A platform for research: civil engineering, architecture and urbanism
Research on Passengers’ Preferences and Impact of High-Speed Rail on Air Transport Demand
The new high-speed rail (HSR) routes are expected to have a large impact on air transport demand. In some cases, HSR can be a complementary mode to air transport. However, a number of studies have pointed out that HSR can have a negative impact on air transport demand. Various approaches have been used to model mode choice behaviour, such as the discreet choice model, logistic regression and the analytical hierarchy process. OLS and MLE are two methods that are commonly used for parameter estimations. However, these approaches have some limitations. This study aims to understand the travel behaviour, mode choice model, travel variables and the impact of HSR operation on air transport demand through a systematic literature review. This study explores various approaches that are used to model mode choice and identify possible alternative approaches to overcome the limitations of current methods. The key variables that influence mode choice and the impact of HSR operation are elaborated in this study. Several points can be concluded from the analysis of the literature, such as: (1) the operation speed set by HSR should be reliable to enable it to compete with airplane travel time; (2) the model to represent mode choice behaviour should be derived from a suitable analysis method and Bayesian method is one of the alternatives for the parameter estimation; (3) there are various variables that are yet to be included in the current mode choice models, and they can be further explored to better present the needs of the customers; and (4) the impact of HSR operation on airplane travel demand, explained by previous studies, can be used as a reference for the policy maker in implementing transport projects.
Research on Passengers’ Preferences and Impact of High-Speed Rail on Air Transport Demand
The new high-speed rail (HSR) routes are expected to have a large impact on air transport demand. In some cases, HSR can be a complementary mode to air transport. However, a number of studies have pointed out that HSR can have a negative impact on air transport demand. Various approaches have been used to model mode choice behaviour, such as the discreet choice model, logistic regression and the analytical hierarchy process. OLS and MLE are two methods that are commonly used for parameter estimations. However, these approaches have some limitations. This study aims to understand the travel behaviour, mode choice model, travel variables and the impact of HSR operation on air transport demand through a systematic literature review. This study explores various approaches that are used to model mode choice and identify possible alternative approaches to overcome the limitations of current methods. The key variables that influence mode choice and the impact of HSR operation are elaborated in this study. Several points can be concluded from the analysis of the literature, such as: (1) the operation speed set by HSR should be reliable to enable it to compete with airplane travel time; (2) the model to represent mode choice behaviour should be derived from a suitable analysis method and Bayesian method is one of the alternatives for the parameter estimation; (3) there are various variables that are yet to be included in the current mode choice models, and they can be further explored to better present the needs of the customers; and (4) the impact of HSR operation on airplane travel demand, explained by previous studies, can be used as a reference for the policy maker in implementing transport projects.
Research on Passengers’ Preferences and Impact of High-Speed Rail on Air Transport Demand
Asep Yayat Nurhidayat (author) / Hera Widyastuti (author) / Sutikno (author) / Dwi Phalita Upahita (author)
2023
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Cluster Analysis of Intercity Rail Passengers in Emerging High-Speed Rail Corridor
British Library Online Contents | 2011
|High speed rail drives composites demand
British Library Online Contents | 2013
Forecasting demand for high speed rail
Elsevier | 2014
|