2021
Kruijf, J.; Waerden, P.; Feng, T.; Böcker, L.; Lierop, D.; Ettema, D.; Dijst, M.
Integrated weather effects on e-cycling in daily commuting: A longitudinal evaluation of weather effects on e-cycling in the Netherlands Journal Article
In: Transportation Research Part A: Policy and Practice, vol. 148, 2021, ISSN: 09658564.
Abstract | Links | BibTeX | Tags: Behavior change, E-bike, E-cycling, GPS-data, Weather conditions
@article{nokey,
title = {Integrated weather effects on e-cycling in daily commuting: A longitudinal evaluation of weather effects on e-cycling in the Netherlands},
author = {J. Kruijf and P. Waerden and T. Feng and L. Böcker and D. Lierop and D. Ettema and M. Dijst},
doi = {10.1016/j.tra.2021.04.003},
issn = {09658564},
year = {2021},
date = {2021-01-01},
journal = {Transportation Research Part A: Policy and Practice},
volume = {148},
abstract = {While in many regions the conventional bicycle has already been regarded as an environmentally friendly and healthy alternative to the car for daily commuting, societal and policy agendas are also increasingly promoting e-bike adoption. Adding to recent research on e-bike safety, satisfaction with travel and behavioral change, this paper reports on the impact of weather circumstances on the use of the e-bike in daily commuting in an e-cycling incentive program in the province of Noord-Brabant, the Netherlands. The impact of this incentive program was analyzed using a longitudinal design, and it combined travel patterns that were derived from individuals’ GPS data over nine months, hourly observed meteorological data, and questionnaires on intended behavior and sociodemographic characteristics. The findings suggest that the presence of snow and ice, total precipitation, and high windspeed negatively affected the choice of commuting to work by e-bike, in this decreasing order of impact. Although the overall impact of air temperature on e-cycling was positive, the likeliness to commute by e-bike decreased at higher air temperatures. E-cycling under specific weather conditions was more likely if participants’ intention to e-cycle under such weather conditions was stronger. Our study indicates that the benefits of the e-bike in daily commuting are underestimated in relation to adverse weather conditions. Respondents from households with one car only, therefore, have fewer alternatives in poor weather conditions: for these individuals, only total precipitation and the presence of relatively low air temperature impact e-cycling. In addition, reported gender and high wind speeds might have been expected to influence participation in e-cycling.},
keywords = {Behavior change, E-bike, E-cycling, GPS-data, Weather conditions},
pubstate = {published},
tppubtype = {article}
}
While in many regions the conventional bicycle has already been regarded as an environmentally friendly and healthy alternative to the car for daily commuting, societal and policy agendas are also increasingly promoting e-bike adoption. Adding to recent research on e-bike safety, satisfaction with travel and behavioral change, this paper reports on the impact of weather circumstances on the use of the e-bike in daily commuting in an e-cycling incentive program in the province of Noord-Brabant, the Netherlands. The impact of this incentive program was analyzed using a longitudinal design, and it combined travel patterns that were derived from individuals’ GPS data over nine months, hourly observed meteorological data, and questionnaires on intended behavior and sociodemographic characteristics. The findings suggest that the presence of snow and ice, total precipitation, and high windspeed negatively affected the choice of commuting to work by e-bike, in this decreasing order of impact. Although the overall impact of air temperature on e-cycling was positive, the likeliness to commute by e-bike decreased at higher air temperatures. E-cycling under specific weather conditions was more likely if participants’ intention to e-cycle under such weather conditions was stronger. Our study indicates that the benefits of the e-bike in daily commuting are underestimated in relation to adverse weather conditions. Respondents from households with one car only, therefore, have fewer alternatives in poor weather conditions: for these individuals, only total precipitation and the presence of relatively low air temperature impact e-cycling. In addition, reported gender and high wind speeds might have been expected to influence participation in e-cycling.
2020
Sun, Q.; Feng, T.; Kemperman, A.; Spahn, A.
