• Proceedings of the Korea Technology Innovation Society Conference
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• 2015.11a
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• pp.430-443
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• 2015

신약개발은 국민의 건강권과 직결되며 국가 차원의 제약산업 육성을 위해 매우 중요하다. 그동안 신약개발 분야와 관련하여 다양한 연구가 수행되었지만, 신약개발 분야의 국가연구개발사업에 대한 효율성 분석은 매우 부족한 실정이다. 특히 R&D 분야는 연구개발시차, 일출효과(spill-over effect) 등으로 인해 투입과 산출의 일정한 방향성과 등비율적인 증감을 가정하는 CCR 모형이 적합하지 않다. 또한 가변규모수익을 가정하는 BCC 모형도 여유분(slack)으로 인해 의사결정단위간의 명확한 우선순위 도출이 어려운 한계점이 있다. 최근에는 R&D 분야의 특수성을 고려해서 자료포락분석 모형 중 RAM(Range Adjusted Measure) 모형을 활용한 분석방법이 제시되고 있다. RAM 모형은 가변규모수익 가정 하에 투입지향이나 산출지향처럼 방향성에 대한 사전적인 가정 없이 비효율성을 최대한 제거하는 방향으로 효율성을 측정하므로 R&D 분야의 효율성 분석에 적합하다. 특히 RAM 모형은 매우 강건한 단조성을 인해 의사결정단위 간 명확한 순위 구분도 용이하다. 따라서 본 연구에서는 자료포락분석 모형 중 RAM 모형과 토빗 회귀분석이 결합된 2단계 접근법을 활용해서 범부처전기신약개발사업을 중심으로 신약개발 분야의 국가연구개발사업들에 대한 효율성을 분석하고 주요 시사점들을 논의하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.679-687
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• 2017

This study examines financial factors affecting cash holdings of firms in the domestic capital markets. Specifically, this study focuses on regional firms with headquarters in Chungcheong province, the Republic of Korea, which features little previous research concentrating on the firms in the particular region. Three primary hypotheses were empirically tested utilizing robust econometric models, including static panel data, Tobit regression, and logistic models.Results reveal only five explanatory variables, including DSO, LIQUID, LEVERAGE, PMARGIN, and SIZE, showed statistically significant effects on the level of cash holdings among the nine variables studied. In addition two IDVs, LEVERAGE and FOS, showed significant differentiated effects between firms with headquarters in North and South Chungcheong regions. With continued debate among interested parties on the optimal level of cash reserves, the study provides a new vision for the optimal cash reserves for firms with headquarters in Chungcheong Province, where unprecedented socio-economic factors are driven.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.92-101
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• 2012

Trip demands and patterns on weekends have been changed significantly over the past decade due to the income growth and the spread of the 5-day workweek in Korea. The increased weekend trips for shopping, leisure activities, entertainment and friendship have exacerbated traffic congestion in major highways or principal arterial roads from Friday afternoon through Sunday. Therefore, it is necessary to focus on travel demand forecasts and transport policies for weekend trips by investigating specific characteristics of the trips. Previous research efforts focus on simple analysis of characteristics of weekend trips and comparison of travel characteristics between weekdays and weekends. The paper analyzes the differences between weekday and weekend trips via statistical analyses to derive multiple types of characteristics of weekend trips, and develops Tobit models to identify key factors that may affect the number of trips, using Seoul city's weekend trip survey data in 2006. The model results show that weekend trips appear differently from weekdays by household or individual characteristics. Age, residence area and type of residence affected the number of trips, regardless of the type of the day, whereas gender, occupation, income, presence of household vehicle showed different impacts on trips between weekdays and weekends.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.43-49
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• 2019

The purpose of this study is to estimate the expenditure determinants of the leisure goods consumption market. In order to achieve the research purpose, 6597 samples of household trend survey data were used. Tobit model was applied to estimate expenditure determinants. As a result of analysis, expenditure determinants for sporting goods were influenced by marital status, education level, age, number of households, housing ownership and income level. The variables influencing spending on leisure items such as mountain climbing, fishing and hunting items were influenced by gender, marital status, education level, age, number of households, housing ownership and income level. The analysis results can be used as policy data for the establishment of leisure culture. The National Statistical Office's household trend survey is a yearly survey through a nationwide survey, but despite the fact that it is reliable data, it is not possible to apply various variables such as psychological characteristics to estimate consumer expenditure determinants more concretely. Has a limit of.

