• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.49-63
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• 2001

The pattern of urban transport activity has two major components: the movement of people and the movement of goods. Roads in urban areas carry large number of trucks laden with goods that support urban economy and lifestyle. Therefore urban goods movement plays a vital role, but at the same time, urban goods movement are an important source of congestion, and a major contributor to the adverse environmental and social impacts of urban transport. In addition, the demand for goods movement is growing at a faster rate than personal travel in many cities, due to changes in industry logistics and consumer purchasing patterns. As a result, the significance of urban freight activity is increasing in terms of both its role in urban economy and its adverse impacts on urban amenity. This study is focused on the role and involvement scope of metropolitan government in urban logistics aimed at increasing its efficiency and reducing its negative impacts. The major suggestions of this study are (a) development of a measure of urban goods movement activity, (b) evaluation of data requirements and availability, (c) dialogue between the public sector and private sector, and (d) the role of metropolitan government.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.73-81
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• 2009

While various factors in passenger and freight demand analysis affect on destination choice, a key factor, in general. is an attractiveness measure by size variable (e.g., population. employment etc) in destination zone. In order to measure the attractiveness, some empirical studies suggested that disaggregate gravity model are more suitable than aggregate gravity model. This study proposes that truck travelers trip diary data among Korean commodity flow data could be used to estimate the behaviors of incorporating trip departure time, activity duration and attractiveness in destination. As a result, the main findings of size and distance variables coincide with the conventional gravity model having a positive effect of population variable and a negative effect of distance variable. Due to disaggregate gravity modeling, the unique findings of this study reports that small trucks are more likely to choose short distance and early morning, morning peak and afternoon peak departure time choice. On the other hand, large trucks are more likely to choose long distance and night time departure time choice.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.31-41
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• 2010

The objective of this paper is to evaluate production efficiency of the commercial road freight transportation industry using quarterly actual data by individual truck drivers from January 2005 to September 2009. In addition, this study analyzes various impact factors that influence production efficiency, including regulatory factors (e.g., entrust management system and multi-level transactions). For this purpose, this study uses data envelopment analysis and a truncated Tobit model. As a result, production efficiency of the general freight sector is higher than those of the other two sectors. Also, production efficiency in the steel goods sector ranks the highest; meanwhile, production efficiency in the oil goods sector ranks the lowest. In particular, production efficiency indicators of the commercial road freight transportation industry fluctuate with time by a small margin, and have an upward tendency on the whole. Finally, some policy implications are given to promote production efficiency of the commercial road freight transportation industry.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.152-166
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• 2022

This study analyzed the causal relationship among operating characteristics of commercial freight vehicles, dangerous driving behaviors, and traffic accident risk. The study applied the existing accident cause and prevention theory to arrive at this relationship. Data related to working characteristics of driver, driving experience, driving ability, driving psychology, vehicle characteristics (size), dangerous driving behavior, and traffic accidents were collected from 303 commercial freight vehicle drivers. Working characteristics and dangerous driving behavior data are based on the driver's digital driving record. The traffic accident data is based on the insurance accident data reflecting actual traffic accidents. First, a structural equation model was built and verified using the model fitness index. Then, the developed model was used to analyze the causal relationship between multiple independent and dependent variables simultaneously. Four dangerous driving behaviors (sudden deceleration, sudden acceleration, sudden passing, and sudden stop) were found to be highly related to traffic accidents. The results further indicate that it is necessary to establish a safety management policy and intensive management for small-sized freight vehicles, drivers with insufficient driving ability, and drivers with dangerous driving behaviors. Such policy and management are expected to reduce traffic accidents effectively.

• Journal of Korea Port Economic Association
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• v.29 no.2
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• pp.159-171
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• 2013

This paper aims to analyse the relative efficiency of logistics facilities and suggest the policy alternatives for exploring and activating them. This study also divides the logistics facilities into airport terminals, logistics complexes, container terminals, and trucking freight terminals. For this purpose, the CCR-DEA as well as the BCC-DEA techniques are employed to show which part explains the primary cause of inefficiencies of each DMU(Decision Making Unit). The empirical results indicate that the efficiency of logistics complex is the lowest of all, while freight trucking terminal has the highest efficiency. This study also reveals that operation inefficiency is greater than scale inefficiency in most of DMUs, showing that much more effort be done for alleviating the cost resulting from irrational management.

• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.463-491
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• 2005

• Transportation Technology and Policy
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• v.10 no.3
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• pp.63-68
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• 2013

• Korean Architects
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• s.617
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• pp.56-61
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• 2020

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.119-137
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• 2022

This paper aims to confirm the necessity of the consignment system in Korea's trucking market for the purpose of analyzing the difference in perception between the transportation company and the consignment owner to provide a basis for continuous development of the cargo transportation business. A survey was conducted on the current status of the domestic transportation market with transportation companies and consignment owners, and the perceptions between the two were compared and analyzed. Overall, satisfaction with the consignment system was in the order of transportation companies handling supplies, transportation companies that did not pay supplies, consignment owners belonging to supply companies, and consignment orders belonging to non-volume companies. Similar results were obtained in individual questions. In order for transport companies and consignment owners to coexist and develop in the freight car transport market, it will be necessary to prepare a strategy to increase the satisfaction of consignment owners belonging to transport companies that do not handle relatively low-satisfaction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.755-761
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• 2006

Though freight origin and destination data is essential for analysing transport investment and planning logistics facilities, the study on the establishment of the freight origin and destination data is very rare. The purpose of this study is to introduce a method on weight and expansion of sample freight data focusing on the Seoul metropolitan area. In particular, this study suggests the weight and expansion method which consider truck and commodity tonnage together. This paper also discuss the origin and destination trips in Seoul metropolitan area. This paper will contribute to establish more reliable freight origin and destination data.