• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.57-66
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• 2003

Because the Logit model easily calculates probabilities for choice alternatives and estimates parameters for explanatory variables, it is widely used as a traffic mode choice model. However, this model includes an assumption which is independently and identically distributed to the error component distribution of the mode choice utility function. This paper is a study on the estimation of the Heteroscedastic Logit Model. which mitigates this assumption. The purpose of this paper is to estimate a Logit model that more accurately reflects the mode choice behavior of passengers by resolving the homoscedasticity of the model choice utility error component. In order to do this, we introduced a scale factor that is directly related to the error component distribution of the model. This scale factor was defined so as to take into account the heteroscedasticity in the difference in travel time between using public transport and driving a car, and was used to estimate the travel time parameter. The results of the Logit Model estimation developed in this study show that Heteroscedastic Logit Models can realistically reflect the mode choice behavior of passengers, even if the difference in travel time between public and private transport remains the same as passenger travel time increases, by identifying the difference in mode choice probability of passengers for public transportation.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.811-827
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• 2010

This paper deals with a density estimation method in binary choice models that can be regarded as a statistical inverse problem. We use an orthogonal basis to estimate density function and consider the choice of an appropriate truncation parameter to reflect the model complexity and the prediction accuracy. We propose a data-dependent rule to choose the truncation parameter in the context of binary choice models. A numerical simulation is provided to illustrate the performance of the proposed method.

• Journal of the Korean Institute of Landscape Architecture
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• v.23 no.1
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• pp.141-156
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• 1995

This research is executed to find out the boundary of use by the conscious of local residents and to get the basic materials for the distribution of outdoor leisure-facilities. The map of use distribution of the outdoor leisure-facilities in a neighbourhood unit is made by applying a concept of the probabilistic contour line based on the choice model of outdoer leisure-facilities in the city of Seoul, Taegu an\ulcorner Kwangju. The results are listed as follows. 1) The use of outdoor leisure-facilities is influenced on the accessibility by the physical obstacles of streets and hills, etc. 2) The limitation of uses applying the model of choice probability are different according to the accessibility, the percentage of utilities and the arriving range based on the questionnaires which are surveyed the choice of outdoor leisure facilities of the residents of Seoul, Taegu and Kwangju. 3) The distribution of outdoor leisure facilities is decided by the limitation of use with the conscious of local residents.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10B
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• pp.900-908
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• 2006

This paper studied on the future market competitive structure among mobile multimedia services that offer a variety of multimedia services and contents through wireless networks. In the past, forecasting methods based on market data would be used popularly in telecommunications industry. However, methods must focus on not market data but customer preferences. In this reason, paper use to forecast the market competitive structure and offer firm strategies and policies using a customer choice probability model.

• Journal of Korean Society of Transportation
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• v.18 no.2
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• pp.63-71
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• 2000

One Problem of the choice Property in logit model is interpreted as the Problem of common links and common nodes in choice set. Common node Problem Plays important role in deciding the efficiency of network loading and common link problem is connected with choice Problem, both of which are to be solved to improve the logit choice model. Although much need has been pointed out for research on the topic, however, no Paper as yet considers these two factors at the same time. In the Paper we develop a new logit formulation, which is able to ease the logit Problem, widely known as the Problem of IIA(Independence of Irrelevant Alternatives). An example network is used to assess the Proposed model and compare it with other conventional models. From the results, we find out that the model is superior to others.

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.323-338
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• 2009

This study analyzes the changes in commuter's mode choice between 2002 and 2006 according to the implement of the integrated public transit system in Seoul metropolitan city. Especially this study focuses on differential changes in a transit modal choice among socioeconomic status, trip purpose and spatial characteristics of origin and destination. The probability of public transit use against automobile is modeled as a function of socioeconomic variables, spatial characteristics of origin and destination and the utility of the commuter's mode. The results from conditional logit model analyses suggest that people with lower income show the larger changes in the ratio of public transit choice between 2002-06. Also both higher density, more accessible to public transit and more diverse land uses in residence zone and in work place generally increase the ratio of public transit choice between 2002-06. Car and subway have the most strong alternative relation in commuter's mode choice. The findings give an important implication that the integrated public transit system has differential impacts on commuter's mode choice in Seoul.

