• Journal of Technology Innovation
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• v.25 no.3
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• pp.265-297
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• 2017

As corporate management enters the era of informatization or knowledge management, the level of patent quality, which is the fruit of R&D and technical innovation, is an important element of corporate competitiveness in this age of unbridled competition. This study analyzes the relevance between R&D stocks and 6 types of knowledge stock (patent quality) and corporate market values in utilization of related research models. With Tobin Q model utilized, 108,851 U.S. patents (observed value per year: 2,795) registered by 402 domestic enterprises were analyzed. As the Hall model was analyzed, it turned out that the R&D stock/asset, claim stock/patent stock, and citation stock/patent stock had positive effect on corporate market values. The inventor stock/patent stock also show positive effect on corporate market values.

• Journal of Digital Convergence
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• v.15 no.9
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• pp.167-178
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• 2017

Big Data is a key asset for the company and a key factor in boosting its competitiveness in the logistics sector. However, there is still a lack of research on how to collect, analyze and utilize Big Data in logistics. In this context, this study has developed a value model applicable to logistics companies based on the results of analysis and application of Big Data in the logistics of previous studies and DHL. The purpose of this study is to improve the operational efficiency and customer experience maximization level of logistics companies through utilization of big data analysis in logistics, to improve competitiveness of big data utilization and to develop new business opportunities. This study has a significance to newly create a value model for utilization of big data analysis in logistics sector and can provide implications for other industries as well as logistics sector in the future.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.197-212
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• 2019

The purpose of this study is to identify the maturity stages of venture firms through classification analysis, which is widely used as a big data technique. Venture companies should develop a competitive advantage in the market. And the maturity stage of a company can be classified into five stages. I will analyze a difference in the growth stage of venture firms between the survey response and the statistical classification methods. The firm growth level distinguished five stages and was divided into the period of start-up and declines. A classification method of big data uses popularly k-mean cluster analysis, hierarchical cluster analysis, artificial neural network, and decision tree analysis. I used variables that asset increase, capital increase, sales increase, operating profit increase, R&D investment increase, operation period and retirement number. The research results, each big data analysis technique showed a large difference of samples sized in the group. In particular, the decision tree and neural networks' methods were classified as three groups rather than five groups. The groups size of all classification analysis was all different by the big data analysis methods. Furthermore, according to the variables' selection and the sample size may be dissimilar results. Also, each classed group showed a number of competitive differences. The research implication is that an analysts need to interpret statistics through management theory in order to interpret classification of big data results correctly. In addition, the choice of classification analysis should be determined by considering not only management theory but also practical experience. Finally, the growth of venture firms needs to be examined by time-series analysis and closely monitored by individual firms. And, future research will need to include significant variables of the company's maturity stages.

• Environmental and Resource Economics Review
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• v.14 no.3
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• pp.595-626
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• 2005

The purpose of this paper is to estimate technical efficiency, scale efficiency, and environmental efficiency by income level of Korean farms, and analyze the factors to decide three efficiencies. Depending on the non-parametric methods, we estimate technical using inputs and outputs of total farms without assuming of goods or behavior of optimization. The average technical efficiency of total firms under constant return to scale and strong disposability is 0.437. The technical inefficiency was caused by 47.7% in pure technical inefficiency, 11.3% in scale failure, and 3.2% in environmental inefficiency. The number of firms under increasing return to scale occupied almost 70% and 27% of total firms respectively. Higher are income class, middle debt & long debt per asset, and N effluents per cultural land, higher technical efficiency. The increases of BOD discharges per cultural land and machines per cultural land deteriorate environmental efficiency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1901-1910
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• 2014

Current domestic and overseas BIM practice and research efforts show very few examples that design and construction BIM data could be successfully used for efficient operation and maintenance (O&M) of infrastructure in particular. This study takes public wastewater treatment plant requiring an enhancement of operation and maintenance capability into account to develop a prototype BIM-based maintenance management system. The system is designed and implemented following a typical system development procedure and validated by the system outputs per four scenarios being considered to be main maintenance activities: The research results are expected to contribute to the upgrade of current wastewater treatment plant maintenance level, which is more demanded as water-related regulation and policy direction changes to region-based large scale O&M and asset management adoption, and overseas market participation.

