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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This empirical study investigated the relationship between the learning climate and training participation in Dutch organizations and how subsidies and the sharing of investments in time and costs between employers and employees affect this relationship. Our analyses are based on a survey of a representative sample of 512 organizations with at least five employees in a Dutch region. Respondents replied to five statements to measure the learning climate, while training was measured through participation and intensity. We found that an organization’s learning climate is positively related to participation and intensity of training in terms of hours. However, we observe that the effect of learning climate on the number of hours of training decreases when the employer pays the costs for the training and when the training takes place during working hours. When organizations can use government subsidies, participation in training increases, and the number of hours per participant increases.
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.
