• Korean Journal of Community Nutrition
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• v.11 no.2
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• pp.253-260
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• 2006

The purpose of this study was to suggest menu pricing strategy based on understanding about customer perceived value of products and services. The technique known as PSM (Price Sensitivity Measurement) was used for analysis of price sensitivity for 3 menu items of a family restaurant in Seoul. A questionnaire was developed through literature review and modified after pilot test. Questionnaires for the main survey were distributed to 250 customers on their visit to the restaurant, and a total of 138 questionnaires were used for analysis (55.2%). The statistical analysis of price sensitivity was conducted using PSM, and descriptive analyses were conducted using SPSS Win (12.0). The main results of this study were as follows: the price sensitivity of beef tenderloin steak was higher than two other menus and the stress range of teriyaki chicken was almost 0, that is, the price sensitivity of teriyaki chicken was very low. Present menu prices of 3 menu items were within the range of acceptable prices, but had some distances from the optimal pricing point. From the result of this study, it was concluded that price adjustment or price promotion strategy would be effective for increase in sales of beef tenderloin steak, and marketing strategies to enhance consumers' perceptions of value should be conducted for all menu items by situations. Overall, PSM technique could be a helpful tool for researchers and managers of foodservice organizations to understand how consumers' perceptions of value are affected by the interaction of price and quality.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1504-1511
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• 2009

By development of renewable energies and high-efficient facilities and deregulated electricity market, the operation cost of distributed generation(DG) becomes more competitive. The amount of distributed resource is considerably increasing in the distribution network consequently. Also, international environmental regulations of the leaking carbon become effective to keep pace with the global efforts for low-carbon paradigm. It contributes to spread out the business of DG. Therefore, the operator of DG is able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, community energy system(CES) having DGs is recently a new participant in the energy market. DG's purchase price from the market is different from the DG's sales price to the market due to the transmission service charges and etc. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize the profit. If there is no regulation for carbon emission(CE), the generators which get higher production than generation cost will hold a prominent position in a competitive price. However, considering the international environment regulation, CE newly will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and unit's efficiency. This paper will introduce the optimal operation of CES's DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES and Particle Swarm Optimization (PSO) will be used to solve this problem. The optimal operation of DG represented in this paper is to be resource to CES and system operator for determining the decision making criteria.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.4
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• pp.663-670
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• 2016

This paper analyzes the asymmetric pass-through effects of crude oil price changes on export prices in Korea's manufacturing sector using a nonlinear autoregressive distributed lag (NARDL) model. These pass-through effects are important for Korean companies that are highly dependent on exports. Because the effects differ by industry, eight sectors of the manufacturing industry were examined. The model is effective for separately testing the long-term and short-term differences between the export-price pass-through effects when crude oil prices increase and decrease. The estimation results show that there is positive pass-through to export prices as crude oil prices change, and there are asymmetric effects in some manufacturing sectors. Short-term asymmetries were detected in the export prices of five sectors that include general machinery and transport equipment, and significant long-term asymmetries were found for petroleum and coal products and for textile and leather products. The long-term export price of oil and coal products rose by 0.992% with a 1% increase in the oil price and fell by 0.977% with 1% decrease. Therefore, corporate strategies and government export policies should be established in accordance with these asymmetric pass-through effects.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.57-72
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• 2020

The price of iron ore has continued to fluctuate with high demand and supply from many countries and companies. In this business environment, forecasting the price of iron ore has become important. This study developed the machine learning model forecasting the price of iron ore a one month after the trading events. The forecasting model used distributed lag model and deep learning models such as MLP (Multi-layer perceptron), RNN (Recurrent neural network) and LSTM (Long short-term memory). According to the results of comparing individual models through metrics, LSTM showed the lowest predictive error. Also, as a result of comparing the models using the ensemble technique, the distributed lag and LSTM ensemble model showed the lowest prediction.

