• Journal of the Korean Regional Science Association
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• v.38 no.4
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• pp.75-91
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• 2022

With the recent increase in interest in climate change issues, the use of bicycles is complementing public transportation and attracting attention as one of the eco-friendly means of transportation. Daejeon Metropolitan City has been operating Tashu, a public bicycle, since 2008. This study empirically analyzed the spatial characteristics that affect the use of public bicycles by grasping the current status and characteristics of public bicycles and applying spatial econometrics analysis, an analysis model that considers the spatial dependence of spatial data. In addition, a comparative analysis was performed by deriving the results of analyzing six models in terms of rental, return, peak time, non-peak time, weekday, and weekend based on the spatial error model identified as the optimal spatial econometrics model. The analysis model results showed that significant spatial characteristics differed according to the type of public bicycle use. In general, the use of public bicycles was high in areas with a high proportion of young people, a high number of public transportation users, good access to universities and rivers, and relatively low land use mix, and high proportion of apartments. These results indicated that public bicycles are used for commuting purposes on weekdays and leisure purposes on weekends, and if the convenience of using bicycles is improved, the use of public bicycles can be further increased.

• Environmental and Resource Economics Review
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• v.33 no.1
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• pp.1-32
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• 2024

The emissions trading system stands as a pivotal climate policy in Korea, incentivizing abatement equivalent to 87% of total emissions (as of 2021). As the system likely has a far-reaching impact, it is crucial to understand how the real economic activity, energy sector, as well as environment would be influenced by its implementation. Employing a macroeconometric model, this paper is the first study analyzing the effects of the Korean emissions trading policy. It interconnects the Korean Standard Industrial Classification (Economy), Energy Balance (Energy), and National Inventory Report (Environment), enhancing its real-world explanatory power. We find that a 50% increase in emission permit price over four years results in a decrease in greenhouse gas emissions (-0.043%) and downward shifts in key macroeconomic variables, including real GDP (-0.058%), private consumption (-0.003%), and investment (-0.301%). The price increase in emission permit is deemed crucial for achieving greenhouse gas reduction targets. To mitigate transition risk associated with price shocks, revenue recycling using auction could ensure the sustainability of the economy. This study confirms the comparative advantage of expanded current transfers expenditure over corporate tax reduction, particularly from an economic growth perspective.

• Journal of Korean Society of Transportation
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• v.23 no.5 s.83
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• pp.65-71
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• 2005

Area type is often used in freight demand analysis and logistics planning models. For example, in freight transportation planning. area type variable is most often commonly used in freight generation (attraction) model. Yet a reliable, forecastable and measurable definition or area type is generally not documented. In fact, there is little literature on the subject of predicting area type in the context of freight planning models. This can be troublesome when applying models to long-range logistics planning where significant changes in population and employment result in changes in the general character of an area. Through the use of Discriminant Model, GIS (Geographic Information System) analysis and Delphi methods, this paper presents the successful exploration for a quantifiable means of determining area type.

• Journal of the Korean Geographical Society
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• v.51 no.2
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• pp.219-233
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• 2016

In social science fields, statistical models are used almost exclusively for causal explanation, and explanatory modeling has been a mainstream until now. In contrast, predictive modeling has been rare in the fields. Hence, we focus on constructing the predictive non-parametric model, instead of the explanatory model. Gangnam-gu, Seoul was chosen as a study area and we collected single-family house sales data sold between 2011 and 2014. We applied non-parametric models proposed in machine learning area including generalized additive model(GAM), random forest, multivariate adaptive regression splines(MARS) and support vector machines(SVM). Models developed recently such as MARS and SVM were found to be superior in predictive power for house price estimation. Finally, spatial autocorrelation was accounted for in the non-parametric models additionally, and the result showed that their predictive power was enhanced further. We hope that this study will prompt methodology for property price estimation to be extended from traditional parametric models into non-parametric ones.

