• Korean Journal of Heritage: History & Science
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• v.55 no.4
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• pp.56-70
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• 2022

Tombs No. 39 and No. 63 in Gyo-dong, Changnyeong, are unique in the Changnyeong area in that they do not have additional burials because they are hoenggu-style tombs with an entrance on the north side. This study tried to understand the nature and meaning of the two separate stone walls at the entrance of the tomb along with the burial process of the tomb. These two stone walls mark small tombs built independently within a large tomb, with stone wall No. 39 stone wall No. 3 (No.39-3) and No. 63 stone wall No. 3 (No. 63-3). Both units are located in the middle of the northern wall of the burial body part and share one wall with the burial body part wall stone. All animal fluids inside the stone wall were identified. In particular, it was estimated that at least three dogs were buried as a result of identification of animal fluids No. 63-3. Above all, these animals have their heads facing outward with their backs to the main occupants, and do not overlap in a limited space and are placed side by side. Changnyeong Gyo-dong No. 39-3 and 63-3 were created in the process of building the burial body, and although they are independent relics, they form a subordinate relationship in that they were built along the main burial within one tomb. In addition, it is coercive in that it is placed in an orderly manner according to a certain direction in a state that has not been dismantled after killing an animal. Therefore, It is understood to be the SHUNJANG of dogs. Studies on animal fluids excavated from tombs in the Three Kingdoms period are interpreted as animal stewardship, sacrificial collection, and animal sacrifice depending on their location, and this is known as a series of animal sacrifice rites, namely, animal stewardship and sacrifice. This recognition is based on material objectification of animals, such as food or sacrifices. However, Changnyeong Gyo-dong No. 39-3 and 63-3 are different in that they recognize animals as spiritual beings in the process of funeral rites and are closely related to the ideology that there is life after death. In addition, analysis of the location and directionality of the remains is also required from multiple angles. These two SHUNJANG correspond to the entrance to the tomb, and the location is the most open space at the entrance. The appearance of a dog looking outward, etc., can also be interpreted as the meaning of protecting the tombs and byeoksa. This appearance can be compared with the dog depicted in a mural in a Goguryeo tomb that reflects the ancient world's thought and stone figures excavated from the tomb of King Muryeong of Baekje, and it is also consistent with the meaning of the JINMYOSU protecting the ancient tombs. This suggests that a multifaceted study on animal fluid burial remains is needed in the future.

• Journal of the Korean Society of Radiology
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• v.85 no.3
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• pp.581-595
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• 2024

Purpose The present study aimed to investigate the frequency and extent of compensatory common bile duct (CBD) dilatation after cholecystectomy, assess the time between cholecystectomy and CBD dilatation, and identify potentially useful CT findings suggestive of obstructive CBD dilatation. Materials and Methods This retrospective study included 121 patients without biliary obstruction who underwent multiple CT scans before and after cholecystectomy at a single center between 2009 and 2011. The maximum short-axis diameters of the CBD and intrahepatic duct (IHD) were measured on each CT scan. In addition, the clinical and CT findings of 11 patients who were initially excluded from the study because of CBD stones or periampullary tumors were examined to identify distinguishing features between obstructive and non-obstructive CBD dilatation after cholecystectomy. Results The mean (standard deviation) short-axis maximum CBD diameter of 121 patients was 5.6 (± 1.9) mm in the axial plane before cholecystectomy but increased to 7.9 (± 2.6) mm after cholecystectomy (p < 0.001). Of the 106 patients with a pre-cholecystectomy axial CBD diameter of < 8 mm, 39 (36.8%) showed CBD dilatation of ≥ 8 mm after cholecystectomy. Six of the 17 patients with long-term (> 2 years) serial follow-up CT scans (35.3%) eventually showed a significant (> 1.5-fold) increase in the axial CBD diameter, all within two years after cholecystectomy. Of the 121 patients without obstruction or related symptoms, only one patient (0.1%) showed IHD dilatation > 3 mm after cholecystectomy. In contrast, all 11 patients with CBD obstruction had abdominal pain and abnormal laboratory indices, and 81.8% (9/11) had significant dilatation of the IHD and CBD. Conclusion Compensatory non-obstructive CBD dilatation commonly occurs after cholecystectomy to a similar extent as obstructive dilatation. However, the presence of relevant symptoms, significant IHD dilatation, or further CBD dilatation 2-3 years after cholecystectomy should raise suspicion of CBD obstruction.

