• Proceeding of Spring/Autumn Annual Conference of KHA
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• 1992.11a
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• pp.45-51
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• 1992

The purpose of this study was to predict the spatial housing demand of households in Seoul with the use of residential choice probabilitics. An multinomial legit model is developed using socio-demographic and housing characteristics. SAS package was utilized to estimate this model. This study used the data obtained by the Korea Rosearch Institute for Human Settlemente in 1989. The sample size was 3941 households in Seoul.The residential choice probability varicd depending upon the residential area, head age, head age, tenure and work place. The households with students were more likely to choose kangnam are. The households without young children had higher probability to choose new town near Seoul. Prime reason of this two results were considered the chi Id education and their better housing, Kangnam area was known to be the first consideration for residential choice regardless of work place. Low level of choice probability of kangman area for future residences however, was evidenced. Prime reason of such seemingly contradicting phenomenon is suspected for higher housing prices and limited affordability of people surveyed.

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.1
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• pp.19-28
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• 2000

The purposes of this study are two folds: a) to introduce conjoint choice model to research the choice behavior of theme park users, and b) to suggest the strategies to strengthen the competitiveness of theme parks. The major four theme parks in Seoul metropolitan areas were selected as study areas. A leading polling agency was employed to select 432 respondents by probability sampling and to conduct face-to-face interview. Both alternative generating and choice set generating fractional factorial design were conducted simultaneously to meet the necessary and sufficient conditions for calibration of the conjoint choice model. Dummy coding was used to represent the attribute levels, and the alternative-specific model was calibrated. The goodness-of-fit of the model was quite satisfactory($\rho$$^2$=0.47950), and most parameters values had to expected sign and magnitude. Car was preferred transport mode to shuttle bus for visiting theme parks ; however the most ideal attribute levels only were estimated significantly. Most attribute levels of shuttle bus were estimated significantly except the Dream Land, which is the least attractive park among study areas. Simulation results showed that the shuttle bus was a mode worth providing to switch the current car dominant visiting pattern of theme parks, which will be one the effective strategies to attract more patrons, especially for potential users adjacent to parks. Several ideals were suggested for future researches, in terms of utilization of more general utility function and new base alternative, and inclusion of more salient attributes such as constraints in the model.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.209-216
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• 2003

Contingent valuation method (CVM) is a main evaluation method of nonmarket goods for which markets either do not exist at all or do exist only incompletely; an example is environmental good. A dichotomous choice approach, the most popular type of CVM in environmental economics, employs binary discrete choice models as statistical estimation models. In this paper, we propose a semiparametric dichotomous choice CVM method using local linear model of Fan and Gijbels (1996) in which probability distribution of error term is specified parametrically but latent structural function is specified nonparametrically. The computation procedures of the proposed method are illustrated with a simple design of simulations.

• Journal of the Korean Regional Science Association
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• v.11 no.1
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• pp.31-60
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• 1995

The distribution of economic activity over a mutually exclusive and exhaustive categorical industry-region matrix is modeled as a composition of two random components: the probability-like share distribution of jobs and the dynamic evolution of absolute aggregates. The former describes the individual activity location choice by comparing the predicted profitability of the current industry-region pair against that of all other alternatives based on the available information on industry-specific, region specific, or activity specific attributes. The latter describes the time evolution of macro-level aggregates using a dynamic reduced from model. With the seperation of micro choice behavior and macro dynamic aggregate constraint, the usual independence and identicality assumptions become consistent with the activity share distribution, hence multi-regional industrial migration can be represented by a set of probability evolution equations in a conservative Markovian from. We call this a Micro-Macro Composition Approach since the product of the aggregate prediction and the predicted activity share distribution gives the predicted activity distribution gives the predicted activity distribution which explicitly considers the underlying individual choice behavior. The model can be applied to interesting practical problems such as the plant location choice of multinational enterprise, the government industrial ploicy to attract international firms, and the optimal tax-transfer mix to influence activity location choice. We consider the latter as an example.

