• Journal of the Korean earth science society
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• v.30 no.6
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• pp.721-733
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• 2009

A pattern of tropical cyclone (TC) movement in the western North Pacific area was studied using the empirical orthogonal function (EOF) and the best track data from 1951 to 2007. The independent variable used in this study was defined as the frequency of tropical cyclone passage in 5 by 5 degree grid. The $1^{st}$, $2^{nd}$ and $3^{rd}$ modes were the east-west, north-south and diagonal variation patterns. Based on the time series of each component, the signs of first and second mode changed in 1997 and 1991, respectively, which seems to be related to the fact that the passage frequency was higher in the South China Sea for 20 years before 1990s, and recent 20 years in the East Asian area. When the eigen vectors were negative values in the first and second modes and TC moves into the western North Pacific, TC was formed mainly at the east side relatively compared to the case of the positive eigen vectors. The first mode seems to relate to the pressure pattern at the south of Lake Baikal, the second mode the variation pattern around $30^{\circ}N$, and the third mode the pressure pattern around Japan. The first mode was also closely related to the ENSO and negatively related to the $Ni\tilde{n}o$-3.4 index in the correlation analysis with SST anomalies.

• Management & Information Systems Review
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• v.36 no.2
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• pp.277-306
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• 2017

Most past studies on the Critical Success Factors of Company Informatization focused on the completeness of Informatization and its financial effect, and there have not been enough studies on whether a company's management strategies can be supported by establishing Informatization direction. This implies that there must be verification on the followings; whether Informatization focuses on steering the implementation of management strategies, what correlation there are between major mechanism factors and Informatization performance. This also implies that there must be a new study to re-interpret the existing success factors of Informatization into strategic management paradigm. The purpose of this study is to empirically verify the influence of subject, environment, resource, and mechanism factors on informatization achievement, and to analyze the differences in influence of informatization success factors on informatization achievement depending on domestic large corporations and SMEs. This study presented the verification results for seven research hypotheses. It was confirmed through empirical analysis that securing resource factor was significant in informatization performance and that all sub-factors of learning mechanism and coordination mechanism were also significant in enterprise informatization achievement. In addition, it was confirmed through the control effect analysis depending on enterprise size that the differences in informatization performance of large corporations and SMEs are due to support environment factor, learning mechanism, and selection mechanism. The implications of this study are as follows: First, the significance of mechanism factors such as learning, internal coordination, and external coordination are relatively higher than other factors in informatization achievement. Secondly, informatization success factors that SMEs must focus on achieving are presented by analyzing the differences on informatization achievement of large corporations and SMEs. Third, since empirical research for informatization success mechanism factors not covered empirically in the prior research was directly progressed, it is thought that it could provide a comprehensive understanding for mechanism factors. In addition, this study is thought to provide a practical contribution that can be applied to other industrial areas and enterprises.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Astronomy and Space Sciences
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• v.26 no.4
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• pp.425-438
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• 2009

We reevaluate the Burton equation (Burton et al. 1975) of predicting Dst index using high quality hourly solar wind data supplied by the ACE satellite for the period from 1998 to 2006. Sixty magnetic storms with monotonously decreasing main phase are selected. In order to determine the injection term (Q) and the decay time ($\tau$) of the equation, we examine the relationships between $Dst^*$ and $VS_s$, ${\Delta}Dst^*$ and $VS_s$, and ${\Delta}Dst^*$ and $Dst^*$ during the magnetic storms. For this analysis, we take into account one hour of the propagation time from the ACE satellite to the magnetopause, and a half hour of the response time of the magnetosphere/ring current to he solar wind forcing. The injection term is found to be $Q(nT/h)\;=\;-3.56VS_s$ for $VS_s$ > 0.5mV/m and Q(nT=h) = 0 for $VB_s\;{\leq}\;0.5mV/m$. The $\tau$ (hour) is estimated as $0.060Dst^*\;+\;16.65$ for $Dst^*$ > -175nT and 6.15 hours for $Dst^*\;{\leq}\;-175nT$. Based on these empirical relationships, we predict the 60 magnetic storms and find that the correlation coefficient between the observed and predicted $Dst^*$ is 0.88. To evaluate the performance of our prediction scheme, the 60 magnetic storms are predicted again using the models by Burton et al. (1975) and O'Brien & McPherron (2000a). The correlation coefficients thus obtained are 0.85, the same value for both of the two models. In this respect, our model is slightly improved over the other two models as far as the correlation coefficients is concerned. Particularly our model does a better job than the other two models in predicting intense magnetic storms ($Dst^*\;{< \atop \sim}\;-200nT$).

