• 한국전자거래학회지
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• 제20권4호
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• pp.19-39
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• 2015

사물인터넷(Internet of Things)은 기존에 인간들이 사용하고 있는 사물(Things)에 인터넷을 접목하여 인간의 삶에 효율성과 편리성을 제공하는 기술이다. 사물 인터넷을 통해 새로운 비즈니스가 창출될 수 있다. 특별히 사물간의, 사물과 인간간의 연결을 통하여 생성되는 데이터를 기반으로 다양한 서비스를 제공할 수 있기 때문에 사물인터넷은 인간의 삶에 많은 변화를 가져다 줄 것으로 본다. 본 연구에서는 정성적 연구방법인 전문가 인터뷰 기법과 정량적인 방법으로 국내 신문기사들을 텍스트 네트워크 방법을 적용하여 국내외 주요 기업들의 사물인터넷과 관련된 전략 및 기술 동향을 분석하였다. 또한, 본 연구에서는 사물인터넷의 성공적 실용화를 위해 고려해야 할 사항들을 기술, 비즈니스 등의 측면에서 논의해보고자 한다.

• 한국항해학회지
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• 제23권1호
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• pp.85-97
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• 1999

Vessels chartering has contributed to developing Korean shipping industry over the past three decades. Vessels chartered by shipping companies have been employed in cross trades as well as in the Korean foreign trade to achieve their business strategy. Meanwhile, some problems such as speculation, sales-oriented expansion with poor margin, poor forecasting capacity, over excessive competition in cross trades among Korean owners, and lack of speciality in decision-making, have played adverse roles in promoting chartering business in Korea. There(ore, this paper aims to discuss motives for vessel chartering business and its significance in the Korean shipping industry and to identify problems in the business.

• 무역학회지
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• 제46권5호
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• pp.83-98
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• 2021

This study aims to examine the effects of international trade in intermediate input on the implications of international business cycle properties in Korea. To do this, I have extended standard one goods New Keynesian international business cycle model to incorporate the role of intermediate inputs. After constructing the DSGE model, I have analysed the impulse response function and varian decomposition results. The results show that the model could introduce a new channel, that is, "cost channel" like Eyquem and Kamber (2014). In other words, the model has changed the dynamics of aggregate inflation by the cost channel. When the trade in intermediate goods increase, which is measured by openness of foreign input, the volatility of output, consumption and inflation increase two or three times. However, the model itself fails to explain the full account of cycle behavior of historical data, but the results imply that the trade in intermediate input assumption can help to improve the forecasting ability of international business cycle models.

• KIEE International Transactions on Power Engineering
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• 제5A권3호
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• pp.300-302
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• 2005

We employ a new technique to account for extreme values when using the generalized autoregressive conditionally heteroskedastic (GARCH) methodology to forecast day-ahead electricity prices in New York City.

• 유통과학연구
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• 제12권2호
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• pp.59-71
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• 2014

