• Korean Journal of Organic Agriculture
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• v.8 no.3
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• pp.111-120
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• 2000

In this study, by-products of rice bran, rice hull, bean curd dregs and food waste were fermented with different ratios of 26, 26, 34 and 14% respectively and the experimental diets were prepared mixing it with various ratios of commercial diets (fermented feed commercial feed : A 80 : 20, B 70 : 30, C 60 : 40, D 50:50). In Experiment I, feed intake, nutrients digestibilities and nitrogen retention were investigated and body weight gain in Experiment 1. For chemical composition of experimental diets, crude protein contents were 13.73, 13.78, 14.45 and 15.14% in A, B, C and D respectively and the contents of crude fat and crude fiber were highest in A as 8.66 and 27.82% respectively. 2. Dry hurler intakes were significantly higher (P<0.05) in A(362.06g/d) and C(358.49g/d) than B and D. Intakes of crude protein and crude fat were not significantly different (P>0.05) among treatments however those of crude fiber and crude ash were significantly higher (P>0.05) in A(101.47g/d). 3. Dry matter digestibilities in the range of 53.38∼68.81% in all treatments have shown the highest value in C of 60% fermented feed plus 40% commercial diet but the lowest in A of 80% of fermented feed plus 20% commercial diet (P<0.05). 59.85% of digestibility of crude protein in A was also lowest among all treatments (p<0.05), 4. 8.47g/d of nitrogen intake in C was recorded highest (P<0.05) however the highest nitrogen retention was marked in B of 50% fermented feed plus 50% of commercial diet due mainly to lower excretion of nitrogen through feces. 5. The data of live weight gain in Experiment II has not been shown as a result since the proper daily gain of body weight was achieved only in D as 88.89g/d and the goats in other treatments have shown frequent diarrhea. However, neglecting the animals with diarrhea, higher amounts of concentrates in the diets (C and D) showed the tendency of higher weight gain. 6. In this study, feeding 60% fermented feed manufactured with domestic agricultural by-products of rice bran, rice hull, bean curd dregs and food waste to Korean native goats have shown satisfactory results of intake and digestibility and it indicates that utilization of domestic agricultural by-products in goats could be improved by the process of fermentation. However it's effects on body weight gain and nitrogen retention were below than expected. Different sources of feedstuff for fermentation may result in different performances of animals. However, to draw overall conclusion from this study, 50∼60% of fermented feed can be recommended in the case of mixing with concentrates.

• Korean Journal of Organic Agriculture
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• v.15 no.1
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• pp.71-84
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• 2007

Predicting plant responses to changing atmospheric $CO_2$ and to the possibility of global warming are important concerns. The $CO_2$ concentration of the global atmosphere has increased during the last decades. This increase is expected to result in changes of global temperatures and this will also affect the growth and development of bell pepper (Capsicum annum L.) and other crops. The objective of this study was to evaluate the effects of atmospheric $CO_2$ enrichment and high temperature on the growth and development of bell pepper under three temperature regimes. There was no statistical difference in the days required from seeding to flowering between $CO_2$ treatments, whereas among three temperature regimes, high temperature plots of $35/25^{\circ}C$ showed the shortest days (52.5 days) required from seeding to flowering. The plant height of bell peppers 15 weeks after emergence showed no statistical significance, while plots of $30/20^{\circ}C$ showed the highest plant height among the three temperature regimes. Time-course response of plant height to $CO_2$, enrichment was restrained in high $CO_2$, concentration (800ppm), at the same time higher temperature promoted plant height. Average leaf area per plant of 400ppm was $6,008.8cm^2$ and it was $5,225.1cm^2$ in the plots of 800ppm, showing 15% more leaf area compared to 400ppm $CO_2$ concentration. Leaf dry weight between $CO_2$ concentration and among temperature regimes showed a statistical significance. The average leaf dry weight in the plot of 800ppm showed the highest (44.1g), which was 18.5% higher compared to that of 400ppm (37.2g) and among temperature regimes, it was the highest (49.8g) in the plot of $35/25^{\circ}C$. Above-ground dry weight showed statistical significance between $CO_2$ concentration and among temperature regimes. The average above-ground dry weight of 800ppm $CO_2$ concentration was 141.4g, 17.9% higher compared to 400ppm $CO_2$ concentration (119.9g). Among three temperature regimes, plots of $30/20^{\circ}C$ showed the highest average above-ground dry weight (168.9g), while plots of $35/25^{\circ}C$ were the lowest (102.3g). In the average bell pepper dry weight, 800ppm of $CO_2$ concentration showed higher bell pepper dry weight (59.5g) than that (44.3g) of 400ppm of $CO_2$ concentration. It was judged that high $CO_2$ concentration was profitable fur bell pepper yield and there was a tendency that when there was high $CO_2$, concentration (800ppm), low