Analysis of Travel Mode Choice Behavior Considering the Indifference Threshold

Zhang, Xinjie; Guan, Hongzhi; Zhu, Haiyan; Zhu, Junze

doi:10.3390/su11195495

Cited by 16 publications

(12 citation statements)

References 26 publications

(32 reference statements)

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“…Numerous studies have indicated that travelers tend to choose cheaper modes of transport [43,44]. In addition, studies have shown that these variables have the highest impact on a traveler's mode choice behavior [45][46][47][48]. Among socioeconomic variables, the variables that significantly contributed to the mode choice are monthly income, gender, education level and age.…”

Section: The Modelmentioning

confidence: 99%

Estimation of Travel Demand for Bangkok–Chiang Mai Hyperloop Using Traveler Surveys

Agrawal

Pravinvongvuth

2021

Sustainability

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Hyperloop, projected as fast and efficient, and envisaged as the future of high-speed transportation, does not have much published information about its demand estimation. This paper aims to estimate the willingness of air and car passengers to shift to hyperloop. A nested logit model was used to analyze stated preference data gathered from the air and car travelers along the Bangkok–Chiang Mai sector in Thailand. The variables contributing the most to the modal shift towards hyperloop are total travel cost, total travel time, monthly income, gender, education level, bearer of trip expenses, and number of trips in the last 6 months and duration of stay at the destination. The highest value of elasticity for hyperloop is obtained for the total travel cost followed by total travel time and monthly income. It is concluded that hyperloop will be the predominant mode of transportation between the Bangkok–Chiang Mai sectors with a modal share of almost 50% by the year 2025. Survey results also revealed that the preferences of the passengers in order of priorities for long distance travel are comfort, low travel cost, less travel time, safety, high frequency of travel mode and low CO2 emission. The main contribution of this paper is to provide an insight on factors that may contribute towards a possible shift in mode from car and air to hyperloop. The study will be beneficial to policy makers in developing a strategy for a more efficient mass transportation system using new and emerging technologies.

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Section: The Modelmentioning

confidence: 99%

Estimation of Travel Demand for Bangkok–Chiang Mai Hyperloop Using Traveler Surveys

Agrawal

Pravinvongvuth

2021

Sustainability

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“…Thus, these theories are particularly relevant to the present study. Within the field of sustainability, they covered a large variety of contexts and behaviors: restauration [70], driving [71], transport and travel mode choice [72][73][74][75], green products and food [76][77][78], waste management, recycling [79,80], and agriculture [81,82].…”

Section: Theory Of Reasoned Action (Tra) and Theory Of Planned Behavimentioning

confidence: 99%

From Values to Behavior: Proposition of an Integrating Model

Aride

Pàmies

2019

Sustainability

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Human values are at the heart of our lives. We all hold a set of values that influence our actions. The protection of the natural environment is no exception to this rule. That is why the study of human values is key to reaching the imperative of sustainability. In this conceptual paper, we aim to (1) integrate the key theories and models explaining the influence of human values on behavior and to (2) identify factors that might have previously been overlooked. Drawing from a range of disciplines, this article proposes an integrated model mapping the influence of human values on behavior. It also puts forward the concept of consequences as an emerging factor that could play an important role in this relationship. Recommendations are to extend the research to an empirical investigation of the model and to develop the definition of the concept of consequences and the role they play in the influence of values on consumer behavior.

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“…However, the potential shift away from passenger car use has to account for constrained daily travel time budget and activity space [5,6]. Specifically, understanding potential for modal shift requires comparing travel times of alternative modes for individual travelers, as they can influence travelers' decisions [7]. From the standpoint of steering sustainability transitions, understanding the potential for modal shift by taking into account changes in travel time, carbon emissions, and physical activity is important for large infrastructural investments, such as public transport network overhauls [8], or for piloting new mobility services and policy programs [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Potential Shift to Low-Carbon Urban Travel Modes: A Computational Framework Based on High-Resolution Smartphone Data

et al. 2020

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Given the necessity to understand the modal shift potentials at the level of individual travel times, emissions, and physically active travel distances, there is a need for accurately computing such potentials from disaggregated data collection. Despite significant development in data collection technology, especially by utilizing smartphones, there are limited efforts in developing useful computational frameworks for this purpose. First, development of a computational framework requires longitudinal data collection of revealed travel behavior of individuals. Second, such a computational framework should enable scalable analysis of time-relevant low-carbon travel alternatives in the target region. To this end, this research presents an open-source computational framework, developed to explore the potential for shifting from private car to lower-carbon travel alternatives. In comparison to previous development, our computational framework estimates and illustrates the changes in travel time in relation to the potential reductions in emission and increases in physically active travel, as well as daily weather conditions. The potential usefulness of the framework was evaluated using long-term travel data of around a hundred travelers within the Helsinki Metropolitan Region, Finland. The case study outcomes also suggest that in several cases traveling by public transport or bike would not increase travel time compared to the observed car travel. Based on the case study results, we discuss potentially acceptable travel times for mode shift, and usefulness of the computational framework for decisions regarding transition to sustainable urban mobility systems. Finally, we discuss limitations and lessons learned for data collection and further development of similar computational frameworks.

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Analysis of Travel Mode Choice Behavior Considering the Indifference Threshold

Cited by 16 publications

References 26 publications

Estimation of Travel Demand for Bangkok–Chiang Mai Hyperloop Using Traveler Surveys

Estimation of Travel Demand for Bangkok–Chiang Mai Hyperloop Using Traveler Surveys

From Values to Behavior: Proposition of an Integrating Model

Analysis of Potential Shift to Low-Carbon Urban Travel Modes: A Computational Framework Based on High-Resolution Smartphone Data

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