Modal shift implications of e-bike use in the Netherlands: Moving towards sustainability? Journal Article
In: Transportation Research Part D: Transport and Environment, vol. 78, 2020, ISSN: 13619209.
Abstract | Links | BibTeX | Tags: Cycling, E-bike, Modal shift, Panel data
@article{Sun2020,
title = {Modal shift implications of e-bike use in the Netherlands: Moving towards sustainability?},
author = {Q. Sun and T. Feng and A. Kemperman and A. Spahn},
doi = {10.1016/j.trd.2019.102202},
issn = {13619209},
year = {2020},
date = {2020-01-01},
journal = {Transportation Research Part D: Transport and Environment},
volume = {78},
abstract = {This paper investigates the modal shift patterns of e-bike users in the Dutch context. We focus on the change in e-bikers’ travel behavior to assess whether this change benefits sustainability. Our study provides direct ecologically valid evidence on modal shift by using a longitudinal dataset from the Netherlands Mobility Panel survey. We examine e-bikers’ modal shift patterns before and after acquiring an e-bike. The findings indicate that after e-bike adoptions, conventional bike use reduces significantly, while car use reduces less strongly. Nonetheless, the share of car kilometers is much larger than that of conventional bikes at the baseline. Besides, the emission rate per passenger kilometer of an e-bike is several times lower than that of a car. These imply a net environmental gain after e-bike adoptions. The present study also sheds light on modal shifts at a disaggregated level by investigating those e-bikers who are more likely to drive less after e-bike adoption. The findings suggest that e-bikers younger than 50 and those around retirement age (60–69) seem more likely to step out of their cars. Additionally, people living in rural areas tend to be more likely to reduce their car use than their counterparts in highly urbanized areas. Based on our findings, we present policy recommendations for achieving a greener shift in mobility systems.},
keywords = {Cycling, E-bike, Modal shift, Panel data},
pubstate = {published},
tppubtype = {article}
}
This paper investigates the modal shift patterns of e-bike users in the Dutch context. We focus on the change in e-bikers’ travel behavior to assess whether this change benefits sustainability. Our study provides direct ecologically valid evidence on modal shift by using a longitudinal dataset from the Netherlands Mobility Panel survey. We examine e-bikers’ modal shift patterns before and after acquiring an e-bike. The findings indicate that after e-bike adoptions, conventional bike use reduces significantly, while car use reduces less strongly. Nonetheless, the share of car kilometers is much larger than that of conventional bikes at the baseline. Besides, the emission rate per passenger kilometer of an e-bike is several times lower than that of a car. These imply a net environmental gain after e-bike adoptions. The present study also sheds light on modal shifts at a disaggregated level by investigating those e-bikers who are more likely to drive less after e-bike adoption. The findings suggest that e-bikers younger than 50 and those around retirement age (60–69) seem more likely to step out of their cars. Additionally, people living in rural areas tend to be more likely to reduce their car use than their counterparts in highly urbanized areas. Based on our findings, we present policy recommendations for achieving a greener shift in mobility systems.
Dane, G.; Feng, T.; Luub, F.; Arentze, T.
Route choice decisions of E-bike users: Analysis of GPS tracking data in the Netherlands Book
2020, ISSN: 18632351.
