• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.537-557
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• 2005

The estimate on volatility of stock price is related with optimum of portfolio and Important for allocation of capital asset. If the volatility of stock price is varied according to macroeconomic variables on monetary policy and industrial production, it will assist capital asset to allocate. This paper is related with stock market volatilities on macroeconomic variables in U.S. and Europe, Korea. And, it Is pertain to vary in time of this variables. Thus, this paper is related with volatilities of monetary and physical macroeconomic variables on basis of statistics. And, it is ranged front capital investment to portfolio allocation. Also, this paper takes out of sample forecast and study more after this. In case Germany, France, Italy and the Netherlands, the relative importance of monetary policy and Industrial production Is different from these countries. In case Italy and the Netherlands, monetary policy is primary factor at stabilizing for volatility of stock price. In case Korea, increasing monetary policy and industrial production is positively affected stock market. It is that the positive effect of stock price is caused by mollifying monetary policy and economic growth. Specially, this conclusion is similar to US. In Korea, gradual increase in monetary and industrial production is necessary to stability of stock market. It is different to previous results on basis of increasing stock price of money in long period.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

• Knowledge Management Research
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• v.14 no.4
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• pp.87-98
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• 2013

Along with the recent development of Social Network Service (SNS), such as Facebook and Twitter, social commerce market is expanding rapidly. As much, understanding consumers' purchase intention in social commerce becomes important. This study attempted to investigate the factors of consumers' purchase intention, and the effects of these determinants(price discount, perceived risk and product review) on consumer's purchasing intension in social commerce networks. Also, the interaction effects between these factors on consumer's purchasing intension were studied. The results showed that the effect of perceived risk on consumer's purchase intention found to be significantly negative. The interaction effect between price discount and perceived risk, and the interaction effect between price discount and review were meaningful on consumers' purchase intention. It indicates that the important factor for consumers to purchase products in social commerce is not just price discount but perceived risk, and that review which consumers think is manipulated has negative effect on purchase intention.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.8
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• pp.341-350
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• 2006

This paper presents a new methodology to draw the components of locational marginal price (LMP) in electricity market. Recently, the changing environments surrounding electricity industries resulted in the unbundled services provided by electricity market players, which may require the new pricing mechanisms based on the LMP. The changed pricing mechanisms will provide the price signals of time and location to the market participants. Most of the existing studies of LMP are based on the Lagrangian multipliers as shadow prices to evaluate the equivalent values of constraints or factors for security, reliability and quality. However, the shadow prices cannot provide enough information for components of LMP. In this paper, therefore, we proposed a new approach that LMP is divided into three components. To do this, we first present the method for shadow prices calculation and then break down LMP into a variety of parts corresponding to the concerned factors. The proposed approach is applied to 5-bus and modified IEEE 14-bus sample system in order to verify its validity.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.3
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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.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.67-72
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• 2018

The purpose of this study is to investigate the effect of quality of management discussion and analysis (MD&A) disclosure on stock price crash risk. The MD&A can be seen to reflect the management's intention on public announcement and reveals directly what the management says to communicate with outside investors. A firm's high-quality MD&A implies the management's commitment to communicating with the market, not allowing the managers to have incentives to hoard unfavorable news, which if revealed to the public, may lead to downward stock price corrections, damaging corporate values. The high-quality MD&A is, thus, likely to reduce the stock price crash risk. We use a logistic regression to test whether MD&A influences crash risk using listed companies in the Korean Stock Exchange (KSE) stock market between 2010 and 2013. Findings of the empirical test show that the higher the quality of MD&A, the less likely crash risk appears, implying that the MD&A disclosed adequately can be one of the factors mitigating firm's stock price crash risk. This study has implications as it presents the MD&A disclosure as a factor influencing stock price crash risk and suggests voluntary disclosure as well as mandatory disclosure acts as a variable that explains the risk of stock price crash.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.1
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• pp.12-21
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• 2004

The purposes of this research were (1) to identify service quality and apparel quality in apparel stores, (2) to examine the influence of service quality, product quality and price on customer satisfaction, (3) to examine the influence of service quality, product quality, price and customer satisfaction on repurchase intention that is important feature of store patronage. The data was collected from 435 female students, career women, and house wives using questionnaire and analyzed by frequency analysis, factor analysis, reliability analysis and regression. The results of this research were as follows: (1) Service quality in apparel stores was divided into six factors: facilities and policy/ salesperson VMD/ after service/ impression and atmosphere/ promotion. (2) Product quality was divided into four factors: objective feature/ expressive feature/ wearing sensation/ fitness. (3) Service quality, product quality, price influenced customer satisfaction. (4) Product quality, price and customer satisfaction influenced repurchase intention directly, but service quality influenced repurchase intention indirectly. (5) Service quality factors that influenced customer to have repurchase intention were facilities and policy, salesperson, and VMD. (6) Product quality factors that influenced customer to have repurchase intention were objective feature and wearing sensation.

• Journal of Family Resource Management and Policy Review
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• v.11 no.4
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• pp.1-20
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• 2007

The purpose of this study was to identify the criteria of evaluating a price-comparison website, and to investigate the consumers' perceived importance and satisfaction of each criterion. Also, it compared both the importance and satisfaction levels based on consumers' socio-economic and Internet-usage characteristics. Data for this study came from a questionnaire completed by consumers (n=417), who had used the price-comparison website, and were analyzed through factor analysis, t-test, and ANOVA. The findings of the study were as follows: First, the evaluation criteria of the price-comparison website were categorized into five variety of information, accuracy, convenience, credibility, and the website system. Second, convenience of searching information was seen by consumers as both the most important and most satisfactory criterion. Variety of information was also considered important. For most of the evaluation criteria, the level of consumers' satisfaction was significantly lower than the level of consumers' recognized importance. Third, consumers in their 20s, students, and housewives were less likely to be satisfied by the price-comparison website overall. Older people were less likely to be satisfied with the convenience of the website, and the higher-income group was less likely to be satisfied with the variety of information on hand.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.9
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• pp.1506-1518
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• 2009

This study identifies the relationships among demographic variables, well-being health consciousness, sports/leisure activity, and the perceived premium price for high functional sports/leisure wear. An empirical study was conducted with the data collected by questionnaires distributed to male and female respondents aged 15 and over. Descriptive statistics, factor analysis, MANOVA, two-way ANOVA, and regressions were used to analyze 244 answers. As a result, 3 factors were determined for well-being health consciousness: nature-friendly life, premium consumption for health, and health care. The older group pursued a nature-friendly life more than the younger group, the female group pursued premium consumption for health more than male group, and older women and younger men pursued health care more than their counterparts. Sports/leisure activity was relatively intensive in the male group and in the younger group. Sports/leisure activity was explained by male characteristic and health care factors. Sports/leisure activity was the only element for predicting the perceived premium price ratio for high functional sports/leisure wear.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.05a
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• pp.151-152
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• 2021

The sale price of apartment buildings is a key factor in the success or failure of apartment projects, and the factors that affect the sale price of apartments vary widely, including location, environmental factors, and economic conditions. Existing methods of predicting the sale price do not reflect the nonlinear characteristics of apartment prices, which are determined by the complex impact factors of reality, because statistical analysis is conducted under the assumption of a linear model. To improve these problems, a new analysis technique is needed to predict apartment sales prices by complex nonlinear influencing factors. Using machine learning techniques that have recently attracted attention in the field of engineering, it is possible to predict the sale price reflecting the complexity of various factors. Therefore, this study aims to conduct a basic study for the development of a machine learning-based prediction model for apartment sale prices.