• Information Systems Review
• /
• v.20 no.4
• /
• pp.59-78
• /
• 2018

With the advent of the various device types and marketing communication, customer's search and purchase behavior have become more complex and segmented. However, extant research on multichannel marketing effects of the purchase funnel has not reflected the specific features of device User Interface (UI) and User Experience (UX). In this study, we analyzed the marketing channel effects of multi-device shoppers using a unique click stream dataset from global online retailers. We examined device types that activate online shopping and compared the differences between marketing channels that promote visits. In addition, we estimated the direct and indirect effects on visits and purchase revenue through customer's accumulated experience and channel conversions. The findings indicate that the same customer selects a different marketing channel according to the device selection. These results can help retailers gain a better understanding of customers' decision-making process in multi-marketing channel environment and devise the optimal strategy taking into account various device types. Our empirical analyses yield business implications based on the significant results from global big data analytics and contribute academically meaningful theoretical framework using an economic model. We also provide strategic insights attributed to the practical value of an online marketing manager.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.123-139
• /
• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• Korean Journal of Ecology and Environment
• /
• v.49 no.3
• /
• pp.197-207
• /
• 2016

This study aims at providing basic data to objectively evaluate the areas suitable for reintroduction of the species of Asiatic black bear (Ursus thibetanus) in order to effectively preserve the Asiatic black bears in the Korean protection areas including national parks, and for the species restoration success. To this end, this study predicted the potential habitats in East Asia, Southeast Asia and India, where there are the records of Asiatic black bears' appearances using the Maxent model and environmental variables related with climate, topography, road and land use. In addition, this study evaluated the effects of the relevant climate and environmental variables. This study also analyzed inhabitation range area suitable for Asiatic black and geographic change according to future climate change. As for the judgment accuracy of the Maxent model widely utilized for habitat distribution research of wildlife for preservation, AUC value was calculated as 0.893 (sd=0.121). This was useful in predicting Asiatic black bears' potential habitat and evaluate the habitat change characteristics according to future climate change. Compare to the distribution map of Asiatic black bears evaluated by IUCN, Habitat suitability by the Maxent model were regionally diverse in extant areas and low in the extinct areas from IUCN map. This can be the result reflecting the regional difference in the environmental conditions where Asiatic black bears inhabit. As for the environment affecting the potential habitat distribution of Asiatic black bears, inhabitation rate was the highest, according to land coverage type, compared to climate, topography and artificial factors like distance from road. Especially, the area of deciduous broadleaf forest was predicted to be preferred, in comparison with other land coverage types. Annual mean precipitation and the precipitation during the driest period were projected to affect more than temperature's annual range, and the inhabitation possibility was higher, as distance was farther from road. The reason is that Asiatic black bears are conjectured to prefer more stable area without human's intervention, as well as prey resource. The inhabitation range was predicted to be expanded gradually to the southern part of India, China's southeast coast and adjacent inland area, and Vietnam, Laos and Malaysia in the eastern coastal areas of Southeast Asia. The following areas are forecast to be the core areas, where Asiatic black bears can inhabit in the Asian region: Jeonnam, Jeonbuk and Gangwon areas in South Korea, Kyushu, Chugoku, Shikoku, Chubu, Kanto and Tohoku's border area in Japan, and Jiangxi, Zhejiang and Fujian border area in China. This study is expected to be used as basic data for the preservation and efficient management of Asiatic black bear's habitat, artificially introduced individual bear's release area selection, and the management of collision zones with humans.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.201-220
• /
• 2019

Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.23 no.4
• /
• pp.329-339
• /
• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• Cartoon and Animation Studies
• /
• s.28
• /
• pp.209-233
• /
• 2012

The animation cluster in Korea has begun as a part of the local cultural cluster in the late 1990s with components of companies, local governments, educational institutions, and human resources, which were necessary to run the cluster. And, the animation cluster was initiated for the purpose of encouraging regional economies, but the basic unit was the local on a small scale. Because of this inherent weakness in the local cluster, it was needed to add some additional strategies that could expand the local animation industry into the formal leading industry. That is why the development policy was set up, and the local promotion agency based on this policy was established. It has been several years to manage the local promotion agency, and it is reported that there have been some visible effects. But, it is found out that analyzing the outcome of small unit cluster on the basis of existing criteria on a large scale is not reliable, which means it is not possible to evaluate the outcome of local cluster in a material way. Some examples of problems are as follows. First, the local cluster was made not autonomously but deliberately. Second, the animation cluster of each province has the same market as its target. Therefore, this research - on the basis of the diamond model - focuses on analyzing the existence and role of local promotion agencies rather than evaluating the outcome itself. Through the cases of two provincial cities, Chuncheon and Bucheon, this research examines if it is possible to evaluate the outcome of local clusters managed by promotion agencies.