• Proceedings of the Korean Society for Information Management Conference
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• 1999.08a
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• pp.95-98
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• 1999

본 연구의 목적은 양질의 웹사이트를 선별하기 위한 평가 기준을 수립하고 평가 항목에 계량적인 평가 척도를 적용한 평가 모형을 제시하는 데 있다. 문헌연구 및 예비실험을 통해 보편적이고 객관적으로 적용될 수 있다고 판단된 평가 항목을 선정하여 내용, 디자인, 접근의 용이성 범주로 구분, 국내 웹사이트 평가실험에 사용하였다. 평가실험은 객관적 평가와 주관적 평가를 사용하였으며, 이를 토대로 산출된 각 품질 평가 지수에 근거하여 유용한 웹사이트를 선정하는 단계를 제시하였다.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.970-973
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• 2007

정보보호의 중요성에 대한 인식은 매우 높아졌으나 정보보호에 대한 투자는 인식수준만큼 확대되지 않고 있다. 이는 정보보호 투자는 기업의 정보이용환경에 많은 변화를 가져오지만 투자효과에 대한 세부적 분석과 투자대상이 명확하지 않고, 그 효과를 측정하기 어려운 것이 주요원인이다. 본 연구에서는 기업과 조직에 적합한 정보보호 투자를 위한 선행 과제로 비용 및 효과요인을 분석하고자 한다. 이를 통해 기업에 적합한 정보보호 투자 대안을 선정하기 위한 연구모형을 제시한다. 기업의 정보보호 투자 의사결정시 계량화하기 어려운 기준들을 이용해서 합리적인 투자 대안을 선정하는데 활용될 수 있을 것이다.

• Korean Management Science Review
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• v.11 no.2
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• pp.99-131
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• 1994

This paper shows the direction in which logistics modellers should make their effort by examining the gap between desirable characteristics which logistics decision models should possess and deficiencies from which existing models suffer. For this purpose, we(1) categorized logistics models into facility planning, inventory management and transportation/delivery planning models, (2) carried out a wide survey of theoretical and industry models within each category and (3) assessed recent development of integrated logistics models.

• Journal of Applied Reliability
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• v.2 no.1
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• pp.33-45
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• 2002

We investigate into some problems related to Corruption Perception Index(CPI). Delphi method is a popular for obtaining CPI; it is a mean of systematically collecting and progressively refining information provided by a group of selected experts in order to obtaining the weight values of questionnaires. However, Delphi method hold low aspect, to some extent, for it is solely dependent upon the judgment of a few professionals. In this paper, we propose the measurement model for X in LISREL as alternative for gaining the weight values of questionnaires. We use the 1999 Seoul ACI(Anti- Corruption Index) for empirical study.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.117-124
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• 2015

As the acceptance of statistical analysis has been increased because of Big Data, the needs for an advanced second generation of statistical analysis method like Structural Equation Model are also increasing. This study suggests how R-Program, as open software, can be utilized when Partial Least Square Model, one of the SEMs, is applied to statistical analysis. R is a free software as a part of GNU projects as well as a powerful and useful tool for statistical analysis including Big Data. The study utilized R and SmartPLS, a representative statistical package of PLS-SEM, and analyzed internal consistency reliability, convergent validity, and discriminant validity of the measurement model. The study also analyzed path coefficients and moderator effects of the structural model and compared the results, respectively. The results indicated that R showed the same results with SmartPLS on the measurement model and the structural model. Therefore, the study confirmed that R could be a powerful tool that is alternative to a commercial statistical package in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.1
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• pp.1-8
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• 2009

This paper aims mainly to reinterpretate Optimal Bus Scheduling Model by applying System Dynamics Perspective. Traditionally, the study regarding Optimal Bus Scheduling Model stems on the linear relationshp. However, this paper attempted to convert linear relationship based Optimal Bus Scheduling Model to causal loop perspective based Model. In result, the paper present Casual Loop Diagram for Optimal Bus Scheduling Model. Furthermore, the paper also ran a simulation based on Stock & Flow Diagram for Optimal Bus Scheduling Model. The outcome was not much different from the linear relationship based Model due to the similarity of the equation applied on two models.