• KDI Journal of Economic Policy
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• v.38 no.1
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• pp.23-52
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• 2016

This paper examines the impact of introducing high-speed trains on consumer welfare, taking the ensuing changes in train schedules into account. Based on the estimated demand model for travel which incorporates consumer's heterogeneous preferences for travel schedules into the standard discrete-choice model, I separately evaluate the impact from adding high-speed trains and that from changes in train schedules. The results indicate that consumers who travel between two cities connected by high-speed trains benefit from the introduction of high-speed trains, while some travelers whose choice set does not include high-speed trains face a reduced frequency of non-high-speed trains, resulting in significant losses.

• Asia pacific journal of information systems
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• v.15 no.4
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• pp.165-192
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• 2005

This study introduces how to estimate the monetary value of intellectual capital of a public research institute by incorporating a non-market valuation technique, the choice experiments(CE). CE is a survey-based environmental valuation technique that has increasingly been popular over the last decade. The members of institute E, a typical type of public research institutes in Korea, were surveyed, before the data were fit to the conditional logit and mixed logit models. The total value of the institute's intellectual capital was estimated at approximately W3,377 billion for the year 2003. The institute's human, structural and relational capitals that comprise the intellectual capital were estimated at W18.7 billion, W10.7 billion and W4.4 billion respectively, for each of the components' index values improving by 1%. The human capital was placed a higher value than the other two. The study also shows that CE is a flexible technique that enables the researcher to estimate the monetary value of the intellectual capital whatever the index values of the component capitals and to interpret model estimation results more in depth by incorporating the mixed logit, a state-of-the-art discrete choice model, than the conventional conditional logic.

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

• 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.4
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• pp.220-225
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• 1988

A class of adaptive controllers with integral action is proposed, which may riject the offset due to any load disturbance on the plant. Effective integral action and robust identification against the offset can be achieved via the zero-gain predictor. The system is improved, in this paper, to be of more generalized structure, and the detuning control weight which can cope with nonminimum-phase systems is tuned on-line. Discrete-time versions of the improved system are developed, which may be more flexible for the choice of the design parameters. The resulting control systems may also be shown to be robust to the unmodelled dynamics.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.89-102
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• 2006

The purpose of this paper is to develop a dynamic OD estimating model to overcome the limitation of depicting teal situations in dynamic simulation models based on static OD trip. To estimate dynamic OD matrix we used the hybrid discrete choice model(called the 'Demand Simulation Model'), which combines travel departure time with travel mode and travel path. Using this Demand Simulation Model, we deduced that the traveler chooses the departure time and mode simultaneously, and then choose his/her travel path over the given situation In this paper. we developed a hybrid simulation model by joining a demand simulation model and the supply simulation model (called LiCROSIM-P) which was Previously developed. We simulated the hybrid simulation model for dependent/independent networks which have two origins and one destination. The simulation results showed that AGtt(Average gap expected travel time and simulated travel time) did not converge, but average schedule delay gap converged to a stable state in transportation network consisted of multiple origins and destinations, multiple paths, freeways and some intersections controlled by signal. We present that the hybrid simulation model can estimate dynamic OD and analyze the effectiveness by changing the attributes or the traveler and networks. Thus, the hybrid simulation model can analyze the effectiveness that reflects changing departure times, travel modes and travel paths by demand management Policy, changing network facilities, traffic information supplies. and so on.

• Environmental and Resource Economics Review
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• v.15 no.4
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• pp.741-760
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• 2006

As a part of the 21st Century Frontier Projects, Korea is building a proton linear accelerator complex. Using the discrete choice conjoint analysis method, this study evaluates the complex. Multinomial logit model is employed as an econometric model and Hicks' compensating variation is adopted as a welfare measure. The results show that an average willingness-to-pay (WTP) of a would-be user measured by the compensating variation is estimated by 1.93 million Korean won per hour for the specification of the complex being built.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup1
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• pp.79-84
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• 2016

Graphic health warnings (GHW) on tobacco packages have proven to be effective in increasing quit attempts among smokers and reducing initial smoking among adolescents. This research aimed to examine the relative importance of different attributes of graphic health warnings on tobacco packages in Viet Nam. A discrete choice experimental (DCE) design was applied with a conditional logit model. In addition, a ranking method was used to list from the least to the most dreadful GHW labels. With the results from DCE model, graphic type was shown to be the most important attribute, followed by cost and coverage area of GHW. The least important attribute was position of the GHW. Among 5 graphic types (internal lung cancer image, external damaged teeth, abstract image, human suffering image and text), the image of lung cancer was found to have the strongest influence on both smokers and non-smokers. With ranking method, the image of throat cancer and heart diseases were considered the most dreadful images. GHWs should be designed with these attributes in mind, to maximise influence on purchase among both smokers and non-smokers.

• Information Systems Review
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• v.9 no.1
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• pp.67-84
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• 2007

In diffusing an information systems(IS), the provider of the IS can be more effective if they can identify user groups who can adopt the system early. By focusing on the user groups, system providers can encourage them to adopt the IS. After the early adopters adopt an IS, the diffusion of the system to other groups can be easier by early adopters' voluntary advertisement and help in adopting the IS. Instead of discrete choice methods which are usually used for this purpose, we suggest a decision tree method. Compared to discrete choice methods, this method is more accurate for prediction and can easily identify non-linear segments of groups. By testing the data of adopters of an IS in agricultural business, we show the excellence of this method in identifying target groups to focus on. This method would help system providers to diffuse their systems by starting from early adopters.

• Journal of the Korean Society of Food Culture
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• v.21 no.1
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• pp.57-64
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• 2006

The purpose of this study was to measure the pizza purchasing behavioral characteristics of respondents and importances of factors affecting pizza purchase, to estimate the effects of attributes on pizza restaurant choice, and to predict probability of selecting a particular pizza restaurant. The questionnaire consisted of two parts: The paired experimental profiles, purchasing behavior and importances of factors affecting pizza purchase. This study generated profiles of 16 hypothetical pizza restaurant based on the seven attributes. The profiles comprised 16 discrete sets of variables, each of which had two levels. For this study, researcher randomly selected 150 students of university as respondents. Twenty students did not complete the survey instrument, resulting in a final sample size of 129. All estimations were carried out using frequencies, $X^2$, independent samples t-test, phreg procedure of SAS package. The results are as follows. Some purchasing behavioral characteristics and importances of factors affecting pizza purchase were significantly different by gender. Based on the estimated models developed for male student group and female student group, the Chi-square statistics were significant at p<0.001. The parameter estimate for late delivery time with male student group was highest, and the parameter estimate for price with female student group was highest. The pizza restaurant that charged \20,000, offered 100% discount on eleventh pizza, promised to deliver pizza in 40 mins, usually delivered the pizza as promised time, offered only 1 type of pizza crust, delivered warm pizza, offered the money-back guarantee was favored by each of male student group and female student group. The results from this study suggested that there was an opportunity to increase market share and profit by improving operations so that customers receive discount and money-back guarantee simultaneously, and by reducing price, delivery time.