• International Area Studies Review
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• v.20 no.2
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• pp.47-62
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• 2016

This paper is to set up the empirical model in order to estimate industrial markup and to analyze the determinants for industrial markup by estimating the factor price elasticities of markup in the Korean manufacturing industries using the autoregressive distributed model. The import price elasticities of markup were estimated to be -1.025, -0.176, and -0.260 respectively in Machinery products, Chemical products, and Metallics which proved to have higher ratios of imported intermediate goods to industrial output. The interest elasticities of markup were also estimated to be -0.165, -0.147, and -0.210 respectively in Chemical products, Metallics, and Machinery products which are capital-intensive industries. Thus, the paper suggests that both import price index and interest rate have had more decisive effects on the changes in industrial markup in the Korean manufacturing industries, in particular, since the foreign currency crisis beginning in late 1997.

• Journal of Korean Society of Forest Science
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• v.97 no.1
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• pp.118-126
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• 2008

This research was conducted to develop pricing strategy based on understanding about customer perceived value of lodging facilities in national recreation forest. The technique known as PSM (price-sensitivity measurement) was used for analysis of price sensitivity for two kinds of lodging (log-cabin and forest-hotel) and for room sizes (4, 5, 6, 7 persons). PSM questionnaire for on-site survey were distributed to 236 customers on their visit to the six national recreation forests. The main results of this study were as follows: the price sensitivity of big size was higher then small, also, the price sensitivity of log cabin was higher then forest-hotel. Present prices were within the range of acceptable prices except prices of the use of 6 and 7 person of log-cabin. From the result of this study, it was concluded that price adjustment or price promotion strategy would effective for increase in sales and marketing strategies to enhance consumers' perceptions of value should be conducted for two room types by situations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.6
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• pp.298-304
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• 2000

In this paper, we propose that the SCOPF be solved in a decentralized framework, consisting of regions, using a price-based mechanism. We first solve the distributed OPF problem to determine the maximum secure simultaneous transfer capability of each tie-line between adjacent regions by taking only the security constraints imposed on the tie-lines into account. And then, the regional SCOPF is performed using the conventional LP approach. A description on the inclusion of security constraints with distributed OPF algorithm will be given, folowed by a case study for Korea power system.

• Journal of Korean Society for Quality Management
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• v.33 no.4
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• pp.111-116
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• 2005

This paper considers the problem of optimally choosing the sub-process means of a mixture production process where two important ingredients are mixed. The quantity of each ingredient is controlled through each corresponding sub-process. The values of the sub-process mean directly affect the defective rate, production, scrap and reprocessing costs for the mixture production process. After inspecting every incoming item, each conforming item is sold in a regular market for a fixed price and any nonconforming item is scraped. A model is constructed on the basis of the selling price, production, inspection, and scrap and reprocessing costs. The goal is to determine the optimum sub-process mean values based on maximizing expected profit function relating selling price and cost components. A method of finding the optimum sub-process means is presented when the quantities of the two ingredients are assumed to be normally distributed with known variances. A numerical example is given and numerical studies are performed.

• Plant Resources
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• v.6 no.3
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• pp.165-169
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• 2003

American ginseng (Panax quinquefolium) is herbaceous perennial plants indigenous to North American forests. This is highly valued as medicinal herbs with a long history of collection from wild populations since 1716. Wild American ginseng distributed from Quebec in Canada to northern Florida in USA. A heavy concentration is found in the Appalachian mountains, although wild American ginseng is considered endangered. The price paid for field cultivated ginseng has dropped dramatically in the past 10 years, while the price for wild or woods cultivated ginseng has rised significantly. The price curve for ginseng resembles a roller coaster, reflecting not only supply and demand but many other factors. This information will be useful to understand American ginseng compared to Korean ginseng.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.96-102
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• 2022

We aim to build predictive models for Airbnb's prices using a GPU-accelerated RAPIDS in a big data cluster. The Airbnb Listings datasets are used for the predictive analysis. Several machine-learning algorithms have been adopted to build models that predict the price of Airbnb listings. We compare the results of traditional and big data approaches to machine learning for price prediction and discuss the performance of the models. We built big data models using Databricks Spark Cluster, a distributed parallel computing system. Furthermore, we implemented models using multiple GPUs using RAPIDS in the spark cluster. The model was developed using the XGBoost algorithm, whereas other models were developed using traditional central processing unit (CPU)-based algorithms. This study compared all models in terms of accuracy metrics and computing time. We observed that the XGBoost model with RAPIDS using GPUs had the highest accuracy and computing time.