scholarly journals Understanding Attitudes towards Proenvironmental Travel: An Empirical Study from Tangshan City in China

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Xiaoping Fang ◽  
Yajing Xu ◽  
Weiya Chen

Understanding people’s attitudes towards proenvironmental travel will help to encourage people to adopt proenvironmental travel behavior. Revealed preference theory assumes that the consumption preference of consumers can be revealed by their consumption behavior. In order to investigate the influences on citizens’ travel decision and analyze the difficulties of promoting proenvironmental travel behavior in medium-sized cities in China, based on revealed preference theory, this paper uses the RP survey method and disaggregate model to analyze how individual characteristics, situational factors, and trip features influence the travel mode choice. The field investigation was conducted in Tangshan City to obtain the RP data. An MNL model was built to deal with the travel mode choice. SPSS software was used to calibrate the model parameters. The goodness-of-fit tests and the predicted outcome demonstrate the validation of the parameter setting. The results show that gender, occupation, trip purpose, and distance have an obvious influence on the travel mode choice. In particular, the male gender, high income, and business travel show a high correlation with carbon-intensive travel, while the female gender and a medium income scored higher in terms of proenvironmental travel modes, such as walking, cycling, and public transport.

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Chuan Ding ◽  
Yu Chen ◽  
Jinxiao Duan ◽  
Yingrong Lu ◽  
Jianxun Cui

Transport-related problems, such as automobile dependence, traffic congestion, and greenhouse emissions, lead to a great burden on the environment. In developing countries like China, in order to improve the air quality, promoting sustainable travel modes to reduce the automobile usage is gradually recognized as an emerging national concern. Though there are many studies related to the physically active modes (e.g., walking and cycling), the research on the influence of attitudes to active modes on travel behavior is limited, especially in China. To fill up this gap, this paper focuses on examining the impact of attitudes to walking and cycling on commute mode choice. Using the survey data collected in China cities, an integrated discrete choice model and the structural equation model are proposed. By applying the hybrid choice model, not only the role of the latent attitude played in travel mode choice, but also the indirect effects of social factors on travel mode choice are obtained. The comparison indicates that the hybrid choice model outperforms the traditional model. This study is expected to provide a better understanding for urban planners on the influential factors of green travel modes.


2018 ◽  
Vol 34 (1) ◽  
pp. 38-58 ◽  
Author(s):  
Z. Zarabi ◽  
S. Lord

Daily home–work travel is a habitual behavior that can be disrupted when the location of work, as one of the behavioral contexts, changes. It is then likely that individuals will reconsider their travel behavior more intentionally and choose alternative transport modes. To identify motivations and barriers to incorporating the use of sustainable modes into the individual’s daily travel, this article systematically reviews the literature on the impacts of involuntary workplace relocation on commuting behavior. Effective measures that incentivize sustainable commuting behavior are also discussed. This study on involuntary workplace relocation informs considerations of changes in travel behavior related to other contextual changes.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Xiaowei Li ◽  
Qiangqiang Ma ◽  
Wenbo Wang ◽  
Baojie Wang

To explore the influence of weather conditions on the choice of the intercity travel mode of travelers, four modes of traveler transportation were studied in Xi'an, China, in March 2019: airplane, high-speed rail, conventional train, and express bus. The individual characteristics of travelers and intercity travel activity data were obtained, and they were matched with the weather characteristics at the departure time of the travelers. The Bayesian multinomial logit regression was employed to explore the relationship between the travel mode choice and weather characteristics. The results showed that temperature, relative humidity, rainfall, wind, air quality index, and visibility had significant effects on the travel mode selection of travelers, and the addition of these variables could improve the model’s predictive performance. The research results can provide a scientific decision basis for traveler flow transfer and the prediction of traffic modes choice due to the effects of climate change.


2020 ◽  
Vol 02 (02) ◽  
pp. 25-33
Author(s):  
J. Slik ◽  
S. Bhulai

Urban planning can benefit tremendously from a better understanding of where, when, why, and how people travel. Through advances in technology, detailed data on the travel behavior of individuals has become available. This data can be leveraged to understand why one prefers one mode of transportation over another one. In this paper, we analyze a unique dataset through which we can address this question. We show that the travel behavior in our dataset is highly predictable, with an accuracy of 97%. The main predictors are reachability features, more so than specific travel times. Moreover, the travel type (commute or personal) has a considerable influence on travel mode choice.


2014 ◽  
Vol 8 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Ruijing Chen

In this paper, we study the travel mode choice of residents to determine the set of factors which can influence travel mode choice of residents and analyze the influence factor characteristics. Using Bayesian theory, we analyze the travel decision-making data of the residents, discrete them, and use them in Bayesian network structure learning and parameter estimation by K2 algorithm. We establish a Bayesian network simulation model to analyze the dependence probability relationship between the parent nodes and child nodes. Validation test was carried out for the building simulation model of Bayesian network. Data analysis results showed that the Bayesian network has a high accuracy prediction for actual travel mode choice of residents. This paper studies the Bayesian structure and parameters learning method for the actual travel behavior, and this method which provides a new method for studying the travel mode choice of residents can reveal the relationship between the various attributes associated with travel mode choice through a new perspective.


2019 ◽  
Vol 11 (12) ◽  
pp. 3403
Author(s):  
Arefeh Nasri ◽  
Lei Zhang

Understanding travel behavior and its relationship with built environment is crucial for sustainable transportation and land-use policy-making. This study provides additional insights into the linkage between the built environment and travel mode choice by looking at the built environment characteristics at both the trip origin and destination in the context of transit-oriented development (TOD). The objective of this research is to provide a better understanding of how travel mode choice is influenced by the built environment surrounding both trip end locations. Specifically, it investigates the effect of transit-oriented development policy and the way it affects people’s mode choice decisions. This is accomplished by developing discrete choice models and consideration of urban form characteristics at both trip ends. Our findings not only confirmed the important role the built environment plays in influencing mode choice, but also highlighted the influence of policies, such as TOD, at both trip end locations. Results suggest that the probability of choosing transit and non-motorized modes is higher for trips originating and ending in TOD areas. However, the magnitude of this TOD effect is larger at trip origin compared to destination. Higher residential and employment densities at both trips ends are also associated with lower probability of auto and higher probability of transit and non-motorized mode choices.


2019 ◽  
Vol 11 (17) ◽  
pp. 4698 ◽  
Author(s):  
Matus Sucha ◽  
Lucie Viktorova ◽  
Ralf Risser

In order to determine whether an experimentally induced experience has the potential to change future travel mode choice, we recruited 10 families living in a middle-sized city who used a car at least four times a week, and made them stop using the car for one month. Each adult family member kept a travel diary and interviews were conducted prior to the experiment, after one month without a car, and then three months and one year after the experiment ended. The results suggest that the participants’ attitudes towards different transportation modes did not change during the period of the study, but their actual travel behavior did. In this respect, several factors were identified that influence travel mode choice, once the participants are made aware of the decision process and break the habit of car use.


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