A Stated preference freight mode choice model

2003 ◽  
Vol 26 (2) ◽  
pp. 1-1 ◽  
Author(s):  
O. Norojono ◽  
W. Young
Keyword(s):  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Mode Choice Model ◽  
Freight Mode Choice

scholarly journals Mode choice analysis using discrete choice model from transport user (Case study: Jakarta LRT, Indonesia)

2018 ◽  
Vol 181 ◽  
pp. 03001
Author(s):  
Dwi Novi Wulansari ◽  
Milla Dwi Astari
Keyword(s):  
Discrete Choice ◽  
Public Transportation ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Choice Models ◽  
Discrete Choice Models ◽  
Light Rail ◽  
Choice Analysis ◽  
Mode Choice Model

Jakarta Light Rail Transit (Jakarta LRT) has been planned to be built as one of mass rail-based public transportation system in DKI Jakarta. The objective of this paper is to obtain a mode choice models that can explain the probability of choosing Jakarta LRT, and to estimate the sensitivity of mode choice if the attribute changes. Analysis of the research conducted by using discrete choice models approach to the behavior of individuals. Choice modes were observed between 1) Jakarta LRT and TransJakarta Bus, 2) Jakarta LRT and KRL-Commuter Jabodetabek. Mode choice model used is the Binomial Logit Model. The research data obtained through Stated Preference (SP) techniques. The model using the attribute influences such as tariff, travel time, headway and walking time. The models obtained are reliable and validated. Based on the results of the analysis shows that the most sensitive attributes affect the mode choice model is the tariff.

An inter‐Urban freight mode choice model

1983 ◽  
Vol 8 (1) ◽  
pp. 61-80 ◽  
Author(s):  
W. Young ◽  
A. J. Richardson ◽  
K. W. Ogden ◽  
A. L. Rattray
Keyword(s):  
Choice Model ◽  
Mode Choice ◽  
Urban Freight ◽  
Mode Choice Model ◽  
Freight Mode Choice

scholarly journals Pemodelan Pemilihan Moda Rute Medan–Binjai Antara Kereta Api dan Bus dengan Metode Stated Preference

2018 ◽  
pp. 35-43
Author(s):  
Indra Markeshwan Zagoto ◽  
Charles Sitindaon ◽  
Oloan Sitohang
Keyword(s):  
Service Quality ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Access Time ◽  
Stated Preference Survey ◽  
User Choice ◽  
Trip Purpose ◽  
Railway Line ◽  
Mode Choice Model

The objective of this research is to construct a user mode choice model between BRT Mebidang and Sri Lelawangsa railway line, and further to test the sensitivity of trip user choice toward certain change in attributes value. Data were collected using stated preference survey, and analysed using logit biner model. Based on user responses, it was found that 50.96% trip purpose is related to family/social matter, while the main reason to travel using both modes is convenience. The tility function of Mebidang bus is given as follow: UBM-KA = 7.256 - 0.565X1 - 0.031X2 + 0.101X3 - 0.071X4 + 0.088X5 where X1 is cost, X2 is time, X3 is headway, X4 is accesstime, dan X5 is service quality. The model shows that cost, time, and access time negatively affect Mebidang bus utility thus will lower the probability of user choosing bus over rail. In terms of sensitivity, access time and service quality are considered more sensitive in affecting the probability of choosing bus.

A weighted logit freight mode-choice model

2009 ◽  
Vol 45 (6) ◽  
pp. 1006-1019 ◽  
Author(s):  
J. Rich ◽  
P.M. Holmblad ◽  
C.O. Hansen
Keyword(s):  
Choice Model ◽  
Mode Choice ◽  
Mode Choice Model ◽  
Freight Mode Choice

scholarly journals An Intercity Freight Mode Choice Model : A Case Study of High Speed Rail Link Northern Line Thailand (Bangkok – Chiangmai)

2020 ◽  
Vol 308 ◽  
pp. 04003
Author(s):  
Jessada Pochan ◽  
Wachira Wichitphongsa
Keyword(s):  
High Speed ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Selling Price ◽  
High Speed Rail ◽  
Time Frequency ◽  
Rail System ◽  
Loading And Unloading ◽  
Freight Mode Choice

