• Environmental and Resource Economics Review
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• v.21 no.3
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• pp.465-491
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• 2012

Climate change, a result of increasing global warming, has been receiving more public attention due to its serious impact upon many industries. In this study we consider sustainable- (Green-) Growth and Green-Finance, and in particular temperature derivatives, as appropriately active responses to the world's significant climate change trends. We characterize the daily average temperatures in Seoul, South Korea with their seasonal properties and cycles of error terms. We form forecasting models and perform Monte Carlo simulations, and find that the risk-neutral values for CDD call-options and HDD put-options have risen since 1960s, which implies that the trend of temperature increase can be quantified in the financial markets. Contrary to the existing models, the Vasicek model with the explicit consideration of cycles in the error terms suggests that the significant option-values for the CDD call -options above certain exercise prices, implying that there is the possibility of explicit hedging against the considerable and stable increase in temperature.

• Proceedings of the Korea Association of Information Systems Conference
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• 2000.11a
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• pp.3101-3110
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• 2000

인터넷이 본격적으로 상거래목적으로 사용된 이후로 전자상거래 활성화의 큰 장애요인으로 작용하고 있는 것 중의 하나는 소비자 신뢰라고 할 수 있다. 전자상거래에서는 상품을 보거나 만질수도 없고, 상품을 판매하는 상점의 위치도 알기 어려우며, 인터넷이라는 가상의 공간에서 상품을 판매하고 구매하는 행위가 일어난다. 이런 특성 때문에 소비자 신뢰가 중요하다고 할 수 있다. 이 연구에서는 소비자 신뢰에 영향을 미치는 선행요인에 대한 이론적 연구 모형을 제시한다.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.298-301
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• 2000

본 논문은 금융상품을 나타내는 자료 객체로부터 분석 모형을 분리해 내고 사용자의 필요에 따라 이들을 자유롭게 통합할 수 있는 객체 지향 구조를 제안한다. 이를 위해 자료와 모형을 효과적으로 다루는 구체적 객체 지향 구성체를 제시한다. 또한, CORBA나 DCOM과 같은 분산 객체 기술을 이용하여 분산 시스템 환경에도 적용될 수 있도록 설계한다.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.579-585
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• 2006

We consider a ruin model where the surplus process is formed by a Brownian motion. If the level of surplus exceeds V, then we assume that a insurer invests an amount of S to other place. In this paper, we apply martingale methods to the surplus process and obtain the expectation of period T, time from origin to the point where the level of surplus reaches either V or 0. As a consequence, we finally derive the total and average amount of surplus during T.

• Journal of the Korea Society of Computer and Information
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• v.7 no.1
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• pp.88-93
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• 2002

In this thesis, we propose an Intelligent Agent based on CORBA technology which can exchange and share data under distributed computing environment using Agent Communication Language(ACL), Recently, due to the rapid development of network technology, the need for the database management appeared. So representative standard, CORBA have been applied and used under distributed environment. Agent applications are being developed for various fields such as electronic commerce, user interface, information retrieval. When a user searches goods, he navigates several servers on different platform until he finds desired goods. The Intelligent Agent presented in this thesis, does these tedious navigations on behalf of the user through communication between different platform.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.145-160
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• 2021

This study attempted to analyze the trade in goods effect of the Korea-ASEAN FTA by using logistics performance index, which are evaluation indicators of logistics industry workers on the logistics environment and logistics system in international trade. The World Bank's logistics performance index are six indicators: customs clearance, logistics infra, ease of shipment, logistics services, goods tracking abilities, and on-time transportation. The purpose of this study was to examine how it affects commodity trade between Korea and ASEAN states using the gravity model using panel data. Through this, it was confirmed that logistics performance index affect the increase in commodity trade.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2010.10a
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• pp.52-62
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• 2010

