• 대한공업교육학회지
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• v.40 no.2
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• pp.155-174
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• 2015

The purposes of this study were to analyze the property of educational needs of teachers for educational contents of invention and intellectual property in secondary vocational education and provide fundamental data for the development of job training programs so as to develop the capabilities of teachers, the base for effective education of invention intellectual property in secondary vocational education. To achieve them, educational needs for the educational contents of invention intellectual property and the priority of the educational needs in secondary vocational education based on the recognition of the teachers were analyzed and suggested. Concrete results of this study can be suggested as follows. First, the average of educational needs of the teachers for the educational contents of invention intellectual property in secondary vocational education was 5.02. There were 23 items of the educational contents whose educational needs were higher than the average of the whole items and for those items and the average of each item, there were F4(The average of patent applications) 6.72, F5(Modification and supplementation of specification sheets) 6.46, F2(Writing of patent floor plans) 6.39, F3(Writing of patent specification sheets and abstraction) 6.31, A5(Invention method and activity) 6.27, E6(Invention design project) 6.15, H3(Invention commercialization) 5.97, F1(Patent information and application) 5.90, E5(Design obligation) 5.78, E3(Designing process of inventional design) 5.77, A4(Invention and problem solving) 5.57, G2(Patent investigation and classification) 5.47, C2(Thinking method of inventional problem solution) 5.45, E4(Production of inventional design product) 5.45, B5(Inventional patent project) 5.42, A2(Creativity development) 5.26, C4(Inventional problem solving project) 5.26, H4(Invention marketing) 5.26, H2(Analysis on invention commercialization) 5.20, D4(Invention and management) 5.16, C3(Problem solving activity) 5.14, E2(Inventional design devise and expression) 5.11, B3(Actuality of inventional method) 5.08 in order. Second, for the priority of educational needs of the teachers for the educational contents of invention intellectual property in secondary vocational education, there were 13 items of the educational contents for the first rank, 10 for the second rank and 17 for the third rank. The items of the educational contents for the first rank were A4(invention and problem solving), A5(inventional method and activity), B5(Invention patent project), C2(Thinking method of inventional problem solution), C4(Inventional problem solving project), E3(Inventional design process), E4(Production of inventional design product), E5(Design obligation), E6(Invention design project), F1(Patent information and application), F2(Writing of patent floor plan), F3(Writing of patent specification sheet and abstract), and H3(Invention commercialization. The items of the educational contents for the second rank were A2(Creativity development), B3(Actuality of inventional method), C3(Problem solving activity), D4(Invention and management), E2(Invention design devise and expression), F4(Range of patent demand), F5(Modification and supplementation of specification sheet), G2(Patent investigation and classification), H2(Analysis on invention commercialization), and H4(Invention marketing). The items for the third rank were the educational contents except the ones of the first rank and the second rank.

• Journal of Labour Economics
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• v.34 no.1
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• pp.33-69
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• 2011

This study analyses a productivity effect by E&T and R&D activities via estimation of E&T stock, R&D stock, and patent stock in a corporate level. Particularly, the analysis reflects the effects of skilled training after estimating E&T stock from E&T flow. When a spillover effect of E&T is analyzed, a methodology using technical proximity concept becomes a new experiment. Also classifying long and short term effects from the usage of Dynamic Panel Data Analysis becomes a new trial, too. The results of study appear that the productivity effects from E&T investments are relatively lager than R&D investments. Through spillover effects and long-term effects E&T and R&D activities have a strong influence on the corporate's productivity.

• Journal of Technology Innovation
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• v.25 no.4
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• pp.211-238
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• 2017

This study was conducted using social network analysis, variance analysis, and regression analysis to investigate the effects of cooperation between innovators on technical performance. Based on data of joint applicants filed with the Korean Intellectual Property Office from 2009 to 2012, we derive network structural variables and characteristic variables, and identify network characteristics that affect the overall network structural type, roles for each subject of innovation, and innovation performance. The findings are as follows: ⅰ) The network of this study is a distributed, small-world network within which relatively small groups of innovators are distributed. ⅱ) Universities were found to play the most important role in cooperation, but diversity of cooperating partners exhibited similar effects. ⅲ) It was shown that access to quick and accurate knowledge from familiar partners exhibits a more positive influence on generating innovative performance than unfamiliar knowledge from a variety of cooperating partners in non-familiar fields.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.41-47
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• 2023

Financial instruments valuation continues to evolve due to various technological changes. Recently, there has been increased interest in valuation using machine learning and artificial intelligence, enabling the financial market to swiftly adapt to changes. This technological advancement caters to the demand for real-time data processing and facilitates accurate and effective valuation, considering the diverse nature of the financial market. Numerical analysis techniques serve as crucial decision-making tools among financial institutions and investors, acknowledged as essential for performance prediction and risk management in investments. This paper analyzes Korean patent trends of numerical analysis-based financial systems, considering the diverse shifts in the financial market and asset data to provide accurate predictions. This study could shed light on the advancement of financial technology and serves as a gauge for technological standards within the financial market.

