• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Fashion & Textile Research Journal
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• v.12 no.1
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• pp.38-45
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• 2010

Cosmetics retailers would benefit from studies that examine which shopping-mall attributes can be manipulated to favorably affect consumer satisfaction and revisit intention at Internet. The purposes of this study were (1) to examine the dimensionality of shopping-mall attribute for cosmetics retailers, (2) to determine which dimensions of shopping-mall attribute were significant predictors of consumer satisfaction and revisit intention and (3) to find out the moderating effect of consumer satisfaction through shopping-mall attributes on revisit intention to buy cosmetics across the types of shopping-mall at Internet (i.e., total mall and specialty mall). Data were collected from 209 online cosmetic shoppers among high school girls. Factor analysis identified five dimensions of shopping-mall attributes at Internet, such as Convenience, Price, Loading speed, Sales promotion, and Service. Only two dimensions(i.e., convenience and service) were significant predictors of online shopper satisfaction in both total mall and specialty mall. The moderating effect of consumer satisfaction on revisit intention was significant in both two mall types at Internet. For total mall, price was a significant predictor through consumer satisfaction on revisit intention, while loading speed was a significant predictor directly on revisit intention for specialty mall. In light of the major findings, this study sets forth strategic implications for consumer satisfaction and revisit intention to buy cosmetics in the setting of electronic commerce.

• Architectural research
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• v.24 no.3
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• pp.85-91
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• 2022

The public rental housing policy aims to provide the housing to the vulnerable class who do not have enough credit to own houses. The Korean government introduced new policies for housing supply to improve the availability of new houses. However, it is difficult to expand the supply because of the accumulated deficit of public rental housing. In this study, the economic feasibility of long-term public rental housing reconstruction projects was examined to ensure the economic and sustainable growth of public rental housing. The research found that the compensation for the accumulated deficit is needed. Also the research analyzed and identified the factors affecting the economic feasibility of reconstruction projects. The significant factors identified in this research are: the supply price of pre-sale/rental housing in the reconstruction project, total cost of the reconstruction project, and total floor area of the reconstruction project. According to the analysis results, it is necessary to increase the rent of existing long-term public rental housing, expand the government subsidy, increase the supply price of pre-sale/rental housing, and reduce the total project cost. However, there are limitations. For example, the fluctuations of construction market, residents' burden of housing costs, and the limit of the budget of the public housing authority. The increasing total Floor Area Ratio(FAR) limitation of the reconstruction project would be the realistic solution to the problem because it gives incentives to the reconstruction project.

• Culinary science and hospitality research
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• v.19 no.3
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• pp.274-290
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• 2013

The purpose of this research was to conduct an empirical research on the relations between perceived satisfaction level and value, brand attitude and repurchase intention after receiving price discount in such brand coffee shops as Starbucks, Coffee Bean, Angel-In-Us, and Caffebene. To do this, surveys were conducted in those 4 brands of coffee shops, distributing 100 copies of questionnaire each, from December 1st to December 31st, 2012. A total of 400 copies were collected for the final analysis, and the results are as follows. The level of satisfaction with price discount policy was displayed as causing a significant positive influence on hedonic and utilitarian values, and the hedonic and utilitarian values were identified as causing a significant positive influence on brand attitude and repurchase intention. Additionally, it was shown that brand attitude caused a significant positive influence on repurchase intention. A further analysis revealed that the number of customers who do not utilize the discount policy was highest in Starbucks, while the number of customers who utilize stamp coupons was displayed as the highest in Coffee Bean. In case of Angel-In-Us, the number of customers who use other price discount policies instead of stamp coupons was displayed as the highest, while the number of customers who utilize other price discount policies along with stamp coupons was displayed as the highest in Caffebene. Moreover, the level of satisfaction with price discount policies was higher for customers who use discount policies compared to those who do not.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.119-138
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• 2016

