Bobin Wang
Biographic Data
| ID | 6720949 |
|---|---|
| NAME | Bobin Wang |
| GIVEN NAMES | Bobin |
| FAMILY NAME | Wang |
| SIGNATURE | WANG B |
| AFFILIATIONS | Université Laval |
| ORCID | 0000-0003-4437-2490 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Which variables influence electric vehicle adoption
Evolutionary optimization for neural network-based discrete choice modeling
How to effectively communicate about greenhouse gas emissions with different populations
The climate change stage of change measure
Various measures have been proposed and validated to assess environmental motivation and explain peoples’ consumer behavior. However, most of the measures are rather complex, sometimes comprising dozens of items. In order to overcome the associated response burden, the goal of our research is to validate a much simpler measure of environmental motivation, namely the measure of Climate Change-Stage of Change. To do so we analyze data from a discre…
The Impact of Covid-19 on Travel Mode Choice Behavior in Terms of Shared Mobility
Shared mobility is growing rapidly and changing the mobility landscape. The COVID-19 pandemic has complicated travel mode choice behavior in terms of shared mobility, but the evidence on this impact is limited. To fill this gap, this paper first designs a stated preference survey to collect mode choice data before and during the pandemic. Different shared mobility services are considered, including ride hailing, ride sharing, car sharing, and bik…
Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters
Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous studies have focused on TMC in adults, whereas predicting TMC in children has received less attention. On the other hand, previous children’s TMC prediction studies have generally focused on home-to-school TMC. Hence, LIGHT GRADIENT BOOSTING MACHINE (LGBM), as a robust machine learning method, is applied to predict children’s TMC and detect its determinants …
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The climate change stage of change measure
Various measures have been proposed and validated to assess environmental motivation and explain peoples’ consumer behavior. However, most of the measures are rather complex, sometimes comprising dozens of items. In order to overcome the associated response burden, the goal of our research is to validate a much simpler measure of environmental motivation, namely the measure of Climate Change-Stage of Change. To do so we analyze data from a discre…
The Impact of Covid-19 on Travel Mode Choice Behavior in Terms of Shared Mobility
Shared mobility is growing rapidly and changing the mobility landscape. The COVID-19 pandemic has complicated travel mode choice behavior in terms of shared mobility, but the evidence on this impact is limited. To fill this gap, this paper first designs a stated preference survey to collect mode choice data before and during the pandemic. Different shared mobility services are considered, including ride hailing, ride sharing, car sharing, and bik…
Application of Machine Learning to Child Mode Choice with a Novel Technique to Optimize Hyperparameters
Travel mode choice (TMC) prediction is crucial for transportation planning. Most previous studies have focused on TMC in adults, whereas predicting TMC in children has received less attention. On the other hand, previous children’s TMC prediction studies have generally focused on home-to-school TMC. Hence, LIGHT GRADIENT BOOSTING MACHINE (LGBM), as a robust machine learning method, is applied to predict children’s TMC and detect its determinants …
How to effectively communicate about greenhouse gas emissions with different populations
Evolutionary optimization for neural network-based discrete choice modeling
Which variables influence electric vehicle adoption
Computer Science (4 works) · Economics (4 works) · Economic and Environmental Valuation (3 works) · Engineering (3 works) · Environmental economics (3 works) · Environmental Education and Sustainability (3 works) · Urban Transport and Accessibility (3 works) · Business (2 works) · Climate change (2 works) · Ecology (2 works)