Travel Mode Choice: Effects of Previous Experience on Choice Behaviour and Valuation

2003 ◽  
Vol 9 (1) ◽  
pp. 5-30 ◽  
Author(s):  
Lena Nerhagen

This paper investigates how past experience influences choice behaviour and valuation in a hypothetical travel mode choice situation. Using a stated choice question asked of visitors to a major ski resort in Sweden, the author explores whether an individual's choice behaviour, when he or she is offered a comfort improvement to train travel, can be explained with reference to the individual and to the circumstances of his or her previous journey. The analysis models and compares the response behaviour of travellers who used a car and travellers who used the train on their original trip. It is found that past experience influences travellers' choice behaviour. Twenty per cent of former car users choose the train, while most train users again choose the train. As reasons for choosing car travel once again, car users mention a preference for shorter travel time and/or a preference for flexibility, while environmental concerns and long travel distance favour the use of the train. Concerning comfort improvement, as expected, willingness-to-pay estimates for the former train users are lower and more precise than those for the former car users.

Author(s):  
Eeshan Bhaduri ◽  
B.S. Manoj ◽  
Zia Wadud ◽  
Arkopal K. Goswami ◽  
Charisma F. Choudhury

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jianhui Wu ◽  
Yuanfa Ji ◽  
Xiyan Sun ◽  
Yan Xu

This aim of this study is to improve the guidance role of the fuel tax rate and bus departure quantity on travel mode choice. Car and bus travel are chosen as the research object, and a day-to-day evolution model of dual-mode network traffic flow (based on a stochastic user equilibrium model and the method of network tatonnement process) is established. Subsequently, a guidance optimization model of fuel tax rate and bus departure quantity is designed. This guidance optimization model is formulated to determine the comprehensive minimum value among system total travel time of car travel, system total comprehensive cost of bus travel, and the difference between the total operating cost of bus departure increment and the total amount of fuel tax levied on car travelers. Through numerical examples, the validity of this guidance optimization model is verified, and the influence of fuel tax rate and bus departure quantity on the traffic network is analyzed. The results show that a guidance optimization scheme based on fuel tax rate and bus departure quantity can help regulate the proportion of car travel and improve bus service quality.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Fang Zhou ◽  
Jianhui Wu ◽  
Yan Xu ◽  
Chi Yi

To analyze the influence of tradable credits and bus departure quantity on travelers' travel mode choice, this study investigated car travel and bus travel as research objects and established a two-mode day-to-day travel mode choice model based on tradable credits and bus departure quantity. To improve the guiding effect of tradable credits and bus departure quantity, an optimization scheme of tradable credits and bus departure quantity was developed with the goal of minimizing the system total travel time of car travel and the system total comprehensive cost of bus travel. Taking a test transportation network as an example, the influence of no tradable credits scheme, tradable credits scheme, and tradable credits and bus departure quantity scheme on the travelers’ travel mode choice behavior was analyzed. The results showed that the tradable credits and bus departure quantity scheme could reduce the saturation of road traffic and improve bus service quality.


2021 ◽  
Vol VI (III) ◽  
pp. 106-118
Author(s):  
Fariha Tariq ◽  
Nabeel Shakeel

The travel mode preference exists in both culture and theenvironment. The wide scale of people's mobility makesour cities more polluted and congested, eventually affecting urban assets.Understanding people’s mode choice is important to develop urbantransportation planning policies effectively. This study aims to model andpredict the commuter’s mode choice behaviour in Lahore, Pakistan. A surveywas conducted, and the data was used for model validation. Thecomparative study was further done among multinomial logit model (MNL),Random Forest (RF), and K-Nearest Neighbor (KNN) classificationapproaches. It’s common in existing studies that vehicle ownership is rankedas the most important among all features impacting commuters’ travel modechoice. Since many commuters in Lahore own no vehicle, it’s unclear whatthe rank of factors impacting non-vehicle owners is. Other than thecomparison of predicting the performance of the methods, our contributionis to do more analysis of the rank of factors impacting the different types ofcommuters. It was observed that occupation is ranked as the most importantamong all features for non-vehicle owners.


2021 ◽  
pp. 1-18
Author(s):  
Jonas De Vos ◽  
Patrick A. Singleton ◽  
Tommy Gärling

2021 ◽  
Vol 106 ◽  
pp. 271-280
Author(s):  
Siliang Luan ◽  
Qingfang Yang ◽  
Zhongtai Jiang ◽  
Wei Wang

Sign in / Sign up

Export Citation Format

Share Document