• Korea journal of population studies
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• v.33 no.1
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• pp.1-25
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• 2010

This study looks into travel behavior differences by sex, gender role and economic status. Source for analysis in this study is from Time Use Survey conducted by Korea National Statistical Office in 2004. The sample considered of 3,122 women's time diaries and 2,678 men's, whose age range from 20-59. The results of the study show that married women, women with child under age 6 and unemployed women have less travel time quantity, travel during the daytime and use mass transportation than men and single women. However single women and working women, especially working women having high income level, show more similar patterns of travel behavior with men's which are quite unvarying regardless of marital, parental and economic status.

• Journal of KIISE
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• v.42 no.3
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• pp.295-306
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• 2015

MOnCa2 is a framework for building intelligent smartphone applications based on smartphone sensors and ontology reasoning. In previous studies, MOnCa determined and inferred user situations based on sensor values represented by ontology instances. When this approach is applied, recognizing user space information or objects in user surroundings is possible, whereas determining the user's physical context (travel behavior, travel destination) is impossible. In this paper, MOnCa2 is used to build recognition models for travel behavior and routes using smartphone sensors to analyze the user's physical context, infer basic context regarding the user's travel behavior and routes by adapting these models, and generate high-level context by applying ontology reasoning to the basic context for creating intelligent applications. This paper is focused on approaches that are able to recognize the user's travel behavior using smartphone accelerometers, predict personal routes and destinations using GPS signals, and infer high-level context by applying realization.

• Journal of Applied Tourism Food and Beverage Management and Research
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• v.10
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• pp.139-158
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• 1999

This study is concerned with analysis of user satisfaction for travel behavior. It is aimed at investigating the socioeconomic characteristics, motivation, and use pattern of the visitors at tour. For tourists' perception and preference analysis, multi-dimensional scaling was used. It is left that this type of marketing analysis of tourism and travel offers great potentional for those concerned with the developement and management of tourist vacation areas. First, the study demanstrated clearly that different tourist and portential visitors to a tourist area seek different benefit bundles from their vacation in a particular tourist areas. Second, it demonstrated that a benefit segmentation approach to tourism and travel would be the most effective that the demographic segmentation approach usually pursued in the tourism and travel industry. Form a methodological viewpoint, it has demonstrated an application of multidimensional scaling techniques to marketing in an important industry.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.63-72
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• 2002

We applied 3-D balancing technique to estimate nationwide travel demand using travel behavior of Toll Collecting System data, socio-economic data in the region, and the data of several organizations connected with travel demand estimation. The results from this study were validated by the indices of RMSE(Root Mean Square Error), TLFD(Trip Length Frequency Distribution). TCS based inter-city average travel to measure of reliability and adequacy of estimated travel demand. Finally, 3-D technique seems to reflect more travel behavior of TCS OD than 2-D technique, but we cannot assert that 3-D technique superior to 2-D technique.

• Journal of the Korean Institute of Landscape Architecture
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• v.32 no.5
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• pp.1-10
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• 2004

This study applied the leisure constraints and negotiation concept to the travel context, especially for traveling in national parks. More specifically, it tries to identify how constraints and negotiation impact a person's travel behavior. The population of this study is the people who intend to visit the national parks for their summer vacations. The data was collected through the panel study, which surveyed the same set of people before and after their trip. Among 527 samples, 39.7％ traveled what they planned without any changes. 24.7％ did not travel or postponed their trip, and 35.7％ enjoyed their vacation but with changes of destination, time or travel periods. These results support that people may use negotiation strategies to overcome their constraints in a travel context. However, there were no statistically significant differences in the impact of constraints on travel behavior among the three groups. The results also confirm that people have to overcome intra-, inter-, and structural constraints for visiting the national parks. Thus, the findings of the study suggest that the concepts of leisure constraints and negotiation is applicable to the travel contexts. Because of its exploratory characteristics, several limitations and cautions were raised.

