• Proceedings of the Korea Society for Simulation Conference
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• 1998.03a
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• pp.101-105
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• 1998

A large system predictor, which can perform prediction of sales trend in a huge number of distribution centers, is presented using neural predictive model. There are 20,000 number of distribution centers, and each distribution center need to forecast future demand in order to establish a reasonable inventory policy. Therefore, the number of forecasting models corresponds to the number of distribution centers, which is not possible to estimate that kind of huge number of accurate models in ERP (Enterprise Resource Planning)module. Multilayer neural net as universal approximation is employed for fitting the prediction model. In order to improve prediction accuracy, a sequential simulation procedure is performed to get appropriate network structure and also to improve forecasting accuracy. The proposed simulation procedure includes neural structure identification and virtual predictive model generation. The predictive model generation consists of generating virtual signals and estimating predictive model. The virtual predictive model plays a key role in tuning the real model by absorbing the real model errors. The complement approach, based on real and virtual model, could forecast the future demands of various distribution centers.

• Proceedings of the Korean DIstribution Association Conference
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• 2000.10a
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• pp.91-105
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• 2000

Results of a study of the coordination effect in stocking and promotional markdown policies for a supply chain consisting of a retailer and a discount outlet (DCO) are reported here. We assume that the products are sold in two consecutive periods: Normal Sales Period (NSP) and subsequent Promotional Sales Period (PSP). When managers in the two periods coordinate, they share information on the demand forecast and jointly decide the stocking quantity, markdown time schedule, and markdown price to maximize mutual profit. In the absence of coordination, decisions are decentralized to optimize the individual party's objective function. Optimal coordination policy for the retailer/DCO problem setting is analyzed, and the coordination policy is compared with the uncoordinated policy to explore factors that make coordination an effective approach.

• Management & Information Systems Review
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• v.7
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• pp.169-186
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• 2001

The strategic management for Innovation and competetion of small and medium firms is practical innovation strategic of cost down and sales increace. Framework of the strategic management for thr forecast of changed industry and formal competetion. Practice and planning to the small and medium firms for innovation, cost down, sales increace, revolution management, etc. The results of study are as follows ; 1) study of pre-model for innovation and competetive advantage. 2) Draw of the creative factor for industrial structure analysis, cost advantage analysis and competetive advantage. 3) Exhibit of the practice model for strategic management approach. 4) Application and modification to the small and medium firms for results of study.

• Journal of Fashion Business
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• v.22 no.5
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• pp.83-95
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• 2018

As the paradigm of fashion retail industry moves rapidly to the multi-channel, the role of shop master has changed as well. Therefore, the purpose of this study is to examine in-depth the changing role of shop masters in multi-channel retail paradigms. In-depth interviews were conducted, and all interviews were recorded with permission. Seven shop masters participated in in-depth interviews. All of them were sales specialists, with more than 10 years working experience, at department stores. Results of this study are as follow: First, the roles of a multi-channel shop master include store management, management of sales associates, customer relationship management, and management in relation to the headquarters and suppliers. Second, the most important competencies of shop masters are to forecast future demand, establish information networks, communicate well with others, and create a work environment resulting in higher productivity.

• The Journal of Economics, Marketing and Management
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• v.2 no.2
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• pp.10-14
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• 2014

The study investigated consumption patterns and inclination of consumers of Hanwoo meat being more expensive than imported meat and/or beef cattle meat based on the author's business experience at the shop in Budang Seongnam. The author who has managed shop firstly investigated customers' inclination and/or propensity. The author heard specific customer's story at neighboring shopping center, and each customer's buying method, occupation, financial power and apartment size and others, and forecast visiting customer's buying and demand upon part of the beef that customer asks for. The aut hor who sold out limited scope of beef product at limited area thought that he did narrow scope of business. The author would make effort to sell product enough to meet customer's taste by better quality product from point of view of customers. The author would make effort to supply good quality beef products to the customers who relied upon the author's butcher's.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.169-176
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• 2019

