Cross-border commuting might be a way to improve an efficient allocation of labour resources, improve the economic performance of border regions and reduce economic and territorial inequality. This study explores the impact of a set of socio-economic, infrastructural or cultural explanatory variables that drive cross-border commuting in the EU and Switzerland for all outgoing commuters from living countries and for all incoming commuters towards their working countries. We find that cross-border commuters respond in general in the theoretically expected way to wages, unemployment, accessibility, language similarity and distance. But besides these general findings we also find that, in the end, cross-border commuting is a result of push and pull factors that seem to work out differently for different groups of commuters. This may reduce the inequality at the region level both between countries and within countries, although the effects are most likely small given the relatively small number of commuters. However, the results by gender, age, education and sector show substantial differences indicating that at the level of individuals and specific groups the reduction in inequalities might be very limited and may even increase.
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Car use in the sprawled urban region of Noord‐Brabant is above the Dutch average. Does this reflect car dependency due to the lack of competitive alternative modes? Or are there other factors at play, such as differences in preferences? This article aims to determine the nature of car use in the region and explore to what extent this reflects car dependency. The data, comprising 3,244 respondents was derived from two online questionnaires among employees from the High‐Tech Campus (2018) and the TU/e‐campus (2019) in Eindhoven. Travel times to work by car, public transport, cycling, and walking were calculated based on the respondents’ residential location. Indicators for car dependency were developed using thresholds for maximum commuting times by bicycle and maximum travel time ratios between public transport and car. Based on these thresholds, approximately 40% of the respondents were categorised as car‐dependent. Of the non‐car‐dependent respondents, 31% use the car for commuting. A binomial logit model revealed that higher residential densities and closer proximity to a railway station reduce the odds of car commuting. Travel time ratios also have a significant influence on the expected directions. Mode choice preferences (e.g., comfort, flexibility, etc.) also have a significant, and strong, impact. These results highlight the importance of combining hard (e.g., improvements in infrastructure or public transport provi-sion) and soft (information and persuasion) measures to reduce car use and car dependency in commuting trips.
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This paper reports on the effects of an e-cycling stimulation program on travel satisfaction in the province of North-Brabant, the Netherlands. The program was designed to stimulate car-commuters to shift to e-bike in daily commuting, earning a monetary incentive for each kilometre e-cycled. With a longitudinal design, this study shows a significant increase in travel satisfaction when switching from car to e-bike. Starting from an average slightly positive satisfaction with car commuting, participants reported an extremely positive expected travel satisfaction by e-bike. Although a bit less than expected, the experienced travel satisfaction with e-cycling was high after a period of a month and even increased in the following period of half a year. Where the participants can be sub-divided into car-only and multi-modal car-commuters, this distinction does not show in the experienced travel satisfaction with e-cycling. Our study indicates that the hedonic treadmill mechanism does not automatically apply to the satisfaction with e-cycling. Multivariate analyses suggest that the increase in the travel satisfaction is affected by self-reported health, car ownership, urbanization degree, whether car use and e-cycling are experienced as strenuous, congestion on the route and the attractiveness of the cycle route.
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This paper reports on the effects of an e-cycling incentive program in the province of North-Brabant, The Netherlands, in which commuters could earn monetary incentives when using their e-bike. The study used a longitudinal design allowing to observe behaviour change and mode shifts. The program appeared to be highly effective in stimulating e-bike use, as one month after the start of the program, the share of commute trips made by e-bike increased from 0% to 68%, with an increase up to 73% after half a year of participating. The environmental, congestion and health benefits of this shift are however mixed. Half of the e-bike trips substitute car trips, with positive effects on environment, congestion and health. The other half substitutes conventional cycling trips, implying fever health benefits. Our analyses further suggest that distance is an important factor for adopting e-cycling, where e-bike has a larger acceptable distance than a conventional bike. Nevertheless, we observed that the likelihood to use the e-bike decreased as commuting distance increased. Multivariate analyses suggest that a shift to e-cycling is affected by age, gender, physical condition, car ownership and household composition. Our study did find support for the hypothesis that having a strong car-commuting habit decreases the probability of mode shift to a new mode alternative. In contrast, multimodality may increase the likelihood of e-bike use as a result of openness to other travel options and a more deliberate mode choice. Lastly, dissatisfaction with the current travel mode positively influences mode shift towards the e-bike. Our results imply that stimulating e-cycling may be a promising way of stimulating physical activity, but that it will be most effective if targeted at specific groups who are not currently engaging in active travel.
