Travel duration tolerance: Examining the sensitivity of emotional well-being to trip duration

Ermagun, Alireza; Erinne, Jacquelyn; Fan, Yingling

doi:10.1016/j.trd.2021.103137

Cited by 15 publications

(10 citation statements)

References 36 publications

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“…Using data from a retrospective survey among commuters following a workplace relocation, Ma et al (2021b) found that the amount of variation in commute time has a greater impact on commute satisfaction than the gap between the actual and ideal commute time. Relying on a smartphone-based survey, Ermagun et al (2022) examined the correlation between travel duration and emotional wellbeing. They found that bus, rail, and bike users withstand longer commute durations before their emotional wellbeing worsens, suggesting positive benefits of such travel modes.…”

Section: • New Methods In Travel Satisfaction Researchmentioning

confidence: 99%

New insights in travel satisfaction research

Vos

2022

Transportation Research Part D: Transport and Environment

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Section: • New Methods In Travel Satisfaction Researchmentioning

confidence: 99%

New insights in travel satisfaction research

Vos

2022

Transportation Research Part D: Transport and Environment

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“…Young [49] found that commuting satisfaction rose first and then decreased with the hypothetical commuting time (HCT). Subsequently, the relevant literature on the positive utility of an ideal commuting time and the negative utility of an acceptable (tolerable) commuting time emerged [50][51][52][53][54]. The ideal commuting time (ICT) reflects commuters' preferences for commuting times; people's ICTs are mainly around 10-20 min [55,56], while the tolerance threshold for commuting times (TTCT) reflects commuters' tolerance of commuting times; people's TTCTs was 30-40 min [57,58].…”

Section: Literature Reviewmentioning

confidence: 99%

“…When the ACT is close to the ICT, the perceived satisfaction of commuters is better [41,43,78]. While the TTCT reflects commuters' tolerance of commuting times [57,58], When the ACT approaches or even exceeds the TTCT, the negative motions of commuters significantly increase [54], which leads to a sharp satisfaction decrease [40,42]. In addition, the advantage of clustering respondents in this way is that it not only reflects the relationship between the actual commuting time and commuting satisfaction, but also helps to reveal the specific impact of respondents' subjective commuting-time boundary points on commuting satisfaction.…”

Section: Group Differences In the Nonlinear Relationships Between Com...mentioning

confidence: 99%

Exploring the Group Difference in the Nonlinear Relationship between Commuting Satisfaction and Commuting Time

Yang

2022

Sustainability

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Analyzing commuting-time satisfaction could help to improve the subjective well-being of society. This study aimed to explore the nonlinear relationship between commuting satisfaction and commuting times in different groups and its influencing factors. An empirical study was conducted in Kunming, China. Firstly, applying a random forest algorithm revealed that there was a nonlinear relationship between commuting satisfaction and commuting time. Secondly, the k-means clustering algorithm was used to divide the respondents into three types of commuter: short-duration-tolerant (group 1), medium-duration-tolerant (group 2), and long-duration-tolerant (group 3). It was found that the commuting-time satisfaction of these three clustered groups had different threshold effects. Specifically, the commuting satisfaction of group 1 showed a nonlinear downward trend, which decreased significantly at 12 and 28 min, respectively; the commuting satisfaction of group 2 rapidly decreased at 35 min; the commuting satisfaction of group 3 first increased in the range of 20–30 min, decreased significantly after 45 min, and decreased sharply above 70 min. These time thresholds were consistent with the ideal commuting times (ICTs) and tolerance thresholds of the commuting times (TTCTs) of the three clustered groups, which indicates that the ICT and TTCT had significant effects on commuting satisfaction. Lastly, the results of the multinominal logistic model showed that variables such as the commuting mode, job–housing distance, income, and educational background had significant effects on the three clustered groups. The policy implications of the study are that commuting circles should be planned with the TTCT as a constraint boundary and ICT as the optimal goal; in addition, different strategies should be adopted for different commuting groups to improve commuting satisfaction.

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“…Public transport facilities can improve the attractiveness of urban parks, and increasing the number of bus stations can attract more residents to urban parks [41]. e convenience of travel also affects the attractiveness of urban parks, because the attractive radius of urban parks is mainly 1-3 km [42]. Residents living nearby are more convenient to travel to and are more likely to go to urban parks [43,44].…”

Section: Introductionmentioning

confidence: 99%

Study on Influencing Factors of the Duration of Residential Leisure Travel to Urban Parks

Yan

Dong

et al. 2022

Journal of Advanced Transportation

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With the improvement of living standards, more and more residents in China choose short leisure travel at weekends. This study aims to model the leisure travel duration to investigate the relationship between travel time and residents’ factors, which can provide guidance for the development of urban parks and improve the structure of transportation modes to promote low-carbon travel modes. The accelerated hazard model is applied to establish the model equation between travel time and various factors, to obtain the differences between weekend travel time in scenic spots and personal characteristics such as residents’ playing time and travel mode choice. First, an analysis of variance was performed on the valid data which have been collected. Then, the Kaplan–Meier test proved that weekend activity types tend to follow different survival functions. Finally, this study established the lifespan regression equation of the travel time, and we found that the best fit is the Log-normal distribution. This study shows clearly that accelerated hazard models based on fixed parameters are better at evaluating the attractiveness of urban parks, and they can also get feedback travel characteristics of primary residents. So, we can build a lifespan analysis-based model for the travel time of urban residents, to help plan the urban parks. The result of this study can be used for predicting the flow of different travel modes at urban parks in cities, which can be helpful for regional traffic organization such as regional traffic flow guidance and signal timing.

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Travel duration tolerance: Examining the sensitivity of emotional well-being to trip duration

Cited by 15 publications

References 36 publications

New insights in travel satisfaction research

New insights in travel satisfaction research

Exploring the Group Difference in the Nonlinear Relationship between Commuting Satisfaction and Commuting Time

Study on Influencing Factors of the Duration of Residential Leisure Travel to Urban Parks

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