Purpose - In recent years, many firms have attempted various approaches to cope with the continual increase of aviation transportation. The previous research into freight charge forecasting models has focused on regression analyses using a few influence factors to calculate the future price. However, these approaches have limitations that make them difficult to apply into practice: They cannot respond promptly to small price changes and their predictive power is relatively low. Therefore, the current study proposes a freight charge-forecasting model using time series data instead a regression approach. The main purposes of this study can thus be summarized as follows. First, a proper model for freight charge using the autoregressive integrated moving average (ARIMA) model, which is mainly used for time series forecast, is presented. Second, a modified ARIMA model for freight charge prediction and the standard process of determining freight charge based on the model is presented. Third, a straightforward freight charge prediction model for practitioners to apply and utilize is presented. Research design, data, and methodology - To develop a new freight charge model, this study proposes the ARIMAC(p,q) model, which applies time difference constantly to address the correlation coefficient (autocorrelation function and partial autocorrelation function) problem as it appears in the ARIMA(p,q) model and materialize an error-adjusted ARIMAC(p,q). Cargo Account Settlement Systems (CASS) data from the International Air Transport Association (IATA) are used to predict the air freight charge. In the modeling, freight charge data for 72 months (from January 2006 to December 2011) are used for the training set, and a prediction interval of 23 months (from January 2012 to November 2013) is used for the validation set. The freight charge from November 2012 to November 2013 is predicted for three routes - Los Angeles, Miami, and Vienna - and the accuracy of the prediction interval is analyzed using mean absolute percentage error (MAPE). Results - The result of the proposed model shows better accuracy of prediction because the MAPE of the error-adjusted ARIMAC model is 10% and the MAPE of ARIMAC is 11.2% for the L.A. route. For the Miami route, the proposed model also shows slightly better accuracy in that the MAPE of the error-adjusted ARIMAC model is 3.5%, while that of ARIMAC is 3.7%. However, for the Vienna route, the accuracy of ARIMAC is better because the MAPE of ARIMAC is 14.5% and the MAPE of the error-adjusted ARIMAC model is 15.7%. Conclusions - The accuracy of the error-adjusted ARIMAC model appears better when a route's freight charge variance is large, and the accuracy of ARIMA is better when the freight charge variance is small or has a trend of ascent or descent. From the results, it can be concluded that the ARIMAC model, which uses moving averages, has less predictive power for small price changes, while the error-adjusted ARIMAC model, which uses error correction, has the advantage of being able to respond to price changes quickly.

• 한국전자거래학회지
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• 제24권2호
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• pp.199-216
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• 2019

공공 SW 시장은 국내 시장 특성상 중소 SW 기업에게는 상대적으로 중요한 시장이다. 이에 정부는 공공정보화 시장에서의 중소기업 지원을 위해 공공 SW 사업 수요예보 조사제도를 시행하고 있으나 아직 중소기업이나, 발주기관 입장에서의 편의성은 부족한 실정이다. 또한 SW 사업의 발주 이후의 집행정보를 관리하는 SW 사업정보저장소 제도가 별도로 운영되고 있으나, 이는 중소 SW 기업보다는 발주기관을 위한 제도에 머무르고 있다. 본 연구는 두 제도가 가지고 있는 문제점과 개선 가능성에 대한 분석을 통해 사용자 편의성을 높이고 SW 사업정보의 활용도를 확대할 수 있는 시스템의 설계 방안을 제안하고자 한다. 이를 위하여 먼저 발주기관, 정책당국, 공공 SW 사업자, 조사기관의 4대 이해당사자를 식별하였고, 요구사항들을 분석하였다. SW 사업정보 관리체계 분석을 위해 2단계 수요예보 주기, SW 프로젝트 관리 주기, 그리고 SW 시스템 수명주기의 분석 체계를 제안하고, 이들 사이에서 SW 사업정보를 식별, 연계할 수 있도록 단일식별자(UID) 개념도 제안하였다. 그 결과 SW 사업 수요예보 및 사업진행 단계에 따른 사업정보의 통합적 관리체계를 설명할 수 있는 '시스템 수명주기 기반의 SW 사업정보 관리체계 참조모델'을 도출하였으며, 이를 실행할 수 있도록 이해당사자들이 사이의 개선된 프로세스를 설계하였다. 이를 통하여 공공 SW 사업정보의 통합적인 관리가 가능하게 될 것으로 기대된다.