• Journal of Korea Port Economic Association
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• v.37 no.3
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• pp.75-91
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• 2021

Due to increased competition in supply side to reduce operational costs, port professionals have experienced extreme pressure, which demanded academicians to develop the model for efficient port operations from the industry perspective. Among many ports in the world, U.S. ports are our primary interest to analyze in our study for its high volume of cargoes transacted in the U.S. ports. We primarily employed DEA (Data Envelopment Analysis) technique to research the productivity of U.S. ports and applied the algorithm of double bootstrapped DEA proposed by Simar & Wilson (2007) to further investigate the driving forces of the performance of U.S. port operations. The external variables employed in our study comprise onDock Rail, Channel Depth, Location, Area, Acres, ForeignCargoRatio, and TEUChange, out of which onDock Rail, Acres, ForeignCargoRatio, and TEUChange were significant. In order to evaluate the effects of methodology selection, we conducted the same analysis applying the Censored model (Tobit) and contrasted the outcomes drawn from the two different techniques. Based on the findings from this work we proposed managerial implications and concluded.

• Industry Promotion Research
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• v.9 no.1
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• pp.259-273
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• 2024

In this study, 31 provincial-level administrative regions in China from 2011 to 2021 were taken as the research objects, and the super-SBM model was used to measure the regional eco-efficiency with capital, labor, land and resource input as input variables, GDP and green coverage as the desirable outputs, and wastewater, waste gas and solid waste emissions as the undesired outputs. Tobit regression was used to analyze the effects of external environmental factors on eco-efficiency. The results showed that the average level of eco-efficiency in China was low, and the eco-efficiency in the eastern region was higher than that in other regions, and there were great differences in the western, northeast and central regions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.50-59
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• 2015

This study aimed at suggesting Willingness To Pay (WTP) for introduction of the Traffic Accident emergency Call (TAC) system by using Contingent Valuation Method (CVM) which is a general valuation method. As the method, this study suggested a WTP estimation method of the TAC system with the double-bound dichotomous choice model. In previous studies, the data are processed differently according to the type of questions and analysis models used for the calculation of willingness to pay. Therefore, we re-organized the model by the cases using the truncated data sets, and showed the difference in WTPs. The dataset was developed by more than 500 questionnaire obtained from online and offline survey with the consideration of composition ratio by age group referring housing census in 2010 to mitigate regional bias of samples. At last, this study applied various statistical methods, survival analysis, multiple regression, and Tobit model for better interpretation of the questionnaires.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.737-746
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• 2013

The Bayesian method can be applied successfully to the estimation of the censored regression model introduced by Tobin (1958). The Bayes estimates show improvements over the maximum likelihood estimate; however, the performance of the Bayesian interval estimation is questionable. In Bayesian paradigm, the prior distribution usually reflects personal beliefs about the parameters. Such subjective priors will typically yield interval estimators with poor frequentist properties; however, an objective noninformative often yields a Bayesian procedure with good frequentist properties. We examine the performance of frequentist properties of noninformative priors for the Tobit regression model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.248-258
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• 2021

The study analyzed the financial determinants of corporate R&D intensity that require more attention from academics and practitioners in the Korean capital market. Domestic small and medium enterprises (SMEs) may face with developing substitutes by making more R&D investments in scale and scope, given the unprecedented economic conditions such as the limitation of importing core components and materials from other nation(s). KOSDAQ-listed SMEs were selected as sample data, whose R&D expenditures may be less than those of large firms during the post-global financial turmoil period (2010~2018). Static panel data model was applied, along with Tobit and stepwise regression models, for examining the validity of results. Logit, probit, and complementary log-log regressions were also employed for a relative analysis. R&D expenditures in the prior year, the interaction effect between the previous R&D intensity and high-tech sector, firm size, and growth rate were significant to determine R&D intensity. Moreover, a majority of explanatory variables were found to change between the years 2011 and 2018, while time-lagged effects between the R&D intensity and growth rate exist. Results of the study are expected to be used for future research to detect optimal levels of R&D expenditures for the value maximization of SMEs.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.41-49
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• 2008

According to the demand for services. a single point contract between a user and provider spreads over the industry, and the relationship between them is a main issue. The user wants to make a deal with the contributor which can provide the effective services to the user. This study is to estimate the efficiency of global logistics industry with Data Envelopment Analysis, by nations from 2001 to 2005. Furthermore, it tries to estimate the inefficiency affected by macro factors, and proves the association between them using Tobit model. Global logistics industry has made growth both externally and internally more than doubled for the last 5years. Technical inefficiency of global logistics industry is more influenced by pure technical inefficiency than inefficiency of scale. Therefore technical efficiency can be increased by decreasing pure technical inefficiency. Through this study, it found that the logistics industry got influenced to its efficiency by high price of oil, and courier and transportation service market is formed stably. Furthermore, it advocates policy planners to consider effectiveness and clearness of policy which influence to inefficiency of logistics industry. Also, it found that labor and financial support can give critical effect.