• Journal of The Korean Association For Science Education
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• v.28 no.4
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• pp.316-330
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• 2008

During the past two decades or so, science (or scientific or scientific & technological) culture has become one of the main themes not only of policy makers but also of science educators. Although, the idea of science culture has been taken as a desirable goal, there is little agreement about what it means and how to measure it. Particularly in Korea, there has been a rapid growth of science culture projects and programs, either by governmental or non-governmental, but with little systemic monitoring and evaluation for its practice. The purpose of this study is, thus, to explore a model of measuring science culture and develop a comprehensive indicator system for it. We reviewed many literatures on definitions of science culture and the surveys for related terms, particularly, of recent national and international surveys (e.g. US Science and Engineering Indicators, Eurobarometer, Japanese Science and Technology Indicators). Based on this review, a model for science culture is proposed and then used to define the Science Culture Indicators (SCI). This model encompasses two dimensions(i.e. individual and social), which are further divided into two aspects (i.e. potential and practice). Each dimension is expected to represent citizen literacy of and national infrastructure of science culture respectively. Each category in this $2{\times}2$ matrix is further divided into several sub-categories. The discussion concerning how the model and the indicators can be used to check the states of science culture at social as well as individual levels will be given with some concrete examples, such as indicators particularly related to science education.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.49-58
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• 2010

Corporate social responsibility has become a very important issue for researchers (Greenfield, 2004; Maignan & Ralston, 2002; McWilliams et al., 2006; Pearce & Doh 2005), and many consider it necessary for businesses to define their role in society and apply social and ethical standards to their businesses (Lichtenstein et al., 2004). As a result, a significant number of retailers have adopted CSR as a strategic tool to promote their businesses. To this end, this study sought to discover U.S. consumers' attitudes and behavior in ethical purchasing and consumption based on their subjective perception and evaluation of a retailer. The objectives of this study include: 1) determine the participants awareness of retailers corporate social responsibility; 2) assess how participants evaluate retailers corporate social responsibility; 3) examine whether participants evaluation process of retailers CSR influence their attitude toward the retailer; and 4) assess if participants attitude toward the retailers CSR influence their purchase behavior. This study does not focus on actual retailers' CSR performance because a consumer's decision making process is based on an individual assessment not an actual fact. This study examines US college students' awareness and evaluations of retailers' corporate social responsibility (CSR). Fifty six college students at a major Southeastern university participated in the study. The age of the participants ranged from 18 to 26 years old. Content analysis was conducted with open coding and focused coding. Over 100 single-spaced pages of written responses were collected and analyzed. Two steps of coding (i.e., open coding and focused coding) were conducted (Esterberg, 2002). Coding results and analytic memos were used to understand participants' awareness of CSR and their ethical purchasing behavior supported through the selection and inclusion of direct quotes that were extracted from the written responses. Names used here are pseudonyms to protect confidentiality of participants. Participants were asked to write about retailers, their aware-ness of CSR issues, and to evaluate a retailer's CSR performance. A majority (n = 28) of respondents indicated their awareness of CSR but have not felt the need to act on this issue. Few (n=8) indicated that they are aware of this issue but not greatly concerned. Findings suggest that when college students evaluate retailers' CSR performance, they use three dimensions of CSR: employee support, community support, and environmental support. Employee treatment and support were found as an important criterion in evaluation of retailers' CSR. Respondents indicated that their good experience with a retailer as an employee made them have a positive perception and attitude toward the retailer. Regarding employee support four themes emerged: employee rewards and incentives based on performance, working environment, employee education and training program, and employee and family discounts. Well organized rewards and incentives were mentioned as an important attribute. The factors related to the working environment included: how well retailers follow the rules related to working hours, lunch time and breaks was also one of the most mentioned attributes. Regarding community support, three themes emerged: contributing a percentage of sales to the local community, financial contribution to charity organizations, and events for community support. Regarding environments, two themes emerged: recycling and selling organic or green products. It was mentioned in the responses that retailers are trying to do what they can to be environmentally friendly. One respondent mentioned that the company is creating stores that have an environmentally friendly design. Information about what the company does to help the environment can easily be found on the company’s website as well. Respondents have also noticed that the stores are starting to offer products that are organic and environmentally friendly. A retailer was also mentioned by a respondent in this category in reference to how the company uses eco-friendly cups and how they are helping to rebuild homes in New Orleans. The respondents noticed that a retailer offers reusable bags for their consumers to purchase. One respondent stated that a retailer uses its products to help the environment, through offering organic cotton. After thorough analysis of responses, we found that a participant's evaluation of a retailers' CSR influenced their attitudes towards retailers. However, there was a significant gap between attitudes and purchasing behavior. Although the participants had positive attitudes toward retailers CSR, the lack of funds and time influenced their purchase behavior. Overall, half (n=28) of the respondents mentioned that CSR performance affects their purchasing decisions making when shopping. Findings from this study provide support for retailers to consider their corporate social responsibility when developing their image with the consumer. This study implied that consumers evaluate retailers based on employee, community and environmental support. The evaluation, attitude and purchase behavior of consumers seem to be intertwined. That is, evaluation is based on the knowledge the consumer has of the retailers CSR. That knowledge may influence their attitude toward the retailer and thus influence their purchase behavior. Participants also indicated that having CSR makes them think highly of the retailer, but it does not influence their purchase behavior. Price and convenience seem to surpass the importance of CSR among the participants. Implications, recommendations for future research, and limitations of the study are also discussed.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• (The) Research of the performance art and culture
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• no.36
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• pp.531-551
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• 2018

