Influence of childhood and adulthood attitudinal perceptions on bicycle usage in the Bangalore city

Verma, Rahul, Vinayak, Verma, 2018, in Journal of Transport Geography

doi:10.1016/j.jtrangeo.2018.08.016
Location Bangalore, India
Population Other (specify)
Sample size 522
Factor analysis type principal components, oblimin rotation
Stepwise regression yes
Removal of insignificant variables yes
Reviewed by LCM

Abstract

Bicycle commuting holds the potential to be an effective solution in combating anthropogenic pollution, urban congestion and increasing health concerns. In a developing country context, few studies have attempted to analyse the influence of various factors that contribute to a low ridership of bicycle. Using data collected through a questionnaire survey in the Indian city of Bangalore, the present study investigates the extent to which variables capturing the attitudinal and social norms, in childhood, affect an individual's decision to continue or discontinue bicycle on transition to adulthood. Further, the study elicits the influence of various adulthood perceptions that limit the usage of bicycles and that can motivate the future usage of bicycles. The study also examines the substitutive effect between bicycles, and the sustainable modes of walking and public transit. The results suggest that a negative social image attached with cycling in childhood contribute to an individual's decision to continue or discontinue cycling after childhood. Further, the results show that part-time cyclists are more sensitive to structural barriers (infrastructure, build environment) while non-cyclists weigh more heavily on personal barriers (attitudes and social norms). Portrayal of cycling in positive light through promotional programs also has a strong positive impact on the choice to bicycle. The study findings shed light on policies and strategies that can help improve the attractiveness of bicycling and augment bicycle use in Indian cities. © 2018 Elsevier Ltd

Factors

Variable Pattern loading
Hostile traffic conditions (Safety) 0.548
Lack of safe parking facilities (Safety) 0.636
Lack of separate bicycle lane (Safety) 0.832
Lack of separate traffic signal (Safety) 0.854
Variable Pattern loading
Family constraints (Convenience) 0.648
Negative image of a bicycle (Social norms) 0.903
Variable Pattern loading
Inclement weather (Comfort) 0.756
Clothing constraint as adult (Convenience) 0.702
Difficulty in carrying luggage (Convenience) 0.692
Variable Pattern loading
Low purchase/maintenance costs (Cost) -0.78
Environmental consciousness (Environmentalism) -0.717
Associated health benefits for self (Lifestyle) -0.822
Positive image in society (Social norms) -0.555
Variable Pattern loading
Augmented publicity (Social norms) 0.754
Publicity using celebrities (Social norms) 0.876
Variable Pattern loading
Proximity to destination (Convenience) 0.687
Dedicated lanes (Safety) 0.705
Bicycle-friendly transport policy (Transport policy) 0.743
End destination facilities parking (Convenience) 0.789

Models

Dependent variable Adulthood bicyling frequency
Model type Logistic regression
Sample size 522.0
R2 0.1
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero -326.472
Log-likelihood at constants nan
Log-likelihood at convergence -296.792
Variable Coefficient p-value
Natural inclination to motor vehicle -0.551 <0.01
Socially acceptable -0.657 <0.01
Travel time -0.552 <0.01
Inconvenience due to dresses -0.28 <0.1
Dependent variable Propensity to shift to bicycle
Model type Logistic regression
Sample size 200.0
R2 0.11
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero -122.687
Log-likelihood at constants nan
Log-likelihood at convergence -110.494
Variable Coefficient p-value
Occupation type -0.781 <0.05
Walking as mode 1.03 <0.01
Public transport as mode 1.32 <0.01
Absence of bicycle friendly infrastructure -0.253 <0.1
Inconvenience during travel -0.302 <0.05
Attitude and preferences -0.241 <0.15
Dependent variable Propensity to shift to bicycle
Model type Logistic regression
Sample size 295.0
R2 0.141
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero -182.298
Log-likelihood at constants nan
Log-likelihood at convergence -156.518
Variable Coefficient p-value
Commute distance -0.36 >0.01
Income -0.0008 >0.1
Walking as mode 0.359 >0.15
Absence of bicycle friendly infrastructure -0.243 >0.1
Inconvenience during travel -0.247 >0.1
Attitude and preferences -0.341 >0.05
Dependent variable Propensity to shift to bicycle
Model type Logistic regression
Sample size 200.0
R2 0.1
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero -122.687
Log-likelihood at constants nan
Log-likelihood at convergence -116.211
Variable Coefficient p-value
Absence of bicycle friendly infrastructure -0.311 <0.05
Inconvenience during travel -0.309 <0.05
Attitude and preferences -0.198 <0.15
Dependent variable Propensity to shift to bicycle
Model type Logistic regression
Sample size 295.0
R2 0.113
Adjusted R2
Pseudo R2 (nan) nan
AIC nan
BIC nan
Log-likelihood at zero -182.298
Log-likelihood at constants nan
Log-likelihood at convergence -161.657
Variable Coefficient p-value
Absence of bicycle friendly infrastructure -0.25 <0.05
Inconvenience during travel -0.262 <0.05
Attitude and preferences -0.304 <0.05

The Attitudes and Travel Database is produced with support from the Center for Teaching Old Models New Tricks at Arizona State University, a University Transportation Center sponsored by the US Department of Transportation through Grant No. 69A3551747116.

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