Abstract | Links | BibTeX | Tags: Big data, E-bike, GPS, Route choice
@book{Dane2020b,
title = {Route choice decisions of E-bike users: Analysis of GPS tracking data in the Netherlands},
author = {G. Dane and T. Feng and F. Luub and T. Arentze},
doi = {10.1007/978-3-030-14745-7_7},
issn = {18632351},
year = {2020},
date = {2020-01-01},
journal = {Lecture Notes in Geoinformation and Cartography},
abstract = {Over the past years, the usage of electric bikes has emerged. E-bikes are suitable for short and medium distance trips. Therefore, the Dutch government promotes using e-bikes for daily commuting trips. However, the impact of increasing demand on the cycling infrastructure is unclear. Additionally, route choice models for e-bikes are limited. This paper estimates a route choice model for e-bike users in the Noord-Brabant region of The Netherlands. The data used are based on 17626 trips from 742 users including user profiles extracted from GPS data. In order to analyze the data, a mixed logit model is applied on the route choice of respondents with addition of the path-size attribute. Mixed logit model allows a panel data setup and enables the examination of preference heterogeneity around the mean of distance attribute. Moreover, the path-size attribute is included on the model to account for the overlap between alternatives. Socio-demographic characteristics and trip-related factors are found to be influencing on the route choice decisions of e-bike and bike users. There are differences on the significance of variables between e-bike and bike users.},
keywords = {Big data, E-bike, GPS, Route choice},
pubstate = {published},
tppubtype = {book}
}
Over the past years, the usage of electric bikes has emerged. E-bikes are suitable for short and medium distance trips. Therefore, the Dutch government promotes using e-bikes for daily commuting trips. However, the impact of increasing demand on the cycling infrastructure is unclear. Additionally, route choice models for e-bikes are limited. This paper estimates a route choice model for e-bike users in the Noord-Brabant region of The Netherlands. The data used are based on 17626 trips from 742 users including user profiles extracted from GPS data. In order to analyze the data, a mixed logit model is applied on the route choice of respondents with addition of the path-size attribute. Mixed logit model allows a panel data setup and enables the examination of preference heterogeneity around the mean of distance attribute. Moreover, the path-size attribute is included on the model to account for the overlap between alternatives. Socio-demographic characteristics and trip-related factors are found to be influencing on the route choice decisions of e-bike and bike users. There are differences on the significance of variables between e-bike and bike users.
Gu, G.; Feng, T.
Heterogeneous choice of home renewable energy equipment conditioning on the choice of electric vehicles Journal Article
In: Renewable Energy, vol. 154, 2020, ISSN: 18790682.
Abstract | Links | BibTeX | Tags: Car sharing, E-bike, Mobility tool, Solar panel
@article{Gu2020,
title = {Heterogeneous choice of home renewable energy equipment conditioning on the choice of electric vehicles},
author = {G. Gu and T. Feng},
doi = {10.1016/j.renene.2020.03.007},
issn = {18790682},
year = {2020},
date = {2020-01-01},
journal = {Renewable Energy},
volume = {154},
abstract = {New mobility tools like electric vehicle and e-bike have been an important strategy in many cities for the reduction of traffic problems and the implementation of renewable energy infrastructures. The choice of individuals on mobility tools however may depend on the magnitude of a comparable cost. Home renewable energy equipment like solar panel which generates energy at home may potentially reduce the electricity expenditure of e-mobility. This paper therefore aims to investigate the choice behavior of individuals on their home renewable energy equipment conditioning on the choice of mobility tools. More specifically, we identify the differences among individuals in their preferences and the latent groups. Using the stated preference data collected in the city of Weiz, Austria, we estimated a latent class choice model with social demographics representing the user group membership. Results show that the synergy effect between EV and solar panels and self-sufficient home energy system is more attractive to people with low income although their willingness to buy are lower than people with high income.},
keywords = {Car sharing, E-bike, Mobility tool, Solar panel},
pubstate = {published},
tppubtype = {article}
}
New mobility tools like electric vehicle and e-bike have been an important strategy in many cities for the reduction of traffic problems and the implementation of renewable energy infrastructures. The choice of individuals on mobility tools however may depend on the magnitude of a comparable cost. Home renewable energy equipment like solar panel which generates energy at home may potentially reduce the electricity expenditure of e-mobility. This paper therefore aims to investigate the choice behavior of individuals on their home renewable energy equipment conditioning on the choice of mobility tools. More specifically, we identify the differences among individuals in their preferences and the latent groups. Using the stated preference data collected in the city of Weiz, Austria, we estimated a latent class choice model with social demographics representing the user group membership. Results show that the synergy effect between EV and solar panels and self-sufficient home energy system is more attractive to people with low income although their willingness to buy are lower than people with high income.