• 한국산학기술학회논문지
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• 제8권3호
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• pp.639-645
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• 2007

본 연구에서는 우리나라의 인터넷전화 통화수요함수를 2001년 6월부터 2004년 12월까지의 월별 데이터를 이용하여 추정하고 있다. 추정식에서 인터넷 통화수요는 통화요금, 타서비스의 요금, 소득, 품질 등의 함수로 가정하였으며, 통화량의 부분적응모형을 이용하여 시차변수도 설명변수에 포함시켰다. 추정결과 인터넷전화는 해당 요금에 대해 탄력적인 것으로 파악되었고 소득에 대하여는 비탄력적으로 나타났다. 품질은 인터넷전화수요에 큰 영향을 미치는 것으로 파악되었으며 인터넷전화 통화수요가 설명변수의 변화에 대하여 반응하는데 있어 시차가 존재함을 보이고 있다.

• 산업경영시스템학회지
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• 제10권16호
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• pp.143-147
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• 1987

Safety stocks constitute one of the major means of dealing with the uncertainties associated with variation in demand and lead time. Adeguate safety facilitate production activities and help to assure customers if good service on the other hand, carrying safety storks ties up working capital on goods that sit idle. The major problem of safety stocks management thus of consists of trying to achieve an optimal balance between the other carrying cost and the costs of stock shortage. Therefore, this study aims to find safety stock level of the fixed reorder quantity system and the fixed reorder cycle system of minimizing total cost when both demand and lead time are variable. (The distribution of demand and lead time is a mere assumption that follows the normal distribution) The results can be summarized as follows. i) Safety factor on the safety stock is determined by carrying cost and the costs of stock shortage: An optimal safety stick=the costs of stork shortage($C_s$) (the carrying cost($C_h$)+the costs of stock storage($C_s$). ii) The safety stock level of the fixed reorder quantity system is ($a{\;}_p\sqrt{L}{\sigma}$) under uncertainties. iii) The safety stock level of the fixed reorder cycle system is ($a{\;}_p\sqrt{R+L{\sigma}}$) under uncertain demand and constant lead time. ($a{\;}_p\sqrt{L{\sigma}_d{\;^2+{\mu}^2L{\sigma}^2}$) under demand and lead time uncertainties.

• 산업경영시스템학회지
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• 제8권12호
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• pp.65-77
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• 1985

The mainpoints of General Theory is 1) the mainspring of economic activity is effective demand which can expand or control in relation to supply as a result of spontaneous decision by customer or government. 2) change in effective demand Produce change in output and employment in the same direction 3) which given productivity of labour the Vice level depend on the money supply affect the in downward direction 4) change in the money supply affect the economy through the rates of interest 5) the only automatic mechanism through which the economy can adjust itself to a deficiency of effective demand is the long process which unemployment reduces wage rates and consequently the demand for money and interest rates, above summarized contents are General Theory frame-work. The neo-classical macro general equilibrium theory, which has been reconstructed subsequent to Keyneses critism is treated the neo-classical macro-general equilibrium theory which inherits the classical theories of labour market and the aggregate production function, on demand side, it introduce the Keyneses macro-general equilibrium theory, which function through flexible movement of prices, wage and interest. Nowadays, Keynes General Theory is being developed into new dimension i, e. the macro-disequilibrium theory, and adequacy, and appropriateness of the theory and its significant contributions to modern economics are being reinterpreted and substantiated.

• Industrial Engineering and Management Systems
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• 제14권2호
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• pp.129-158
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• 2015

It is necessary for retailers to determine the optimal ordering policy of products considering supply disruptions due to a natural disaster and a production process failure as quality and machine breakdowns. Under the situation, a dualsourcing supply chain (DSSC) is one of effective SC for retailers to order products reliably. This paper proposes the optimal ordering policy of a product in a DSSC with a retailer and two manufacturers. Two manufacturers may face supply disruptions due to a natural disater and a production process failure after they received the retailer's order of products. Here, two scenarios of demand information of products are assumed: (i) the demand distribution is known (ii) mean and variance of the demand are known. Under above situations, two types of DSSC are discussed. Under a decentralized DSSC (DSC), a retailer determines the optimal ordering policy to maximize his/her total expected profit. Under the integrated DSSC (ISC), the optimal ordering policy is determined to maximize the whole system's total expected profit. Numerical analysis investigates how demand information and supply disruptions affect the optimal decisions under DSC and ISC. Besides, profitability of supply chain coordination adjusting the wholesale price is evaluated to encourage the optimal decision under ISC.

