• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.4
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• pp.118-126
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• 2007

This study presents the intellectual capital (IC) indicator selection criteria based on the review of qualitative characteristics of financial accounting information and data quality of information systems. The AHP survey has been performed to verify the weight difference of the criteria to select effective IC indicators among industry. The results shows that there exists the weight differences in relevance and comparability factor by industry. To management IC effectively, different method considering industry environment should be required.

• Journal of Technology Innovation
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• v.15 no.2
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• pp.177-209
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• 2007

This work firstly aims to analyse the balance between tangibles and intangibles as well as among human capital, structural capital and relational capital of evaluation indicators for the research institutes in science and technology sector conducted in 2006, by adopting intellectual capital model. The research question of this work comes from that while the R&D activity can produce both tangibles and intangibles, there have no been methodologies to relevantly measure and rationally judge these, in particular, intangible performance. The result shows that the institute evaluation system in 2006 had given more weight on tangibles and structural capital than intangibles and other intellectual capitals such as human capital and relational capital, in comparison to the past evaluation system, even though, in principle, the current evaluation system has to deal with the intangible research performances as well as tangible ones in economic, social and cultural perspective. Finally, based on these analysis, I will try to suggest some policy directions for overcoming the deficits of indicators in institute evaluation system.

• Journal of Nutrition and Health
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• v.38 no.9
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• pp.765-776
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• 2005

The purposes of this study were to a) examine IC (intellectual capital) circumstance of CFMC (contract foodservice management company), b) identify the correlation between IC of CFMC, c) analyze the cause and effect of IC in the viewpoint of contractor, client, and customer. The questionnaires of IC measurement were handed out to 108 CfHCs, there composing of main office employees, foodservice managers, customers, and clients of 207 school, 38 hospital, and 86 business/industry foodservices. The statistical data analysis was completed using SPSS Win (ver 12.0) for descriptive analysis, correlation analysis, simple linear regression analysis. First, CFMCs had operational experience for an average of 8 years and 8 months, and served an average of 38,540 meals a day. Most of the respondent companies operated 'food supply/distribution($50\%$)', 'catering ($46.7\%$)', and restaurant business ($43.3\%$)' except for institutional foodservice and managed an average of 66 clients for the contract period of 2 years and 3 months. Second, there was positive correlation between $\ulcorner$sales of foodservice$\lrcorner$ and 'market ability', $\ulcorner$client satisfaction$\lrcorner$ and necessary intellectual capital for managing branch/chain foodservice office, and $\ulcorner$customer satisfaction$\lrcorner$ and $\ulcorner$renewal and development$\lrcorner$, 'market ability', 'infrastructure support for foodservice operation', 'employee satisfaction', respectively. Finally, the result of the cause and effect analysis on CFMCs, clients, and customers was positively influenced by 'client satisfaction' with 'customer satisfaction', 'infrastructure support for foodservice operation' and 'customer satisfaction' with 'employee satisfaction', and 'infrastructure support for foodservice operation'. In conclusion, if CFMCs were to perform a routine checkups by utilizing CFMC's IC measuring tool, improvements in CFMC operational capacities as well as foodservice quality can be noted. Additionally, CFMCS can satisfy their client-customer relationship by employing internal marketing thechniques for employee, a more efficient infrastructure support system, and construc tive infrastructure utilization. Therefore, CFMCs can show significant improvement in their sales and foodservice quali-ty though continuous maintenance of the client and customer satisfaction.

• Journal of Nutrition and Health
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• v.38 no.10
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• pp.880-894
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• 2005

The purposes of this study were to a) measure the IC identified of CFMC (contract foodservice management company) ,b) examine IC circumstance of CFMC, c) evaluate practically IC measurement tool of CFMC, and d) present information for selecting an adequate CFMC to clients. The questionnaires of IC measurement were handed out to 108 CFMCs, there composing of main office employees, foodservice managers, customers, and clients of 207 school,38 hospital, and 86 husiness/industry foodservices. The statistical data analysis was completed using SPSS Win (ver 12.0) for descriptive analysis, t-test, Mann-Whitney U test. First, CFMCs had operational experience for an average of 8 years and 8 months, and served an average of 38,540 meals a day. Most of the respondent companies specialized in the school foodservice field and managed an average of 66 clients for the contract period of 2 years and 3 months. Second, the respondent companies had gotten a score of 77.78 points for the total average, 77.7 points in the large enterprise group and 78.1 points in the small and medium-sized enterprise group. Therefore, the minimum number of points for the accrediting license on Qualification is suggested to be over 70 out of a 100 point scale; this study would be serve as reference for the certification license on qualification. On the level of evaluation category, the scores were 14.15 to 20 points on $\ulcorner$finance$\urcorner$, 19.24 to 25 points on $\ulcorner$customer$\urcorner$, 19.33 to 25 points on $\ulcorner$process$\urcorner$, 14.31 to 20 points on $\ulcorner$human resource$\urcorner$, and 8.6 to 10 point on $\ulcorner$renewal and development$\urcorner$ . $\ulcorner$Renewal and development$\urcorner$ and $\ulcorner$customer focus$\urcorner$ received better grades than other evaluation categories. Third, $\ulcorner$Finance$\urcorner$ indicated similar distribution overall. Small and medium-sized companies had lower grades than large companies on 'market ability' of $\ulcorner$customer$\urcorner$ , but, clients of small and medium-sized companies had higher grade for 'client satisfaction' than large companies. Most of the companies supported 'infrastructure support for foodservice operation' of $\ulcorner$process$\urcorner$ by the main office of CFMCs, but, the branch chain offices of CFMCs were not applied efficiently. Large companies made more effort to improve the 'employee ability' of $\ulcorner$human focus$\urcorner$ than small and medium-sized CFMC. The 'research and development cost' of $\ulcorner$renewal and development$\urcorner$ was increased compared to the previous year. In conclusion, if CFMCs were to perform self-evaluation and a routine checkups by utilizing CFMC's IC measuring tool, improvements in CFMC operational capacities as well as foodservice quality can be noted. (Korean J Nutrition 38(10)'880$\sim$894,2005)

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.21-37
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• 2013

Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.