• Journal of Korean Society of Transportation
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• v.11 no.2
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• pp.5-26
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• 1993

In order to analyze travel mode choice behavior, behavioral models including logit model, based on revealed preference theory, have been using easily measurable variables such as individual socioeconomic characteristics and physical attributes of travel modes. But some recent attitudinal models of travel choice behavior have implied that the negligence of individual psychological variables and individual choice constraints in travel mode choice might preclude better prediction of individual travel mode choice behavior. In this context, this study was attempted to reconstruct an attitudinal model(AM), especially focused on the decision rules in travel mode choice decision making process, consistent with the conceptual framework relating individual attitude and choice constraints to choice behavior. And to evaluate the strengths of the AM to other comparative models(logit, linear-additive, conjunctive, lexicographic model) in predicting travel mode choice bebavior, an empirical study of the mode choice in work-trip to CBD in Seoul was performed. According to the results the percent of correct prediction(PCP) derived from the AM was higher than those derived from comparative models by at least 7 to 20% in predicting travel mode choice. But each model produced a different prediction accuracy depending on market segmentation by travel modal users, individual socioeconomic characteristics, transportation system characteristics, and satisfaction levels. The finding that different groups divided by a certain criterion employ different decision rules supports the necessity of developing a choice model such as the AM combining compensatory and noncompensatory decision rules, and suggests that a proposed transportation system management plan or policy may have different effects on each group.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.23-31
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• 2019

In this study, we collected data through online travel notes from January to December 2018 and analyzed the seasonal travel characteristics of individual visiting Chinese by utilizing social network analysis. The analysis showed that Seoul is a hub for Chinese travel to Korea and the main destinations for individual visiting Chinese are concentrated in Seoul, Busan, Jeju Island, Gyeongju and Gangneung, with wide differences in seasons. The research results can be used as basic data for the development of tourism courses for individual Chinese tourists to Korea, provision of tourism services and optimization of tourism facility layout. Future research can consider continuing to use network travel notes to study the tourist destination and the mode of transportation between tourist nodes, which can provide reference for the development of tourist market and the planning and design of tourist traffic.

• Ocean and Polar Research
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• v.30 no.2
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• pp.141-148
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• 2008

This paper aims at estimating consumer surplus for recreational sea fishing in Tongyeong coastal area using individual travel cost method. A Poisson model (PM), a negative binomial model (NBM), a truncated Poisson model (TPM), and a truncated negative binomial model (TNBM) are applied for individual travel cost method in order to account characteristics of count data (non-negative discrete data.) The survey was conducted for 462 inshore anglers using personal interview method in Tongyeong during July and October 2007. Respondents were asked about how often they do fishing, travel costs, catch, income, and so on. Because of over-dispersion problem in PM and TPM, NBM and TNBM were considered to be more appropriate statistically. All parameters estimated are statistically significant and theoretically valid. As the results based on TNBM, consumer surplus per trip was estimated to be 183,486 won, total consumer surplus per person and per year 3,399,658 won, and the marginal effect of consumer surplus on % changes in catch rate is 185,372 won.

• The Journal of Industrial Distribution & Business
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• v.11 no.1
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• pp.29-38
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• 2020

Purpose: Understanding which product types of overseas travel (free independent travel vs. package travel) consumers will choose is one of the key issues of marketing and consumer behavior in travel agency management. Prior studies on overseas travel type preferences mainly focused on comparing regional differences (e.g., Asian vs. Westerner, or Korean vs. Australian, or Korean vs. Japanese, or American, French, Italian vs. Japanese) influencing the choice of overseas travel type. Another researchers focused on comparing cultural differences (e.g., individualism vs. collectivism, or individualistic culture vs. collectivistic culture), subcultural difference (e.g., acculturation; Koreans living in Republic of Korea vs. Koreans living in Australia), travel lifestyle, and socio-demographics (e.g., age, gender, income level, education level, marital status, occupation etc.). However, there are few studies that identify individual psychological differences (i.e., individual psychological differences within the same culture) influencing the choice of overseas travel type. Self-construal is a psychological factors that greatly influences choice behavior. The purpose of this study was to examine the role of self-construal as an antecedent variable influencing choice of overseas travel product type. Research design, data and methodology: To achieve the purpose of this study, the questionnaire survey method was used. Self-construal items composed of independent self-construal items and interdependent self-construal items. Product types of overseas travel were free independent travel (FIT) type versus package travel type. In this study, the correlation coefficient between independent self-construal and interdependent self-construal was nonsignificant. It meant that the relationship between independent self-construal and interdependent self-construal was orthogonal. Therefore it was analyzed that independent self-construal and interdependent self-construal separately. Reliability analysis, factor analysis, and logistic regression analysis (controlling gender and age) was used as the data analysis method. Results: According to the results of this study, the stronger independent self-construal, the more preference for the free independent travel type rather than package travel, and the stronger interdependent self-construal, the more preference for the package travel type rather than free independent travel. Conclusions: Self-construal is an antecedent variable influencing the choice of travel type. Travel agencies must consider the consumer's self-construal (independent self-construal vs. interdependent self-construal) before planning and designing overseas travel products.

