In the growth of the government's investment in national R&D project and the abuse of research expense, an effective control and management mechanism is strongly demanded. However, an excessive regulation might hinder the R&D performance, which also endangers the underlying objective of R&D policy. Especially, an excessive regulation on the R&D expenditure may damage the SMEs (Small and Medium sized Enterprises) where securing an adequate level of R&D funding is vital. This study investigates the R&D funding and R&D performance of SMEs participating in the national R&D project by using fixed effect panel model. As a result, this paper reveals the effectiveness of 'Government R&D subsidy'. However, that of 'private R&D fund' is not supported strongly. Also, this paper empirically demonstrates the efficiency of both 'Government R&D subsidy' and 'Private R&D fund' as the R&D costs are spent discretionarily (as the degree of 'Indirect Cost Ratio' increases). Especially, the effectiveness of 'Private R&D fund' can be moderated by 'Indirect Cost Ratio'. On the basis of the conclusions, this paper draws an implication that can increase R&D performance of SMEs through the interactions of manifold administrative values (i.e. effectiveness, efficiency and responsibility).
This study aims to analyze the factors that influence the technological performance of national R&D programs, and to compare these factors with those that affect R&D in the machinery and chemical industry. This study also seeks to explore policy implications for the national R&D programs to meet the characteristics of each industrial technology. The results of this study are as follows: First, big enterprises create more Korean patents than small- and medium-sized enterprises (SME) in the machinery R&D. Moreover, government-funded research institutes produce more SCI articles than enterprises in the chemical technology R&D. Second, there is no significant difference in the number of institutions that participate in the machinery technology R&D. Third, the production of Korean patents and Science Citation Index (SCI) articles on all samples in the machinery industry are influenced by government grants. For instance, in the samples, which consist of enterprises, the creation of overseas patents is influenced by the amount of government grants. Fourth, there is no significant difference in the magnitude of private investment, regardless of the sample and industry. In conclusion, different factors influence the technological performances of the national R&D programs in the chemical and machinery technology R&D. This shows that it is necessary to consider the characteristics of industry-specific technology when making science and technology policies for the national R&D programs.
This study has analyzed whether the virtuous cycle of value-added between the processes within the company has formed and whether the virtuous ecosystem between the processes within the industry has been built through the analysis of value chain(VC) and value system(VS) targeting the Korean photovoltaic companies. For a study method, after conducting a survey on the companies, a regression analysis was performed on the causal relationship between the process within the VC and VS. Based on the results of the analysis, for the VC of the Korean photovoltaic industry, an increase in the R&D support from the government has led to the increase in the investment of R&D for the related industry, and the increase in the investment of R&D has contributed to the increase in the growth of its productivity, and the growth in the productivity of R&D has influenced the increase in the production of solar products. In addition, the reduction of photovoltaic production cost for the company has influenced the increase of recurring profit margin compared to the sales. However it was shown that the increase in the company's production volume does not contribute to the reduction of production cost. Meanwhile, the increase in recurring profit margin compared to the sales were influencing the increase in the production volume but it was shown that the increase in the company's investment of R&D was not a contributing factor thus it was not included in the virtuous cycle. It was analyzed that the VS was shown not to influence all other processes within the industry except for the module companies where the increase in the recurring profit margin compared to the sales was influenced by the increase in the recurring profit margin compared to the sales of solar cell companies. This shows that the virtuous industrial ecosystem which should be made under the mutual cooperation by the ingot, wafer, solar cell, module and system companies are yet incomplete.