Recently, the Korean economy is congested with Japan's economic retaliation, the US-China trade war, the Bank of Korea's 0.25% base rate cut and Korea's economic growth forecast revision. The purpose of this study is to analyze the KOSPI, CPI, Treasury bonds(3 years) Interest rate & sales performance of all industries, and examine the impact of each index on the KOSPI. The analysis period is from January 2003 to June 2019, and the effect of each index on the KOSPI is analyzed. In numerical analysis, we performed correlation coefficients and regression analysis. In the model analysis, the distribution, quadrant, scatter, box-plot and impulse response were examined. This study examined the volatility and dynamic characteristics of each index. As a result, the KOSPI showed a high correlation with sales and Treasury bonds, but showed a very low correlation with the CPI. The KOSPI will continue to be affected by sales and interest rates.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.179-186
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• 2022

This study aims to develop a predictive model to suggest a used sales price to sellers and buyers when trading used tablet PCs. For model development, we analyzed the real used tablet PC transaction data and additionally collected detailed product information. We developed several predictive models and selected the best predictive model among them. Specifically, we considered a multiple linear regression model using the used sales price as a dependent variable and other variables in the integrated data as independent variables, a multiple linear regression model including interactions, and the models from stepwise variable selection in each model. The model with the best predictive performance was finally selected through cross-validation. Through this study, we can predict the sales price of used tablet PCs and suggest appropriate used sales prices to sellers and buyers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.458-468
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• 2019

This research attempted to estimate monthly sales of food and beverage at the passenger terminal of Incheon int'l airport from June of 2015 to December 2020. This paper used ARIMA-Intervention model which can estimate the change of the sales amount suggesting the predicted monthly food and beverage sales revenue. The intervention variable was travel-ban policy against south Korea from P.R. China since July 2016 to December 2017 due to THAAD in south Korea. According to ARIMA, it was found normal predicted sales amount showed the slow growth increase rate until 2020 due to the effect of intervened variable. However, the monthly food sales in July and August 2019 was 20.3 and 21.2 billion KRW respectively. Each amount would increase even more in 2020 and the amount would increase to 21.4 and 22.1 billion KRW. The sales amount in 2019 would be 7.7 and 8.1 billion KRW and climb up 7.9 and 8.2 billion KRW in 2020. It was expected LCC passengers tend to spend more money for F&B at airport due to no meal or drink service of LCC or the paid-in meal and beverage service of LCC. The growth of sales of food and beverate will be accompanied with the growth of LCC according to estimated data.

• Journal of Distribution Science
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• v.16 no.11
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• pp.21-27
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• 2018

Purpose - This study investigates the financial ratio of savings banks and the effect of the ratio having influence upon bankruptcy by quantitative empirical analysis of forecast model to give material of better management and objective evidence of management strategy and way of advancement and risk control. Research design, data, and methodology - The author added two growth indexes, three fluidity indexes, five profitability indexes, and four activity indexes CAMEL rating to not only the balance sheets but also the income statement of thirty savings banks that suspended business from 2011 to 2015 and collected fourteen financial ratio indexes. IBMSPSS VER. 21.0 was used. Results - Variables having influence upon bankruptcy forecast models included total asset increase ratio and operating income increase ratio of growth index and sales to account receivable ratio, and tangible equity ratio and liquidity ratio of liquidity ratio. The study selected total asset operating ratio, and earning and expenditure ratio from profitability index, and receivable turnover ratio of activity index. Conclusions - Financial supervising system should be improved and financial consumers should be protected to develop saving bank and to control risk, and information on financial companies should be strengthened.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1116-1123
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• 2006

The methodological framework proposed in this paper addresses the strength of the applied Bass model by Mahajan and Muller(1996) that it reflects the substitution of next generations among products. Also this paper is to estimate and analyze the forecast of demand for products that do not exist in the marketplace. We forecast the sales of digital TV using estimated market share and data obtained by the face to face Interview. In this research, we use two methods to analyze the demand for Digital TV that are the forecasting the Demand for the Substitution and binary logit analysis. The logit analysis is to estimate the decisive factor of purchasing digital TV. The decisive factors are composed of purchasing plan, region, gender, TV price, contents, coverage, income, age, and TV program. We apply the model to South Korea's market for digital TV. The results show that (1) Income, region and TV price play a prominent part which is the decisive factor of purchasing digital TV. (2) We forecaste the demand of digital TV that will be demanded about 18 millions TVs in 2015