temperature ($25/15^{\circ}C$) was profitable for bell pepper dry weight, whereas it was the reverse ($30/20^{\circ}C$), in the case of ambient $CO_2$, concentration (400ppm). In the specific leaf area according to $CO_2$, concentration, 800ppm showed 117.4, which was 35.5% higher compared to that (159.1) of 400ppm, showing that leaf becomes thicker as $CO_2$ concentration increases. Regarding correlation coefficients among crop characteristics, leaf area was negatively correlated with the number of bell peppers per plant and bell pepper dry weight, showing that the higher the leaf area, the lower the bell pepper yield. Bell pepper dry weight per plant showed positively significant correlation with the number of bell peppers per plant and total above dry weight, which showed that the higher the number of bell peppers and the total above dry weight, the higher the bell pepper yield.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.101-123
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• 2012

Currently, Social Media, it has widely a renown keyword and its related social trends and businesses have been fastly applied into various contexts. Social media has become an important research area for scholars interested in online technologies and cyber space and their social impacts. Social media is not only including web-based services but also mobile-based application services that allow people to share various style information and knowledge through online connection. Social media users have tendency to common identity- and bond-attachment through interactions such as 'thumbs up', 'reply note', 'forwarding', which may have driven from various factors and may result in delivering information, sharing knowledge, and specific experiences et al. Even further, almost of all social media sites provide and connect unknown strangers depending on shared interests, political views, or enjoyable activities, and other stuffs incorporating the creation of contents, which provides benefits to users. As fast developing digital devices including smartphone, tablet PC, internet based blogging, and photo and video clips, scholars desperately have began to study regarding diverse issues connecting human beings' motivations and the behavioral results which may be articulated by the format of antecedents as well as consequences related to contents that people create via social media. Social media such as Facebook, Twitter, or Cyworld users are more and more getting close each other and build up their relationships by a different style. In this sense, people use social media as tools for maintain pre-existing network, creating new people socially, and at the same time, explicitly find some business opportunities using personal and unlimited public networks. In terms of theory in explaining this phenomenon, social capital is a concept that describes the benefits one receives from one's relationship with others. Thereby, social media use is closely related to the form and connected of people, which is a bridge that can be able to achieve informational benefits of a heterogeneous network of people and common identity- and bonding-attachment which emphasizes emotional benefits from community members or friend group. Social capital would be resources accumulated through the relationships among people, which can be considered as an investment in social relations with expected returns and may achieve benefits from the greater access to and use of resources embedded in social networks. Social media using for their social capital has vastly been adopted in a cyber world, however, there has been little explaining the phenomenon theoretically how people may take advantages or opportunities through interaction among people, why people may interactively give willingness to help or their answers. The individual consciously express themselves in an online space, so called, common identity- or bonding-attachments. Common-identity attachment is the focus of the weak ties, which are loose connections between individuals who may provide useful information or new perspectives for one another but typically not emotional support, whereas common-bonding attachment is explained that between individuals in tightly-knit, emotionally close relationship such as family and close friends. The common identify- and bonding-attachment are mainly studying on-offline setting, which individual convey an impression to others that are expressed to own interest to others. Thus, individuals expect to meet other people and are trying to behave self-presentation engaging in opposite partners accordingly. As developing social media, individuals are motivated to disclose self-disclosures of open and honest using diverse cues such as verbal and nonverbal and pictorial and video files to their friends as well as passing strangers. Social media context, common identity- and bond-attachment for self-presentation seems different compared with face-to-face context. In the realm of social media, social users look for self-impression by posting text messages, pictures, video files. Under the digital environments, people interact to work, shop, learn, entertain, and be played. Social media provides increasingly the kinds of intention and behavior in online. Typically, identity and bond social capital through self-presentation is the intentional and tangible component of identity. At social media, people try to engage in others via a desired impression, which can maintain through performing coherent and complementary