• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 A
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• pp.386-388
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• 2001

The change of the electricity charge from cost base to price base due to the introduction of the electricity market competition causes consumer to choose a variety of charge schemes and a portion of loads to be affected by this change. Besides, it is required the index that consolidate the price volatility experienced on the power exchange with gaming and strategic bidding by suppliers to increase profits. Therefore, in order to find a mathematical model of the sensitively-responding-to-price loads, the price-sensitive load model is needed. And the development of state-of-the-art technologies affects the electricity price, so the diffusion of high-efficient end-uses and these price affect load patterns. This paper shows the analysis on learning curves algorithms which is used to investigate the correlation of the end-uses' price and load patterns.

• Journal of Information Technology Applications and Management
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• 제13권1호
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• pp.1-16
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• 2006

This paper empirically analyzed consumer price search behavior using Web log data of a Korean web site for price comparison. Consumer click-stream data of the site was used to test the effects of price level, product category, third party certification, reputation of retailers on click behavior. According to the descriptive statistics, 67.4% of shopbot users clicked the offer which was the lowest price returned in a search. We found that third party certification and reputation of retailers were significant determinants of clicking the lowest priced offer from legit analysis. We also applied Tobit regression analysis to estimate the price premium of the two determinants, but only reputation of retailers was found to have price premium of 4.9%.

• 한국디지털건축인테리어학회논문집
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• 제12권1호
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• pp.89-98
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• 2012

While the housing transaction price of Seoul tends to be stagnant or declining in line with the housing market recession since 2007, the jeonse price keeps continual increase. Such flow of jeonse price change has a serious influence on ordinary person's housing stability seriously. Therefore, it is very meaningful in terms of social policy to analyze the trend of recent jeonse price change. This study aims to have an empirical analysis of structural characteristics of the trend of recent jeonse price change. After the review of various previous studies, this study selected housing jeonse price index, non-sold house quantity, jeonse vs. transaction price rate, and housing construction performance as analytical variables, and employed monthly time series resources from January 2007 to April 2011. As a result, when the housing supply reduced, the potential quantity for jeonse market reduced that occurred unbalance of supply and demand in jeonse market. In turn, it caused the increase of jeonse price. And, in case of jeonse vs. transaction price rate change, the rate increased which means the increase of required rate of return of invested demand. As such, the increase of market risk degenerates the investment sentiment which caused the reduction of quantity for jeonse market as a submarket.

• 한국의류학회지
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• 제40권3호
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• pp.574-589
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• 2016

This research investigates the characteristics of the mobile social commerce and explores the moderating effects of perceived risk and price sensitivity. This survey targeted consumers in their 20s to 30s who use mobile social commerce applications. We used 261 questionnaires for the final statistical analysis. Descriptive analysis, factor analysis, reliability analysis, and hierarchical regression analysis were applied in the data analysis. The results are summarized as follows. First, characteristics of mobile social commerce are composed of economics, informativeness, entertainment and promotion. Second, perceived risk (which had a negative effect on purchase intention) had moderating effects between perceived risk and economics or entertainment. Third, price sensitivity (which had a positive effect on purchase intention) had a moderating effect between price sensitivity and promotion. This study contributes to the disclosure of the role of perceived risk and price sensitivity as moderating factors between the characteristics of mobile social commerce and purchase intention. Finally, useful implications (both academic and practical) are provided for fashion retail managers.

• 대한가정학회지
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• 제49권9호
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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.

• 한국유기농업학회지
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• 제28권2호
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• pp.155-170
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• 2020

The objective of this study is to analyze factors affecting purchase intention and conduct price sensitivity analysis of Korean Shine-muscat for Chinese consumers. Logit model has been set up to find purchase intention with survey data which was conducted in Beijing China. The results show that the high-income, unmarried consumers are more sensitive to the price of Korean Shine-muscat than low-income, married consumers, but have higher purchase intention. Also, consumers who perceive Korea positively and those who prefer Korean dramas are more sensitive to the price but have higher purchase intention. Consumers with a high monthly purchase frequency of Shine-muscat have higher purchase intention of Korean Shine-muscat, but are more sensitive to the price. The results of this study can be utilized as basic information for promoting the export of Korean Shine- muscat to China.

