effect on both time and money expenditure on sports participation, although differences are found between the 13 sports activities. For example, the effect of income on time and money expenditure is relatively high for sports activities like running and winter sports, while it is lower for other sports such as fitness, horse riding, walking and swimming. Commercial enterprises can use the results of this study to identify which sports to focus on, and how they will organise their segmentation process. For government, the results demonstrate which barriers prevent people from taking part in specific sports activities, based upon which they should evaluate their policy decisions.
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The purpose of this article is to explore the determining factors of household expenditures on sports participation. Due to a relatively large amount of zero-expenditures, simple regression methods are not suited. Because of methodological reasons, the two-step Heckman approach is used over the Tobit approach and the Double Hurdle approach. The participation decision (spend money or not) is influenced by sports participation of the parents, family income, education, sports club membership, and sports frequency. Determining factors of the intensity decision (amount of money that is spent on sports participation) are family income, sports participation of parents during their youth, sports club membership, sports frequency, age of youngest child, and household size. Moreover, the results indicate that a two-stage approach is needed because it gives a more in-depth insight in the household spending behavior. For example, higher educated households more often spend money on sports participation. However, this research demonstrates that once higher educated households have decided to spend money on sports participation, the amount of money spent does not differ from lower educated households.
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