• 응용통계연구
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• 제29권5호
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• pp.987-998
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• 2016

자동차 보험은 치열한 시장경쟁과 금융당국의 요율 규제로 가격 조정에 합리적인 적용 방식이 요구되는 대표적인 보험상품이다. 특히 고령화 사회로 인한 인구변화와 가격경쟁으로 인한 요율 세분화는 보험료 결정에 주요한 요인으로 작용하게 된다. 따라서 본 논문에서는 여러 가지 요율 요소 중 연령에 대한 분포 추정을 통해 가격 최적화 방안을 제시하고자 한다. 미래 분포를 추정하는 방식으로 고객의 연령이동, 신규유입, 고객이탈 3가지 요인에 대한 최적화 방안을 적용함으로써 합리적인 연령 분포를 추정하여 가격 조정 과정에 반영하고자 한다. 기존 연령 분포를 적용한 보험료와 미래 연령 분포를 추정하여 적용한 보험료를 수지 불균등 원칙에 적용하여 위험도 추정에 대한 적정성을 비교 분석하는 것이 목적이다. 보험료 인상 또는 인하 문제와는 별개로 인구변화에 대한 적정 분포를 추정함으로써 가입자의 분포 변화로 인한 결손 또는 초과 이득이 발생하지 않는 적정 보험료 추정 방식을 제안하고자 한다.

• 조명전기설비학회논문지
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• 제21권9호
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• pp.81-86
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• 2007

Electric utility companies have the responsibility of providing good electricity for their customers. They have introduced the DAS(Distribution Automation System) to automate the power distribution networks. DAS engineers require state-of-the-art applications, such as a way to actively manage the distribution system and gain economic benefits from a flexible DAS architectural design. The existing DAS is not capable of handling these needs. It requires operator intervention whenever feeder overloading is detected while operator error could cause the feeder overload area to be extended. It also utilizes a closed architecture and it is therefore difficult to meet the system migration and future enhancement requirements. This paper represents a web based, platform-independent, flexible DAS architectural design and active database application. Recent advanced Internet technologies are fully utilized in this new DAS architecture allowing it to meet the system migration and future enhancement requirements. By using an active database, the DAS can minimize the feeder overloading area in the distribution system without operator intervention, thereby minimizing mistakes due to operator error.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1998년도 The Korea Society for Simulation 98 춘계학술대회 논문집
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• pp.101-105
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• 1998

A large system predictor, which can perform prediction of sales trend in a huge number of distribution centers, is presented using neural predictive model. There are 20,000 number of distribution centers, and each distribution center need to forecast future demand in order to establish a reasonable inventory policy. Therefore, the number of forecasting models corresponds to the number of distribution centers, which is not possible to estimate that kind of huge number of accurate models in ERP (Enterprise Resource Planning)module. Multilayer neural net as universal approximation is employed for fitting the prediction model. In order to improve prediction accuracy, a sequential simulation procedure is performed to get appropriate network structure and also to improve forecasting accuracy. The proposed simulation procedure includes neural structure identification and virtual predictive model generation. The predictive model generation consists of generating virtual signals and estimating predictive model. The virtual predictive model plays a key role in tuning the real model by absorbing the real model errors. The complement approach, based on real and virtual model, could forecast the future demands of various distribution centers.

• Journal of Ecology and Environment
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• 제38권1호
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• pp.15-23
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• 2015

This study was conducted in an effort to provide important clues pertaining to the conservation and restoration of Aporia crataegi by identifying the spatial distribution characteristics of the current habitats, prospective habitats, and future habitats of A. crataegi in accordance with climate changes. To determine the distribution of A. crataegi, data from a total of 36 collecting points throughout South Korea, North Korea, China, Japan, Mongolia, and Russia are used. The spatial distributions of the data were examined through MaxEnt modeling. The distribution probability rates exceeded 75% at 18 locations among the 36 species occurrence locations, with Gangwon province showing the highest distribution probability in South Korea. The precision of the MaxEnt model was remarkably high, with an AUC value of 0.982. The variables that affect the potential distribution of A. crataegi by more than 10% are the degree of temperature seasonality, the amount of precipitation in the warmest quarter, the annual mean temperature, and the amount of precipitation in the driest month, in that order of importance. It was found that the future potential distribution area of A. crataegi continuously moves northward over time up to 2070s. In addition, the area of the potential distribution showing a habitable probability rate that exceeds 75% in northeast Asia was $28,492km^2$, where the area of potential distribution in the north part of Korean peninsula was $20.404km^2$ in size. Thus, it is anticipated that the most important future habitats of A. crataegi in the northeast Asia will be North and South Hamgyeong provinces and Ryanggang province near Mt. Baekdoosan in the northern area of the Korean peninsula.

• 한국환경복원기술학회지
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• 제18권3호
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• pp.51-64
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• 2015

Climate change will make significant impact on species distribution in forest. Pinus koraiensis which is commonly called as Korean Pine is normally distributed in frigid zones. Climate change which causes severe heat could affect distribution of Korean pine. Therefore, this study predicted the distribution of Korean Pine and the suitable habitat area with consideration on uncertainty by applying climate change scenarios on an ensemble model. First of all, a site index was considered when selecting present and absent points and a stratified method was used to select the points. Secondly, environmental and climate variables were chosen by literature review and then confirmed with experts. Those variables were used as input data of BIOMOD2. Thirdly, the present distribution model was made. The result was validated with ROC. Lastly, RCP scenarios were applied on the models to create the future distribution model. As a results, each individual model shows quite big differences in the results but generally most models and ensemble models estimated that the suitable habitat area would be decreased in midterm future(40s) as well as long term future(90s).