• Computational Structural Engineering
• /
• v.7 no.3
• /
• pp.95-103
• /
• 1994

The safety related components in the nuclear power plant should be designed to withstand the seismic load. Among these components the integrity of reactor internals under earthquake load is important in stand points of safety and economics, because these are classified to Seismic Class I components. So far the modelling methods of reactor internals have been investigated by many authors. In this paper, the dynamic behaviour of reactor internals of Yong Gwang 1&2 nuclear power plants under SSE(Safe Shutdown Earthquake) load is analyzed by using of the simpled Global Beam Model. For this, as a first step, the characteristic analysis of reactor internal components are performed by using of the finite element code ANSYS. And the Global Beam Model for reactor internals which includes beam elements, nonlinear impact springs which have gaps in upper and lower positions, and hydrodynamical couplings which simulate the fluid-filled cylinders of reactor vessel and core barrel structures is established. And for the exciting external force the response spectrum which is applied to reactor support is converted to the time history input. With this excitation and the model the dynamic behaviour of reactor internals is obtained. As the results, the structural integrity of reactor internal components under seismic excitation is verified and the input for the detailed duel assembly series model could be obtained. And the simplicity and effectiveness of Global Beam Model and the economics of the explicit Runge-Kutta-Gills algorithm in impact problem of high frequency interface components are confirmed.

• Journal of Digital Convergence
• /
• v.16 no.5
• /
• pp.173-183
• /
• 2018

In this study, we tried to examine the effect of service quality on the current industrial product B2B trading market on the degree of sustainable purchase for employees engaged in industrial product B2B trading market. We gathered data from questionnaires from employees who worked in the industrial product B2B trading market for this research. Empirical analysis is carried out through the collected questionnaire materials and finally the research model is finally verified using reliability analysis, validity analysis, discrimination validity analysis, and structural equation model fitness test, and finally Analysis of differences between cooperating companies and vendor, analysis of differences between companies engaged in purchasing industrial materials and developers. The results of the research analysis did not positively influence the quality of the relationship with relativity satisfaction with ease of information exchange and adaptability did not have a positive influence on the quality of the relationship. However, product service exchange, product development cooperation, adaptability, correspondence, reliability had a positive influence on the quality of relationship with relation satisfaction. Relationship of parameters The satisfaction has a positive influence on the quality of the relationship, the degree of sustainable purchase, and eventually the quality of the relationship has a positive influence on each successive purchase. By using the results of this research it is possible to confirm the factors which directly or indirectly influence the strengthening of the relationship between suppliers and purchasers in the industrial material B2B trading market and provide the basis for strategy to B2B trading companies It seems to be meaningful to offer.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.1
• /
• pp.111-120
• /
• 2017

In this paper, we propose novel feature extraction algorithm for classification of seabed sediment. In previous researches, acoustic reflection coefficient has been used to classify seabed sediments, which is constant in terms of frequency. However, attenuation of seabed sediment is a function of frequency and is highly influenced by sediment types in general. Hence, we developed a feature vector by using attenuation variation with respect to frequency. The attenuation variation is obtained by using reflected signal from the second sediment layer, which is generated by broadband chirp. The proposed feature vector has advantage in number of dimensions to classify the seabed sediment over the classical scalar feature (reflection coefficient). To compare the proposed feature with the classical scalar feature, dimension of proposed feature vector is reduced by using linear discriminant analysis (LDA). Synthesised acoustic amplitudes reflected by seabed sediments are generated by using Biot model and the performance of proposed feature is evaluated by using Fisher scoring and classification accuracy computed by maximum likelihood decision (MLD). As a result, the proposed feature shows higher discrimination performance and more robustness against measurement errors than that of classical feature.

• Journal of dental hygiene science
• /
• v.17 no.1
• /
• pp.20-29
• /
• 2017

The purpose of this study was to investigate the validity and reliability of the Korean version of a tool used to measure dental anxiety and fear. The Index of Dental Anxiety and Fear ($IDAF-4C^+$) was translated into Korean, and modified and revised to adapt to Korean culture. A survey was conducted among 457 patients in a dental clinic. The validity and reliability were determined using PASW Statistics ver. 18.0 and IBM SPSS AMOS ver. 21.0. Factor analysis showed that Korean version of $IDAF-4C^+$ was composed of three elements: dental anxiety, dental phobia, feared stimulus. The validity of the model was examined by confirmatory factor analysis and satisfied relevant requirements. All elements had convergent validity and discriminant validity exceeding requirements to ensure validity. Cronbach's ${\alpha}$ showed good reliability. In conclusion, the findings of this study demonstrate that the Korean version of $IDAF-4C^+$ has high validity and reliability. Furthermore, it can be used in clinical practice and research to decrease dental anxiety and fear.