• 한국산학기술학회논문지
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• 제16권9호
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• pp.5843-5849
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• 2015

본 연구는 단감농가의 생산비절감방안 모색을 위해 생산요소 수요구조를 분석했다. 2001~2013년간 농산물소득조사 원자료를 이용해 초월대수 비용함수를 추정하고 노동, 자본, 중간투입재간 가격 및 대체탄력성을 계측했다. 분석결과 생산요소 모두 가격변화에 따른 수요변화가 크지 않고 특히 비용부담이 가장 큰 노동의 가격상승에 따른 타 생산요소의 대체성이 낮아 구조적으로 단기간에 노동 수요를 줄이기는 어려운 것으로 나타났다. 이는, 생산비절감을 위해서는 노동에 비해 수요가 탄력적인 중간투입재, 특히 탄력성이 큰 비료와 기타재료비를 중심으로 비용절감이 이뤄져야함을 시사한다.

• International Journal of Railway
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• 제5권4호
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• pp.139-143
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• 2012

In Korea, almost 700 industrial parks are under operation. Generally, industrial parks consist of national industrial parks and local industrial parks which are managed by a central government and by local governments respectively. The developing countries such as Korea, China and Vietnam etc. have constructed many industrial parks, which result in the change of land use pattern and also affect future trip demands. Therefore, in estimating traffic demands, it is very important to consider the industrial park development. This study aims to improve the methodology in estimating a freight trip generation rate with the data based on a nationwide commodity freight survey. The result showed that it is desirable to apply freight trip generation rate by the industry sector in estimating freight trip generations and using the production area of firm as an indicator. Specially, the reliability of the rates through a survey could be made sure because a sample rate based on firms in industrial parks was over 25% and the response rate was over 67%. The sample rate and response rate are very superior as compared to surveys conducted in many other countries. Because industrial parks have significant effects on forecasting transportation demand in pre-feasibility studies of transport and logistics projects, it is expected that the accuracy of freight trip demands would be improved through the results of this study.

• 응용통계연구
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• 제23권3호
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• pp.559-571
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• 2010

본 연구는 직무스트레스 분야에서 가장 널리 연구 된 직무요구-통제 모형을 팀 수준으로 확대하여 개인 수준에서의 직무요구와 직무스트레스간의 관계를 재검증 하고, 이 관계를 조절하는 사회적 지지를 팀의 풍토로서 정의하여 팀 수준의 조절효과를 검증하는데 목적이 있다. 자료는 다양한 성격의 19개 조직의 34개 팀에서 수집하였으며 분석 결과, 개인 수준에서 직무요구가 직무스트레스를 유의하게 예측하였으며, 팀의 관계중시풍토는 직무요구와 직무스트레스간의 관계를 조절하는 것으로 나타났다. 또한 팀의 관계중시풍토는 리더의 개인배려행동과 유의하게 관련되었다. 마지막으로 본 연구의 제한점과 시사점 그리고 미래 연구에 대해 논의하였다.

• 산업경영시스템학회지
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• 제40권4호
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• 산업공학
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• 제24권4호
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• pp.373-378
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• 2011

High level of accuracy in forecasting heat demand of each district is required for operating and managing the district heating efficiently. Heat demand has a close connection with the demands of the previous days and the temperature, general demand forecasting methods may be used forecast. However, there are some exceptional situations to apply general methods such as the exceptional low demand in weekends or vacation period. We introduce a new method to forecast the heat demand to overcome these situations, using the linearities between the demand and some other factors. Our method uses the temperature and the past 7 days' demands as the factors which determine the future demand. The model consists of daily and hourly models which are multiple linear regression models. Appling these two models to historical data, we confirmed that our method can forecast the heat demand correctly with reasonable errors.

• 대한안전경영과학회지
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• 제18권4호
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• pp.161-169
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• 2016

In this research, we propose efficient demand forecasting scheme for intermittent demand. For this purpose, we first extensively analyze the drawbacks of the existing forecasting methods such as Croston method and Syntetos-Boylan approximation, then using these findings we propose the new demand forecasting method. Our goal is to develop forecasting method robust across many situations, not necessarily optimal for a limited number of specific situations. For this end, we adopt combining forecasting method that utilizes unbiased forecasting methods such as simple exponential smoothing and simple moving average. Various simulation results show that the proposed forecasting method performed better than the existing forecasting methods.