1. How may bike-sharing choice be affected by air pollution
How may bike-sharing choice be affected by air pollution? A seasonal analysis in Taiyuan, China
- ETC 2016 Barcelona -
Weibo Li & Maria Kamargianni
Energy Institute, University College London

2. Objectives Study bike-sharing choice behaviour in a developing country
Incorporate seasonality influence on the factors affecting choice behaviour

3. Background Urban mobility challenges in developing countries
Car ownership
Congestion & Air pollution
Role of bike-sharing
Avoid parking troubles with private bikes
Connection to public transport
Travel time and cost reduction
Open opportunities for more social and leisure purposes

4. Background Bike-sharing in developing countries Plenty of schemes
Lack of research:
Mode choice behaviour
Impact of air pollution

5. Case Study: Taiyuan
Taiyuan

6. Case Study: Taiyuan The most popular bike-sharing
-used 0.45 billion times in total
-highest daily demand 0.57 million
-average daily demand 0.4 million
-a bike used times per day
*data from 09/2012 to 06/2016*
Severe & seasonal
air pollution

7. Survey Design RP SP Questionnaire
Personal socio-economic characteristics
Household socio-economic characteristics
Trip dairy
Attitudes and perceptions
Retrospective survey
Stated preference experiment RP SP

8. Data Collection Pilot survey in January 2015
Summer data collection 2015: paper questionnaires distributed, 9499 individuals provided valid data
Winter data collection 2016: 492 individuals provided valid data
Air pollution data
Weather condition data

9. Modelling Framework Air pollution & weather conditions Mode attributes
Trip characteristics
Socio-economic characteristics
Utilities of modes
Choice set:
car driver, car passenger, bus, electric bike,
bike, bike share, walk, taxi
Availability constraints
Two multinomial logit models
RP data from the same 492 individuals in summer (1797 trips) & winter (1722 trips)

10. Results-bike sharing part
Summer
Winter
Coefficient
t-stat
Significance
- 9.06
- 2.57
95%
14.50
7.97
99%
Work-bike share
0.40
1.02 -
1.05
2.37
Education-bike share
1.77
4.67
0.67
1.01
Temperature-bike share
0.13
4.02
0.04
1.07
Air pollution-bike share
0.017
2.20
- 6.71
Travel time-bike share
- 0.07
- 4.81
- 0.24
- 7.42
Male-bike share
- 0.66
- 0.94
0.73
1.18
Age (lower)-bike share
- 0.51
- 0.67
0.41
0.65
Income (lower)-bike share
- 1.11
- 0.60
0.32
0.34

11. Results
Severe air pollution can significantly discourage the usage of bike-sharing and other active transport modes.
Bike-sharing users who go to work have more inelastic demand towards adverse air quality and temperature conditions than those going to education.
Negative willingness to pay exists but only in summer with better natural environment conditions and only on bus and taxi which have faster mobility than bike-sharing.
Females, elderly and wealthier people are more sensitive to worse air quality and lower temperature.

12. Policy Implications
When there are relatively high levels of air pollution, improving air quality can effectively encourage the take up of active transport including bike-sharing.
Besides keeping the price at low level specific for short distance trips, measures can be taken to enhance bike-sharing mobility for longer distance trips (e.g. introducing electric bikes).

13. Policy Implications
Improve bike-sharing service standards in areas that have high workplace densities.
Focus on changing young people’s transport mode choice behaviour.
Design bespoke policies to secure bike-sharing as the primary transport choice for lower income groups.

14. Future Research Combining SP with RP data
Taste heterogeneity, latent variables etc.
Simulation to estimate the effects of different policy pathways

15. Thank you!