communications including displaying signs, symbols, brands made of digital stuffs(information, interest, pictures, etc,). In marketing area, consumers traditionally show common-identity as they select clothes, hairstyles, automobiles, logos, and so on, to impress others in any given context in a shopping mall or opera. To examine these social capital and attachment, we combined a social capital theory with an attachment theory into our research model. Our research model focuses on the common identity- and bond-attachment how they are formulated through social capitals: cognitive capital, structural capital, relational capital, and individual characteristics. Thus, we examined that individual online kindness, self-rated expertise, and social relation influence to build common identity- and bond-attachment, and the attachment effects make an impact on both the willingness to help, however, common bond seems not to show directly impact on information sharing. As a result, we discover that the social capital and attachment theories are mainly applicable to the context of social media and usage in the individual networks. We collected sample data of 256 who are using social media such as Facebook, Twitter, and Cyworld and analyzed the suggested hypotheses through the Structural Equation Model by AMOS. This study analyzes the direct and indirect relationship between the social network service usage and outcomes. Antecedents of kindness, confidence of knowledge, social relations are significantly affected to the mediators common identity-and bond attachments, however, interestingly, network externality does not impact, which we assumed that a size of network was a negative because group members would not significantly contribute if the members do not intend to actively interact with each other. The mediating variables had a positive effect on toward willingness to help. Further, common identity attachment has stronger significant on shared information.

• 한국유가공학회:학술대회논문집
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• 2007.09a
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• pp.49-58
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• 2007

Inflammatory process leads to the well-known mucosal damage and therefore a further disturbance of the epithelial barrier function, resulting abnormal intestinal wall function, even further accelerating the inflammatory process[1]. Despite of the records, etiology and pathogenesis of IBD remain rather unclear. There are many studies over the past couple of years have led to great advanced in understanding the inflammatory bowel disease(IBD) and their underlying pathophysiologic mechanisms. From the current understanding, it is likely that chronic inflammation in IBD is due to aggressive cellular immune responses including increased serum concentrations of different cytokines. Therefore, targeted molecules can be specifically eliminated in their expression directly on the transcriptional level. Interesting therapeutic trials are expected against adhesion molecules and pro-inflammatory cytokines such as TNF-${\alpha}$. The future development of immune therapies in IBD therefore holds great promises for better treatment modalities of IBD but will also open important new insights into a further understanding of inflammation pathophysiology. Treatment of cytokine inhibitors such as Immunex(Enbrel) and J&J/Centocor(Remicade) which are mouse-derived monoclonal antibodies have been shown in several studies to modulate the symptoms of patients, however, theses TNF inhibitors also have an adverse effect immune-related problems and also are costly and must be administered by injection. Because of the eventual development of unwanted side effects, these two products are used in only a select patient population. The present study was performed to elucidate the ability of TNF-${\alpha}$ antibodies produced in sheep colostrums to neutralize TNF-${\alpha}$ action in a cell-based bioassay and in a small animal model of intestinal inflammation. In vitro study, inhibitory effect of anti-TNF-${\alpha}$ antibody from the sheep was determined by cell bioassay. The antibody from the sheep at 1 in 10,000 dilution was able to completely inhibit TNF-${\alpha}$ activity in the cell bioassay. The antibodies from the same sheep, but different milkings, exhibited some variability in inhibition of TNF-${\alpha}$ activity, but were all greater than the control sample. In vivo study, the degree of inflammation was severe to experiment, despite of the initial pilot trial, main trial 1 was unable to figure out of any effect of antibody to reduce the impact of PAF and LPS. Main rat trial 2 resulted no significant symptoms like characteristic acute diarrhea and weight loss of colitis. This study suggested that colostrums from sheep immunized against TNF-${\alpha}$ significantly inhibited TNF-${\alpha}$ bioactivity in the cell based assay. And the higher than anticipated variability in the two animal models precluded assessment of the ability of antibody to prevent TNF-${\alpha}$ induced intestinal damage in the intact animal. Further study will require to find out an alternative animal model, which is more acceptable to test anti-TNF-${\alpha}$ IgA therapy for reducing the impact of inflammation on gut dysfunction. And subsequent pre-clinical and clinical testing also need generation of more antibody as current supplies are low.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.57-79
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• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.197-218