• Asia Marketing Journal
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• v.15 no.3
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• pp.159-172
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• 2013

In the present study, we apply the multiple cue probability learning (MCPL) paradigm to examine consumer learning from feedback in repeated trials. This paradigm is useful in investigating consumer learning, especially learning the relationships between the overall quality and attributes. With this paradigm, we can analyze what people learn from repeated trials by using the lens model, i.e., whether it is knowledge or consistency. In addition to introducing this paradigm, we aim to demonstrate that knowledge people gain from repeated trials with feedback is robust enough to weaken one of the most often examined contextual effects, the asymmetric dominance effect. The experiment consists of learning session and a choice task and stimuli are sport rafting boats with motor engines. During the learning session, the participants are shown an option with three attributes and are asked to evaluate its overall quality and type in a number between 0 and 100. Then an expert's evaluation, a number between 0 and 100, is provided as feedback. This trial is repeated fifteen times with different sets of attributes, which comprises one learning session. Depending on the conditions, the participants do one (low) or three (high) learning sessions or do not go through any learning session (no learning). After learning session, the participants then are provided with either a core or an extended choice set to make a choice to examine if learning from feedback would weaken the asymmetric dominance effect. The experiment uses a between-subjects experimental design (2 × 3; core set vs. extended set; no vs. low vs. high learning). The results show that the participants evaluate the overall qualities more accurately with learning. They learn the true trade-off rule between attributes (increase in knowledge) and become more consistent in their evaluations. Regarding the choice task, there is a significant decrease in the percentage of choosing the target option in the extended sets with learning, which clearly demonstrates that learning decreases the magnitude of the asymmetric dominance effect. However, these results are significant only when no learning condition is compared either to low or high learning condition. There is no significant result between low and high learning conditions, which may be due to fatigue or reflect the characteristics of learning curve. The present study introduces the MCPL paradigm in examining consumer learning and demonstrates that learning from feedback increases both knowledge and consistency and weakens the asymmetric dominance effect. The latter result may suggest that the previous demonstrations of the asymmetric dominance effect are somewhat exaggerated. In a single choice setting, people do not have enough information or experience about the stimuli, which may lead them to depend mostly on the contextual structure among options. In the future, more realistic stimuli and real experts' judgments can be used to increase the external validity of study results. In addition, consumers often learn through repeated choices in real consumer settings. Therefore, what consumers learn from feedback in repeated choices would be an interesting topic to investigate.

• 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.

• Speech Sciences
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• v.11 no.4
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• pp.43-52
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• 2004

Model parameters in HMM based speech recognition systems are normally estimated using Maximum Likelihood Estimation(MLE). The MLE method is based mainly on the principle of statistical data fitting in terms of increasing the HMM likelihood. The optimality of this training criterion is conditioned on the availability of infinite amount of training data and the correct choice of model. However, in practice, neither of these conditions is satisfied. In this paper, we propose a training algorithm, MCE(Minimum Classification Error), to improve the performance of a speech recognizer detecting mispronunciation of a foreign language. During the conventional MLE(Maximum Likelihood Estimation) training, the model parameters are adjusted to increase the likelihood of the word strings corresponding to the training utterances without taking account of the probability of other possible word strings. In contrast to MLE, the MCE training scheme takes account of possible competing word hypotheses and tries to reduce the probability of incorrect hypotheses. The discriminant training method using MCE shows better recognition results than the MLE method does.

• Land and Housing Review
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• v.11 no.2
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• pp.1-14
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• 2020

The aim of this study is to empirically identify the differentiating characteristics of determinant factors on sing-person households' commuting mode choice compared to multi-person households' one in order to establish the customized police directions to decrease private car use in commuting. While the study use the 2% sample survey data on the population and housing in 2015, it employ multinomial logit models on relative choice probability of such alternative commuting modes as bus, subway or rail, and walking, rather than driving. As potential determinant factors, the study employs demographic, socio-economic, and housing and residential one for both models of single-person and multi-person households. The study finds that the behavior of commuting mode choice has distinctive difference by gender, marriage status, physical activity constraint, job type, residential period in current housing of the single-person household's workers compared to the multi-person households' ones. Based on the findings, the study deduce ten commuting policy directions customized for the single-person household.