• Journal of Korean Society of Transportation
• /
• v.7 no.1
• /
• pp.35-42
• /
• 1989

The multinomial logit model has been applied for various choice problems. Among others, the joint destination mode choice, the mode choice and the route choice are the three major modeling topics for korean transportation planners. This paper examines with real world data (the Olympic road and its competing two major arterials) the usefulness of a Logit route choice model. Quites surpisingly, it is found that the multinomial route choice behavioral model calibrated for this study based on (0,1) individula data base can not provide a good estimate for O-D trips less than 6㎞. 400data points and 3case studies might not be sufficient for a sound conclusion. It is, however, believed from a series of similar studies conducted by the authors that the route choice behavior is more sensitive (more demand elastic with respect to travel time changes) than the mode choice and the shorter trip, the more sensitive. The travel time parameters for destination choice models are usually smalle than the travel time parameters for mode choice models and these parameters (for mode choice models) turn our smaller than the travel time parameters for route choice models from this study. Table 2 in this paper shows parameter changes for three different markets and Table 3 shows the modeling errors when the estimated individual probabilities are aggregated into a route level.

• Journal of Korean Society of Transportation
• /
• v.13 no.4
• /
• pp.79-103
• /
• 1995

The elasticity of a model is considered most important. Without showing the proper elasticity any model cannot provide useful information for decision making. This paper demonstrates a macro model which can generate dynamic transport informations every 15 minutes. Without the Wardrop principles and the monotonicity assumptions for the link travel time and link volume relationship, the basic elements of this new modeling approache are composed of link density simulation, stochastic incremental route choice, departure time choice, destination choice and mode choice. The elasticity of the proposed model is examined based on elasticity equations and simulation results. Also the transferability from a mega city like Seoul to a big city like Daejon is demonstrated for the choice model. The issues centering around the dynamic relations among density(k), speed(u), and flow rate(v) are also discussed for the modeling of highly congested situations.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.23 no.3
• /
• pp.59-68
• /
• 1995

This paper intends to identify recreation destination choice process, in particular, considering need/motive theory, recreation opportunity spectrum, information integration theory, and to review critically the status of development of the various modeling approaches. Two attempts are then made to explain consumers' choice begavior of theme park and national park, respectively, applying conjoint model and discrete choice experiment model. Three theme parks and three national parks were selected as study areas, resolution Ⅲ designs were constructed, and data was collected by in-personal interviews on the study areas. The results illustrated the part-worth utilities and the relative importance of the attributes of theme park and national park. In addition, further research directions were discussed.

• Industrial Engineering and Management Systems
• /
• v.15 no.4
• /
• pp.324-334
• /
• 2016

Manufacturers and retailers are interested in how prices, promotions, discounts and other marketing variables can influence the sales and shares of the products that they produce or sell. Therefore, many models have been developed to predict the brand share. Since the customer choice models are usually used to predict the market share, here we use hybrid model of Probabilistic Neural Network and Artificial Bee colony Algorithm (PNN-ABC) that we have introduced to model consumer choice to predict brand share. The evaluation process is carried out using the same data set that we have used for modeling individual consumer choices in a retail coffee market. Then, to show good performance of this model we compare it with Artificial Neural Network with one hidden layer, Artificial Neural Network with two hidden layer, Artificial Neural Network trained with genetic algorithms (ANN-GA), and Probabilistic Neural Network. The evaluated results show that the offered model is outperforms better than other previous models, so it can be use as an effective tool for modeling consumer choice and predicting market share.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.8
• /
• pp.465-473
• /
• 2021

This study is the application of a choice experiment to assess Mekong Delta urban households' preferences and motivations for ecosystem conservation in the U Minh forest. The study applied a choice modeling approach to estimate the economic values of the proposed ecosystem conservation program in the U Minh forest by accessing urban consumer preferences and their willingness to pay for the project. Discrete choice experimental data was collected from 450 residents in the cities of the Vietnamese Mekong Delta. The multinomial logit model was employed to identify consumer's stated preferences for the environmental and sustainability attributes of the conservation project. The results showed that Mekong Delta urban residents paid much attention to the proposed project to protect and develop the U Minh forest. In addition, the results showed that higher education, income, and knowledge of the U Minh forest revealed a higher likelihood of selecting the project, while the older residents would select the status quo more than the younger ones. The study also proved that the effect of participation had a strong impact on the willingness to pay for the project. The findings could be useful for policymakers to take action to raise resident's awareness and willingness to pay for the U Minh forest project.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.7
• /
• pp.4580-4587
• /
• 2014

