• Journal of Technology Innovation
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• v.23 no.3
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• pp.225-253
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• 2015

The standard is a nation's one of the most important industrial issues that improve the social and economic efficiency and also the basis of the industrial development and trade liberalization. This research analyzes the enactment and the utilization of Korean industrial standards(KS) of various industries. This paper examines Korean industries' KS utilization status based on the KS possession, enactments and inquiry records. First, we implement multidimensional scaling method to visualize and group the KS possession records and the nation's institutional issues. We develop several hypothesis to find the decision factors of how each group's KS possession status impacts on the standard enactment activities of similar industry sectors, and analyzes the data by implementing regression analysis. The results show that the capital intensity, R&D activities and sales revenues affect standardization activities. It suggests that the government should encourage companies with high capital intensity, sales revenues to lead the industry's standard activities, and link the policies with the industry's standard and patent related activities from R&D. Second, we analyze the impacts of each KS data's inquiry records, the year of enactments, the form and the industrial segment on the utilization status by implementing statistical analysis and decision tree method. The results show that the enactment year has significant impact on the KS utilization status and some KSs of specific form and industrial segment have high utilization records despite of short enactment history. Our study suggests that government should make policies to utilize the low-utilized KSs and also consider the utilization of standards during the enactment processes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.455-460
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• 2020

The governments of Korea, China, and Japan have operated comprehensive research institutes for railway technologies. Korea Railroad Research Institute (KRRI), China Academy of Railway Sciences Corporation Limited (CARS), and Railway Technical Research Institute (RTRI) are representatives of comprehensive railway research institutes in each country. KRRI was found to be the most advanced in the quantitative competitiveness of patents. In terms of qualitative competitiveness, KRRI has strength in civil engineering, whereas RTRI has strength in electricity. KRRI was found to have the greatest efforts in securing competitiveness in overseas property rights. By comparing the publication of papers, CARS published the most papers. On the other hand, from 2015, KRRI showed an upward trend and published the most papers. By examining the impact of the papers by the citation, KRRI was found to have higher competitiveness than the other two institutions. In the future, it will be necessary to perform big data analysis on patents and papers of the three organizations, derive the key research areas and promising technology areas for each institute, and establish a mid-to-long-term development plan for railway technology based on scientific evidence.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.19-34
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• 2021

The government budget for promoting startup have been skyrocketed as catching up with increasing demands for high-tech startup by disruptive innovation resulted from rapid technology change. However, major trend of startup have still fallen on self-employed type of startup due to the lack of expertise and fund in spite of desperate government policy efforts. In reality, the access to high-tech startup has been very limited and too high huddle to would-be entrepreneur. This paper implement empirical analysis on the effects of entrepreneur competency and satisfaction level to government support, considering these as the KSF for the growth and success of high-tech startup, to the performance of the company. In particular, it focus on defining unique characteristics of high-tech startup through differential proving by the backgrounds of entrepreneur such as major, R&D experience, patent possession, CTO possession. This research carry out survey to 217 entrepreneurs in high-tech company in Daejon and Daegue at R&D Special Innopolis Zone. Research results are as follow. First, entrepreneurial achievement competencies, conceptualization competencies, network competencies and market recognition competencies positively affect the financial and non-financial performance and organizational and technical competencies, while organizational and technological competencies only positively impact on non-financial performance. Second, the satisfaction level of government support showed a positive moderating effect on entrepreneurial achievement competencies and financial performance, while no significant effect in other competencies. Third, positive differential effect by the technological background of entrepreneur such as Major, R&D experience, patent possession, CTO possession) have been confirmed. This paper deliver several significant implications and contributions, First, it propose classified and systematized entrepreneur competency through the domestic and foreign literature reviews. Second, it proves the need for the wider spread of team based startup culture rather then sole startup. Third, it also proves the important role of technological background of entrepreneur among the characteristics of high-tech startup.

• Journal of Korea Technology Innovation Society
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• v.18 no.1
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• pp.98-125
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• 2015

This study will show the determinants of research productivity by fields in science and engineering. However, we present the differences between fields by personal attributes, research resources, and research productivities. The data includes 1,383 researchers who participated in the BK21 PLUS program during 2010-2012. The fields are physics, chemistry, biology, mechanics, electricity and electronics and chemical engineering. As for research productivity, 3 indices are used such as the number of papers publicized, patents and combination of papers and patents. As for explanation factors, two kinds of variables are used. The personal factors include sex, age, academic rank, location of affiliation, and country of PhD acquisition, and the resource factors are the number of graduate students, 3 types of research funds such as government fund, industrial fund and overseas fund. This study is unique in several aspects; Dealing with 3 productivity indices, and using massive official data, 6 different fields, and determinants of research productivity. The results are as follows; 1) there is a big difference in determinants by fields. 2) No variables affect the research productivity of all the fields at the same time. 3) In science, the number of determinants are quite low than engineering. 4) The ratio between papers and patents are different by fields. 5) The correlations between paper and patent by fields are different; no relationship in the field of physics and chemistry and positive relationship in the other 4 fields.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.134-142
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• 2016

