• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.95-108
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• 2020

A coronavirus disease 2019 (COVID-19) is a new global health problem. The Korean government is pursuing to gain its future growth engines and promoting short-term economic stimulation by investing in research and development (R&D) to improve national technological capabilities that can respond to the spread of the global epidemic. It is required to need knowledge information to establish the direction of future national planning thru understanding the status quo of R&D investment in terms of research fields. Four corona-related R&D fields were drawn on the basis of analyzing major nations' R&D funding data (USA, EU etc.) and two differentiated R&D fields were added through comparative analysis with domestic R&D projects. Domestic and foreign research organization-the research title-the scale of the research funding-the project period were presented in terms of the suggested 6(7 details) R&D research fields. Meanwhile R&D projects that have featured in the convergence of interdisciplinary were provided. This study proved the excellence of coronavirus detection and on-site diagnostic capabilities that are currently globally highlighted by deriving differentiated research fields from the domestic competitive advantage fields related to corona viruses and also suggested intensive investment research fields.

• Journal of Korea Technology Innovation Society
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• v.21 no.3
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• pp.1077-1100
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• 2018

The present study analyzed the effect of firms' external research and development (R&D) on corporate productivity, while investigating the moderating effect of firm size on the external R&D-productivity nexus. In the empirical analysis, we estimated South Korean manufacturing firms' total factor productivity (TFP) using the firm level data drawn from the Survey of Business Activities (Korea National Statistical Office) for the years 2006-2015. Thereafter, focusing on the role of external R&D and its interaction with the firm size in determining firms' TFP, the productivity function was estimated as well. To this end, we used ordinary least squares (OLS) and quantile regression to highlight the heterogeneous impacts of external R&D by companies' productivity level. Empirical results confirmed that firms' external R&D significantly enhanced corporate productivity in all manufacturing industries, from high-tech to low-tech. The moderating effect of firm size in determining the productivity effect of external R&D was not as prominent as in the case for internal R&D, which exhibited some degree of the size premium in the productivity-enhancing effect. These results suggest that regardless of the firm size, external R&D can be an important channel for corporate productivity improvement, and can be a particularly effective strategy for SMEs with relatively limited internal R&D capacities.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.129-129
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• 2017

In planning and evaluating government R&D programs, one of the first steps is to understand the government's current R&D investment portfolio - which fields or topics the government is now investing in in R&D. Analysis methods of an investment portfolio of government R&D tend traditionally to rely on keyword searches or ad-hoc two-dimensional classifications. The main drawback of these approaches is their limited ability to account for the characteristics of the whole government investment in R&D and the role of individual R&D program in it, which tends to depend on the relationship with other programs. This paper suggests a new method for mapping and analyzing government investment in R&D using a combination of methods from natural language processing (NLP) and network analysis. The NLP enables us to build a network of government R&D programs whose links are defined as similarity in R&D topics. Then methods from network analysis show the characteristics of government investment in R&D, including major investment fields, unexplored topics, and key R&D programs which play a role like a hub or a bridge in the network of R&D programs, which are difficult to be identified by conventional methods. These insights can be utilized in planning a new R&D program, in reviewing its proposal, or in evaluating the performance of R&D programs. The utilized (filtered) Korean text corpus consists of hundreds of R&D program descriptions in the budget requests for fiscal year 2017 submitted by government departments to the Korean Ministry of Strategy and Finance.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.1-21
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• 2021

As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.

• Management & Information Systems Review
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• v.33 no.1
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• pp.191-217
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• 2014

The Purpose of this study is to find the effect factors of R&D investment in SMEs which plays an important role in the national economy, and the differences of the effect factors by the type of SMEs. The subject of this study is about 3,400 SMEs mentioned in "The survey of technical statistics on SMEs in 2007" by Korea Federation of Small and Medium Business. The effect factors are related with the size of business, the infrastructure of R&D and the activities of R&D which have been studied by many researchers. The methods of analysis are regression analysis, moderating effect analysis and the software package used is SPSS 12.0. The results of the study are as fallow. First, it was found that unlike in previous studies which show the effect of the elements of business's size, research infrastructure, research activities on R&D investment, one element alone can't be considered for meaningful result but the various elements have effect on R&D investment at the same time. In other words, the number of employees and the sales as the elements of business's size, the ratio of researchers, the technical ability, the ratio of equipment possession and the intellectual properties as the elements of R&D infrastructure, the activity of ideas and joint research as the elements of R&D activities have positive(+) effect, whereas the participation of CEO in the activity of R&D as the elements of R&D activities activity has negative(-) one. The number of employees, the ratio of researchers, and the sales had relatively high influence whereas equipment possession, technical ability, intellectual properties, the participation of CEO in the research, the activity of idea, joint research had relatively low influence. Next, it was also found that there are differences of the effect factors over the types of SMEs. SMEs were classified into 19 types by eight criteria such as start-ups and existing business by business age; small business and medium business by size; manufacturing business and service business by product type;independent business and subcontractor business by dealing type; businesses in the entering, growing, maturing and restructuring stage by growth stage; businesses with low, medium and high technology by technological level; pioneering business and non-pioneering business by industrial type; and businesses with state-of-the-art technology and non-advanced business by the level of business activities. The meaning of this study lies in the fact that it found the various effect factors should be considered at the same time when conducting study on SMEs' R&D investment, and the differences by the type should be acknowledged. This study surpassed the limitations of the previous studies which focused on a couple of factors and types. This study result can also be considered for other studies on achievement, organization, marketing and others. Moreover, it shows that a differential policy by business type is needed when formulating SME policy.

