• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.14-19
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• 2008

The paper presents an intelligent time series model to predict uncertain electricity market price in the deregulated industry environment. Since the price of electricity in a deregulated market is very volatile, it is difficult to estimate an accurate market price using historically observed data. The parameter of an intelligent time series model is obtained based on the simultaneous perturbation stochastic approximation (SPSA). The SPSA is flexible to use in high dimensional systems. Since prediction models have their modeling error, an error compensator is developed as compensation. The SPSA based intelligent model is applied to predict the electricity market price in the Pennsylvania-New Jersey-Maryland (PJM) electricity market.

• Journal of the Korean Home Economics Association
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• v.49 no.9
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• pp.73-81
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• 2011

The purpose of this study was to find out how price perception and the site's delivery system affected consumer satisfaction in surrogate internet shopping for apparel products. A survey questionnaire was used to collect information from 233 respondents who had experience in purchasing apparel products from online venues within the preceding 6 months. Collected data underwent descriptive analysis, factor analysis, and regression analysis. Results showed that the price perception and the delivery system was influenced by three factors. Both price perception and the delivery system factors showed a significant difference depending on the gender of consumers. Also, according to the regression results, both price perception and the delivery system had a positive effect on consumer satisfaction in surrogate Internet shopping mall for apparel products.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.9 no.14
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• pp.49-58
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• 1986

Those facts I have studied on the theoretical characteristics of stock price earning ratio related with firm evaluation are as followings. First, I have investigated stock valuation analysis under certainty in view of Miller's, Modigliani's and Linter's theories in Chapter Ⅱ, and it is found that stock valuation under uncertainty to which the basic model of MM theory and the concept of capitalization ratio are applied is the same output, as in the case under certainty. And I have examined the stock valuation of growth corporations in which net investment, total capitals and operating profits are expected. Second, I have reexamined the fact that stock price profits are the erotical indices of firm valuation and the firm valuation on the basis of stock price earning ratio in Chapter III. As a whole, I have surveyed the stock price earning ratio theory of the growth stocks and there have been found some problems as such scholars as Malkiel and others have suggested focusing on the stock price structure of growth stocks. To conclude, there must be incessant efforts for the study of security analysis to make it develop ideally.

• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.44-61
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• 1999

Cost estimation has posed a significant challenge to estimators, planners, and managers in both government and military. Considerable historical evidence shows that accurate cost estimation has been difficult to achieve across a wide range of projects, including weapon systems. This paper introduces new cost estimating concept, CAIV(Cost As an Independent Variable) and a cost estimating case study using PRICE model, computer aided parametric estimating models(CAPE) for K1 tank cost estimate. CAIV concept is to set realistic but aggressive cost objectives easily in each acquisition program and to achieve cost, schedule, and performance objectives considering various managing risks with a project manager and industry teams. The Price model is one of computer aided cost estimating models and widely used in U.S. defense system analysis as a tool for CAIV. We analyze theories, inputs, outputs of the PRICE model and present a case study for K1 tank to estimate costs in requirement and concept phase, program and budgeting phase, and life cycle phase. Finally we obtain results that the Price model can be used in various phases of PPBEES depending upon available data and time.

• Journal of the military operations research society of Korea
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• v.27 no.1
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• pp.10-27
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• 2001

This paper deals with the application of PRICE model in estimating the proper acquisition cost for weapon budgeting phase. The PRICE(Parametric Review of Information for Costing and Evaluation) Hardware model is a computerized method for deriving cost estimates of electronic and mechanical hardware assemblies and systems. The model can be used in obtaining not only initial cost estimates in conceptual phase, but also detailed cost estimates in budgeting phase depending on available historical and empirical data. We analyzed first step cost estimate parameters and derived cost equations using PRICe output dta. Using weight and complexity, We can find cost variation. Sensitivity analysis shows that cost increases exponentially as complexity increases exponentially as complexity increases. We estimated KAAV\`s (Korea Amphibious Assault Vehicle) production cost using the PRICE model and compare with engineering cost estimates which is based on actual production data submitted by the production company. The result shows that tow estimates are close within $\pm2%$ differences.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.51-58
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• 2022

Various studies have been conducted from the past to the present because stock price forecasts provide stability in the national economy and huge profits to investors. Recently, there have been many studies that suggest stock price prediction models using various input data such as macroeconomic indicators and emotional analysis. However, since each study was conducted individually, it is difficult to objectively compare each method, and studies on their impact on stock price prediction are still insufficient. In this paper, the effect of input data currently mainly used on the stock price is evaluated through the predicted value of the deep learning model and the error rate of the actual stock price. In addition, unlike most papers in emotional analysis, emotional analysis using the news body was conducted, and a method of supplementing the results of each emotional analysis is proposed through three emotional analysis models. Through experiments predicting Microsoft's revised closing price, the results of emotional analysis were found to be the most important factor in stock price prediction. Especially, when all of input data is used, error rate of ensembled sentiment analysis model is reduced by 58% compared to the baseline.

• Management & Information Systems Review
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• v.1
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• pp.293-307
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• 1997

This paper addresses the critical factors of customer satisfaction between department store which is characterized as a good service quality and discount store which has a competitive advantage on price dimension. The result showed that overall satisfaction of department store was slightly higher than that of discount store. Also, it was found that only service quality was a good indicator as a customer satisfaction of department store. However, overall satisfaction of discount store was significantly affected by both price and service quality. The study contributes to our understanding of how department store and discount store develop KSFs(key success factors) of customer satisfaction.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.50
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• pp.231-241
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• 1999

Recent market competition forces the price to be determined in the design stage so that the design would meet the target price of the product. However, most commercial PDM(Product Data Management) systems currently in use lack such a cost estimation function. In this paper, we propose detailed structure and functions of a new approach to estimate the cost of new products using integrated BOM in PDM. Such system will reduce the total life cycle cost of the products to be designed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.85-92
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• 2003

Due to the expansion of freeway networks in Korea, drivers have more routes to choose. Traffic information on various alternative roadway sections and routes may help drivers choose the optimal route that minimizes travel time or cost. Traffic information on roadways is, therefore, invaluable in sense that individual drivers could reduce their travel time or cost by selecting optimal routes, and furthermore total travel cost of the system could be lowered. However, consensus about the price of traffic information that drivers are willing to pay is not made yet. Current price of traffic information is decided according to the price of similar information such as stock, weather and so on. To investigate the value of traffic information, a survey was conducted at freeway rest areas near Seoul Megalopolis area including Kyunggi Province. Eight hundred drivers who had travelled on freeway within a year were randomly selected. Purposive Quota Sampling was used. A price-response function, a relationship between price and sales, was obtained based on the survey, followed by sensitivity analysis

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.1
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• pp.81-89
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• 2013

The purpose of this study is to analyze the information effect about the pricing using the ETF price, the benchmark index, and the total tracking error between the ETF price and the benchmark index on the index ETF market and sector ETF markets. Furthermore, the total tracking error is distinguished between the market tracking error and the NAV tracking error. Summary of this study are as follows: First, While KODEX200 don't have impact factors on the price, the most sectors of ETF have the factors affecting the pricing decision. They are the day before the total tracking error or market tracking error. Second, for the ETF price of the most industry, we find that the day before the market tracking error have the price discovery function because it is a negative(-) coefficients. But NAV tracking error could not find such a feature. Finally, the sector ETF price of energy chemical, construction, IT, and semiconductor industries affected of the day before positive(+) impact by the benchmark index price.