This study provides an improved transportation mode choice models applicable to the Busan-Ulsan Metropolitan area by scrutinizing previous study results developed using the multinomial logit model. Although the previous model has an appropriate modeling structure in terms of the sign of coefficient estimates and goodness-of-fit, the model ignores the total number of trips and traffic congestion condition between the two zones and partially reflects zone-specific variables and choice set. Therefore, this study considered all of these modeling faults by re-constructing the representative utility functions. The modeling results show that travelers in Busan-Ulsan metropolitan area tend to choose their mode using mode-specific characteristics rather than the classical travel time and/or cost variables.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.6
• /
• pp.157-167
• /
• 2023

The use of big data for transportation often involves using data that includes personal information, such as the driver's driving routes and coordinates. This study explores the creation of a route choice prediction model using a large dataset from mobile navigation apps using federated learning. This privacy-focused method used distributed computing and individual device usage. This study established preprocessing and analysis methods for driver data that can be used in route choice modeling and compared the performance and characteristics of widely used learning methods with federated learning methods. The performance of the model through federated learning did not show significantly superior results compared to previous models, but there was no substantial difference in the prediction accuracy. In conclusion, federated learning-based prediction models can be utilized appropriately in areas sensitive to privacy without requiring relatively high predictive accuracy, such as a driver's preferred route choice.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2010.04a
• /
• pp.359-361
• /
• 2010

This research is thing about location choice of solar power generation equipment to increase efficiency of solar power generation equipment. In the case of current solar power generation equipment, location of large scale solar power generation equipment facilities choice or, have localized in small scale equipment by individual. This research uses various climatic elements of small scale area for efficient location choice of solar power generation facilities and quantity of solar radiation did back-tracking.

• Journal of the Korean Institute of Navigation
• /
• v.24 no.1
• /
• pp.35-45
• /
• 2000

Recently, in the shipping companies have been employing prudently in order to prevent from sea accidents occurred by human factors. Also the students of merchant marine universities are choosing prudently the shipping companies when taking a job. But many qualitative and quantitative factors are considered in decision making for the employment and the choice of a company. FSM(Fuzzy Structural Modeling) has been widely used in modeling the system composed of such qualitative and quantitative factor. In this paper, a case study is discussed for the analysis of the consciousness of the employment of shining companies and students' choice of such company in maritime university using FSM. Also this paper proposed the planes for educating and recruitment guiding the student in maritime university.

• Journal of The Korean Association For Science Education
• /
• v.23 no.5
• /
• pp.517-530
• /
• 2003

The purpose of this study is to find out a model to explain the process of students' science-related career choice by identifying the causal relationships between science career choice and related factors. Important factors of science-related career choice were identified through factor analysis. 'Perception about career related to science', 'preference for science learning' and 'participation in science related activity' were three main factors of science-related career choice. A questionnaire was developed to know the factors of students' science-related career choice, and so as to make it possible to be analysed by structural equation modeling. The subject were 947 grade 6, 9, and 11 students in Seoul. Numbers of boys and girls in each grade was almost same. According to the structural equation modeling, 4 corrected models were obtained. In all 4 corrected models, 'perception about career related to science' had direct influence, and 'preference for science learning' and 'participation in science related activity' had indirect influence on science-related career choice. In the most fitting model. 'perception about career related to science' had an effect on science-related career choice with standardized total effect coefficient 1.03(direct effect 0.82, indirect effect 0.21). 'Preference for science learning', which influence 'participation in science related activity', had an effect on science-related career choice with standardized indirect effect coefficient 0.65. 'Participation in science related activity', which influence 'perception about career related to science'. had an effect on science-related career choice with standardized indirect effect coefficient 0.79. The implication to school science education is that it is most effective to raise the 'perception about career related to science' in order to make more students choose science related career. It is also effective to have more students participate in science related activity and enhance the preference for science learning. To explain the process of science related career choice more fully, it is necessary to build a more comprehensive model containing more factors influencing science-related career choice. It is necessary to test and complement the structural equation model by enlarging the subject to science high school students and science related college students.