The educational trait that the arts and cultural education and dance strive for at a time when the ethical tasks of life is the experience for insight of life. The awareness of time entrusted with the intensity [depth] of artistic and aesthetic experience is to contain its implication with policy and system. In the policy territory, broad perception and strategy are combined and practiced to produce new implication. Therefore, on the basis of characteristics and spectrum persuaded at a time when the arts and cultural education and dance education are broadly expanded, the result of this study after taking a look at the role of dance education within the arts and cultural education is shown as follows. The value striving for by the culture and arts education and dance education is to structure the life form with the artistic experience through the art as the ultimate life description. This is attributable to the fact that the artistic trait structured with self-understanding and self-expression contains the directivity of life that is recorded and depicted in the process of life. The dance education in the culture and arts education has the trait to view the world with the dance structure as the comprehensive study as in other textbook or art genre under the awareness of time and education system category within the school system and it has diverse social issues combined as related to the frame of social growth and advancement outside of school. When taking a look at the practical characteristics (method) of dance based on the arts and cultural education business, it facilitates the practice strategy through dance, in dance, about dance, between dance with the artist for art [dance]. At this time, the approachability of dance is deployed in a program based on diverse artistry for technology, expression, understanding, symbolism and others and it has the participation of enjoyment and preference. In the policy project of the culture and arts education, the dance education works as the function of education project as an alternative model on the education system and it also sometimes works as the function for social improvement and development to promote the community awareness and cultural transformation through the involvement and intervention of social issues.

• (The)Study of the Eastern Classic
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• no.55
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• pp.223-264
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• 2014

Yeoncheon Hong Seok-joo(淵泉 洪奭周: 1774-1842) faithfully followed a policy of restoration of literary style of king Jeongjo. He was an young vassal after 1794 and influenced by Jeongjo because Yeoncheon was around the king. Furthermore, he had comparatively favorable working period as a vassal(仕宦期, 1795-1836) after death of Jeongjo(1800) while establishing his own academic viewpoint. Therefore, a study about art theory of Yeoncheon Hong Seok-joo is one about logical system to accept various desires for change of then while not getting rid of scope of Neo-Confucianism after Jeongjo. It is catched that exchange of Hong Seok-joo and Jeong Yak-yong was made relating to study of Sangseo. Hong Seok-joo and Jeong Yak-yong absorbed in study of Sangseo, which is come from putting importance on 6 scriptures (經) among studies of scriptures by both of them. Through this, they aimed to re-discover ideology of original Confucian studies as one for cultivating oneself and governing people (修己治人之學). Dasan and Yeoncheon have something in common that they were young vassals who were cultivated as a guarding power for Jeongjo centered on Gyujanggak. They were largely fit to view of literature(文體觀) of Jeongjo. Hong Seok-joo distinguished function of prose(文) and poetry(詩) into teaching moral(明敎) and moving people(感人) in the category of Mun-yi-jae-do(文以載道) based on thoughts of 'literature is linguistic device for Taoism '(道本文末)' which is a core concept of literature theory based on Neo-Confucianism. He gave a careful attention on instructional and social function in prose while on emotional understanding that puts importance on temper and the secrets of nature in poetry. Hong Seok-joo regarded moral impression and edification through this as a core of artistic creation based on Segyoseol(世敎說). Furthermore, expressions such as 'Heunggwangunwon(興觀群怨)' or 'Yeohangguyo(閭巷謳謠) which are mentioned as important elements in his artistic works put importance on actual existence of objective things in artistic activity and this is connected to an attitude to require description fit to fact. So, it is assumed that such expression style aimed for features of genre painting in painting arts. Understanding of the study of ancient documents by Yeoncheon developed from critical perspective. He criticized the study of ancient documents, saying it as first, Pasoijisul(破碎之術), second, Dotaekjisul(塗澤之術), third, Hoimojisul(毁侮之術). Jeong Yak-yong criticized ' theory on the Odes' from viewpoint of theory of Mun-yi-jae-do(文以載道) based on Neo-Confucianism. He stressed political and social function of Sipeon and general poetry in "the Odes" and reinterprets discourses about poetry of Zhu Xi based on his own opinion. He says that poems of national fashion do political and social criticism. The theory of national fashion by Jeong Yak-yong clearly discloses his thoughts that stress practical role of noblemen in the social and political context.