• International Commerce and Information Review
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• v.14 no.2
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• pp.3-27
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• 2012

As Chinese political and economical status gets higher, a lot of multinational firms have tried to find some chances from the Chinese market successfully. Though geographically Korea is located closely to China, a lot of firms entering into Chinese market have turned out failed. Thus, this study researched Korean manufacturing firms in China, surveyed their localization degree of distribution, and tried to find out factors which influence these localization from a far-reaching literature. As a result of analyzing 146 questionnaires, the length of channel, among Chinese environmental factors, has a positive influence on the distribution localization degree. In addition, the factor of distribution relation assets has a positive effect on the distribution localization degree. Considering this study, the Chinese market, especially distribution field, has recently grown up to the world-class level. Therefore a firm intending to enter into China needs to be careful not to underestimate China.

• The Journal of Society for e-Business Studies
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• v.20 no.3
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• pp.1-10
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• 2015

The main objective of this study was to identify the factors that can maximize the effect of preventing technology leakage by government support. Therefore we used the 2013 small business technology protection capabilities and level of research which is conducted by the Small and Medium Business Administration, and have analyzed the presence of small business technological assets leakage protection eand skills. Multiple logistic regression analysis was performed to identify 1,518 small companies (43 big companies are excluded) which are divided into 155 technological assets leaked small business and non-leaked 1363 small business. The most important factors associated with technology leakage were entrant control system, security audit, employee absence of security activities and important data protection measures. This result shows that if the government can support more for these details, technological asset leakage prevention effect is expected to be maximized.

• Journal of Technologic Dentistry
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• v.38 no.4
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• pp.315-325
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• 2016

Purpose: This study investigated perception and plan of dental technologists regarding the old age and retirement for them to enjoy stable old age. Methods: Dental technologists working in Seoul, Incheon, and Gyeonggido were asked to fill out a self-administered questionnaire, and a total of 200 copies were used for analysis. The collected data were statistically analyzed by using SPSS 22.0(Statistical Package for Social Sciences. Chicago, IL, USA) (a=0.05). In order to compare perception toward old age preparation among the subjects, a Chi-square test was performed, and, to investigate the level of preparedness for old age according to general characteristics, t-test was performed. Results: In the analysis of the old age preparedness by age, there was a significant difference in financial preparation, Asset identification, use of retiring allowance, information gathering, senior town home, and stability (p<0.05). To the questions regarding perception toward retirement, the majority of the subjects (60.5%) answered they had thought about retirement, and many (23.9%) of them attributed the reason to job stress (23.9%). Regarding old age preparedness according to workplace, there was a significant difference in use of retirement allowance and education for old age preparedness between general dental laboratories and general hospitals (p<0.05). Conclusion: It is believed that, for preparation of dental technologists for stable old age, in addition to their personal effort, it is important to provide social support and practical measures to ensure welfare and retirement.

• Journal of Information Management
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• v.42 no.1
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• pp.199-219
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• 2011

Currently, managers and researchers have come to recognize the importance of knowledge as an asset to the organization. Knowledge Management System (KMS) is developed as a tool to manage the organizational knowledge. A significant literature about Knowledge Management in the private, but not public sector. The purpose of the study is to analyze the influencing factors for KMS utilization in a public sector, Jeju Provincial Government Organization. This study performed an empirical research on factors that affect the use of KMS using Knowledge Management system capability and individual & organizational capability criteria. Survey was conducted with 150 employees from Jeju Provincial Government Organization. The Results show that an ability to create knowledge, and knowledge infrastructure are significant factors in determining the level of usage of Knowledge Management system. In particular, the most important factor that influences the usage of Knowledge Management is knowledge creation. and then knowledge infrastructure. The result also shows that the usage of KMS is affected by management's support willingness.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.165-173
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• 2017

The purpose of this study was to analyze the correlation and volatility of Korea and neighboring East Asia stock markets. East Asian stock markets were selected for Japan, China, Hong Kong and Taiwan by economically and geographically close with Korea. If you understand the volatility and the correlation between Korea and the East Asian stock market, it may be helpful in predicting investment. And It may reduce the risk of investing of asset allocation in global portfolio level. For this using the national monthly return data for the last 163 months, I was calculating and comparison the rate and correlation, and regression analysis. Result of the correlation analysis, Korea have shown a low correlation with China. while showing a high correlation with Taiwan and Hong Kong. China has been forming its own market in East Asia and showing a low correlation with other countries exception Hong Kong. Hong Kong has been determined as the highest harmonization within the East Stock Market.