• Journal of Korea Port Economic Association
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• v.20 no.2
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• pp.151-167
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• 2004

Traditional traffic forecast has employed regression analysis or time-series analysis based on past trends of explanatory variables. However, not existing but planned port facilities do not have historical data for traffic estimation. Consequently, arbitrary traffic allocation has been subject to researcher's intuition. In this paper, container throughput at New Incheon Outer-South Port will be estimated using stated preference(SP) and sample enumeration methodology on the basis of survey data about the choice behaviors of port users in a theoretical situation. In the SP survey, shippers, freight forwarders and carriers were required to answer a choice between two alternative ports: Busan and Incheon. Although total 27 scenarios of questionnaires were constructed with 3 levels of 3 explanatory variables, each interviewee was asked to answer for just 9 scenarios chosen at random. A binary choice logit model was applied to the survey data. The elasticity of travel time is estimated to be very high, implying that building New Incheon Outer-South Port could be effective in relieving the congestion of the Kyungin corridor. The analysis result shows that increasing service level at Incheon Port would bring in the substantial diversion of container cargo in the Capital region to Incheon Port from Busan Port.

• 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.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.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.31-45
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• 1995

In recent year, 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 revealed preference data . Since SP experiments present respondent with various hypothetical alternatives, which are produced by a combination of a number of different attribute levels, and ask them to indicate a preference, it is possible to analyze travel behavior under a situation of potential environment change such as proposed alternative mode of transportation. The basic problems, however, remains that SP are not consistent with the actual travel behaviors and the research reports for stability of mode choice model using SP data has not been sufficient. Under this background, this study is to examine the characteristics of mode choice model using the SP data by the following items. $\circled1$ Analysis of factors affecting the mode choice behavior by the variance analysis of orthogonal-arrays-table $\circled2$ The reliability of SP data by transfer intention data $\circled3$ The stability of SP responses obtained from repetitive question by the comparison of model coefficient specified by each repetitive data. $\circled4$ The stability of ranking data in mode choice model For the analysis, we assumed subway operations in the Gwang-Ju , and set up a choice-set of hypothetical options based on Experimental Design Method.

• International Journal of Railway
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• v.7 no.1
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• pp.24-33
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• 2014

The Korean high-speed rail (HSR) began its commercial service in 2004. This service has been created significant changes in the system of intercity passenger travels of Korea. However, the actual ridership was approximately half of the estimated one in the planning stage. In this background, this paper presents the difference between the stated preference (SP) before the HSR service and the revealed preference (RP) after it using the intercity travel mode choice models. Several meaningful differences are found in terms of the factors affecting the travel mode choice, the estimation results of model, the monetary values of time, and elasticities. While the access/egress travel time of high-speed rail is less important than in-vehicle travel time in the SP sample, they have same weight in the RP sample. Also the RP models show that the probability of choosing HSR can be decreased by the increase of the number of vehicles in household contrary to the results from the SP models. The monetary values of travel time are relatively high and the direct and cross elasticities in response to changes in level-of-service of HSR are relatively low in the RP sample. This Korean case is expected to offer referable material for preparing high-speed rail services in other countries by showing the difference between the SP and RP before/after the actual service, identifying the importance of access/egress travel time and lower direct elasticities of HSR demand.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.985-990
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• 2005

The success of road transportation, in dominating the surface movement of freight, is now threatened by increased traffic congestion, falling average motorway speed and rising in logistics costs, oil price. Due to the necessity for an effective transport system, we need to improve domestic transport infrastructure to reduce logistics cost by shifting to rail system. To analysis the demand characteristics in advance against these hypothetical circumstances, Stated Preference, which is called SP, approaches have been adopted to analysis the shipper's mode choice behaviors as RP(Revealed Preference) approaches are not appropriate. The results also indicate that the most effective policy to divert the freight volume from road to railway is to reduce freight rates for the railway with improved reliability.

• Proceedings of the KOR-KST Conference
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• 1999.10a
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• pp.9-14
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• 1999

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.565-569
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• 2012

This study selected blind spot areas for public transportation in four metropolitan cities including Busan, Daegue, Gwangju, and Daejeon. Then this study developed a nested logit model and analyzed the changes of mode choice behaviors after adopting rapid transit system using stated preference(SP) survey. As the study results, blind spot areas have more potential public transportation demand and tendency to shift to public transportation from autos than built-up areas. This study results can be utilized to evaluate demand changes for new rapid transit system in a circular expressway and an arterial highway connecting CBD and surrounding areas. The study results also can be utilized to analyze the potential public transportation demand in the surrounding areas.

• Journal of Korean Society of Transportation
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• v.18 no.4
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• pp.19-30
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• 2000

The purpose of the Paper is to estimate values of transfer related variables on route choices of subway users in Seoul. Four attributes were estimated affecting route choices, i.e. in-vehicle time, transfer time, number of transfers and existence of escalators. Stated preference and revealed preference techniques were used to estimate these values. The values of transfer related variables can be shown by in-vehicle time equivalents. One minute of transfer is 1.5∼2 times one minute of in vehicle times one time of transfer is 10∼15 times, and the existence of escalator is 2∼8 times. Women generally show stronger impedance than men and the elder does than the younger. Working, commuting and educational trips show stronger impedance than others too.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.49-65
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• 2023

In response to the growing global concern for the environment, the international community has recently committed to achieving 'carbon neutrality.' As a result, numerous studies have been conducted on mode choice models that include carbon emissions as a variable. However, few studies have established a correlation between individual preferences and carbon emissions. In this study, a new mode of transportation named sustainable public transit (SPT), incorporating carbon-reducing transport options like electric scooters, is proposed. Analyzing the individual preferences of commuters on carbon emissions through factor analysis, a stated preference (SP) survey was conducted. A mode choice model for SPT was constructed using multinomial logit models. The results of the analysis showed that gender, income, and specific preferences, such as a passion for exploring new routes, a preference for intermodal transfers, knowledge of carbon reduction, and carbon reduction practices, significantly influence latent preferences for SPT. Therefore, this study is significant as it considers carbon emissions as an attribute variable during the construction of mode choice models and reflects the individual preference variables associated with carbon reduction.