Separation of car-dependent commuters from normal-choice riders in mode-choice analysis

Sohn, Keemin; Yun, Ji-Young

doi:10.1007/s11116-009-9209-9

Cited by 38 publications

(25 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A principal component analysis (PCA) was conducted to derive several factors from Likert-scaled answers (Norusis 2007). PCA has been used in many transportation studies to reduce a large number of variables into a tractable number of factors (Sohn and Yun 2009;Johansson et al 2006;Morikawa et al 2002). In the present study, seven factors were derived from 28 questions and an appropriate title was successfully given to each factor.…”

Section: Survey and Data Gatheringmentioning

confidence: 99%

“…In particular, the symbolic motive for cars is sure to be associated with car dependence. Thus, more intensive, compulsory measures such as congestion tolls and gas taxes should be implemented in order to limit car-dependent commuters (Sohn and Yun 2009). Personal physical conditioning was the next most influential factor on duration.…”

Section: Marginal Effects Of Covariatesmentioning

confidence: 99%

See 1 more Smart Citation

Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist

et al. 2010

Self Cite

View full text Add to dashboard Cite

show abstract

Section: Survey and Data Gatheringmentioning

confidence: 99%

Section: Marginal Effects Of Covariatesmentioning

confidence: 99%

Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist

et al. 2010

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is well known that many existing neighborhoods are "car-dependent", that is, they are designed so that almost all trips are expected to be taken by private automobile (Sohn & Yun, 2009). Under these conditions, it is difficult to avoid increased use of automobiles, and encourage use of alternative modes.…”

Section: Altering the Choice Architecture Of Existing Car-dependent Nmentioning

confidence: 99%

Neighborhood “Choice Architecture”: A New Strategy for Lower-Emissions Urban Planning?

Mehaffy

2018

View full text Add to dashboard Cite

Recent advances in the field of behavioral economics offer intriguing insights into the ways that consumer decisions are influenced and may be influenced more deliberately to better meet community-wide and democratic goals. We demonstrate that these insights open a door to urban planners who may thereby develop strategies to alter urban-scale consumption behaviors that may significantly reduce greenhouse gas (GHG) emissions per capita. We first hypothesize that it is possible, through feasible changes in neighborhood structure, to alter the "choice architecture" of neighborhoods in order to achieve meaningful GHG reductions. We then formulate a number of elements of "choice architecture" that may be applied as tools at the neighborhood scale. We examine several neighborhoods that demonstrate variations in these elements, and from known inventories, we generate a preliminary assessment of the possible magnitude of GHG reductions that may be available. Although we acknowledge many remaining challenges, we conclude that "neighborhood choice architecture" offers a promising new strategy meriting further research and development.

show abstract

“…Hunecke et al (2007) projected 21 psychological variables on eight principal components that capture attitude towards ecologic use of transport means. Sohn and Yun (2009) examined differences between car-dependent (using a car regardless the alternative options) and normal-choice commuters and analyzed a role of both groups in a mode choice analysis. PCA resulted in six factors using 19 psychometric variables on car-usage motives which were collected by an online survey.…”

Section: Transportationmentioning

confidence: 99%

Analysis of travel activity determinants using robust statistics

et al. 2016

View full text Add to dashboard Cite

This study investigates travel behavior determinants based on a multiday travel survey conducted in the region of Ghent, Belgium. Due to the limited data reliability of the data sample and the influence of outliers exerted on classical principal component analysis, robust principal component analysis (ROBPCA) is employed in order to reveal the explanatory variables responsible for most of the variability. Interpretation of the results is eased by utilizing ROSPCA. The application of ROSPCA reveals six distinct principal components where each is determined by a few variables. Among others, our results suggest a key role of variable categories such as journey purpose-related impedance and journey inherent constraints. Surprisingly, the variables associated with journey timing turn out to be less important. Finally, our findings reveal the critical role of outliers in travel behavior analysis. This suggests that a systematic understanding of how outliers contribute to observed mobility behavior patterns, as derived from travel surveys, is needed. In this regard, the proposed methods serve for processing raw data typically used in activity-based modelling.

show abstract

Separation of car-dependent commuters from normal-choice riders in mode-choice analysis

Abstract: Car-dependence, Mode-choice, Latent variables, Support vector machine (SVM),

Cited by 38 publications

References 19 publications

Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist

Analyzing the time frame for the transition from leisure-cyclist to commuter-cyclist

Neighborhood “Choice Architecture”: A New Strategy for Lower-Emissions Urban Planning?

Analysis of travel activity determinants using robust statistics

Contact Info

Product

Resources

About