Since the Industrial Revolution, which made the mass production and mass distribution of standardized goods possible, machine-made (manufactured) products have accounted for the majority of the market. However, in recent years, the phenomenon of purchasing even more expensive handmade products has become a noticeable trend as consumers have started to acknowledge the value of handmade products, such as the craftsman's commitment, belief in their quality and scarcity, and the sense of self-esteem from having them,. Consumer interest in these handmade products has shown explosive growth and has been coupled with the recent development of three-dimensional (3D) printing technologies. Etsy.com is the world's largest online handmade platform. It is no different from any other online platform; it provides an online market where buyers and sellers virtually meet to share information and transact business. However, Etsy.com is different in that shops within this platform only deal with handmade products in a variety of categories, ranging from jewelry to toys. Since its establishment in 2005, despite being limited to handmade products, Etsy.com has enjoyed rapid growth in membership, transaction volume, and revenue. Most recently in April 2015, it raised funds through an initial public offering (IPO) of more than 1.8 billion USD, which demonstrates the huge potential of online handmade platforms. After the success of Etsy.com, various types of online handmade platforms such as Handmade at Amazon, ArtFire, DaWanda, and Craft is ART have emerged and are now competing with each other, at the same time, which has increased the size of the market. According to Deloitte's 2015 holiday survey on which types of gifts the respondents plan to buy during the holiday season, about 16% of U.S. consumers chose "homemade or craft items (e.g., Etsy purchase)," which was the same rate as those for the computer game and shoes categories. This indicates that consumer interests in online handmade platforms will continue to rise in the future. However, this high interest in the market for handmade products and their platforms has not yet led to academic research. Most extant studies have only focused on machine-made products and intelligent services for them. This indicates a lack of studies on handmade products and their intelligent services on virtual platforms. Therefore, this study used signaling theory and prior research on the effects of sellers' characteristics on their performance (e.g., total sales and price premiums) in the buyer-seller relationship to identify the key influencing e-Image factors (e.g., reputation, size, information sharing, and length of relationship). Then, their impacts on the performance of shops within the online handmade platform were empirically examined; the dataset was collected from Etsy.com through the application of web harvesting technology. The results from the structural equation modeling revealed that the reputation, size, and information sharing have significant effects on the total sales, while the reputation and length of relationship influence price premiums. This study extended the online platform research into online handmade platform research by identifying key influencing e-Image factors on within-platform shop's total sales and price premiums based on signaling theory and then performed a statistical investigation. These findings are expected to be a stepping stone for future studies on intelligent online handmade services as well as handmade products themselves. Furthermore, the findings of the study provide online handmade platform operators with practical guidelines on how to implement intelligent online handmade services. They should also help shop managers build their marketing strategies in a more specific and effective manner by suggesting key influencing e-Image factors. The results of this study should contribute to the vitalization of intelligent online handmade services by providing clues on how to maximize within-platform shops' total sales and price premiums.

• The Korean Journal of Financial Management
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• v.22 no.2
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• pp.71-89
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• 2005

The purpose of this research is to examine X-efficiency of Korean local credit unions in 2001 by employing the stochastic frontier approach. This study uses the intermediation approach in order to define outputs and inputs of the credit unions. We define the outputs as the amounts of loans, and securities. The inputs are labor, deposit and physical capital. The price of labor is estimated by dividing the total wages by the number of employees. The price of deposit equals total interest divided by total deposit, and the price of physical capital is also computed to divide the total sales and administrative expenses by the physical capital. By the result of this study, the average efficiency score is 0.81. This fact indicates that credit unions can reduce their inputs by 19% for the given outputs. If results are arranged into quartiles based on the efficiency, inefficiency of top 25% credit unions is below 9%, and half of them is over 17%. In addition, e result shows that the efficiency is significantly influenced by region and size even if credit unions in Seoul and Daegu showed little difference in efficiency by size. Generally, medium size credit unions are more efficient than large size.

• Journal of Korea Technology Innovation Society
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• v.14 no.spc
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• pp.1096-1127
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• 2011

This research focus on estimating the economic effects of TOD system development from the perspective of new market creation, R&D planning cost reduction and increase of R&D projects' commercialization success rates. The research is conducted through simulation and scenario analysis with assumptions about economic effect parameters. Scenario analysis shows that scenario 1 (the application ratio of the new TOD system to total Korean R&D programs' planning is 1.4%) results in total economic effects, 921.3 billion won in 2011 price with B/C ratio 6.15, that scenario 2 (the application ratio is 1.9%) results in total economic effects, 1,250.3 billion won in 2011 price with B/C ratio 8.34, and that scenario 3 (the application ratio is 0.9%) results in total economic effects, 592.2 billion won in 2011 price with B/C ratio 3.95. The research contributed to the prior evaluation of economic validity of "R&D on Technology Opportunity Development (TOD) system" and to cultivating the new methodology of economic benefit estimation in the area of R&D on system development.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.7
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• pp.381-386
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• 2003

To provide a specified power quality under electric market system is becoming an important issue for customers and utility company. However, there is no realistic infra-structure to design a power system for the specified power quality. Present electric market is operating under the economic point of view. The low power price could be attractive, but the effect of low price could result the lower power quality for the long time and threat power system security. This paper presents a model which conceptualize the dynamic power quality control mechanism to minimize total cost of a society which is affected electric power quality. This model aims to produce a basic infra-structure to balance cost and quality under the electric market system.

• Journal of Plant Biology
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• v.15 no.2
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• pp.1-6
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• 1972

Cultivar Yeollow Special A, the most leading Korean economic leaf tobacco in Korea, were field-cultivated in four different localities of Korea for the period of two years (1970 and 1971) and sprayed at varied levels of 2-chloroethyl phosphonic acid (CEPA) for foliar application few days after topping. While no striking difference in leaf yield by weight was obtained among the treatments when compared with control, leaf quality as expressed for shipment price in won tended when compared with control, leaf quality as expressed for shipment price in won tended to improve. The treated leaves with 300 to 900 ppm of CEPA (approximately 140 1/acre of 500 ppm) not only showed yellowing and accelerated maturity to pick 4 to 5 days with practicable optimal level earlier than control, but also speeded up to take nearly with practicable optimal level earlier than control, but also speeded up to take nearly last half of the total time required for the five stages of flue-curing. It is therefore considered that CEPA is as effective maturity-accelerating agent and useful as known for other solanaceous plants showing climacteric stage respiration, and discussions were made about physiological actions of ethylene gas released from CEPA at plant tissues sprayed.