• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.1-13
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• 2018

The present study was conducted to analyze transport mode choice factors of shippers in Korea and to suggest policy implications and directions for future research. The findings showed that the research on freight mode choice factors in Korea is somewhat insufficient compared to that of other countries. In order to enhance the research, it is necessary to expand the number of studies and to strengthen the research to reflect characteristics of each transport mode. In particular, it is necessary to focus on identifying the characteristics of multimodal transport, including railway and shipping linked to truck. On the other hand, it was confirmed that the major factors influencing the choice of transport mode of shippers in Korea overlapped with foreign research cases. In addition, the implications for policy were derived when the analysis was separately conducted for Korea and other countries regarding individual transport mode and transport range. These results could be applied to various fields such as policy making to improve the efficiency of shippers' selection of transport mode and the estimation of transport mode choice model.

• Journal of Korean Society of Transportation
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• v.29 no.2
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• pp.81-89
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• 2011

Trip distribution is the second step of the conventional travel demand estimation process, which connects trips between origin and destination, while transport mode choice is the third step of the process, which chooses transport mode among several modes serving for each origin-destination pair. Although these two steps have closely connected, they have been estimated independently each other in the estimation procedure. This paper presents an integrated model combining trip distribution and transport mode choice, and also presents its solution algorithm. The model integrates gravity model adopted for the trip distribution process with logit model employed for the mode choice process. The model would be expected to cope with the inconsistency issue existing in the conventional travel demand estimation procedure. This paper also presents an equilibrium condition, sensitivity of the model, and compares them with those of existing models.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.131-139
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• 2010

The transport mode choice problem is to determine which of the alternative transport modes connecting an origin and destination will be used by a traveler. Most of the research relating to transport mode choice have mainly been focused on modeling, properties, and applications of the model, but rarely were concerned with equilibrium among the modes. This paper proves the equilibrium among the modes by using a logit mode choice model, and then verifies it with the Korean Transport Database (KTDB). In order to obtain such an equilibrium, this paper also presents a solution algorithm based on the fixed point theorem. The algorithm was tested with an example and confirmed the equilibrium solution.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.77-86
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• 2004

In this study, we applied the Bayesian Network for the case of the mode choice models using the Seoul metropolitan area's house trip survey Data. Sex and age were used lot the independent variables for the explanation or the mode choice, and the relationships between the mode choice and the travellers' social characteristics were identified by the Bayesian Network. Furthermore, trip and mode's characteristics such as time and fare were also used for independent variables and the mode choice models were developed. It was found that the Bayesian Network were useful tool to overcome the problems which were in the traditional mode choice models. In particular, the various transport policies could be evaluated in the very short time by the established relation-ships. It is expected that the Bayesian Network will be utilized as the important tools for the transport analysis.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.531-542
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• 2021

The study aims to investigate differences between men and women in influence of various socio-demographic factors on choice of mode of transport. For this purpose, a binary logit model of choice probabilities is implemented on survey data of a developing country city. Results indicate women's choice of travel mode to be more environment-friendly than that of men. Well-educated, working and middle-aged individuals appear to be the most likely to choosing more-polluting modes of transport for frequent travelling purposes. Individuals in the sample who are the least socioeconomically well off are found the most likely to be promising for the environment. The findings of this study suggest the future transportation policies toward development of existing infrastructure of greener modes of transportation in the city such as, public transportation services and pedestrian lanes, so as to manage the rising issues of degrading environmental quality. The study highlights how the consideration and inclusion of socio-demographic factors is crucial for policy recommendation regarding curtailing the environmental damages contributed by transportation sector. Because mobility crucially affects all other indicators of empowerment, and women are the ones using green modes extensively, the city's transportation system should be so developed which gives their safety and security due importance.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.4
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• pp.253-259
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• 2013

Investment scenarios in the transportation network design problem usually contain installation or expansion of multi-mode transportation links. When one applies the mode choice analysis and traffic assignment sequentially for each investment scenario, it is possible that the travel impedance used in the mode choice analysis is different from the user equilibrium cost of the traffic assignment step. Therefore, to estimate the travel impedance and mode choice accurately, one needs to develop a combined model for the mode choice and traffic assignment. In this paper, we derive the inverse demand and the excess demand functions for the multi-mode multinomial logit mode choice function and develop a combined model for the multi-mode variable demand traffic assignment problem. Using data from the regional O/D and network data provided by the KTDB, we compared the performance of the partial linearization algorithm with the Frank-Wolfe algorithm applied to the excess demand model and with the sequential heuristic procedures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.3
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• pp.75-89
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• 2020

This study was conducted to investigate researches related to tourism transport conducted in Korea and to discover new complementary research projects based on this. Forty cases were reflected in the study, including 28 academic papers and 12 policy studies. Based on the characteristics of tourism transport and cases of prior research, this study divided the field of tourism transport research into three ranges: traffic mode choice for tourism, information for tourist traffic and support policy for tourist traffic etc. In particular, mode choice for tourist traffic was divided into four sub-ranges, reflecting the importance of tourist traffic and the weight of research cases. As a result of the study, it was found that there were not many cases of research on tourism transport, and the research cases were concentrated on the mode choice for tourist traffic. To complement this, this study proposed 10 new research projects in 3 ranges. This is a result of reflecting changes in tourist demand and tourism trends. In addition, a new research field was proposed to seek the connection between transport facilities supply and tourist demand.

• Journal of the Korean Society for Railway
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• v.19 no.1
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• pp.87-96
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• 2016

The multinomial logit model, based on random utility maximization (RUM) theory, has been the predominant model used in travel mode choice contexts. In this paper, the travel mode choice model based on random regret minimization (RRM) theory is proposed as an alternative to the RUM model, and the applicability of the RRM model is examined. The presented model is applied to the case of inter-city travel mode choice in Korea. The empirical results show that the RUM model and RRM model have parameters that are consistent with the intuition. The goodness of fit statistics in the RRM model improved compared with the results of the RUM model. Consequently, these results show the possibility of using the RRM model in the context of travel mode choice.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.57-66
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• 2003

Because the Logit model easily calculates probabilities for choice alternatives and estimates parameters for explanatory variables, it is widely used as a traffic mode choice model. However, this model includes an assumption which is independently and identically distributed to the error component distribution of the mode choice utility function. This paper is a study on the estimation of the Heteroscedastic Logit Model. which mitigates this assumption. The purpose of this paper is to estimate a Logit model that more accurately reflects the mode choice behavior of passengers by resolving the homoscedasticity of the model choice utility error component. In order to do this, we introduced a scale factor that is directly related to the error component distribution of the model. This scale factor was defined so as to take into account the heteroscedasticity in the difference in travel time between using public transport and driving a car, and was used to estimate the travel time parameter. The results of the Logit Model estimation developed in this study show that Heteroscedastic Logit Models can realistically reflect the mode choice behavior of passengers, even if the difference in travel time between public and private transport remains the same as passenger travel time increases, by identifying the difference in mode choice probability of passengers for public transportation.

• Journal of the Korean Society for Railway
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• v.11 no.6
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• pp.588-595
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• 2008

This study is carried out for understanding mode choice behavior of shippers and introducing ideal mode share between rail and truck in Korea. The model type is individual behavioral model and the input data type is stated preference (SP) data. SP data was prepared by design of experiments. The explanatory variables in models are transport time, transport cost and service level. The research result shows that it is more effective to reduce transport cost rather than to implement other strategies. For container, reducing transport cost and transport time and increasing service level simultaneously can strengthen the competitiveness of rail over truck transportation. On the other hand, for bulk freight such as cement and steel, it is better to reduce the transport cost than to do other attributes.