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• 2019

In addition to economic growth and national income increase, China is also experiencing rapid growth in consumption of cosmetics. About 67% of the total trade volume of Chinese cosmetics is made by e-commerce and especially K-Beauty products, which are Korean cosmetics are very popular. According to previous studies, 80% of consumer goods such as cosmetics are affected by the word of mouth information, searching the product information before purchase. Mostly, consumers acquire information related to cosmetics through comments made by other consumers on SNS such as SINA Weibo and Wechat, and recently they also use information about beauty related video channels. Most of the previous online word-of-mouth researches were mainly focused on media itself such as Facebook, Twitter, and blogs. However, the informational characteristics and the expression forms are also diverse. Typical types are text, picture, and video. This study focused on these types. We analyze the unstructured data of SINA Weibo, the SNS representative platform of China, and Meipai, the video platform, and analyze the impact of K-Beauty brand sales by dividing online word-of-mouth information with quantity and direction information. We analyzed about 330,000 data from Meipai, and 110,000 data from SINA Weibo and analyzed the basic properties of cosmetics. As a result of analysis, the amount of online word-of-mouth information has a positive effect on the sales of cosmetics irrespective of the type of media. However, the online videos showed higher impacts than the pictures and texts. Therefore, it is more effective for companies to carry out advertising and promotional activities in parallel with the existing SNS as well as video related information. It is understood that it is important to generate the frequency of exposure irrespective of media type. The positiveness of the video media was significant but the positiveness of the picture and text media was not significant. Due to the nature of information types, the amount of information in video media is more than that in text-oriented media, and video-related channels are emerging all over the world. In particular, China has made a number of video platforms in recent years and has enjoyed popularity among teenagers and thirties. As a result, existing SNS users are being dispersed to video media. We also analyzed the effect of online type of information on the online cosmetics sales by dividing the product type of cosmetics into basic cosmetics and color cosmetics. As a result, basic cosmetics had a positive effect on the sales according to the number of online videos and it was affected by the negative information of the videos. In the case of basic cosmetics, effects or characteristics do not appear immediately like color cosmetics, so information such as changes after use is often transmitted over a period of time. Therefore, it is important for companies to move more quickly to issues generated from video media. Color cosmetics are largely influenced by negative oral statements and sensitive to picture and text-oriented media. Information such as picture and text has the advantage and disadvantage that the process of making it can be made easier than video. Therefore, complaints and opinions are generally expressed in SNS quickly and immediately. Finally, we analyzed how product diversity affects sales according to online word of mouth information type. As a result of the analysis, it can be confirmed that when a variety of products are introduced in a video channel, they have a positive effect on online cosmetics sales. The significance of this study in the theoretical aspect is that, as in the previous studies, online sales have basically proved that K-Beauty cosmetics are also influenced by word-of-mouth. However this study focused on media types and both media have a positive impact on sales, as in previous studies, but it has been proven that video is more informative and influencing than text, depending on media abundance. In addition, according to the existing research on information direction, it is said that the negative influence has more influence, but in the basic study, the correlation is not significant, but the effect of negation in the case of color cosmetics is large. In the case of temporal fashion products such as color cosmetics, fast oral effect is influenced. In practical terms, it is expected that it will be helpful to use advertising strategies on the sales and advertising strategy of K-Beauty cosmetics in China by distinguishing basic and color cosmetics. In addition, it can be said that it recognized the importance of a video advertising strategy such as YouTube and one-person media. The results of this study can be used as basic data for analyzing the big data in understanding the Chinese cosmetics market and establishing appropriate strategies and marketing utilization of related companies.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Asia Marketing Journal
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• v.12 no.2
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• pp.27-52
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• 2010