This paper presents a model capturing the intercity freight mode choice behaviour in high-speed rail system from Bangkok to Chiangmai. The model is developed based on the stated preference data collected from 800 freight operators, wholesaler, retailer, and people. The results show that, when the high-speed rail system from Bangkok to Chiangmai are developing in the future, the suitable products for high-speed rail system are types of an express mail service (EMS), air cargo, gold, jewellery, gold accessories, computer circuit boards, high prices agricultural products such as fruit, and flowers. Most of determining the selling price will fluctuate with the speed of transport and damage impairment of the product. With the application of discrete choice models, the results show that, aside from travel cost and time, loading and unloading, delays time, frequency are statistically significant. The application of model indicated that the holder and freight forwarder which in the line of high-speed rail (Bangkok – Chiangmai) tend to use rail-transport such as double-track rail is 27.71%, high-speed rail is 11.18% and the most is trucks 56.51% which is a policy development point loading and unloading, multimodal transportation efficiency and safety of the portion of the freight high-speed rail increased.

Large-Scale Application of a Combined Destination and Mode Choice Model Estimated with Mixed Stated and Revealed Preference Data

2017 ◽  
Vol 2669 (1) ◽  
pp. 31-40 ◽  
Author(s):  
Michael Heilig ◽  
Nicolai Mallig ◽  
Tim Hilgert ◽  
Martin Kagerbauer ◽  
Peter Vortisch
Keyword(s):  
Large Scale ◽  
Travel Demand ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Revealed Preference ◽  
Demand Model ◽  
Agent Based ◽  
Preference Data ◽  
Mode Choice Model

The diffusion of new modes of transportation, such as carsharing and electric vehicles, makes it necessary to consider them along with traditional modes in travel demand modeling. However, there are two main challenges for transportation modelers. First, the new modes’ low share of usage leads to a lack of reliable revealed preference data for model estimation. Stated preference survey data are a promising and well-established approach to close this gap. Second, the state-of-the-art model approaches are sometimes stretched to their limits in large-scale applications. This research developed a combined destination and mode choice model to consider these new modes in the agent-based travel demand model mobiTopp. Mixed revealed and stated preference data were used, and new modes (carsharing, bikesharing, and electric bicycles) were added to the mode choice set. This paper presents both challenges of the modeling process, mainly caused by large-scale application, and the results of the new combined model, which are as good as those of the former sequential model although it also takes the new modes into consideration.

scholarly journals A Mode Choice Model Separating Taste Variation and Stated Preference Reporting Error

1998 ◽  
Vol 15 ◽  
pp. 609-617
Author(s):  
Yoriyasu SUGIE ◽  
Junyi ZHANG ◽  
Akimasa FUJIWARA ◽  
Takeshi MIYAJI
Keyword(s):  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Reporting Error ◽  
Mode Choice Model

scholarly journals Mode choice model analysis between ridesouring and ridesplitting service in DKI Jakarta

2019 ◽  
Vol 270 ◽  
pp. 03013 ◽  
Author(s):  
Anggit Cahyo ◽  
Nahry ◽  
Helen Burhan
Keyword(s):  
Logit Model ◽  
Choice Model ◽  
Stated Preference ◽  
Mode Choice ◽  
Mode Switching ◽  
Additional Time ◽  
Binary Logit Model ◽  
Mode Choice Model ◽  
Binary Logit ◽  
Sensitivity Rate

Beside the ridesoucing service, ridesplitting service is also offered by Transport Network Companies (TNC). The ridesplitting service have more benefit than ridesourcing because it is using the concept of carsharing. The current condition for ridesplitting service is not popular and only have small demand than ridesourcing service. This study aims to establish a mode choice model between ridesourcing and ridesplitting service in DKI Jakarta and to estimate the potential of demand shifting from ridesourcing to ridesplitting service in DKI Jakarta. The mode choice model is developed from binary logit model with stated preference survey using fare saving, additional time travel and security presented by gender parameter of ridesplitting service. the sensitivity of logit model show that highest sensitivity rate to increase mode switching to ridesplitting service is in 20% to 50% fare saving level. The probability of current condition to switch to ridesplitting service is 20%.

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