• Journal of the Korean Society for Railway
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• v.12 no.2
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• pp.302-308
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• 2009

This paper presents a comprehensive analysis of intercity rail passengers' and travel patterns based on the 2001 Seoul-Busan rail passengers' Travel Survey. Results representing personal characteristics such as age and income seem to affect on destination the income was not seen to be a critical effect on destination choice. The variables such as travel time, transfer status, and date for travel seem to be and recreation activity. However, the destination choice would be relationship between Seoul and all four destination cities. The insights gained of an activity-based rail travel demand model.

• Journal of Korean Society of Transportation
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• v.10 no.3
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• pp.21-42
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• 1992

As for the travel demand analysis of the past, forcasting has been conducted by the use of revealed preference(RP) informations about actual or observed choices made by individuals. Forcasting method using RP data needs implicit assumptions that there will be no remarkable changes in existing transport conditions. However in case of occuring the great changes in existing conditions or adding a new choice-set of hypothetical options, it is very difficult to predict future travel demand. Fortunately in recent years, especially in the mode choice analysis, it has been perceived that the importance of individual performance data using stated preference(SP) experiments as well as RP data. But the research reports has not been reported sufficiently from models estimated using SP data. Under this background, we analyze the factors affecting the mode choice behavior as a fundamental study against the modelling task with SP choice data. For this analysis, we assumed subway operations in the secondary cities where there are no subway lines until now, and set up a choice-set of hypothetical options based on Experimental Design Method.

• Journal of Korean Society of Transportation
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• v.12 no.4
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• pp.131-151
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• 1994

An investigation is given to a behavioral analysis of automobile users applying congestion toll theory for the purpose of maintaining the efficiency of transportation system. A case study is performed for the city of Seoul, where modal split behavior of automobile user groups is analysed in various level of congestion toll. Automobile users are grouped with respect to their income levels and work shift times. Automobile user behavior is then explained against the field data. A Logit-type model is applied for modal split changes through the application of congestion toll. It is found in the case study that the users in the monthly income bracket of 1.0~1.5 million won is the most predictable group whose work travel time begins 7:00~9:00 a.m. It is also found in the study that 1,000~1,500 won of congestion toll whould reduce the auto use as much as 5%.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.75-84
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• 2008

In 2002, the 5-day workweek policy was effective in Korea. As we have expected, the 5-day workweek policy has changed people's travel behavior during weekdays and weekends. Several studies have been done to understand these changes and impacts on transportation systems. However, these studies have only focused on travel pattern changes without considering spatial factors. Said in another way, although individual travel pattern changes are usually investigated, indices adopted cannot describe travel pattern changes in a proper way due to lack of the spatial distribution measure. This study aims to analyze travel change since the 5-day work week policy in effect using a new index (i.e. Travel Vector Index) developed in this study, which can explain travel pattern changes in terms of magnitude and spatial point of views. The new index uses a GIS technology and TCS (Toll Collection System) databases in Korea. The results in this study show that the index is very useful and reliable to measure the travel patterns changes. They are applied to TCS data set and the results show that the 5-day workweek policy significantly affects on travel behaviors.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.4
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• pp.540-552
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• 2011

Freight travel pattern has been less studied comparing with the field of passenger travel. Nonetheless, the importance of the freight travel has been increasing in urban travel sector, and the research needs on the freight travel demand hence is increasing. The current paper aims to identify, by tons of freight trucks and cargos, the characteristics of mean travel pattern, efficiency or performance, and the characteristics of freight trip chain regarding destination location, destination type and freight type. The study analyzed the nation-wide data of freight travel behavior survey. This study intended to set the starting framework of decision-making principle in freight travel, which has already been popular in passenger travel study. Findings suggest that those characteristics are clearly distinguished among trucks and cargos of different sizes of tons. The results are expected to provide important insight to the development of relevant transportation policy measures.

• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.301-315
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• 2022

Purpose - The main objective of this study was to investigate tourists behavior by applying protection motivation theory and health belief model during COVID-19 pandemic. Specifically, the study examined how risk perception of COVID-19 affects tourists' protection motivation and travel avoidance intention. Design/methodology/approach - The empirical data was collected by self-administered questionnaires to obtain perception and behavior regarding COVID-19 pandemic situation. A total of 486 questionnaires were used for data analysis and SEM analysis was applied in order to examine seven hypotheses. Findings-The results showed that COVID-19 risk perception is a significant antecedent of threat appraisal, coping appraisal, and cue to action (H1, H2, H6). Moreover, protection motivation is affected by threat appraisal and coping appraisal (H3, H4) and influences on travel avoidance intention (H5). However, cue to action does not affect protection motivation (H7). Research implications or Originality - This study provides insightful implications for tourism industry practitioners who will prepare the post-corona field and the results enrich knowledge of the tourist behavior during pandemic situation.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.259-260
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• 2023

The rapid urbanization and modernization observed in countries like Myanmar have led to significant concerns regarding traffic congestion, especially in urban areas. This study focuses on the analysis and revitalization of urban transport in selected areas of Myanmar. The core of urban transportation planning lies in travel forecasting, which employs models to predict future traffic patterns and guide decisions related to road capacity, transit services, and land use policies. Travel demand modeling involves a series of mathematical models that simulate traveler behavior and decision-making within a transportation system, including highways, transit options, and policies. The paper offers an overview of the traditional four-step transportation modeling system, utilizing a simplified transport network in the context of Mandalay City, Myanmar.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.1-16
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• 2018

Changes in the life style might vary trip purposes, ultimately leading to the change in the travel behavior. Therefore, this study analyzed the factors affecting travel time change by using the time use survey data in Seoul, surveyed by the Statistics Korea in 1999~2014. We developed multiple linear regression models for travel time, considering individual, household and time-related variables as independent variables. The models were separately estimated weekday and weekend. the model results show that the household, individual, and time related variables have an significant effect on the travel time. In addition, travel time is more influenced by individual characteristics thn household ones. Each activity time positively affects the travel time, indicating that travel is derived demand. The variable that have the greatest influence on the travel time is the activity time for leisure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.63-75
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• 2018

A Service Area plays an important role in preventing accidents in advance by creating a space for long distance drivers or drowsy drivers to rest. Therefore, proper positioning of the expressway service area is essential, and it is important to analyze accurate demand forecasting and user travel behavior. Thus, this study analysis travel behavior and developed odel of the probability of using the service area by using the DSRC data collected by the RSE on the highway. According to the analysis, the usage behavior of highway service areas was most frequently when travel time was 90 minutes or more on weekdays and 70 minutes or more on weekends. The utilization rate of the service area estimated from the probability model of use of the rest area in this study was 1 % to 2 % error. The results of this study are meaningful in analyzing the behavior of the use of rest areas using the structured data and can be used as a differentiated strategy for selecting the location of rest areas and enhancing the service level of users.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.147-157
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• 2013

This study developed the transit transfer mode choice model aimed Daegu transit users using multinomial logit model. Dependent variables of estimating multinomial logit model were transit transfer modes such as bus to bus, bus to subway, subway to subway, bus to others, and subway to others, and explanatory variables which affect transit transfer mode choice were sex, age, occupation, handicap, transfer area, purpose of travel and travel time. Also probability regarding explanatory variables was estimated using multinomial logit model and limit marginal analysis was carried out according to explanatory variables(cost, time). In the results, indicating goodness of fit is very reasonable as ${\rho}^2$=0.354. According to the result of marginal analysis for the selection of probability, when travel time is increased, users of bus to bus and bus to subway prefer to use subway to subway. Furthermore users of bus to bus and bus to subway prefer to use bus to others and subway to others when travel cost is increased in the result of marginal analysis for the selection of probability.