• The Journal of Korean Society for Radiation Therapy
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• v.24 no.2
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• pp.67-75
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• 2012

Purpose: The study is to check the specialty of radiotherapists working in the department of radiation oncology and find job satisfaction, organizational commitment and job commitment having an effect on professional parts. After making analysis of the mutual relation, it is to provide radiotechnologists with making progress in the future. Materials and Methods: From March 2 to March 30, we had carried out a survey with email. It is possible to have 272 questionnaires answered in the survey. We make use of SPSS 13.0 for Windows to analyze the data collected for study. Frequency and a percentage are meant to show general characteristics, and t-test and ANOVA to do the difference between general properties and professionalism. Pearson's correlation coefficient also is meant to do the correlation of professionalism, organizational job commitment and job satisfaction, and multiple regression analysis to do the factor for a relevant variable to affect professionalism. Results: There are subdivisions in the professionalism informing us of the self-regulation $17.74{\pm}2.32/3.55{\pm}.46$, a sense of calling $17.58{\pm}2.63/3.52{\pm}.53$, reference of the professional $17.14{\pm}2.39/3.43{\pm}.48$, service to the public $15.97{\pm}2.48/3.19{\pm}50$, and autonomy $15.68{\pm}2.28/3.14{\pm}46$. Grand mean turns out to be $83.89{\pm}7.63$(Summation of items)/$3.37{\pm}0.49$ (Numbers of items). When it comes to a statistical relation between general characteristics and professionalism, the statistics have it that these come within age (P<.001), period of employment (P<.001), education status (P<.05), a monthly income (P<.001), radiotherapists who get a special license (P<.001), the position (P<.001), and an opportunity for developing (P<.001). As a result of organizational commitment, job commitment, and job satisfaction, grand mean in organizational commitment proves to be $80.10{\pm}8.15/3.34{\pm}.34$. There are subvisions showing affective commitment $28.64{\pm}4.61$/3.58, continuance commitment $27.54{\pm}4.22/3.44{\pm}.53$, and normative commitment $23.95{\pm}2.94/2.99{\pm}.37$ in order of precedence. The average grade in job commitment is $32.47{\pm}5.77/3.30{\pm}.60$ and that in job satisfaction is $63.39{\pm}10.16/3.17{\pm}.51$, respectively. We find the positive relationship between professionalism and organizational commitment (r=.522, P<.05), between professionalism and job commitment (r=.444, P<.05), and between professionalism and job satisfaction (r=.507, P<.05). And we also get the positive relationship between organizational commitment and job commitment (r=.549, P<.05), between organizational commitment and job satisfaction (r=.433, P<.05), and between job commitment and job satisfaction (r=.462, P<.05). To catch the factors influencing the professionalism of radiotherapists, we used multiple regression analysis. According to the final model, it appears affective commitment (B=.755, P<.05), normative commitment (B=.305, P<.05), job satisfaction (B=.092, P<.05), an opportunity for developing (B=-1.505, P<.05), and the position (B=-1.155, P<.05) in order of precedence. It seems that explaining influece on $R^2$ is 0.504. Conclusion: The results of the factors that influence professionalism working as radiotherapists in the department of radiation oncology have it that the more affective commitment, normative commitment, and job satisfaction we feel, the more professionalism we recognize. We think that the focus of professionalism is increased if getting the chances for radiotherapists to have little to do with developing opportunities given.