• Korean Journal of Culture and Social Issue
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• v.24 no.4
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• pp.657-689
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• 2018

The purpose of this study is to develop a substantive theory on 'eating alone'(honbob)and the process of maintaining the lifestyle of eating alone for the need of a non-judgmental understanding on the new 'honbob' lifestyle. Data were collected through in-depth interviews with 10 male and female workers in Seoul and Gyeonggi-do, who voluntarily eat alone over 70% of their meals per week with the minimum duration of 5 years. Data analysis was performed using grounded theory proposed by Strauss & Corbin (1998) in the qualitative research method. As a result, a paradigm model on the process of maintaining 'honbob' was derived. Based on categorical analysis, the causal condition was 'not trying to tune' and the central phenomenon was 'following the desire to set efficiency as the top priority. Contextual conditions were 'the atmosphere of fierce competition', 'weakening of organizational culture', 'diffusion of individualistic culture'. The intervening conditions were 'personal trait and emotional experience', 'job characteristics of less organization culture'. The action/interaction strategies were 'accepting internal conflicts', 'acting in autonomy', 'finding relationship through media', and 'distancing from superficial relationship'. The consequences were 'enjoying time for self-exploration', 'valuing self-care', 'becoming a epicurean conventionalist', and 'becoming aware of the need for balance'. The core category has been shown as 'self-oriented in accordance to priority of efficiency and being able to appreciate the importance of social group'. The Such phenomenon passes through four different stages - first, the stage of weighing time efficiency while beginning hon-bob; second, the stage of conflict when one feels nervous and not free from others' view; third, the stage of adjustment to justify his/her 'hon-bob'; and the final stage of balance to perceive the importance of social group while going on 'honbob'. The study had the aim of increasing the understanding and acceptance of the new 'honbob' lifestyle through an in-depth exploration of office worker's 'honbob' experience and the process of maintaining 'honbob' so the society can better accept it and, further, to embrace co-existence of various cultures.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.45-69
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• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Korean Journal of Social Welfare
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• v.59 no.2
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• pp.5-38
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• 2007

This study attempts to develop a theory on the evolving process of wealthy major donors' sharing lives in Korea through a grounded theory approach. To conduct this study, the researchers have in-depth interviews with 11 exemplary wealthy major donors who have more than one million US dollars in his or her own asset and donate more than ten thousand US dollars annually. In data analysis, this study identifies 161 concepts on the evolving process of wealthy major donors' sharing lives; and the concepts are categorized with 33 sub-categories and 14 categories. In the paradigm model on the evolving process of wealthy major donors' sharing lives, it is identified that the central phenomenon, 'practicing sharing lives as noblesse oblige', is related with the causal conditions such as 'learning through memories and observation', 'realizing my duties', and 'emphasizing'; and the central phenomenon is related with the contingent conditions such as 'being sensitive to external evaluation', 'having limited information on giving', 'distrusting donation related environments'. The action/interactional sequences such as 'utilizing relationships' and 'strengthening active participation' are accomplished by moderating conditions such as 'having internal and external supports' and 'guiding by firm conviction'. It reveals that as a result, wealthy major donors enjoy the feeling of becoming a ideal and true wealthy person, establish sharing lives as firm and major parts of overall lives, and experience strong desires for better future and society. In this study, 'generous sharing that shares personal heritages and social benefits' is analyzed as a core category; it shows that sharing of wealthy major donors is related to the characteristics of generosity practice based on moral self-benefiting rather than complete altruistic characteristics or self-sacrificial characteristics. The process analysis reveals that it has the following stages: first, initial giving by exposure to causes or requests; second, routine practice of giving; third, evolution of practice of giving with gradual expansion in quantities and qualities; and fourth, living with giving. In the process, the following four types are identified: devoted wealthy donors for sharing, wealthy donors practicing sharing in daily life, wealthy donors practicing sharing with learning on external stimulus, and wealthy donors practicing sharing on empathy. Finally, this study discusses both meanings of identifying and developing a theory on the evolving process of wealthy major donors' sharing lives and implications of the research results in cultivating and developing potential wealthy major donors in Korea.