• Journal of Korea Technology Innovation Society
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• v.19 no.3
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• pp.465-482
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• 2016

Previous researches have introduced various ways to analyze the impact of standardization on innovation while the works are not only small in number but based on interview or case study. This paper addresses the impact of standardization activities within South Korean industries on technological innovation applying an empirical analysis of standardization activities and technological innovation. Drawing on Korean Industrial Standards Classification from panel data of 2003 to 2012, we employed corresponding data of each industrial classification: Number of standards, Accumulated number of standards, Number of patents applied in Korea, Sales, Operational profit, Intangible asset, and R&D invest. In the first model, we run panel data models employing the number of patents applied in Korea as an independent variable, and the number of standards, accumulated number of standards, sales, and operational profit as dependent variables to observe industrial impacts upon the relationship between standards and patents, along with time lagged consideration. The result shows that number of standards are revealed to have a negative influence on patent applications in the year of research, and no significant effect appears for the next two years while positive effect shows up on the third year. Meanwhie, accumulated number of standards turned out to have positive effects on patent applications in Korea. This implies it takes time for innovation subjects to embrace newly established standards while having a significant amount of positive effect on technological innovation in the long term. In the second model, we use canonical correlation analysis to find industrial-wide characteristics. The result of this model is equivalent to the result of panel data analysis except in a few industries, where some industry specific characteristics appear. The implications of our results present that Korean policy makers have to take account of industrial effects on standardization to promote technological innovation.

• Journal of Oriental Neuropsychiatry
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• v.16 no.1
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• pp.1-17
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• 2005

Objective : This empirical research is performed to recognize diagnostic concept, pattern identification, and clinical features of Hwa-byung. In other words, the aims of this research are to examine the differences of the diagnosis between Hwa-Byung and the other psychiatric disorders, and to find out pattern identification, and clinical characteristics of Hwa-Byung for prescriptions of this syndrome. Method : In the experiment, there were participated 30 patients who were met for our criterions according to HBDIS (Hwa-Byung Diagnostic interview Schedule). These patients were diagnosed as Axis1 according to criterions of DSM-IV with administering SCID-I. OMS-prime was utilized for finding out pattern identification of oriental medicine. Symptom Check List-90-Revision(SCL-90-R), Hemilton rating Scale for Depression(HRSD), Heart Rate Variability(HRV), and Digital Infrared Thermographic imaging(D.I.T.I.) were also utilized to discover clinical characteristics of Hwa-Byung Patients. Results : 1. Regarding Sex-ratio, male subjects were 3(10%), and female subjects are 27(90%). The age of subjects ranged from 22 year old to 75 $(51.87{\pm}11.04;\:Mean{\pm}SD)$ 2. In the results of diagnosis on the basis of DSM-IV, the 17(56.67%) patients were MOD (Major Depressive Disorder), the 5(16.67%) patients were USD (Undifferentiated Somatoform Disorder), the 4(13.33%) patients were Dysthymic Disorder, the 3(10%) patients were GAD (Generalized Anxiety Disorder), and the 1(3.33%) was Panic Disorder. Two of the patients who diagnosed as MOD were diagnosed as Panic Disorder too, and one of them was diagnosed as Pain Disorder too. 3. Regarding pattern identification, Hwa-Byung is positively correlated to deficiency of Heart(心). and then to stagnancy of Liver-Gall bladder. Hwa-Byung is correlated deficiency symptom-complex rather than excessiveness symptom-complex. That is also correlated positively to Pathological heat and fire. 4. In SCL90-R, the mean of PSDI was $(75.3{\pm}10.7;\:Mean{\pm}SD)$. The each mean of the other 11 factors was distributed between50-70. 5. The mean of HRSD was $(17.9{\pm}5.6;\:Mean{\pm}SD)$ in the entire subject's group. Then the group of MDD was $20.9{\pm}4.4$ and the group of USD was $12.0{\pm}4.8$ 6. In the results of HRV. the mean of TP is $972.4{\pm}1174(Mean{\pm}SD)$, this is lower than normal range 1000-200. The other factors were within normal range. Then, there were no significant differences between them (p<0.05). 7. The temperatures of each acupoint have significant differences between HNl(印堂) and PC6(內關), between CV17(顫中) and PC6(內關), between HN1(印堂) and CV8(神闕), between CV17(顫中) and CV8(神闕) in comparison with the average of body temperature in the use of D.I.T.I. (p<0.01) 8. In the analysis of correlation between SCL-90-R, HRSD, HRV. and D.I.T.I. there were no significant results. According to results that the correlation was analyzed with only the MDD group as subjects, there was negative correlation between RMSSD of HRV and HRSD, between LF of HRV and PDSIof SCL-90-R, and between LF/HF of HRV and ANX, PSY, and PDSI of SCL-90-R. Conclusion : In the observation of clinical features of 30 cases of Hwa-Byung patients by using diverse structured tests, there could make diverse diagnosis as depressive disorder, anxiety disorder, and Somatoform Disorder. Particularly. MDD was highly distributed. Considering oriental medicine's pattern identification of Hwa-Byung, this syndrome is related strongly to Heart, and there were demonstrated deficiency symptom-complex, and Pathological heat and fire. One of the limits of this study is lack of control subject's group, therefore, in the future study, it requires reexamination through a comparative research with these data to complete this study.

