Less than half of these jobs are held by people living in the Brussels Region, and the remainder are held by commuters, most of whom live in the Flemish Region. These factors constitute the travel potential of an individual, i. Figure 1. Translation of Kaufmann, Besides availability, there are also financial and time issues. There is usually a positive relationship with car use and an inverse relationship with public transport use.
As incomes rise, people will buy more cars, and at the same time lower their demand for public transport. The costs of a car are usually underestimated compared to the price of public transport for the same journey. As far as time budgets are concerned, consumers have limited time budgets and different types of people have different values of time. These skills can be physical, acquired or organisational. Acquired skills are linked to the knowledge users have developed of the various means of travel at their disposal and of the space in which mobility takes place.
These skills facilitate the use of the considered means of travel. The lifecycle position depends on the age of the person. Lifestyle choices include decisions on education and occupation.
As far as occupation is concerned, the type of work influences the use of and need for a car. Commercial functions, for instance, imply many trips during the day, making the use of a car necessary for the job.
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In Brussels, however, a significant number of jobs are created by public authorities and administrations which are often located near public transport stops, making the use of the car less essential. These choices influence the development of skills concerning the different travel modes. For instance, when deciding on the residential location, the commuting mode choice is one of the factors taken into account.
The car is usually seen as quite positive, and a dependence on the car therefore seems to arise. Such car dependency is not easily reversed. What are the obstacles that need to be overcome in order to make public transport more attractive? What are the advantages of public transport according to the commuters and how can they be exploited?
The survey was tested on a pilot sample of members from the target population: people living outside Brussels who commute to the region on a regular basis to go to work. It is important to mention, however, that it was not a goal to be representative with respect to the travel mode.
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Attention is paid to two major groups: car users and train users, the latter possibly in combination with other transport modes. Within each of these two groups a representative sample was taken. These surveys were part of an assignment for their market research course. The students were instructed to use reference proportions of gender and age corresponding to the proportions of the commuting population as guidelines, but they were free to decide where they searched for respondents.
Consequently, it can be expected that some of them were posted at a train station and others questioned people they encountered near their residential location, for the most part situated in Flanders. As such, the sample is rather regionally selected. The analysis grid provided by Kaufmann was used to categorise the factors being analysed.
The aim was to identify the variables which influence the modal choice made by commuters. As mentioned before, this study focused on two main groups: car and train users, thus ignoring the very small group of other transport mode commuters. Table 1. In this case, the model is formulated such that the probability of using the train for commuting is contrasted with the probability of using the car. As binomial logistic regressions can only be applied to numerical or categorical independent variables, this statistical analysis could only be used on the factors categorised under access and skills.
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As for the appropriation factors, the analysis is rather descriptive. Initially, the model contained the following variables: company car availability, home-work distance and income as access factors, and professional status, educational level and age as skills factors. In addition, two interaction terms were also included to control for potential relations between income on the one hand, and age and education on the other hand. Table 2. Logistic regression parameters for access factors. For instance, with regard to car availability, both variables number of cars in the household and company car ownership have negative B coefficients, indicating that car availability reduces the odds of commuting by train.
Car ownership is related to income but is also determined by the number of adults in the household: when adult children are still living at home, this creates a situation with multiple drivers and earners in the household. This not only results in a rise in the household income, but it also increases the need for additional cars.
The more cars available in the household, the more likely it is that the respondent will commute by car. The analysis shows that each additional car in the household decreases the odds of using the train as a commuting mode. Having a company car influences the commuting mode choice in favour of the car. Compared to people without a company car, the odds of using the train decrease for company car owners.
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Beyond this distance, the train becomes more competitive because of its characteristic of being more cost-effective for longer distances. Car ownership as well as car use are more sensitive to car purchase costs than to the variable costs of car use, such as fuel prices. However, the analyses in this research do not identify income as one of the predictors for the commuting mode choice. This may result from the fact that in most cases it is not the employee, but the employer who pays part of the costs related to commuting. When the company provides company cars or a financial reimbursement, the employees are stimulated to use their car for commuting.
When the company pursues a policy encouraging public transport, employees are more likely to commute by public transport. It was also verified whether education and age interact with net income by adding two interaction terms controlling for these potential relations. Table 3. Civil servants are more likely to commute by train compared to the other types of profession.
The results show that commuters who belong to the group of respondents with a low educational level are more likely to use the train than those with a high educational level.
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Higher educated people in general have higher income levels and consequently also higher car ownership levels, which explains why they are more likely to use the car for their commuting trips. Although an interaction term was included to control for the interaction between education and income, it was not retained in the final model as it did not contribute significantly to improving the model SIG.
Compared to the youngest group, the respondents in the other categories are less likely to commute by train.
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This can be explained by the fact that many young people do not posses their own car immediately and by the differences in household income over the lifecycle. With regard to age also, it was verified whether there was an interaction with income that could possibly influence the outcome of the logistic regression. This interaction term was dropped from the model as it did not contribute significantly to predicting the commuting mode choice SIG.
This affects the way individuals assess their own access and skills as regards the different travel modes. The more positive the experience and perception, the more likely the travel behaviour will not be changed. This indicates that most respondents have quite positive experiences with using the train and are therefore likely to keep commuting by train.
However, it should be mentioned that these experiences are only derived from train users and are not intended to give a general image of satisfaction with regard to the service level of the train. The opinions of car users, who might previously have been train users, are not included here.
It can be expected that people who are not satisfied with the train services simply choose not to make use of it, which supports the supposition that bad experiences lead to changes in travel behaviour. Table 4. The positive reasons are linked to the travel mode they currently use and the negative ones to the other transport alternative. Ever since we were founded in , quality has been prime importance to us. We are therefore proud of the fact that this characteristic is still the basis of our products. You can see this clearly in the Essential line, which offers everything you need as a cyclist to arm yourself against capricious weather.
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