scholarly journals Modelling the effects of COVID-19 on travel mode choice behaviour in India

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


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

1982 ◽  
Vol 8 (4) ◽  
pp. 370 ◽  
Author(s):  
Richard Barff ◽  
David Mackay ◽  
Richard W. Olshavsky

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