• International Journal of Quality Innovation
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• v.10 no.2
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• pp.43-56
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• 2009

Many companies are trying to acquire innovative technologies and relevant knowledge by sending R&D work overseas. Although recent research has been focusing on the aspects that motivate MNCs to establish offshore R&D facilities, such as cost reduction and market expansion, little is known about external or circumstantial factors influencing the performance of global R&D activities. Searching for enhancers of offshore R&D facilities, we investigated the relationships between the performance of offshore R&D and the technological capabilities of a parent company, its home country, and its R&D hosting country. Both patent data of ED and the ED R&D scoreboard of 134 overseas R&D labs from 46 MNCs, dating from the period of 2003 to 2005, are used in the analysis. The same time period is applied in calculating the RTA of each country. Regression analysis results support our main hypothesis that the technological capabilities of the parent company and the hosting country positively affect the performance of overseas R&D.

• ETRI Journal
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• v.20 no.1
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• pp.55-73
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• 1998

In this paper we analyze the technological accumulation processes in the Korean semiconductor industry from the institutional approach. Institutional approach, which is closely connected with Neo-Schumpeterian tradition, has emerged as an alternative theoretical framework to neoclassical approach to understand the process of producing technological knowledge. Traditional wisdom of neoclassical approach revealed the limitation to explain the complex nature of knowledge creation and diffusion. US patent data are analyzed in terms of the increasing trend of numbers and its content to measure the rate and direction of technological capability accumulation. This analysis shows that semiconductor technologies are one of the fastest growing fields among Korean technological activities. Moreover, the analysis of patent content suggests that fabrication technologies are the most important area within the technological development of semiconductors, whilst circuit design and testing technologies are beginning to increase in significance. In addition, it is examined how private sectors and public institutions have contributed to generate technological capabilities, and the relationship between them has been changed during the development processes. It is found that Korean firms enhanced their technological capabilities from the learning and assimilation of imported technology to enhanced in-house R&D capabilities in the later stage. The support of public institution and government policy also played significant role to this successful transformation in conjunction with vigorous R&D investment of public sector.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.342-357
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• 2014

The present study analyzes the relationship between research and development (R&D) inputs and performance of a national technology innovation R&D program using successive binary Logistic regression models based on a typical R&D logic model. In particular, this study focuses on to answer the following three main questions; (1) "To what extent, do the R&D inputs have an effect on the performance creation?"; (2) "Is an obvious relationship verified between the immediate predecessor and its successor performance?"; and (3) "Is there a difference in the performance creation between R&D government subsidy recipient types and between R&D collaboration types?" Methodologically, binary Logistic regression models are established successively considering the "Success-Failure" binary data characteristic regarding the performance creation. An empirical analysis is presented analyzing the sample n = 2,178 R&D projects completed. This study's major findings are as follows. First, the R&D inputs have a statistically significant relationship only with the short-term, technical output, "Patent Registration." Second, strong dependencies are identified between the immediate predecessor and its successor performance. Third, the success probability of the performance creation is statistically significantly different between the R&D types aforementioned. Specifically, compared with "Large Company", "Small and Medium-Sized Enterprise (SMS)" shows a greater success probability of "Sales" and "New Employment." Meanwhile, "R&D Collaboration" achieves a larger success probability of "Patent Registration" and "Sales."

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.101-110
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• 2018

This study aims to objectively measure the efficiency of nanotechnology R&D programs by systematically evaluating the inputs and outputs of nanotechnology R&D activities and to find implications for improving the efficiency of nanotechnology R&D programs. Data on input factors such as R&D investment, R&D manpower, R&D period, and output factors such as paper, patent, and commercialization for R&D projects which started from 2008 or afterwards and ended by 2011 are gathered through National Science and Technology Knowledge Information Service, which are used for efficiency evaluation. In this study, we analyzed R&D efficiency in detailed technology units in depth. The process taken in this study is as follows. First, the basic statistics of input and output factors to compare and analyze R&D investment, R&D manpower, R&D period, paper, patent, and commercialization status by technology unit are analyzed. Next, DEA models are utilized to derive the overall efficiency, pure technology efficiency, and scale efficiency by conducting the efficiency evaluation for each technology unit, from which implications for strategic budget allocation are derived. In addition, partial efficiency evaluation is conducted to identify advantages and disadvantages of each technology unit. In turn, cluster analysis is performed to identify similar technology units, from which implications for efficiency improvement are derived.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.139-146
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• 2017

The interest about Artificial Intelligence through the AlphaGo Match in Korea has been increasing rapidly. So far, very little has been done in Artificial Intelligence. The aim of this paper is to reveal technology convergence and to assess the country profile in the field of artificial intelligence(AI). Technology convergence map was created after extracting USPTO patent grants and Web of Science data and generating matrics in the field of AI. Several Indicators were obtained by extracting and calculating SCOPUS Data that KISTI has. According to USPTO patent grants, it shows that AI technology has a strong relationship with several sectors such as cost/price determination, image analysis, and surgery, etc. Also, AI has a active convergence with some fields of Electrical and Electronic Engineering, BioTechnologies, and Medicine etc. According to country profile analysis, Korea reaches a global average growth index. However, in terms of specialization index (SI) and average of relative citations (ARC), there is a large gap between Korea and research leading countries.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.1-8
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• 2020

The use of text data in big data analytics has been increased. So, much research on methods for text data analysis has been performed. In this paper, we study Bayesian learning based on conjugate prior for analyzing keyword data extracted from text big data. Bayesian statistics provides learning process for updating parameters when new data is added to existing data. This is an efficient process in big data environment, because a large amount of data is created and added over time in big data platform. In order to show the performance and applicability of proposed method, we carry out a case study by analyzing the keyword data from real patent document data.