• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.210-219
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• 2010

Consumers differ in both horizontally and vertically. Market segmentation aims to divide horizontally different (or heterogeneous) consumers into more similar (or homogeneous) small segments. A specific consumer, however, may differ in vertically. He (or she) may belong to a different market segment from another one where he (or she) belonged to before. In consumer panel data, the vertical difference can be observed by his (or her) choice among brand alternatives are changing over time. The consumer's vertical difference has been defined as 'dynamics'. In this research, we have developed a binary probit model with random-walk coefficients to capture the consumer's dynamics. With an application to a consumer panel data, we have examined how have the random-walk coefficients changed over time.

• Journal of the Korean Data and Information Science Society
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• v.22 no.6
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• pp.1017-1028
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• 2011

When it is not easy to decide the credit scoring for some loan applicants, credit evaluation is postponded and reserve to ask a specialist for further evaluation of undecided applicants. This undecided inference is one of problems that happen to most statistical models including the biostatistics and sportal statistics as well as credit evaluation area. In this work, the undecided inference is regarded as a missing data mechanism under the assumption of MNAR, and use the bivariate probit model which is one of sample selection models. Two undecided inference methods are proposed: one is to make use of characteristic variables to represent the state for decided applicants, and the other is that more accurate and additional informations are collected and apply these new variables. With an illustrated example, misclassification error rates for undecided and overall applicants are obtainded and compared according to various characteristic variables, undecided intervals, and thresholds. It is found that misclassification error rates could be reduced when the undecided interval is increased and more accurate information is put to model, since more accurate situation of decided applications are reflected in the bivariate probit model.

• Journal of Environmental Policy
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• v.6 no.1
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• pp.83-109
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• 2007

This study evaluates citizen's willingness-to-pay for the benefits from improved water quality of the Taehwa river in Ulsan, Korea, using a contingent valuation method with double-bounded dichotomous choice. The estimation results of the bivariate probit model shows the amounts of willingness-to-pay are monthly 3,458.5 Korean Won per household and yearly 14,760 million Korean Won for total households in Ulsan, Korea. These estimates are equivalent to the social values of improved water quality of the Taehwa river. This study also tests the inter-dependence between two answers, which may occur in the responses of the questions for the double-bounded dichotomous choice, and all the null hypotheses on the inter-dependence are rejected in this study.

• Environmental and Resource Economics Review
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• v.31 no.1
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• pp.1-30
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• 2022

This study is to investigate consumers' acceptance and their willingness to pay for clothes made of materials with low microplastic emissions as an alternative to synthetic fibers made of plastics by applying the contingent valuation method. A nationwide web-based survey was conducted for 1,052 respondents proportional to region, age, and gender during February 2021. More than 75% of the sample expressed intentions to purchase microplastic emission-reducing clothing instead of synthetic fiber clothing, and more than 80% of them have stated their willingness to pay for additional prices. A variation of Heckman's sample selection model was adopted to estimate factors affecting respondents' intentions to pay for additional prices, in which the probit model of intentions to purchase the clothing with alternative materials was used as a sample selection equation. While respondents were sensitive to the amounts of price increases suggested in the CV scenario, they expressed high acceptance and preferences for eco-friendly materials regardless of the microplastic emission-reducing levels. Consumers in the circular economy were willing to pay for the range of 41,000 to 51,000 won for a pair of clothing made with microplastic emission-reducing materials. In addition, as the microplastic emission-reducing rate has increased from 50% to 80%, the willingness to pay estimates were also significantly increased, ranging from 41,000~50,500 to 42,000~51,700 won.

• Journal of Technology Innovation
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• v.20 no.3
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• pp.57-91
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• 2012

This paper investigates determinants of litigation success in the two distinctive types of patent litigations, ex-parte and inter-parte cases, which are brought in the process where a filed application becomes a valid patent right. We regress winning rates of patent applicants on the characteristics of firms, trials, patent lawyer, and patent itself, using a probit model with sample selections. The paper finds that the relative suit rate of a firm, time to be sued, changes of patent agents by applicants, and multiple agents among explanatory variables affect ex-parte reexamination and in-parte post-grant patent trials differently in the point of average marginal effects. These variables lower the probability of applicant's victory in the ex-parte cases, while they raise the probability in the inter-parte trials. However, the experience that agents represent applicants is a winning rate-increasing factor both in inter-parte and ex-parte reexamination, unexpectedly. This result cannot be applied to the entire domain of the variable, since sample selection effects are reflected in the result. The number of claim increases the winning probability of the applicant in the both types of patent litigations. This study has some limitations because it ignores the information on the legal person to which a patent agent belongs, and confined agent's experience to patent filing. We leave it future studies to investigate the effects of lawsuit experience of patent agent, and those of characteristics of the law firm to which individual patent lawyer is affiliated.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.367-382
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• 2018

Prediction models for a corporate bond rating in existing studies have been developed using various models such as linear regression, ordered logit, and random forest. Financial characteristics help build prediction models that are expected to be contained in the assigning model of the bond rating agencies. However, the ranges of bond ratings in existing studies vary from 5 to 20 and the prediction models were developed with samples in which the target companies and the observation periods are different. Thus, a simple comparison of the prediction accuracies in each study cannot determine the best prediction model. In order to conduct a fair comparison, this study has collected corporate bond ratings and financial characteristics from 2013 to 2017 and applied prediction models to them. In addition, we applied the elastic-net penalty for the linear regression, the ordered logit, and the ordered probit. Our comparison shows that data-driven variable selection using the elastic-net improves prediction accuracy in each corresponding model, and that the random forest is the most appropriate model in terms of prediction accuracy, which obtains 69.6% accuracy of the exact rating prediction on average from the 5-fold cross validation.

• Korea journal of population studies
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• v.29 no.3
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• pp.1-27
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• 2006

Labor market participation and occupational status for workers majoring in(natural) science and engineering are estimated and compared with workers of other majors at three levels: employment, prestigious occupations, and good occupations. For this, we utilized 2% Public Use Sample of 2000 Korea Census. The results of two-stage probit models, which adjust sample selection bias, do not support the argument that graduates of science and engineering majors are relatively disadvantaged. Workers of engineering majors are more likely to have 'good occupations' at their early job careers, but their advantages fade away quickly as they are aging. Especially at their 40s, their probability of having 'good occupations' start to be likely lower than workers of social science majors. This may be due to low human capital accumulation rates at work places along with quickly outdated skills which are acquired in colleges.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4328-4336
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• 2011

The aim of this study is to find changes of the attributes that influence the purchase of cut roses during recent five years(2007~2011) and suggest some implications on ways to promote cut roses marketing. For this purpose, a survey was conducted through the Internet among 1,100 randomly chosen people living in Seoul, Inchon and Gyeonggi Province in 2011. A total of 1,023 valid replies were received for the analysis of the survey which was carried out by the subsidiary consulting firm. The survey panels and estimation models to analyze changes of consumers' preference attributes during recent five years are same to them of Kim, et al.(2007). That is, empirical analysis tools such as ordered probit model, multinomial logit model, and conjoint analysis were used according to Kim, et al.(2007). This paper suggests several policy implications to set up the target market of cut roses and marketing mix strategy to specify the best 4P(product, price, place and promotion).