• 유통과학연구
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• 제20권4호
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• pp.95-100
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• 2022

Purpose: This study aimed to investigate whether distribution and service companies maintained their accounting information quality and provided reliable information despite the economic changes occurring after the outbreak of the COVID-19 pandemic in Korea. The distribution industry has enjoyed increased demand as many companies expanded their untact distribution channels, including to online sales. However, as the pandemic drags on, their future prospects remain uncertain. Research design, data, and methodology: In this study, we define 2018-2019 as the "pre COVID-19 period" and 2020 as the "post COVID-19 period." An empirical analysis was performed using a regression model that includes POST, the independent variable, indicating the post COVID-19 period, and discretionary accruals(DA), a proxy for earnings management, as a dependent variable. Results: The analysis shows that the coefficient of POST is significantly positive (+) for the dependent variable DA. This finding suggests that distribution and service companies engaged in more earnings management during the post COVID-19 period than during the pre COVID-19 period, indicating their awareness of the uncertainty of future business performance as the pandemic persists. An additional analysis confirmed that smaller companies with fewer stakeholders and higher information asymmetry tend to engage more in earnings management than larger companies.

• 유통과학연구
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• 제22권6호
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• pp.107-114
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• 2024

Purpose: The current research investigates historical and future trends of tourist distribution channels in the tourism services business. The research examines historical patterns, current shifts, and new technologies in electricity distribution to offer insight into the distribution dynamics and advice for companies and regulators. Research design, data and methodology: The research in this case specifically employed the PRISMA approach when it comes to the data collection and research methodology. (PRISMA). The process is specifically made up of four steps, such as (1) Identification of Relevant Studies, (2) Screening and Selection Procedures, (3) Data Synthesis and Analysis, and (4) Reporting of Findings. Results: The fast-changing technology offers all opportunities to innovate the sector of tourism services. These upcoming technologies are not just reconstructing the way customers interact and operate but they are also creating room for development. Besides "the utilization of new technologies such as artificial intelligence, augmented reality, virtual reality, and blockchain, the current state of tourism distribution channels also implies some other possible consequences. Conclusions: These research results show that we should not be reluctant about adopting new technologies, we should expand direct booking systems, promote eco-friendly tourism, and use data analytics in order to provide personalized experiences.

• 농업과학연구
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• 제38권2호
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• pp.219-225
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• 2011

Changes in biota, species distribution range shift and catastrophic climate influence due to recent global warming have been observed during the last century. Since global warming affects various sectors, such as agriculture and vegetation, it is important to predict more accurate impact of future climate change. The purpose of this study is to examine the observed distribution of Abeliophyllum distichum in the Korean peninsula. For this purpose, two period (present and future) climate data were used. Mean data between 1950 and 2000, were used as the present value and the year 2050 and 2080 data from A1B senario in IPCC SRES were used for the future value. Potential habitation is analyzed by MaxEnt(Maximum Entropy model), and Abeliophyllum distichum's coordinates data were used as a dependent variable and independent variables are composed of environmental data such as BioClim, altitude, aspect and slope. The result of six types GCM mean calculation, the potential habitability decreased by 40-60% of the average existing distribution. The methodogies and results of this research can be applicable to the climate changing adaptation stratiegies for the biodiversity conservation.

• 유통과학연구
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• 제21권5호
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• pp.31-41
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• 2023

Purpose: Electric vehicle (EV) technology started in 2015 in Thailand. The Thai Government has indicated that 30% of all cars produced in Thailand by 2025 will be EVs. Using EVs in Thailand will reduce road pollution and increase energy efficiency, especially in major cities. Hence, the adoption of EVs in the country has been promoted. This study pointed out that social influence, facilitating conditions, perceived enjoyment, environmental concern, attitude, and perceived behavioral control are key factors affecting the behavioral intention to adopt EVs among logistic and distribution firms in Thailand. Research design, data, and methodology: 500 top management, middle management and purchasing managers of logistic and distribution firms in Thailand are surveyed. The study employed judgmental, convenience, and snowball sampling. Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) are the main statistical tools for data analysis. Results: The results show that all determinants impact customers' willingness to adopt EVs, except perceived enjoyment and environmental control. Conclusions: The study proposes to promote the incentives by decreasing electricity prices and endorsing EVs purchase to accelerate the adoption of EVs in Thailand. Therefore, future policies should focus on behavioral intention toward EVs amongst logistic and distribution firms for enhancing the future of mobility in Thailand.

• 유통과학연구
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• 제20권4호
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• pp.77-83
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• 2022

Purpose: This study aims to find the impact of international trade cooperation and distribution on foreign direct investment (FDI). The study also tests the impact of lag variables of trade cooperation and distribution on FDI in the future. Research design, data, and methodology: Autoregressive Distributed Lag model is applied to analyze the impact of chosen variables such as total trade (TRADE), trade openness (OPEN), the exchange rate (EXR), inflation (INF), and gross domestic growth (GDP) on FDI. Quarterly data is collected from Vietnam General Statistic Office, Vietnam General Department of Customs, International Monetary Fund, and The World Bank from 2006 to 2020. Stata 14 software is used to analyze the regression and test variables. Results: The findings indicate that TRADE, OPEN, INF, GDP, and their lags affect both positively and negatively on FDI in different periods. While OPEN still expresses an unclear impact on FDI. Moreover, this study proves that the FDI of a nation is influenced by international cooperation. Conclusions: This study indicates the importance of international trade cooperation and distribution in not only attracting foreign investment sources but also developing the economy. Findings are necessary bases for governments or authorities in signing international trade agreements in the future.