• Korean small business review
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• v.31 no.2
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• pp.19-37
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• 2009

The purpose of this research is to explore differences between small and medium-sized companies and large-sized companies in the impact of human resource innovativeness(HRI), learning orientation(LO), and HRI-LO interaction on innovation effect and business performance. Although learning orientation has long been considered as a key factor influencing good performance of a business, little research was devoted to exploring the effect of HRI-LO interaction on innovation effect and business performance. In this study, it is investigated whether there is a synergy effect between innovative human workforce and learning orientation corporate culture, in addition to each by itself, to generate good business performance as well as a success of new innovations in the market. Research hypotheses were as follows, including H1) human resource innovativeness(HRI), learning orientation(LO), and interactions of HRI and LO(HRI-LO interaction) positively affect innovation effect, H2) there is a difference of the effect of HRI, LO, and HRI-LO interaction on innovation effect between large-sized and small-sized companies, H3) HRI, LO, HRI-LO interaction, innovation effect positively affect business performance, and H4) there is a difference of the effect of HRI, LO, HRI-LO interaction, and innovation effect on business performance between large-sized and small-sized companies. Data were obtained from 479 practitioners through a web survey since the web survey is an efficient method to collect a national data at a variety of fields. A single respondent from a company was allowed to participate in the study after checking whether they have more than 5-year work experiences in the company. To check whether a common source bias is existed in the sample, additional data from a convenient sample of 97 companies were gathered through the traditional survey method, and were used to confirm correlations between research variables of the original sample and the additional sample. Data were divided into two groups according to company size, such as 352 small and medium-sized companies with less than 300 employees and 127 large-sized companies with 300 or more employees. Data were analyzed through t-test and regression analyses. HRI which is the innovativeness of human resources in the company was measured with 9 items assessing the innovativenss of practitioners in staff, manager, and executive-level positions. LO is the company's effort to encourage employees' development, sharing, and utilizing of knowledge through consistent learning. LO was measured by 18 items assessing commitment to learning, vision sharing, and open-mindedness. Innovation effect which assesses a success of new products/services in the market, was measured with 3 items. Business performance was measured by respondents' evaluations on profitability, sales increase, market share, and general business performance, compared to other companies in the same field. All items were measured by using 6-point Likert scales. Means of multiple items measuring a construct were used as variables based on acceptable reliability and validity. To reduce multi-collinearity problems generated on the regression analysis of interaction terms, centered data were used for HRI, LO, and Innovation effect on regression analyses. In group comparison, large-sized companies were superior on annual sales, annual net profit, the number of new products/services in the last 3 years, the number of new processes advanced in the last 3 years, and the number of R&D personnel, compared to small and medium-sized companies. Also, large-sized companies indicated a higher level of HRI, LO, HRI-LO interaction, innovation effect and business performance than did small and medium-sized companies. The results indicate that large-sized companies tend to have more innovative human resources and invest more on learning orientation than did small-sized companies, therefore, large-sized companies tend to have more success of a new product/service in the market, generating better business performance. In order to test research hypotheses, a series of multiple-regression analysis was conducted. In the regression analysis examining the impact on innovation effect, important results were generated as : 1) HRI, LO, and HRI-LO affected innovation effect, and 2) company size indicated a moderating effect. Based on the result, the impact of HRI on innovation effect would be greater in small and medium-sized companies than in large-sized companies whereas the impact of LO on innovation effect would be greater in large-sized companies than in small and medium-sized companies. In other words, innovative workforce would be more important in making new products/services that would be successful in the market for small and medium-sized companies than for large-sized companies. Otherwise, learning orientation culture would be more effective in making successful products/services for large-sized companies than for small and medium-sized companies. Based on these results, research hypotheses 1 and 2 were supported. In the analysis of a regression examining the impact on business performance, important results were generated as : 1) innovation effect, LO, and HRI-LO affected business performance, 2) HRI by itself did not have a direct effect on business performance regardless of company size, and 3) company size indicated a moderating effect. Specifically, an effect of the HRI-LO interaction on business performance was stronger in large-sized companies than in small and medium-sized companies. It means that the synergy effect of innovative human resources and learning orientation culture tends to be stronger as company is larger. Referring to these result, research hypothesis 3 was partially supported whereas hypothesis 4 was supported. Based on research results, implications for companies were generated. Regardless of company size, companies need to develop the learning orientation corporate culture as well as human resources' innovativeness together in order to achieve successful development of innovative products and services as well as to improve sales and profits. However, the effectiveness of the HRI-LO interaction would be varied by company size. Specifically, the synergy effect of HRI-LO was stronger to make a success of new products/services in small and medium-sized companies than in large-sized companies. However, the synergy effect of HRI-LO was more effective to increase business performance of large-sized companies than that of small and medium-sized companies. In the case of small and medium-sized companies, business performance was achieved more through the success of new products/services than much directly affected by HRI-LO. The most meaningful result of this study is that the effect of HRI-LO interaction on innovation effect and business performance was confirmed. It was often ignored in the previous research. Also, it was found that the innovativeness of human workforce would not directly influence in generating good business performance, however, innovative human resources would indirectly affect making good business performance by contributing to achieving the development of new products/services that would be successful in the market. These findings would provide valuable managerial implications specifically in regard to the development of corporate culture and education program of small and medium-sized as well as large-sized companies in a variety of fields.

