Be green and clearly be seen: How consumer values and attitudes affect adoption of bicycle sharing

Yacan Wang, Matthew A. Douglas, Benjamin Thomas Hazen, Martin Dresner, 2018, in Transportation Research Part F: Traffic Psychology and Behaviour

doi:10.1016/j.trf.2018.06.043

Location	Beijing, China
Population	General
Sample size	424
Factor analysis type	unspecified, unspecified rotation
Stepwise regression	no
Removal of insignificant variables	no
Reviewed by	DS

Abstract

Environmental concerns have propelled public and private entities to search for ways to increase usage of public bicycle sharing systems. However, usage rates in many cities remain below expectations. Using the theory of perceived value to motivate our hypotheses, this paper evaluates the impact of perceived value on consumer adoption intentions, and assesses the moderating effects of social and personal attitudes towards environmental behavior, on perceived value-adoption intention relationships. Our findings suggest that public bicycle sharing adoption intention is significantly influenced by its perceived functional, conditional, green and social values. Moreover, personal and social attitudes towards “greenness” and bicycle sharing, respectively, are found to moderate the relationship between perceived values and adoption intentions. This research contributes to theory-building in bicycle sharing adoption, and informs business and government leaders on how to promote adoption. © 2018 Elsevier Ltd

Factors

Variable	Pattern loading
Assuming that I had the ability to use public bicycles, I intend to do so. (Other)	0.782
I will use a shared bicycle soon. (Other)	0.737
I plan to use public bicycles in the future. (Other)	0.801

Variable	Pattern loading
I will not use a public bicycle if it rains. (Comfort)	0.902
I will not use a public bicycle if the travel distance is long. (Convenience)	0.857
I will not use a public bicycle if the air quality is not good. (Comfort)	0.666

Variable	Pattern loading
Using public bicycles will reduce energy needs. (Environmentalism)	0.776
Using public bicycles will reduce harmful emissions into the atmosphere. (Environmentalism)	0.856
Using public bicycles will help me feel accepted. (Social norms)	0.768
My use of public bicycles will make a good impression on other people. (Social norms)	0.815
There is no shame in using public bicycles. (Social norms)	0.785

Variable	Pattern loading
I would like to do my part to reduce air pollution. (Environmentalism)	0.754
Among my peers, I am usually the first to try environmental products. (Environmentalism)	0.695
I consider myself to be an environmentally conscious person. (Environmentalism)	0.777

Variable	Pattern loading
Using public bicycles is convenient if a map of rental stations is provided. (Convenience)	0.693
Using public bicycles is convenient if there are enough bicycles available in the rental station at all times (i.e., 24 h a day, 365 days per year). (Convenience)	0.792
Using public bicycles will help alleviate traffic congestion. (Transport policy)	0.836

Variable	Pattern loading
Using a public bicycle is convenient if the distance between my residency (living place or working place) to the rental station is appropriate. (Convenience)	0.781
Using a public bicycle is convenient if I can easily find return locations. (Convenience)	0.696
If anything is wrong with the public bicycle, then the problem will not affect my travel plans (i.e., repair or replacement is easy). (Convenience)	0.808

Variable	Pattern loading
To accept the PB system will be easier for me if people around me use it. (Social norms)	0.845
To accept the PB system will be easier for me if the society form a custom of riding bicycle. (Social norms)	0.87
To accept the PB system will be easier for me if the social medias promote it. (Social norms)	0.83

Models

Dependent variable	shared bicycle adoption intention
Model type	linear regression
Sample size	424.0
R²	0.04
Adjusted R²
Pseudo R² (nan)	nan
AIC	nan
BIC	nan
Log-likelihood at zero	nan
Log-likelihood at constants	nan
Log-likelihood at convergence	nan

Variable	Coefficient	p-value
Age	0.144	<0.01
Gender	-0.063	nan
Income	0.106	<0.05
Education	0.008	nan

Dependent variable	shared bicycle adoption intention
Model type	linear regression
Sample size	424.0
R²	0.455
Adjusted R²
Pseudo R² (nan)	nan
AIC	nan
BIC	nan
Log-likelihood at zero	nan
Log-likelihood at constants	nan
Log-likelihood at convergence	nan

Variable	Coefficient	p-value
Age	0.107	<0.01
Gender	-0.037	nan
Income	0.043	nan
Education	-0.024	nan
functional value	0.449	<0.01
green value	0.103	<0.01
social value	0.074	<0.1
conditional value	0.252	<0.01

Dependent variable	shared bicycle adoption intention
Model type	linear regression
Sample size	424.0
R²	0.521
Adjusted R²
Pseudo R² (nan)	nan
AIC	nan
BIC	nan
Log-likelihood at zero	nan
Log-likelihood at constants	nan
Log-likelihood at convergence	nan

Variable	Coefficient	p-value
Age	0.07	<0.1
Gender	-0.025	nan
Income	0.023	nan
Education	-0.024	nan
functional value	0.277	<0.01
green value	0.081	<0.05
social value	0.057	<0.1
conditional value	0.164	<0.01
social attitudes	0.357	<0.01
personal attitudes	0.093	<0.1

Dependent variable	shared bicycle adoption intention
Model type	linear regression
Sample size	424.0
R²	0.534
Adjusted R²
Pseudo R² (nan)	nan
AIC	nan
BIC	nan
Log-likelihood at zero	nan
Log-likelihood at constants	nan
Log-likelihood at convergence	nan

Variable	Coefficient	p-value
Age	0.067	<0.1
Gender	-0.026	nan
Income	0.019	nan
Education	-0.021	nan
functional value (FV)	0.283	<0.01
green value (GV)	0.074	<0.1
social value (SV)	0.024	nan
conditional value (CV)	0.157	<0.01
social attitudes (SA)	0.36	<0.01
personal attitudes (PA)	0.089	<0.1
Functional value x Social attitudes	0.108	nan
Green value x Social attitudes	0.151	<0.05
Social value x Social attitudes	0.041	nan
Conditional value x Social attitudes	0.038	<0.1
Functional value x Personal attitudes	0.076	<0.1
Green value x Personal attitudes	0.166	<0.01
Social value x Personal attitudes	0.015	nan
Conditional value x Personal attitudes	0.001	nan