• Journal of Korean Society of Transportation
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• v.20 no.6
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• pp.129-140
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• 2002

This paper develops a dynamic structural equation model, which captures relationships among socio-demographics, activity participation(i.e., time use) and travel behavior in consideration with time variation effects. The data used in developing the model are two waves(the year 1991 and 1992) from Puget Sound Transportation Panel (PSTP). which is surveyed in Puget Sound Region in United States. The PSTP is widely used in transportation behavior analysis and includes various information of traveler's socio-economic, travel patterns, and activity participation. In the model, we use 10 endogenous variables including activity participations and travel behaviors and 10 exogenous variables composed of time variant and invariant traveler's socio-demographic variables. The empirical model shows that strong relationships exist not only between socio-demographics and travel behavior, but between waves. We also confirm needs of panel data set to identify and understand time variation effects and travel behaviors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.207-218
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• 2023

Jeju Island is a major area generates origin-destination trips, accounting for about 90 % of domestic air transportation, and popular tourist destination visited by more than 10 million domestic and foreign tourists annually. Travel behavior patterns of tourists in Jeju Island have great meaning for not only Jeju Island, but also the inland aviation, tourism, mobility industry. This study presented passenger travel behavior in Jeju Island based on a survey including foreign visitors and residents as well as domestic visitors. In particular, the survey was conducted in early 2020 prior to the COVID-19 pandemic, it is expected to be a major preliminary study for changes in tourist travel and air travel in Jeju Island before and after COVID-19.

• Journal of KIBIM
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• v.9 no.4
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• pp.75-83
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• 2019

Recent data development has made it possible to analyze each individual's daily commuting by using transportation card transaction. This research utilizes about 1 million observations from the subway line no.7 of Seoul metropolitan transportation data. By using such a massive dataset, the authors try to identify daily travel behavior of morning commute and its possible relationship between subway usage and socio-economic factors. There are 4 main types of users and their travel behavior, and top 15 stations with the most users for arrival and departure are selected. Accordingly, 15 stations have distinctive characteristics including population density and the number of businesses around stations. To identify this fact, the 4 most populated stations are selected and their socio-economic factors are examined. According to the analysis, the most departure stations are generally surrounded by hihgly populated residential areas, whereas the most arrival stations are stood within the job concentrated districts.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.49-58
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• 2004

The first and perhaps the most critical and perhaps the most important step in the process of predicting future traffic volume in a region (Zone) is to estimate the number of trips generated in from each traffic analysis zone. Most trip generation models for urban transportation planning, and highway in Korea are regression models. In Korea the category analysis has not been tried for last decades since the proper data such as the household travel behavior data have not been collected. Recently, the comprehensive household travel behavior survey such as ${\ulcorner}$1996 The Household Travel Behavior Survey${\lrcorner}$, ${\ulcorner}$2002 The Household Travel Behavior Survey${\lrcorner}$ has been done. In this paper, the cross-classification tables of Seoul Metropolitan Area including the City of Seoul and Kyonggi Province are estimated by the category analysis. The tables are compared with regression models and ${\ulcorner}$2002 The Household Travel Behavior Survey${\lrcorner}$ data in terms of predictive capabilities in Seoul Metropolitan Area. Improvement strategies for trip generation forecast in Seoul Metropolitan Area are proposed.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.145-154
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• 2003

Multilevel and Multivariate Structural Equation Mpdel is applied to handle the hierarchical nature of the data and explain complex relationship among socioeconomic factors of individuals and household, activity participation, and travel behavior using Puset Sound Transportation Panel data. From analysis, variations of individual activity participation and travel behavior can be divided into two categories : Within-household variation and Between-households variation. Empirical results show that the interdependency index(p) of variables for household members within a household is between 0.13 and 0.33 indicating high interdependency. These results suggest that Multilevel and Multivariate SEM approach is an appropriate modeling methodology and gives additional information for activity participation and travel behavior. Also most of personal and household characteristics influence on activity participation and travel behavior within a household as well as between households.