• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.473-484
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• 2017

This study analyzed collaborative R&D projects funded by the Korean government from 2013-2015. For this analysis, input and output variables of projects were considered, and a combination of those variables was itemized. The output-oriented variable return to scale (VRS) model extended from the DEA methodology was adopted to evaluate the cooperation efficiency of the types of R&D collaboration, which were classified according to the project leader's organizations. In addition, hierarchical cluster analysis was conducted using the efficiency results of the scientific, technical, and economical outcome models. The results showed that cooperation efficiency between large companies and public research institutions was relatively high. Conversely, cooperation among medium-sized companies, small businesses and universities was particularly inefficient. The clustering results demonstrated the various strengths and weaknesses of the types depending on publications, patents, technical loyalties and the number of commercialization. In conclusion, this study suggests differentiated investment portfolios and strategies based on the efficiency results of diverse cooperation types among industries, universities and public research institutions.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.31-39
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• 2023

The purpose of this study is to propose a scientific performance evaluation framework for measuring and managing the overall outcome of complex types of projects that are linked to public demand-based commercialization, such as information system projects and public procurement, in integrated national R&D projects. In the case of integrated national R&D projects that involve multiple research institutes to form a single final product, and in the case of demand-based demonstration and commercialization of the project results, the existing evaluation system that evaluates performance based on the short-term outputs of the detailed tasks comprising the R&D project has limitations in evaluating the mid- and long-term effects and practicality of the integrated research products. (Moreover, as the paradigm of national R&D projects is changing to a mission-oriented one that emphasizes efficiency, there is a need to change the performance evaluation of national R&D projects to focus on the effectiveness and practicality of the results.) In this study, we propose a performance evaluation framework from a structural perspective to evaluate the completeness of each national R&D project from a practical perspective, such as its effectiveness, beyond simple short-term output, by utilizing the Hourglass model. In particular, it presents an integrated performance evaluation framework that links the top-down and bottom-up approaches leading to Tool-System-Service-Effect according to the structure of R&D projects. By applying the proposed detailed evaluation indicators and performance evaluation frame to actual national R&D projects, the validity of the indicators and the effectiveness of the proposed performance evaluation frame were verified, and these results are expected to provide academic, policy, and industrial implications for the performance evaluation system of national R&D projects that emphasize efficiency in the future.

• Journal of Distribution Science
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• v.14 no.2
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• pp.93-101
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• 2016

Purpose - This study aims to advance our knowledge about factors influencing technical startup performance through analysing technical startup process empirically. This study was conducted to focus on industry structure(industry growth rate, competitive intensity, and enter barriers), technology characteristics(technical excellence and wide range of technical application), and the performance in the technology-based start-ups. Specifically, analyzing moderating effect of technology-marketing strategy, this studied how moderating variables affect technical startup performance under industry structure. Research design, data, and methodology - The subject of this study was technology-based start-ups company that received technology transfer from public organization. The development of the paper model is based on the literature of the preceding research analysis in technology commercialization, performance of technology-based start-ups, and marketing strategy. This study has a construct that was defined in the previous studies, such that technology marketing strategy was defined into the two ways of being broad or narrow in strategic application. From November 3. 2015 to December 22, 220 questionnaires were distributed with targeting to start-up companies in technology-based. 188 responses were collected for empirical analysis except the missing and wrong value responses. This data were used for structural equation modeling and regression analysis. Results - The results of this study are as follows. First, as industry structure variables influencing on performance(technical, financial) of technology-based start-ups, industry growth rate, competitive intensity and enter barriers of variables were verified; high growth rate has more positive effect on performance than low growth rate, competitive low intensity has more positive effect on performance than competitive high intensity, low enter barriers have more positive effect on performance than high enter barriers. Second, as technology characteristics variables influences on the performance(technical, financial) of technology-based start-ups, technical excellence and wide range of technical application of variables were verified ; technical high-excellence has more positive effect on performance than technology low-excellence, wide range of technical application has more positive effect on performance than narrow range of technical application. We also find that technology marketing strategy(broad/narrow) in moderating factors on performance (technical, financial) is as follows. Analyzing the moderating effect depending on technology marketing strategy(broad/narrow), application of technology, and the types of technology strategy(broad/narrow) were revealed that broad marketing strategy had a more significant effect on performance of technology-based start-ups. With AMOS, the relevancy of the study model revealed higher for broad technology-marketing strategy than narrow technology marketing strategy, and the explanatory power revealed to be 6.4% higher in broad marketing strategy than narrow marketing strategy. Conclusions - This study confirmed that industry structure and technology characteristics are important factors influencing the performance of technology-based start-ups. Technology-marketing strategy affects the performance of technology-based start-ups between industry structure and technology characteristics. According to additional analysis, moderating variables and technology-marketing strategy are important factors influencing the performance of technology-based start-ups under industry structure and technology characteristics. Broad type of technology-marketing strategy has more attractive industry structure and excellent technology characteristics than narrow types of technology-marketing.

