• Journal of Korean Society of Transportation
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• v.20 no.3
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• pp.83-92
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• 2002

Freight mode choice models are essential to the analysis of many areas of transport research. However, observations of actual market choices have only been made in a limited number of situations. Therefore, stated preference(SP) techniques have emerged as an alternative source of actual market choices to be used for estimating freight mode choice models. Considerable confidence exists about SP data, but little consideration has been given to the potential for estimation bias. This paper has been motivated by the theoretical side of estimating SP discrete choice models, focusing on a case study of freight mode choice. Recently developed simulation methods are used to construct inherent random heterogeneity legit models, which consider individual heterogeneity, its inheritance to the next choices and overcome the independence from irrelevant alternatives (IIA) property. This Paper contributes to the development of models dealing with heterogeneity and its inheritance, and sheds light on the heterogeneity of freight transport.

• 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.23 no.5 s.83
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• pp.65-71
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• 2005

Area type is often used in freight demand analysis and logistics planning models. For example, in freight transportation planning. area type variable is most often commonly used in freight generation (attraction) model. Yet a reliable, forecastable and measurable definition or area type is generally not documented. In fact, there is little literature on the subject of predicting area type in the context of freight planning models. This can be troublesome when applying models to long-range logistics planning where significant changes in population and employment result in changes in the general character of an area. Through the use of Discriminant Model, GIS (Geographic Information System) analysis and Delphi methods, this paper presents the successful exploration for a quantifiable means of determining area type.

• 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.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.265-274
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• 2017

For accurate demand forecasting of railway logistics, we estimated intercity freight mode choice models based on the binary logit model and using production-consumption data from the Korea Transport Database. We estimated two types of models and compared the results by major item of railway logistics, such as container, cement, and steel: 1) The aggregate freight mode choice models are based on the revealed preference (RP) data and 2) The disaggregate models are based on the stated preference (SP) data. With respect to the container, the travel time variable was found to be statistically significant; however, the travel cost variable was not statistically significant in the RP model, while the travel cost variable was statistically significant in the SP model. For cement and steel, the travel cost variables were statistically significant but the travel time variables were not statistically significant in either the RP or the SP models. These results are inconsistent with results from previous studies based on SP data, which showed that the travel time variables were significant. Consequently, it can be concluded that the travel time factor should be considered in container transport, but that this factor is negligible for cement and steel transport.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.133-146
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• 2010

The objective of this study is to develop a supply chain-based freight distribution channel choice model considering shippers' logistics behaviors which will be used for freight demand estimation. For this purpose, this study utilized the distribution channel data of the petrochemical and automobile industries collected by KTDB center. The distribution channel choice models for these industries were developed by including transport mode, time, cost, and shipment size. It was found that the multinomial logit model with transport cost, time and shipment size is the best, and as shipment increases, bigger transport mode is preferred. Generally direct distribution channel with small truck was preferred over the one using distribution center and/or big truck.

• Proceedings of the KOR-KST Conference
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• 2007.11a
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• pp.201-209
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• 2007

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.3
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• pp.1-11
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• 2016

The present study aims to evaluate transfer resistance factors in railway stations and draw new implications. The data used for the model estimation are RP (revealed preference) data and SP (stated preference) data. Two types of models were used for the analysis: integration model which combined line-haul stage, transfer stage and shuttle stage and separation model which assessed the three stages separately. The results revealed that while bulk freight shippers mainly focused on line-haul stage, they put emphasis on transfer stage as well. It's especially notable that transfer stage was considered more important than shuttle stage. Therefore, in future transportation policies concerning rail freight, it would be crucial not only to enhance the competitiveness of line-haul stage but also make improvements in transfer stage regarding railway stations.

• Journal of Korean Port Research
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• v.7 no.1
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• pp.25-42
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• 1993

지난 20여년간 화물수송 분야에는 큰 변화가 있었다. 수송 공급 측면에서는 보다 다양하고 기술적으로 앞선 수송수단들이 등장했으며, 수송 수요 측면에서는 로지스틱스 개념의 도입으로 화주들의 보다 높은 수송 서비스가 요구 되었다. 수송수단의 수송 분담에 있어서도 특히 철도에서 공로로의 두드러진 화물이동 현상이 나타났다. 이러한 변화는 수송 현안 해결에 대한 관심을 높이고 화물수송수요 예측기법의 이론적, 개념적인 발달을 가져왔다. 그 중 두드러진 발달은 화주의 행태를 반영하는 행태모형의 개발과 새로운 자료수집 방법 및 자료형태이다. 전통적으로 화물수송 및 교통 연구에 널리 사용된 행태모형은 확률표본을 사용하여 왔으나, 80년대 부터 비확률 표본 사용에 관심이 높아졌다. 그 대표적인 것으로 기반근거 데이터를 들 수 있다. 이 데이터는 제한된 정보를 제공한다는 자료자체의 한계를 지니고 있으나, 자료수집이 용이하고 비용이 저렴하다는 장점을 가지고 있다. 화물수송 분야에서 선택기반 데이터를 이용한 연구는 현재까지 두 편이 발표 되어 있다. 따라서 볼 연구는 선택기반 데이터를 이용한 개별선택모형의 잠재력을 검증하는 것을 그 목적으로 하고, 네 종류의 제조품 그룹을 대상으로 기반근거 데이터를 수집하여 로짓모형을 추정하였으며, 추정결과를 이전 연구들의 결과와 비교하여 그 타당성을 검토 하였다. 추정된 결과는 통계적으로 유의하며 직관적으로 타당한 것으로 나타난다. 또한 그 결과는 문헌의 결과와도 일치하였다. 수송계획에 있어서 자료수집비용 절감의 필요성을 생각할 때 이것은 중요한 의미를 지닌다.

• Journal of Korean Society of Transportation
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• v.30 no.4
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• pp.85-94
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• 2012

Modern freight transport pursues not only the reduction of logistic costs but also aims at green logistics and efficient shipments. In order to accomplish these goals, various policies regarding the multimodal shipment and stopover to logistic facilities have widely been made. Such situation requires changes in existing methods for analyzing freight demand. However, the reality is that a reliable freight demand forecast is limited, since in the transport research field there is no robust freight demand model that can accommodate transshipments at logistic facilities. This study suggested a novel method to analyze freight demand, which can consider transshipments in multi-modal networks. Also, the applicability of this method was discussed through an example test.