• The Journal of Asian Finance, Economics and Business
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• 제7권6호
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• pp.19-27
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• 2020

This research investigates the determinants of investment capital size in Vietnam's small and medium-sized firms. The study employs a sample of 458 small and medium-sized enterprises in the country. The study is based on data collects in the areas of Hanoi, Bac Can, Buon Ma Thuot and Pleiku Provinces at time series data of October 2019. This study also identifies the factors that affect the size of investment capital in medium and small-sized enterprises in Vietnam. Data are processed via STATA 14.0 and SPSS 20.0 software. The research results indicate that (1) business lines, (2) import and export business, (3) type of business registration, (4) business location, (5) operating time, and (6) the percentage of the organization's capital contribution are factors that impact on the size of the investment capital of the business. Business line and business location have negative impacts on investment capital size. The operating time, the percentage of the organization's capital contribution, import and export business, and the type of business registration have positive impacts on investment capital size. In addition, the findings of this study also suggest that the operation time has the highest impact on investment capital size of the small and medium-sized firms in Vietnam.

• 한국산업정보학회논문지
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• 제25권2호
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• pp.57-72
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• 2020

철광석의 가격은 여러 국가와 기업들의 수요와 공급에 따라서 높은 변동성이 지속되고 있다. 이러한 비즈니스 환경에서 철광석의 가격을 예측하는 것은 중요해졌다. 본 연구는 머신러닝 기법을 이용하여 철광석이 거래되는 시점으로부터 한 달 전에 철광석 거래가격을 미리 예측하는 모형을 개발하고자 하였다. 예측 모형은 시계열 데이터를 활용한 예측 방법론으로 많이 활용되고 있는 시차분포 모형과 다층신경망 (Multi-layer perceptron), 순환신경망 (Recurrent neural network), 그리고 장단기 기억 네트워크 (Long short-term memory)와 같은 딥 러닝(Deep Learning) 모형을 사용하였다. 측정지표를 통해 개별 모형을 비교한 결과에 따르면, LSTM 모형이 예측 오차가 가장 낮은 것으로 나타났다. 또한, 앙상블 기법을 적용한 모형들을 비교한 결과, 시차분포와 LSTM의 앙상블 모형이 예측오차가 가장 낮은 것으로 나타났다.

• 수산경영론집
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• 제38권2호
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• pp.41-62
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• 2007

The Fish aquacultural Industry has been developed rapidly since 1990s in Korea. The total production of fish aquaculture was 5,000ton in the beginning of 1990s, but it was an excess of 80,000ton in 2005. In the beginning of 1990s, the percentage of flatfish yield was 80% of the fish aquaculture in the respect of production. And it has been maintained 50% level in 2005. In this point of view, flatfish aquaculture played the role of leader in the development of fish aquaculture. Rapid increasing of production was not only caused to decreasing in price basically, but also it threatened the management of producer into insecure price for aquacultural flatfish. Therefore, it needs the policy for stabilizing in price, but it is difficult to choose the method because the basic study was not accomplished plentifully. This study analyzed about price structure of aquacultural flatfish. A period of analysis was from January 2000 to December 2005, and a data was used monthly data for price. The principal result of this study is substantially as follows. 1) The price of producing and consuming district is closely connected. 2) A gap between producing district price and consuming district price is decreasing recently, It seems to be correlated with outlook business of aquacultural flatfish. 3) Trend line of the price was declining until 2002, but it turned up after that. The other side, circulated fluctuation was being showed typically. 4) The circle of circulated fluctuation was growing longer, so it seems that the producer was doing a sensible productive activity to cope with changing price. As a result, government's policy needs to be turned into price policy from policy of increased production for aquacultural flatfish. It seems that the best policy is price stabilization polices. And also, government needs to invest in outlook business for aquaculture constantly.

• 지능정보연구
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• 제7권1호
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• pp.97-121
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• 2001

본 연구에서는 웹 마이닝을 이용하여 기업과 소비자간 전자상거래(Business-To-Customer Electronic Commerce)환경에 기초한 가상상점(Cyber market)의 상품 관리자 입장에서 효율적인 상품관리를 가능케 하는 시스템적 접근방법을 통한 상품관리 방법론을 제시하고자 한다. 또한 이 상품 관리 방법론을 실제 웹 상에서 운영되고 있는 가상상점에 직접 적용하여 봄으로써 실증적인 예를 보여주고자 한다.