• Knowledge Management Research
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• v.22 no.4
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• pp.71-85
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• 2021

The purpose of this study is to find out which artificial intelligence methodology is most suitable for creating a foreign exchange rate prediction model using the indicators of bond market and interest rate market. KTBs and MSBs, which are representative products of the Korea bond market, are sold on a large scale when a risk aversion occurs, and in such cases, the USD/KRW exchange rate often rises. When USD liquidity problems occur in the onshore Korean market, the KRW Cross-Currency Swap price in the interest rate market falls, then it plays as a signal to buy USD/KRW in the foreign exchange market. Considering that the price and movement of products traded in the bond market and interest rate market directly or indirectly affect the foreign exchange market, it may be regarded that there is a close and complementary relationship among the three markets. There have been studies that reveal the relationship and correlation between the bond market, interest rate market, and foreign exchange market, but many exchange rate prediction studies in the past have mainly focused on studies based on macroeconomic indicators such as GDP, current account surplus/deficit, and inflation while active research to predict the exchange rate of the foreign exchange market using artificial intelligence based on the bond market and interest rate market indicators has not been conducted yet. This study uses the bond market and interest rate market indicator, runs artificial neural network suitable for nonlinear data analysis, logistic regression suitable for linear data analysis, and decision tree suitable for nonlinear & linear data analysis, and proves that the artificial neural network is the most suitable methodology for predicting the foreign exchange rates which are nonlinear and times series data. Beyond revealing the simple correlation between the bond market, interest rate market, and foreign exchange market, capturing the trading signals between the three markets to reveal the active correlation and prove the mutual organic movement is not only to provide foreign exchange market traders with a new trading model but also to be expected to contribute to increasing the efficiency and the knowledge management of the entire financial market.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.

• Journal of Distribution Science
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• v.10 no.3
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• pp.51-61
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• 2012

This study seeks to understand how the choice of a coffee shop is related to a customer's loyalty and which characteristics of a shop influence this choice. It considers large-sized coffee shops brands whose market scale has gradually grown. The users' choice of shop is determined by price, employee service, shop location, and shop atmosphere. The study investigated the effects of these four properties on the brand attitudes of coffee shops. The effects were found to vary depending on users' characteristics. The properties with the largest influence were shop atmosphere and shop location Therefore, the purpose of the study was to examine the properties that could help coffee shops get loyal customers, and the choice properties that could satisfy consumers' desires The study examined consumers' perceptions of shop properties at selection of coffee shop and the difference between perceptual difference and coffee brand in order to investigate customers' desires and needs and to suggest ways that could supply products and service. The research methodology consisted of two parts: normative and empirical research, which includes empirical analysis and statistical analysis. In this study, a statistical analysis of the empirical research was carried out. The study theoretically confirmed the shop choice properties by reviewing previous studies and performed an empirical analysis including cross tabulation based on secondary material. The findings were as follows: First, coffee shop choice properties varied by gender. Price advantage influenced the choice of both men and women; men preferred nearer coffee shops where they could buy coffee easily and more conveniently than women did. The atmosphere of the coffee shop had the greatest influence on both men and women, and shop atmosphere was thought to be the most important for age analysis. In the past, customers selected coffee shops solely to drink coffee. Now, they select the coffee shop according to its interior, menu variety, and atmosphere owing to improved quality and service of coffee shop brands. Second, the prices of the brands did not vary much because the coffee shops were similarly priced. The service was thought to be more important and to elevate service quality so that price and employee service and other properties did not have a great influence on shop choice. However, those working in the farming, forestry, fishery, and livestock industries were more concerned with the price than the shop atmosphere. College and graduate school students were also affected by inexpensive price. Third, shop choice properties varied depending on income. The shop location and shop atmosphere had a greater influence on shop choice. The customers in an income bracket of less than 2 million won selected low-price coffee shops more than those earning 6 million won or more. Therefore, price advantage had no relation with difference in income. The higher income group was not affected by employee service. Fourth, shop choice properties varied depending on place. For instance, customers at Ulsan were the most affected by the price, and the ones at Busan were the least affected. The shop location had the greatest influence among all of the properties. Among the places surveyed, Gwangju had the least influence. The alternate use of space in a coffee shop was thought to be important in all the cities under consideration. The customers at Ulsan were not affected by employee service, and they selected coffee shops according to quality and preference of shop atmosphere. Lastly, the price factor was found to be a little higher than other factors when customers frequently selected brands according to shop properties. Customers at Gwangju reacted to discounts more than those in other cities did, and the former gave less priority to the quality and taste of coffee. Brand preference varied depending on coffee shop location. Customers at Busan selected brands according to the coffee shop location, and those at Ulsan were not influenced by employee kindness and specialty. The implications of this study are that franchise coffee shop businesses should focus on customers rather than aggressive marketing strategies that increase the number of coffee shops. Thus, they should create an environment with a good atmosphere and set up coffee shops in places that customers have good access to. This study has some limitations. First, the respondents were concentrated in metropolitan areas. Secondary data showed that the number of respondents at Seoul was much more than that at Gyeonggi-do. Furthermore, the number of respondents at Gyeonggi-do was much more than those at the six major cities in the nation. Thus, the regional sample was not representative enough of the population. Second, respondents' ratio was used as a measurement scale to test the perception of shop choice properties and brand preference. The difficulties arose when examining the relation between these properties and brand preference, as well as when understanding the difference between groups. Therefore, future research should seek to address some of the shortcomings of this study: If the coffee shops are being expanded to local areas, then a questionnaire survey of consumers at small cities in local areas shall be conducted to collect primary material. In particular, variables of the questionnaire survey shall be measured using Likert scales in order to include perception on shop choice properties, brand preference, and repurchase. Therefore, correlation analysis, multi-regression, and ANOVA shall be used for empirical analysis and to investigate consumers' attitudes and behavior in detail.