• Journal of Korea Technology Innovation Society
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• v.22 no.2
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• pp.207-219
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• 2019

The international trends in activities of government R&D performance measurement is evolving into evidence-based approach to support the verification of objective policy implementation. The European Commission has been implementing KETs (Key Enabling Technologies) policy that incubates nanotech based emerging technologies to support the fourth industrial revolution/revitalization of high-tech manufacturing, and resulting innovations are quantified by KETs Observatory project. The European Commission also built Innovation Radar system that monitors potentially innovative projects within FP7 and Horizon2020 by data analysis. The United States is also upgrading its Federal RePORTER system to quantitatively monitor federal R&D investments with outcomes (including nanotechnology). In the field of Korean nanotechnology, basic statistical data by analyzing NTIS (National Science & Technology Information Service) information is applied in policy field. Developing innovation measurement methodology beyond basic statistical analysis is an international policy issue, and a long-term R&D investment area of a government. The objective of this model study is to quantify the innovation potential of nano R&D investments conducted by Korea government, using input-output based efficiency measurement model and NTIS (National Science & Technology Information Service) that is comprehensive data portal for national R&D investments/outcomes including nanotechnology.

• Korean Journal of Construction Engineering and Management
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• v.17 no.2
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• pp.49-57
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• 2016

R&D projects for land, infrastructure, and transportation is to identify challenges through academic-industrial demand survey, and to promote R&D projects through detailed planning projects. These R&D projects have been promoted to be applied to most domestic project-oriented. Despite continuous R&D investment, the investment has been promoted to the world top technology rather than to international construction projects. This study analyzed the international construction market trends and international construction contracts in order to promote technology development for enhancing international construction competitiveness. This study suggests three R&D technology development directions and ten research projects for expanding international construction projects.

• Journal of Korea Technology Innovation Society
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• v.18 no.1
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• pp.1-27
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• 2015

Korea has increased R&D investment continuously for the improvement of global technological competencies. Korea ranked first in the world with 4.15 percent in the ratio of R&D investment to GDP. In particular, the private sector occupies a crucial position of technological innovations in Korea, constituting 78.5% of total R&D investment. However, quantitative growth strategy is no longer effective, so efforts to enhance efficiency by upgrading qualitative level are badly needed. This paper studied methods for improving firms' business performance. For this, it tried to empirically verify technology strategy and technology planning capability's influence factors on the improvement of business performance. The study showed that technology strategy and technology planning activities have positive effects on the improvement of business performance. And it was revealed that coordination flexibility contributes to the enhancement of business performance by positively controlling technology planning activities. The study performed sample survey on the companies with R&D centers and multiple regression analysis and quantile regression were used for the analysis.

• Journal of Technology Innovation
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• v.24 no.1
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• pp.143-167
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• 2016

The purpose of this study is to analyze changes of innovation activities and their performance in pre-IPO and post-IPO of KOSDAQ IPO listed companies in medical and pharmaceutical fields, which require high R&D investment, from 2000 to 2005 in Korea. The innovation efficiencies of the IPO companies were measured before and after three years based on the DEA model. The financial data and patent information of the listed company during total 6 years, which were 3 years before IPO and 3 years after IPO, were collected. The main results of this research are as follows. First, it took an average 12.86 years until IPO in the start-up of the IPO companies in the pharmaceutical sector, and innovation was on average more active than the IPO before. R&D investment was higher than the IPO before, and the number of the applied patent during 3 years after IPO was 16.67 which was increased from 8.43 during 3 years before IPO. In addition, the average scope of technology of the IPO companies was expanded from 11 to 22 technology fields during previous 3 year and after 3 year each, and financial growth after IPO was lower than the previous IPO. Second, the financial performance of R&D investment and the performance of patent activity were weakened in the efficiency after the IPO, and the integrated performance from the patenting activities and the R&D investment was decreased after the IPO. Finally, the efficiency of the financial performance of the patenting activity was lower than the efficiency of the financial performance of the patent and R&D investment and patent activities under the R&D investment. In particular, the inefficiency of the firms' patenting activities performance after the IPO was caused by the decreasing return to scale, according to the results of this study. This results implicate that the expansion of R&D investments through the IPO had not lead to the financial performance of the market, and that the overall inefficiency since the IPO is due to the inefficiencies at the stage for the outcome of innovation activity rather than the output obtained through the R&D investments that appear to lead the performance of the market.

• Economic Analysis
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• v.17 no.1
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• pp.103-130
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• 2011

This paper intends to provide applied economists which study the effects of research and development with valuable information on econometric model selection. It includes extensive discussion on econometric models which have been applied for the study on the relationship between research and development and productivity. In particular, it compares various stochastic production frontier models which have been developed recently. The discussion decomposes them into models with scaling property and the ones with nonscaling property as well as models with monotonic and nonmonotonic relationships between research and development and productivity. Finally, this paper applies the models to two different panel data sets (firm level data and country level data) and compare estimation results from competing econometric models.