• 한국시스템다이내믹스연구
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• 제9권1호
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• pp.125-141
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• 2008

It is very difficult to predict future demand/supply, price for resources with acceptable accuracy using regression analysis. We try to use system dynamics to forecast the demand/supply and price for nickel. Nickel is very expensive mineral resource used for stainless production or other industrial production like battery, alloy making. Recent nickel price trend showed non-linear pattern and we anticipated the system dynamic method will catch this non-linear pattern better than the regression analysis. Our model has been calibrated for the past 6 year quarterly data (2002-2007) and tested for next 5 year quarterly data(2008-2012). The results were acceptable and showed higher accuracy than the results obtained from the regression analysis. And we ran the simulations for scenarios made by possible future changes in demand or supply related variables. This simulations implied some meaningful price change patterns.

• 지능정보연구
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• 제24권2호
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• pp.195-220
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• 2018

본 연구는 비트코인 가격 변화량에 영향을 미치는 요인에 대한 실증 분석을 수행하였다. 기존 연구들은 암호화폐와 관련해 블록체인 시스템의 보안성, 암호화폐가 불러일으키는 경제적 파급효과 및 법적 시사점, 소비자 수용 및 사용 의도와 사회현상을 중심으로 이루어졌다. 그러나 암호화폐 가격 변화가 급등과 급락을 반복하면서 많은 사회적 문제를 야기했음에도 불구하고 암호화폐의 가격 변화에 영향을 미치는 요인에 대한 실증적 연구는 부족하다. 때문에 본 연구에서 암호화폐 가격 변화에 미치는 영향 요인을 도출하기 위해 암호화폐 중 가장 대표적인 비트코인을 중심으로 분석을 진행하였다. 분석을 위해 소비자, 산업, 거시경제 세 가지 차원에서 가설을 수립, 각 차원의 변수에 대한 시계열 데이터를 수집하였다. 단위근 검정을 통해 시계열 데이터에 대한 가성 회귀를 제거하고 안정성을 검증한 후, 비트코인 가격 변화량에 영향을 미칠 수 있는 요인들에 대한 회귀 분석을 실시하였다. 분석 결과 비트코인 가격 변화량은 비트코인 거래 금지에 대한 검색 트래픽, 미국 달러지수 변화량과는 음의 상관관계를, GPU 벤더의 주가 변화량, 원유 가격 변화량과는 양의 상관관계를 갖는 것을 확인했다. 그 이유로는 비트코인 거래 금지는 비트코인 존폐와 관련해 투자심리에 부정적 영향을 미친 것으로 판단되며, GPU 벤더 주가는 비트코인 생산 단가 증가와 관련해 비트코인 가격에 영향을 미친 것으로 해석된다. 미국 달러지수와는 반대로 움직임으로서 비트코인이 금의 성격을 갖고 있음을 확인하였으며, 원유 가격과의 관계를 통해 원자재와 같은 투자 자산의 역할도 갖고 있음을 확인하였다. 본 연구의 결과를 통해 비트코인이 가진 성격을 규명하였으며, 비트코인 가격 변화 요인에 대한 실증 검증을 통해, 그 동안 부족했던 비트코인 가격 변화 요인을 규명하였고, 해당 요인들을 통해 실무적으로 소비자나 금융기관, 정부 기관에 대해 비트코인에 대한 전략적인 접근방법에 대한 가이드를 제공할 수 있다는 점에서 의의가 있다.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.211-220
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• 2021

The aim of the study is to implement a factor analysis of the determinants of pricing in a state-regulated competitive market using economic and mathematical modelling methods and to develop ways to improve the pricing environment of the market under study. The purpose of the work defines the main objectives: (i) to investigate the features of the competitive model of the Ukrainian flour market; (ii) to analyse the current price conjuncture of the flour market and the dynamics of the main determinants of pricing; (iii)to develop ways of improving the price situation on the flour market on the basis of the factor analysis on the results of economic and mathematical modelling. In order to ensure the reliability and validity of the research results, the following methods were applied: the logical-dialectical method of scientific knowledge in the study of the main theoretical aspects of flour market functioning, the method of logical generalisation and synthesis, comparison, factor analysis, correlation and regression analysis, the graphical method, etc. It has been shown that pricing in a state-regulated competitive market has its own characteristics. For example, in the flour market the price of goods cannot be influenced by producers (sellers) by any methods, therefore determinants of pricing by indirect influence have been taken into account. The five-factor power model of wheat flour price has been constructed. It was substantiated that the price of wheat flour in Ukraine is mostly influenced by consumer price index (0.92 %). The received complex model of wheat flour price may be used also for medium-term forecasting and working out the ways of price formation optimization in the flour market.

• 유통과학연구
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• 제11권10호
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• pp.63-72
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• 2013

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.