• Knowledge Management Research
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• v.17 no.2
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• pp.131-163
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• 2016

The purpose of this study is to empirically analyze how social comparative learning of forum participants affects learning effects with an emphasis on participants' characteristics. As today's society is changing at a fast pace, the desire for new knowledge and information has grown accordingly. To quench this thirst for knowledge and information, seminars, symposiums, conferences, forums, conventions, exhibitions, and more are taking place as part of knowledge sharing events across the world. Also, the increased need for knowledge and information exchange has led the development and growth of the convention industry and Meetings, Incentives, Conferences, and Events (Exhibitions)(MICE) industry. Especially, forum is a type of event which invites professionals and specialists to discuss diverse topics and share their knowledge and experience with the audience. The participants utilize it as an opportunity to get close to information providers and enjoy the pleasure of knowledge exchange. However, there have been few empirical analyses on who the participants are, why they attend forum, how they pick up and learn new information and knowledge, and what kinds of learning effects they achieve after the event. This paper is to analyze how social comparative learning of the forum's participants influences learning effects based on Albert Bandura's Social Learning Theory (1977, 1997, 1982. 2001) and Leon Festinger's Social Comparative Theory (1950, 1954). By dividing the participants into two groups, one with high level of self-efficacy and the other with low level of self-efficacy, we have examined the differences in learning effects between the two groups using them as moderating variables. This study was conducted in 'MBN Y Forum 2016,' which is one of the most representative knowledge exchange forums of South Korea. An online survey was distributed out and, 1,307(39.2%) out of the total participants of 3,338 have completed the survey. The survey included questions about whether the participants have gained positive or negative motivations by comparing themselves to the speakers (upward comparison learning) and other participants (lateral comparison learning). The results have shown the quality of messages that the speakers are presenting as knowledge providers is the most significant factor that acts on learning effects. Particularly, the participants had higher levels of self-efficacy and self-esteem than average people. They had a clear goal to learn from the speakers (upward comparison) and received positive motivations from them. In other words, no negative learning effects had been found. This presents a managerial implication that having a qualified speaker is necessary for a forum to be successful. On the other hand, the results from the comparison with the other participants (lateral comparison) were different. The participants were likely to compare themselves to the other participants through observational learning. They could compare listening attitudes, language skills, or capabilities to ask a question. The results have showed the participants received positive motivations from the lateral group but at the same time were jealous of abilities of the others. When the quality of a question by a participant is not good enough, it can have a negative influence on the participants' learning effects. The first group with high levels of self-efficacy and self-esteem had no correlation to negative learning effects from the speakers. They rather had a strong desire to learn from the speakers. On the contrary, the participants perceived the lateral group as a learning subset and competitor. The second group with low levels of self-efficacy and self-esteem saw the quasi-group as a rival. This presents that the individual learning effects can be different depending on the participants' characteristics.