• Journal of Technology Innovation
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• v.17 no.2
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• pp.81-107
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• 2009

The Korean government provides a variety of supporting programs with firms to promote technological innovation which is a main driver of economic growth. The existing literature on technological innovation has mainly focused on analysis about determinants of successful innovation and effectiveness of a specific policy measure. However, there is no study deals with characteristics of policy demanders. For this, this study investigates the relationship between barriers and policy measures in technological innovation using the logistic regression analysis method with raw data of Korean Innovation Survey (KIS). The findings from this analysis show that barriers of technological innovation are meaningful variables to determining whether firms adopt a policy measure, although there are some differences according to policy types. Cost barriers increased the probability that firms adopt support programs regardless of policy types. Also, the more firms encounter cooperation barriers, the more likely firms utilize supporting programs in regard to technological advice and information.

• STI Policy Review
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• v.8 no.2
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• pp.75-93
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• 2017

Recently, global competition in the manufacturing sector is driving firms in the manufacturing sector to conduct product innovation projects to maintain their competitive edge. The key points of product innovation projects are 1) what the purpose of the project is and 2) what expected results in the target market can be achieved by implementing the innovation. Therefore, this study focuses on the performance of innovation projects with a business viewpoint. In this respect, this study proposes the "achievement rate" of product innovation projects as a measurement of project performance. Then, this study finds the best strategies from various innovation activities to optimize the achievement rate of product innovation projects. There are three major innovation activities for the projects, including three types of R&D activities: Internal, joint and external R&D, and five types of non-R&D activities - acquisition of machines, equipment and software, purchasing external knowledge, job education and training, market research and design. This study applies decision tree modeling, a kind of data-mining methodology, to explore effective innovation activities. This study employs the data from the 'Korean Innovation Survey (KIS) 2014: Manufacturing Sector.' The KIS 2014 gathered information about innovation activities in the manufacturing sector over three years (2011-2013). This study gives some practical implication for managing the activities. First, innovation activities that increased the achievement rate of product diversification projects included a combination of market research, new product design, and job training. Second, our results show that a combination of internal R&D, job training and training, and market research increases the project achievement most for the replacement of outdated products. Third, new market creation or extension of market share indicates that launching replacement products and continuously upgrading products are most important.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.47-53
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• 2021

With increasing interest in the 4th industrial revolution, data-driven scientific methodologies have developed. However, there are limitations of data collection in the real estate field of research. In addition, as the public becomes more knowledgeable about the real estate market, the qualitative sentiment comes to play a bigger role in the real estate market. Therefore, we propose a method to collect quantitative data that reflects sentiment using text mining and k-means algorithms, rather than the existing source data, and to predict the direction of housing index through artificial neural network learning based on the collected data. Data from 2012 to 2019 is set as the training period and 2020 as the prediction period. It is expected that this study will contribute to the utilization of scientific methods such as artificial neural networks rather than the use of the classical methodology for real estate market participants in their decision making process.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.27-33
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• 2021

With increasing interest in key areas of the 4th industrial revolution such as artificial intelligence, deep learning and big data, scientific approaches have developed in order to overcome the limitations of traditional decision-making methodologies. These scientific techniques are mainly used to predict the direction of financial products. In this study, the factors of apartment prices, which are of high social interest, were analyzed through SOM. For this analysis, we extracted the real prices of the apartments and selected a total of 16 input variables that would affect these prices. The data period was set from 1986 to 2021. As a result of examining the characteristics of the variables during the rising and faltering periods of the apartment prices, it was found that the statistical tendencies of the input variables of the rising and the faltering periods were clearly distinguishable. I hope this study will help us analyze the status of the real estate market and study future predictions through image learning.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.69-76
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• 2017

Recently, it is difficult for a firm to survive and maintain sustainable competitive advantage through internal R&D only, because changes in the environment are very fast and complex. Accordingly, the paradigm of open innovation is gradually emphasized, and the ratio of external R&D has been increasing in various industries. This study analyzed open innovation through Korean Innovation Survey (KIS) data from Science and Technology Policy Institute (STEPI). We confirmed the ratio of open innovation based on firms of the manufacturing industry in South Korea, and examined the relationship between open innovation and innovation performance. This study suggests that open innovation is not a new paradigm that did not exist in the past. While the use of government support programs positively influence innovation performance, the use of external R&D doesn't influence innovation performance due to the difficulties associated with managing it. The results of this study will be used to establish the strategic direction and support the decision making when firms conduct innovation activities in the future.