• International Journal of Human Ecology
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• v.4 no.2
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• pp.77-87
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• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

• Health Policy and Management
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• v.8 no.1
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• pp.183-202
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• 1998

This study is to investigate patient's choice of health care and the demand for Korean traditional medicine care in rural areas in 1995. It tried to evaluate the effect of out-of-pocket expenditure, travel time, and waiting time on improving care-seeking and substituting clinical medicine for pharmacy care and Korean traditional medicine care in rural areas. The statistical model of this study is conditional logit to estimate effects of choice-specific and individual-specific characteristics on the choice of type of services. This study used, as explanatory variables, average out-of-pocket payment, travel time, and waiting time of services required to use the services. The model was empirically tested using data from 1995 Korean National Health Survery. The results showed that rural Koreans responded to out-of pocket payment and travel time. Increases of out-of-pocket payment and travel time decreased the probability to choose care in rural Korea. Rural Koreans were more likely to seek care than others with low out-of-pocket payment and travel time. The probability of choosing Korean traditional medicine were higher among the members of the households with higher education level and older persons, while they were lower in the households with large family than others compared with the probabilities of choosing public health facilities. The result of this study implies that policy on use of health care in rural Korea can be focused in managing travel time and out-of-pocket payment.

• Journal of the Korean Society of Costume
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• v.58 no.7
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• pp.92-103
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• 2008

The purpose of this study was to subdivide the shoes market in Korea and to evaluate the size and competitive strength of each segment. In order to implement the purpose of this study, the data of 300 respondents were analyzed using CBC(Choice-Based Conjoint measurement) and mixture model. The part-worth utilities were then used to predict the impact of price change on the choice probability using the legit model. As a result, the mixture model showed the optimal segments number and the shoes market in Korea was divided into 4 segments. Each segment was identified by distinctive characteristics such as brands, price and demand for comfortable shoes. Also, as a result of grasping the competitive structure and the competitive strength by sub-markets, one group was sensitive to price according to each competitive situation, whereby the choice probability was greatly influenced, and the other group on the contrary. This study made it clear that discrimination between brands whose profits Increase sharply if price is lowered and brands whose profits do not increase even if price is lowered can help brand managers with their decision-making on price lowering.

• Korean Management Science Review
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• v.25 no.1
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• pp.139-147
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• 2008

Conjoint Analysis is marketers' favorite methodology for finding out how buyers make trade-offs among competing products and suppliers. Thousands of applications of conjoint analysis have been carried out over the past three decades. The conjoint analysis has been so popular as a management decision tool due to the availability of a choice simulator. A conjoint simulator enables managers to perform 'what if' question accompanying the output of a conjoint study. Traditionally the First Choice Model (FCM) has been widely used as a choice simulator. The FCM is simple to do, easy to understand. In the FCM, the probability of an alternative is zero until its value is greater than others in the set. Once its value exceeds that threshold, however, it receives 100%. The LOGIT simulation model, which is also called as "Share of Preference", has been used commonly as an alternative of the FCM. In the model part worth utilities aren't required to be positive. Besides, it doesn't require part worth utilities computed under LOGIT model. The simulator can be used based on regression, monotone regression, linear programming, and so on. However, it is not free from the Independent from Irrelevant Alternatives (IIA) problem. This paper proposes the EBA (Elimination-By-Aspects) model as a useful conjoint-like method. One advantage of the EBA model is that it models choice in terms of the actual psychological processes that might be taking place. According to EBA, when choosing from choice objects, a person chooses one of the aspects that are effective for the objects and eliminates all objects which do not have this aspect. This process continues until only one alternative remains.

• Journal of the Korean Society for Railway
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• v.12 no.5
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• pp.656-662
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• 2009

In general, the analysis of travelers' mode choice behavior is accomplished by developing the utility functions which reflect individual's preference of mode choice according to their demographic and travel characteristics. In this paper, we propose a methodology that takes the spatial effects of individuals' departure locations into account in the mode choice model. The statistical models considered here are spatial logistic regression model and conditional autoregressive model taking a spatial association parameter into account. We employed the Bayesian approach in order to obtain more reliable parameter estimates. The proposed methodology allows us to estimate mode shares by departure places even though the survey does not cover all areas.

• Current Photovoltaic Research
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• v.10 no.4
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• pp.121-132
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• 2022

The need for floating photovoltaic is being emphasized to expand renewable energy but low residents' acceptance is a major obstacle to the deployment of floating photovoltaic. Using the discrete choice experiment, this study analyzed the preferences for community-based floating photovoltaic projects and proposed a method to increase the residents' acceptance of floating photovoltaic projects. The estimates of the marginal willingness to accept (MWTA) of the distance, the coverage ratio, the landscape, the project owner (public institution), and the project owner (large company) are -0.69%p/km, 0.13%p/%p, -0.57%p, -2.95%p, -1.73%p, respectively. According to the result of simulation analysis, the residents' acceptance is significantly higher when the project is operated by a public institution, with a choice probability of 58%, than when the project is operated by a private company, with a choice probability of 29%, 12% for a large and small company, respectively. In addition, as a result of the analysis of the expected returns, the results show that the closer the distance from the residence to the power plant, the higher the expected return.