• Journal of Technology Innovation
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• v.22 no.3
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• pp.261-286
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• 2014

Recently, project performance and management of government R&D program investing huge amount of budget is being focused. In this study, I built a model for estimating the performance creating paths of the government R&D program, then I analyzed the attributes of performances created by industries. I used simultaneous equations with FIML and examined the IT industry and CT industry of industrial technology innovation program using survey on R&D performance conducted by KEIT. On the analysis result, all the companies create the innovation performance through the government grants. However, the one who commercialize patents is SMEs in IT industry, and conglomerates in CT industry. SMEs in IT industry, which has characteristic of complex product, need extra self innovation activities even the government supports them. For improving the commercialization performance and technology development of SMEs in CT industry, it is effective when conducting cooperative research. These findings give us the implication that it is needed to consider different factors by industrial and enterprise characteristic when planning the public policy and government tasks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.674-682
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• 2015

RnD Service firms are the innovative company that supports innovation, determines the healthy ecosystem in the high tech business sector. RnD service also brings up a regional innovation through the business ecosystem. This study conducted a case study RnD Service firms leading to the activation of high tech industry. We analyze the role of the RnD Service firms through reports and interviews with corporate managers. We understand the growth process was RnD Service firms, and identify the cost of organizing. RnD Service firms are independent economy, but was also a problem that appears is dependent on universities and research institutions sometimes. When the subject of a regional innovation take place the RnD Service sector, It should be noted that the emergence of innovative business. RnD Service model should not be developed by universities and public institutions, it should be a technology development model that occur between companies.

• Proceedings of the Technology Innovation Conference
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• 1997.07a
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• pp.222-223
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• 1997

By analyzing the successful innovation case of potato microtuber mass production technology, a representative case of technology-push type creative innovation in an imitation oriented research culture, this paper attempts to figure out conceptual model of creative innovation that is initiated by the public laboratories in catching-up country, Stages of creative innovation can be divided into the internal R&D stage and the external commercialization stage. Success of the internal R&D stage depended on autonomy to secure creative research idea and commitment of individual researchers. Psychological pressure evoked from sportlights of mass media and commitment of sponsor increased the intensity of research efforts of the researcher Recognition of research problem and its significance was intensified by site visits of agricultural fields, and the recognized higher impacts of expected research results and knowledge creation achieved were a fundamental source of self-motivation. In the stage of commercialization stage, various legal, socio-economic, and psychological barriers were confronted. In a catching-up country lacking of experiences of creative innovation, creative innovation process can be regarded as a barrier elimination and cultural revolution process. Among the barriers, psychological refusal of farmers to corn-sized potato seeds was critical, which finally enforced to further researches to enlarge the size of potato seeds. In addition, the researcher has concentrated his research efforts in one specialized research area by getting a series of similar research project funds rather than diversification. It was lucky for him to have a chance to carry out a series of similar researches in one research area during the last 10 years. In getting research funds from government and private companies continuously in one research area, both internal and external promoters played significant roles.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.201-209
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• 2019

Recently various start-up competitions have been held in the government, public and private sectors. There is a need to improve the business model of the majority of preliminary founders and early founders through the start - up contest, while improving the possibility of commercialization. The purpose of this study is to analyze the present status of various start - up contests based on the actual survey results of the major start - up contest operators and major participants in Korea. The main results of this study are as follows: First, in the run - up contest, there is a tendency to break out of the event personality, to prevent the opening of the business model of the entrepreneur in the competition, to reduce the formal procedure considering the input time, Improvement of the use of presentation materials, and the purpose of the contest and precise specification of the object of the recruitment. Secondly, it is necessary to establish a juror and a mentor pool with expertise. It is necessary to establish the judges and the mentor pool with expertise in each field, allocate the region according to the regional composition, entrust the judges with entrepreneurial experience, and introduce the post evaluation system for the judges after the competition. Third, most of the contest winners are manufacturing / technology-based businesses.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.57-75
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• 2021

KHNP's shared growth activities are based on such public good. Reflecting the characteristics of a comprehensive energy company, a high-tech plant company, and a leading company for shared growth, it presents strategies to link performance indicators with its partners and implements various measures. Key tasks include maintaining the nuclear power plant ecosystem, improving management conditions for partner companies, strengthening future capabilities of the nuclear power plant industry, and supporting a virtuous cycle of regional development. This is made by reflecting the specificity of nuclear power generation as much as possible, and is designed to reflect the spirit of shared growth through win-win and cooperation in order to solve the challenges of the times while considering the characteristics as much as possible as possible. KHNP's shared growth activities can be said to be the practice of the spirit of the times(Zeitgeist). The spirit of the times given to us now is that companies should strive for sustainable growth as social air. KHNP has been striving to establish a creative and leading shared growth ecosystem. In particular, considering the positions of partners, it has been promoting continuous system improvement to establish a fair trade culture and deregulation. In addition, it has continuously discovered and implemented new customized support projects that are effective for partner companies and local communities. To this end, efforts have been made for shared growth through organic collaboration with partners and stakeholders. As detailed tasks, it also presents fostering new markets and new industries, maintaining supply chains, and emergency support for COVID-19 to maintain the nuclear power plant ecosystem. This reflects the social public good after the recent COVID-19 incident. In order to improve the management conditions of partner companies, productivity improvement, human resources enhancement, and customized funding are being implemented as detailed tasks. This is a plan to practice win-win growth with partner companies emphasized by corporate social responsibility (CSR) and ISO 26000 while being faithful to the main job. Until now, ESG management has focused on the environmental field to cope with the catastrophe of climate change. According to KHNP is presenting a public enterprise-type model in the environmental field. In order to strengthen the future capabilities of the nuclear power plant industry as a state-of-the-art energy company, it has set tasks to attract investment from partner companies, localization and new technologies R&D, and commercialization of innovative technologies. This is an effort to develop advanced nuclear power plant technology as a concrete practical measure of eco-friendly development. Meanwhile, the EU is preparing a social taxonomy to focus on the social sector, another important axis in ESG management, following the Green Taxonomy, a classification system in the environmental sector. KHNP includes enhancing local vitality, increasing income for the underprivileged, and overcoming the COVID-19 crisis as part of its shared growth activities, which is a representative social taxonomy field. The draft social taxonomy being promoted by the EU was announced in July, and the contents promoted by KHNP are consistent with this, leading the practice of social taxonomy

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.