It is not new that today's business organizations are expected to exhibit ethical and moral management and to carry out social responsibility as a good corporate citizen. Since South Korea emerged as a newly industrialized country during the 1980s, Korean corporations have become active in carrying out their social responsibility as a good corporate citizen to society. In spite of the short history of corporate social responsibility, Korean companies have actively participated in corporate philanthropy. Corporations' significant donations to various social causes, no-lay-off policies, corporate volunteerism and green marketing are evidences of their commitment to corporate citizenship. Corporate social responsibility is now an essential management practice whereby corporation can strengthen its sustainable value creation processes by enhancing the trust assets underlying the relationships between the business and the stakeholders. Much of the conceptual work in the area of corporate social responsibility(CSR) has originated from researches conducted in the management field. Carroll(1979) proposed that corporations have four types of social responsibilities: economic, legal, ethical and philanthropic responsibility. Most past research has investigated CSR and its impact on consumers' attitudes toward the corporations and corporate performances. Although there exists a large body of literature on how consumers perceive and respond to CSR, the majority of past studies were conducted in the United States. The stability and applicability of past findings need to be tested across different national/cultural settings, especially since corporate social responsibility is a reflection of implicit conformation with the expectations and criticism that society may have toward a corporation(Matten and Moon, 2004). In this study, we explored whether people in Korea perceive CSR of Korean corporations in the same four dimensions as done in the United States and what were the measurement items tapping each of these four dimensions. In order to investigate the dimensions of CSR and the measurement items for CSR perceived by Korean people, nine focus group interviews were conducted with several stakeholder groups(two with undergraduate students, two with graduate students, three with general consumers, and two with NGO groups). Scripts from the interviews revealed that the Korean stakeholders perceived four types of CSR which are the same as those proposed by Carroll(1979). However we found CSR issues unique to Korean corporations. For example for the economic responsibility, Korean people mentioned that the corporation needed to contribute to the economic development of the country by generating corporate profits. For the legal responsibility, Koreans included the "corporation need to follow the consumer protection law." For the ethical responsibility, they considered that the corporation needed to not promote false advertisement. In addition, Koreans thought that an ethical company should do transparent management. For the philanthropic responsibility, people in Korea thought that a corporation needed to return parts of its profits to the society for the betterment of society. The 28 items were developed based on the results of the nine focus group interviews, while considering the scale developed by Maignan and Ferrell(2001). Following the procedure proposed by Churchill(1979), we started by developing an item poll consisting of 28 items and purified the initial pool of items through exploratory, confirmatory factor analyses. 176 samples were sued for this analysis. Confirmatory factor analysis was performed on the 28 items in order to verify the underlying four factor structure. Study 1 provided new measurement items for tapping the Korean CSR dimensions, which can be useful for the future studies exploring the effects of CSR on Korean consumers' attitudes toward the corporations and corporate performances. And we found the CSR scale(17 items) has good reliability, discriminant validity and nomological validity. Economic Responsibility: "XYZ company continuously improves the quality of our products", "XYZ company has a procedure in place to respond to customer complaint", "XYZ company contributes to the economic development of our country by generating profits", "XYZ company is eager to hire people". Legal Responsibility: "XYZ company's products meet legal standards", "XYZ company seeks to comply with all laws regulating hiring and employee benefits", "XYZ company honors contractual obligations to its suppliers", "XYZ company's managers try to comply with the law related to the business operation". Ethical Responsibility: "XYZ company has a comprehensive code of conduct", "XYZ company does not promote a false or misleading advertisement", "XYZ company seems to conduct a transparent business", "XYZ company does a fair business with its suppliers or sub-contractors". Philanthropic Responsibility: "XYZ company encourages partnerships with local businesses and schools", "XYZ company supports sports and cultural activities", "XYZ company gives adequate contributions to charities considering its business size", "XYZ company encourages employees to support our community". Study 2 was condusted for comprehensive validity. 655 samples were used for this anlysis. Collected samples were tested by factor analysis and Crnbach's Alpha coefficiednts and were found to be satisfactory in terms of validity and reliability. Furthermore, fitness of the measurement model was tested by using conformatory factor analysis. χ²=880.73(df=160), GFI=0.891, AGFI=0.854, NFI=0.908, NNFI=0.913, RMR=0.059, RMESA=0.070. We hope that CSR scale could greatly facilitate research on Corporate social resposibility, it is by no means the final answer.