우리나라 손해보험 업계의 경영실적을 보면 2003년부터 2007까지 5년간 연평균 1조 1,130억원의 당기순이익이 발생하였으나 이는 투자이익에 기인한 것이고 손해보험사업 본업인 보험영업 손익에 있어서는 연평균 5,218억원의 손실을 기록하고 있다. 이와 같이 손실이 발생한 원인은 손해율 증감에 따른 보험요율의 조정미흡, 손해율상승 및 사업비 증가 등의 요인이 있으나 근본적인 요인은 해외 출수재의 불균등과 과다한 해외출재로 인한 수지차의 역조현상에 기인하고 있다. 특히 화재위험을 담보하고 있는 보험상품인 화재보험과 재산종합보험의 출재보험료는 약3,670억원으로써 전체 해외출재보험료에서 가장 높은 30.8%를 차지하고 있다. 이는 방재기술(Loss Control)의 활용미흡과 방재기술에 근간을 두고 있지 못한 보험인수 정책 즉 언더라이팅(Underwriting)기법의 낙후 때문이라고 할 수 있다. 따라서 전통적인 보험 상품인 화재보험에서 보험인수시 물건의 위험도를 측정할 수 있는 화재위험도 평가기법이 필요하고 이를 근간으로 위험을 인수하고 보유의 규모를 결정할 수 있는 체계의 구축이 필요한 실정이다. 이에 본 연구에서는 특정물건의 화재보험 인수과정에서 건물에 내재된 잠재 화재위험의 고저 또는 양 불량을 판정할 수 있는 화재위험도 평가 모형을 개발한 후 이 평가 모형에서 산출된 화재위험도보유계수를 활용하여 보유금액을 결정할 수 있는 보험인수 모형을 도출 하였다.

• The Journal of the Korea Contents Association
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• v.22 no.9
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• pp.349-359
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• 2022

At present, with the diversified development of the global economy, the trade of cultural products has become an important factor affecting the competition of comprehensive strength among countries. As a neighboring country to China, South Korea has a similar cultural development environment to China. As an important pillar of South Korea's economy, cultural product trade, its development experience has reference significance for China. This paper adopts literature research method, comparative analysis method and empirical analysis method to conduct research. The article firstly analyzes the export level of China and South Korea from the scale of the import and export of cultural products, and finds the difference between the import and export of cultural products between the two countries. Then, it compares and analyzes the insufficiency of China's cultural product trade structure and the advantage of Korea's cultural product trade structure. Finally, this paper uses the stochastic frontier gravity model to conduct empirical analysis and draws relevant conclusions about the trade potential of cultural products between China and South Korea. The research results show that: (1) the international competitiveness of cultural products trade in China and South Korea is relatively high, but the competitiveness of China's cultural products has been improved slowly; (2) compared with South Korea, China's cultural product exports are affected by trade inefficiency factors larger. (3) The improvement of government efficiency has a great effect on reducing the inefficiency of trade in China.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.155-164
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• 2012

This study aims to identify the multidimensional variables and sub-variables and study their relative weight in music recommender systems when maximizing the rating function R. To undertake the task, a optimization formula and variables for a research model were derived from the review of prior works on recommender systems, which were then used to establish the research model for an empirical test. With the research model and the actual log data of real customers obtained from an on line music provider in Korea, multiple regression analysis was conducted to induce the optimal correlation of variables in the multidimensional model. The results showed that the correlation value against the rating function R for Items was highest, followed by Social Relations, Users and Contexts. Among sub-variables, popular music from Social Relations, genre, latest music and favourite artist from Items were high in the correlation with the rating function R. Meantime, the derived multidimensional recommender systems revealed that in a comparative analysis, it outperformed two dimensions(Users, Items) and three dimensions(Users, Items and Contexts, or Users, items and Social Relations) based recommender systems in terms of adjusted $R^2$ and the correlation of all variables against the values of the rating function R.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.265-274
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• 2021

In this paper, we propose a novel recommendation model based on Doc2vec using search keywords and product details. Until now, a lot of prior studies on recommender systems have proposed collaborative filtering (CF) as the main algorithm for recommendation, which uses only structured input data such as customers' purchase history or ratings. However, the use of unstructured data like online customer review in CF may lead to better recommendation. Under this background, we propose to use search keyword data and product detail information, which are seldom used in previous studies, for product recommendation. The proposed model makes recommendation by using CF which simultaneously considers ratings, search keywords and detailed information of the products purchased by customers. To extract quantitative patterns from these unstructured data, Doc2vec is applied. As a result of the experiment, the proposed model was found to outperform the conventional recommendation model. In addition, it was confirmed that search keywords and product details had a significant effect on recommendation. This study has academic significance in that it tries to apply the customers' online behavior information to the recommendation system and that it mitigates the cold start problem, which is one of the critical limitations of CF.