• 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.

• Ocean and Polar Research
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• v.39 no.1
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• pp.51-59
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• 2017

The purpose of this paper is to estimate the economic value of beaches which are the major part of the East Sea Coast. ITCM (Individual Travel Cost Method) is applied to estimate the economic value of its beaches using Poisson, negative binomial, truncated Poisson and truncated negative binomial models. The consumer surplus during length of stay per capita is 214,088 won in beaches overall on the East Sea Coast, 206,398 won in Gangwon-do beaches and 271,171 won in Gyeongbuk/Ulsan beaches. Annual total economic value of its beaches considering the number of visitors at beaches is 6,269 billion won (3,970 billion won in Kangwondo beaches, 2,299 billion won in Kyungbuk/Ulsan beaches).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.1
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• pp.56-73
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• 2019

Probe-based systems have been gaining popularity in advanced traveler information systems. However, the high possibility of providing inaccurate travel-time information due to the inherent time-lag phenomenon is still an important issue to be resolved. To mitigate the time-lag problem, different prediction techniques have been applied, but the techniques are generally regarded as less effective for travel times with high variability. For this reason, current 5-min aggregated data have been commonly used for real-time travel-time provision on highways with high travel-time fluctuation. However, the 5-min aggregation interval itself can further increase the time-lags in the real-time travel-time information equivalent to 5 minutes. In this study, a new scheme that uses both individual probe and 5-min aggregated travel times is suggested to provide reliable real-time travel-time information. The scheme utilizes individual probe data under congested conditions and 5-min aggregated data under uncongested conditions, respectively. As a result of an evaluation with field data, the proposed scheme showed the best performance, with a maximum reduction in travel-time error of 18%.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.153-169
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• 2022

With the extension of the average life span and the rapid aging of the population, defining elderly population as a single group is difficult as the physical, economic and social conditions of individual have become different. Therefore, policies that take into account the characteristics of each group are required. The purpose of this study is to classify individual travel types and to analyze the characteristics of each travel type, based on individual public transportation trajectory data as known as smart card data. Among the four classified types, the long-distance low-frequency stay type and the short-range medium-frequency mobile type show external activity traffic characteristics for retirement leisure, while the long-distance high-frequency stay type and the long-distance high-frequency mobile group include regular commuting. Traffic variability and residence areas of stay were identified in terms of each classified travel type. The results of this study provide the important suggestions for establishing a transportation policy that takes into account the characteristics of each type of elderly population in Seoul.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.32-48
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• 2023

Autonomous driving technology is shaping the future of personalized travel, encouraging personalized travel, and traffic impact could be influenced by individualized travel behavior during the transition of driving entity from human to machine. In order to evaluate traffic impact, it is necessary to estimate the total number of trips based on an understanding of individual travel characteristics. The Activity-based model(ABM), which allows for the reflection of individual travel characteristics, deals with all travel sequences of an individual. Understanding the relationship between travel and travel must be important for assessing traffic impact using ABM. However, the ABM has a limitation in the data hunger model. It is difficult to adjust in the actual demand forecasting. Therefore, we utilized a Tour-based model that can explain the relationship between travels based on household travel survey data instead. After that, vehicle registration and population data were used for correction. The result showed that, compared to the KTDB one, the traffic generation exhibited a 13% increase in total trips and approximately 9% reduction in working trips, valid within an acceptable margin of error. As a result, it can be used as a generation correction method based on Tour, which can reflect individual travel characteristics, prior to building an activity-based model to predict demand due to the introduction of autonomous vehicles in terms of road operation, which is the ultimate goal of this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.1-16
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• 2022

Recently, e-scooters have been attracting attention as eco-friendly modes of transportation in cities due to an increasing interest in the environment. Accordingly, various studies on usage behavior are being conducted, but studies that reflect individual travel attitudes are insufficient. Therefore, this study surveyed commuters in Seoul and analyzed respondents' traveling attitudes through factor analysis. It also built a binary logistic regression model for the intention to use shared e-scooters to determine how individual travel behaviors are affected. In particular, the model results showed that age, the main mode of transportation (car), walking time to the bus stop, and four travel attitude variables (disutility of travel, preference to self-drive, internet/smartphone friendliness, and willingness to pay extra money for services) significantly affected the intention to use shared e-scooters. This study is expected to be used as basic data, with aspect to travel behavior, for the efficient operation and use of shared e-scooters in the future.