• Journal of Technology Innovation
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• v.17 no.2
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• pp.55-80
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• 2009

Technology innovation activity plays a pivotal role in constructing the entrance barrier for other firms and making process improvement and new product. and these activities give a profit increase and growth to firms. Thus, technology innovation activity can reduce the default risk of firms. However, technology innovation activity can also increase the firm's default risk because technology innovation activity requires too much investment of the firm's resources and has the uncertainty on success. The purpose of this study is to examine the effect of technology innovation activity on the default risk of firms. This study's sample consists of manufacturing firms listed on the Korea Securities Market and The Kosdaq Market from January 1,2000 to December 31, 2008. This study makes use of R&D intensity as an proxy variable of technology innovation activity. The default probability which proxies the default risk of firms is measured by the Merton's(l974) debt pricing model. The main empirical results are as follows. First, from the empirical results, it is found that technology innovation activity has a negative and significant effect on the default risk of firms independent of the Korea Securities Market and Kosdaq Market. In other words, technology innovation activity reduces the default risk of firms. Second, technology innovation activity reduces the default risk of firms independent of firm size, firm age, and credit score. Third, the results of robust analysis also show that technology innovation activity is the important factor which decreases the default risk of firms. These results imply that a manager must show continuous interest and investment in technology innovation activity of one's firm. And a policymaker also need design an economic policy to promote the technology innovation activity of firms.

• Proceedings of the Korea Contents Association Conference
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• 2014.06a
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• pp.191-192
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• 2014

In this study, diagnostic model was proposed to evaluate and rate the innovation capability of SMEs and suggest alternatives to insufficient capabilities and optimum supporting programs for SMEs from literature survey, GIC model was composed based on KIS value and ASTI(Associate of Science and Technology information) SMEs database, thus, sample deviation can be caused and securing accurate data is insufficient. To compose model by analyzing characteristics of companies accurately, various companies' data for long period will be required.

• International Journal of Contents
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• v.10 no.4
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• pp.75-82
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• 2014

The purpose of this paper was to identify suitable variables for financial distress prediction models and to compare the accuracy of MDA and LA for early warning signals for wind energy companies in Korea. The research methods, discriminant analysis and logit analysis have been widely used. The data set consisted of 15 wind energy SMEs in KOSDAQ with financial statements in 2012 from KIS-Value. We found that five financial ratio variables were statistically significant and the accuracy of MDA was 86%, while that of LA is 100%. The importance of this study is that it demonstrates empirically that financial distress prediction models are applicable to the wind energy industry in Korea as an early warning signs of impending bankruptcy.

• International Commerce and Information Review
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• v.11 no.4
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• pp.183-214
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• 2009

We identify key theoretical approaches, constructs, and primary variables of interest that exist in the foreign market entry mode articles. This provides fertile ground for continued development in our foreign market entry mode research. Using the integrated framework, this paper examines the determinants of foreign market entry mode choice by Korean firms and the impact of the entry mode choice on performance in a unified model. Using a database of KIS-VALUE in Korea from 2003 to 2005, we find that the hypothesized effects of related factors on entry modes are partially supported.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.279-290
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• 2006

This paper proposes a model to assess the maturity level of Six Sigma activities. We classify the maturity level into 5 stages: initial, forming, storming, performing and mature stage. To evaluate the maturity level, 10 categories of Six Sigma with 3 factors each are identified: management leadership, belt system, expert training, establishing execution system, compensation, organization, corporate culture, customer focus, project selection, and management of project results. Scoring 277 items in total, the value of each factor is evaluated by weighted average of those items. Maturity level is appraised by rating the sum of scores of 10 categories that are obtained by summing up the values of its 3 factors. Values of weights and criteria of rating maturity levels are determined by analyzing 90 companies and Six Sigma exper's opinion. This study also shows the actual appraisal results of some companies.