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Active transport to school is associated with higher levels of physical activity in children. Promotion of active transport has therefore gained attention as a potential target to increase children’s physical activity levels. Recent studies have recognized that the distance between home and school is an important predictor for active travel among children. These studies did not yet use the promising global positioning system (GPS) methods to objectively assess active transport. This study aims to explore active transport to school in relation to the distance between home and school among a sample of Dutch elementary school children, using GPS. Seventy-nine children, aged 6-11 years, were recruited in six schools that were located in five cities in the Netherlands. All children were asked to wear a GPS receiver for one week. All measurements were conducted between December 2008 and April 2009. Based on GPS recordings, the distance of the trips between home and school were calculated. In addition, the mode of transport (i.e., walking, cycling, motorized transport) was determined using the average and maximum speed of the GPS tracks. Then, proportion of walking and cycling trips to school was determined in relation to the distance between home and school. Out of all school trips that were recorded (n = 812), 79.2% were classified as active transport. On average, active commuting trips were of a distance of 422 meters with an average speed of 5.2 km/hour. The proportion of walking trips declined significantly at increased school trip distance, whereas the proportion of cycling trips (β = 1.23, p < 0.01) and motorized transport (β = 3.61, p < 0.01) increased. Almost all GPS tracks less than 300 meters were actively commuted, while of the tracks above 900 meters, more than half was passively commuted. In the current research setting, active transport between home and school was the most frequently used mode of travel. Increasing distance seems to be associated with higher levels of passive transport. These results are relevant for those involved in decisions on where to site schools and residences, as it may affect healthy behavior among children. https://doi.org/10.1186/1471-2458-14-227 LinkedIn: https://www.linkedin.com/in/sanned/
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Almere is a green city where the greenery extends into the centre through a framework of nature, forests, parks and canals. With this green environment, Almere fulfils an important condition for a liveable city, where it is pleasant to live and work. An important goal for the municipality is to challenge its residents to develop a healthy lifestyle by using that green framework.But what really motivates Almeerders to go outside to exercise, enjoy the surroundings and meet each other? Are there sufficient green meeting or sports facilities nearby? Could the routes that connect the living and working environment with the larger parks or forests be better designed? And can those routes simultaneously contribute to climate adaptation?With the Green Escape Challenge, we invited students and young professionals to work on these assignments together.
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Background: A consistent finding in the literature is the decline in physical activity during adolescence, resulting in activity levels below the recommended guidelines. Therefore, promotion of physical activity is recommended specifically for prevocational students.Objective: This protocol paper describes the background and design of a physical activity promotion intervention study in which prevocational students are invited to participate in the design and implementation of an intervention mix. The intervention is expected to prevent a decline in physical activity in the target group.Methods: The effectiveness of the intervention was evaluated in a two-group cluster randomized controlled trial with assessments at baseline and 2-year follow-up. A simple randomization was applied, allocating 11 schools to the intervention group and 11 schools to the control group, which followed the regular school curriculum. The research population consisted of 3003 prevocational students, aged 13-15 years. The primary outcome measures were self-reported physical activity levels (screen time, active commuting, and physical activity). As a secondary outcome, direct assessment of physical fitness (leg strength, arm strength, hip flexibility, hand speed, abdominal muscle strength, BMI, and body composition) was included. An intervention-control group comparison was presented for the baseline results. The 2-year interventions began by mapping the assets of the prevocational adolescents of each intervention school using motivational interviewing in the structured interview matrix and the photovoice method. In addition, during focus group sessions, students, school employees, and researchers cocreated and implemented an intervention plan that optimally met the students’ assets and opportunities in the school context. The degree of student participation was evaluated through interviews and questionnaires.Results: Data collection of the SALVO (stimulating an active lifestyle in prevocational students) study began in October 2015 and was completed in December 2017. Data analyses will be completed in 2021. Baseline comparisons between the intervention and control groups were not significant for age (P=.12), screen time behavior (P=.53), nonschool active commuting (P=.26), total time spent on sports activities (P=.32), total physical activities (P=.11), hip flexibility (P=.22), maximum handgrip (P=.47), BMI (P=.44), and sum of skinfolds (P=.29). Significant differences between the intervention and control groups were found in ethnicity, gender, active commuting to school (P=.03), standing broad jump (P=.02), bent arm hang (P=.01), 10× 5-m sprint (P=.01), plate tapping (P=.01), sit-ups (P=.01), and 20-m shuttle run (P=.01).Conclusions: The SALVO study assesses the effects of a participatory intervention on physical activity and fitness levels in prevocational students. The results of this study may lead to a new understanding of the effectiveness of school-based physical activity interventions when students are invited to participate and cocreate an intervention. This process would provide structured health promotion for future public health.
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During the COVID-19—related lockdowns (2020–2022), mobility patterns and charging needs were substantially affected. Policies such as work from home, lockdowns, and curfews reduced traffic and commuting significantly. This global pandemic may have also substantially changed mobility patterns on the long term and therefore the need for electric vehicle charging infrastructure. This paper analyzes changes in electric charging in the Netherlands for different user groups during different phases of the COVID-19 lockdown to assess the effects on EV charging needs. Charging needs dropped significantly during this period, which also changed the distribution of the load on the electricity grid throughout the day. Curfews affected the start times of charging sessions during peak hours of grid consumption. Infrastructure dedicated to commuters was used less intensively, and the charging needs of professional taxi drivers were drastically reduced during lockdown periods. These trends were partially observed during a post–lockdown measuring period of roughly 8 months, indicating a longer shift in mobility and charging patterns.
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