Main infrastructures, such as levee, dam, bridge, road, etc., are very important due to not only the means of support for social and industrial activities in normal situation but also the means of protection of life and property during disaster occurrence. In spite of this importance of infrastructures, however, any disaster management systems that actively use these infrastructures are not developed yet. Moreover, infrastructures are not usually included in emergency action plans, thus it occurs second and third impact on communities and industries due to collapsing or damage of infrastructures. Therefore, the authors in this paper analyzed previous research, SWOT, STEEP, and patents and technical journals and conducted a technology need survey ni order to understand the trend of disaster management system as well as suggest main research fields and detail research items. The results of this paper will be a foundation of developing an advanced infrastructure integrated system of maintenance and disaster mitigation and contribute our nation to have an active response system by using infrastructure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.170-177
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• 2020

The Korean government's R&D budget has risen steadily annually, reaching 24.2 trillion won in 2020, and the ratio of R&D expenditure to GDP ranked high among OECD countries. However, national science and technology innovation ranked low among OECD countries. This study focused on Korean government-funded research institutes in the field of science and technology by analyzing the effects of budget and workforce input on research performance in order to provide directions for management. Multiple regression analysis was conducted with budget and workforce input as independent variables, which influence major research outcomes (SCI paper, patent, royalty). In the research budget, only government contribution had a positive effect on SCI thesis performance, and the increase in the government project and private project funding had a negative effect on the number of patents and technology royalties. For the workforce, the positive effect of regular workers on all research achievements was 3-6 times more than that of non-regular workers. Through this study, policy implications such as establishment of institutional performance indicators according to research types were derived for the outcome driven management of government-funded research institutes in the field of science and technology.

• Journal of Korea Technology Innovation Society
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• v.11 no.4
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• pp.510-531
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• 2008

The importance of universities' knowledge to industrial innovation have widely pervaded the academia as well as policy communities. During the last three decades, a series of policy measures vitalizing the knowledge-transfer activities of academics have been implemented both in industrialized and industrializing countries. However, The concerns on the industry's influences on the academia have been raised by a group of researchers such as 'Economics of science'. Against this background, this paper addresses the issues related to the relationship between the academic research and knowledge-transfer activities. Particularly, based on the 16 years' panel data of Korean academics' patent and paper outputs, the effect of patenting activities on publishing activities is investigated. Moreover, the specific context of Korean academic system as well as general characteristics of academics are considered in the analysis and discussion. According to the results, not just the publishing and patenting outputs but their productivities have been dramatically increased during the last 16 years. The main finding is that the patenting activities have a consistent positive effect on the publishing activities of the academics in the estimations of panel models. Based on these results and the discussions, some policy recommendations for university-industry collaboration are suggested.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.159-173
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• 2017

In order to provide technical financial support to small and medium-sized venture companies based on technology, the government implemented the TCB evaluation, which is a kind of technology rating evaluation, from the Kibo and a qualified private TCB. In this paper, we briefly review the current state of TCB evaluation and available indicators related to technology evaluation accumulated in the Korea Credit Information Services (TDB), and then use indicators that have a significant effect on the technology rating score. Multiple regression techniques will be explored. And the relative importance and classification accuracy of the indicators were calculated by applying the key indicators as independent features applied to the generalized boosting model, which is a representative machine learning classifier, as the class influence and the fitness of each model. As a result of the analysis, it was analyzed that the relative importance between the two models was not significantly different. However, GBM model had more weight on the InnoBiz certification, R&D department, patent registration and venture confirmation indicators than regression model.

• Journal of Technology Innovation
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• v.29 no.4
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• pp.1-30
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• 2021

Due to the recent development of system semiconductors, technical innovation for the electric devices of the automobile industry is rapidly progressing. In particular, the electric device of automobiles is accelerating technology development competition among automobile parts makers, and the development cycle is also changing rapidly. Due to these changes, the importance of strategic planning for R&D is further strengthened. Due to the paradigm shift in the automobile industry, the Product-Technical Roadmap (P/TRM), one of the R&D strategies, analyzes technology forecasting, technology level evaluation, and technology acquisition method (Make/Collaborate/Buy) at the planning stage. The product-technical roadmap is a tool that identifies customer needs of products and technologies, selects technologies and sets development directions. However, most companies are developing the product-technical roadmap through a qualitative method that mainly relies on the technical papers, patent analysis, and expert Delphi method. In this study, empirical research was conducted through simulations that can supplement and strengthen the product-technical roadmap centered on the automobile industry by fusing Gartner's hype cycle, cumulative moving average-based data preprocessing, and deep learning (LSTM) time series analysis techniques. The empirical study presented in this paper can be used not only in the automobile industry but also in other manufacturing fields in general. In addition, from the corporate point of view, it is considered that it will become a foundation for moving forward as a leading company by providing products to the market in a timely manner through a more accurate product-technical roadmap, breaking away from the roadmap preparation method that has relied on qualitative methods.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.