• Journal of Nutrition and Health
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• v.42 no.4
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• pp.386-396
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• 2009

The purpose of this study was to analyze the effect of push, pull and push-pull interactive factors for CFMC (Contract Foodservice Management Company)'s internationalization. The study was a quantitative study part in mixed methods (QUAL ${\rightarrow}$ quan) which was mainly qualitative study and quantitative study. Mail survey was carried out for quantitative study. For study subjects, 1,281 persons who completed 'Food Service Management Professional Program' of 'Y' University were selected as a population because the program was mainly for CFMC's workers. The analysis methods used in this study were frequency analysis, factor analysis, correlation analysis and multiple regression analysis with SPSS 17.0. Push factors had the saturation in domestic market and the manager's purpose (fac.1) and the investment for internationalization (fac.2). Pull factors had the company's external environment for internationalization (fac.3) and the global network and spread of culture (fac.4). Push-pull interactive factors had the information about foreign market (fac.5), the procedure and budget of overseas expansion (fac.6) and the national network and size of domestic market (fac.7). Internal dynamics factors had the deterrents for internationalization (fac.8) and the enablers for internationalization (fac.9). The result showed that the company's external environment in pull factors had positive effects on the deterrents for internationalization. The global network and the spread of culture had positive effects on the enablers for internationalization. The information about foreign market in push-pull interactive factors had positive effects on the deterrents and enablers for internationalization. The national network and the size of domestic market had positive effects on the enablers for internationalization. The deterrents and enablers for internationalization had positive effects on the level of internationalization, and the deterrents had more effects on the level of internationalization than the enablers did (${\beta}$= .492 > .177).

• Journal of agricultural medicine and community health
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• v.27 no.1
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• pp.99-113
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• 2002

For this study a sample of 205 people, 66 males and 139 females, over 65 years of age, residing in C-gu of S-si and utilizing senior centers, were selected, The objective of the study was to provide basic data for health promotion program development provided by health centers. A questionnaire was used to collect date on general characteristics, health status, social health status and utilization rate for health services. The instruments used in this study were the Lawton scale, to measure daily routine function, the MMSE-K developed by Folstein and modified to fit the Korea situation, for mental health status, and the CES-Dtool developed by Radloff, for emotional health status. the SPSS Window program was used to calculate percentages. Tests of significance were done using t-test and ANOVA. Multiple regression analysis was used to identify variables influencing the use of health services. The results are as follows : Of those utilizing senior citizen centers, 40.9% of males and 17.3% of the female thought they were healthy. The average score for IADL was 7.4. The daily routine of female respondents consisted of buying household articles and drugs, and other IADLs such as riding the bus or subway alone. These resulted in a higher score compared to males. For emotional health, 7.6% of the males reported depression compared to 21.6% of the females. For mental health, 48.5% of the males and 28.8% of the females were found to be in the group suspicious for dementia. On social health, 57.6% of the males and 62.6% of the females reported no intimate human relations. Of those older people who had close human relations, 52.5% of the males indicated a friend as the closest person and 53.8% of the females, their children. On use of health services, there was a significantly higher need for mobile medical care services treatment for those with lower education levels and status of window/widower. There was a significantly higher need for health exmination services for those with lower levels of exercise, greater satisfaction with sleep, higher levels of oral health care, and higher social contacts. In conclusion, there is a need to provide varied programs for the promotion of health, along with parallel resolution of social, psychological and economic issues. It is recommended that health services for elderly people provided by the health centers be implemented with full recognition of these characteristics and differences.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.