Health industry, a knowledge based high value-added industry, is being considered as a strategic area for the 21C and many advanced countries are making every endeavors for the promotion of health industry along with information technology, new materials, and mechatronics. Korean health industry, however, has been excluded from the governmental supports as well as bound by strict regulation so far, and there is a significant gap in technology compared with advanced countries. In 21C, technology is the main factor of national competitiveness and that is why the role of R&D institutes are so important in the high level of competition to cope with the technology protection policies of advanced countries. In this article, with Directory of Korean R&D Institutes published by Korea Industry Technology Association, I reviewed the trends of R&D institute of health industry. Main findings of the research can be summarized as follows. The portion of health industry R&D institute is 3.6% of total R&D institute but the amount of R&D investment is over than 5% This means health industry are knowledge based and R&D intensified industry, meanwhile the variations of same industry R&D institutes of health industry is huge in R&D investments and other activities. Regional distributions of health industry institutes show some kind of different patterns in each industry areas. Medical devices and Medical informatics's preference of metropolitan region are distinguished with other industry areas. Many of the institutes are located in same site of it's company rather than operating separate building for R&D specific uses. It is better for transforming ideas to products and close cooperation of research body with product lines, but it is a handicap for networking and communicating with other research institutions too. It takes 18.4yrs for bearing R&D institute on the average. For a long times 'copy products' or 'me too products' policies were easy way to maintain business entities. But recently, it is recognized that research activities are essential component of sustaining it's own business firms. This means technology itself is leading power of corporation itself in the high level of competition.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.19
no.2
/
pp.215-235
/
2024
As artificial intelligence (AI) technology is recognized as a key technology that will determine future national competitiveness, competition for AI technology and industry promotion policies in major countries is intensifying. This study aims to present implications for domestic policy making by analyzing the policies of major countries on the start-up of AI companies, which are the basis of the AI industry ecosystem. The top four countries and the EU for the number of new investment attraction companies in the 2023 AI Index announced by the HAI Research Institute at Stanford University in the United States were selected, The United States enacted the National AI Initiative Act (NAIIA) in 2021. Through this law, The US Government is promoting continued leadership in the United States in AI R&D, developing reliable AI systems in the public and private sectors, building an AI system ecosystem across society, and strengthening DB management and access to AI policies conducted by all federal agencies. In the 14th Five-Year (2021-2025) Plan and 2035 Long-term Goals held in 2021, China has specified AI as the first of the seven strategic high-tech technologies, and is developing policies aimed at becoming the No. 1 AI global powerhouse by 2030. The UK is investing in innovative R&D companies through the 'Future Fund Breakthrough' in 2021, and is expanding related investments by preparing national strategies to leap forward as AI leaders, such as the implementation plan of the national AI strategy in 2022. Israel is supporting technology investment in start-up companies centered on the Innovation Agency, and the Innovation Agency is leading mid- to long-term investments of 2 to 15 years and regulatory reforms for new technologies. The EU is strengthening its digital innovation hub network and creating the InvestEU (European Strategic Investment Fund) and AI investment fund to support the use of AI by SMEs. This study aims to contribute to analyzing the policies of major foreign countries in making AI company start-up policies and providing a basis for Korea's strategy search. The limitations of the study are the limitations of the countries to be analyzed and the failure to attempt comparative analysis of the policy environments of the countries under the same conditions.
Proceedings of the Technology Innovation Conference
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2002.06a
/
pp.238-256
/
2002
Competitiveness of a nation can be explained by the concept of national innovation systems(NIS). As components of NIS, industry clusters become the issue in analysing innovative activity of an economy. Innovative clusters can be identified by the innovation survey or other economic activity data. Input-output Table was used widely as a tool for quantitative analysis, This paper classifies seven clusters in Korean industry based on inter-industries trade of intermediary goods and services, Maximizing procedure method is used in analysing input-output table. Identified clusters are Textiles/chemicals, Construction/Material, Instrument/Equipment, Automobile, Services, Energy, and Agriculture/Food cluster, Among these clusters, some different characteristics in R&D portfolios are detected. R&D investment characteristics of each cluster give us significant implications in understanding innovative dynamics of Korean industry.
Korean government built "2040 Science and Technology Future Vision" in order to show positive future scenarios and suggest a long-term guideline for a progress in science and technology. The S&T Future Vision was built based on an analysis of global megatrends and a prospect of domestic social change. After building S&T Future Vision, the "Government R&E Strategy"s was established as a follow-up action plan. The Government R&D Strategy consists of lists of future emerging technologies for future leadership, government R&D investment status and investment portfolio plans. Exploring future emerging technologies aggressively and making a governmental R&D strategic policy are requirements for national competitiveness, leadership in the world. Therefore search and selection for future emerging technologies is getting more and more important recently. Generally qualitative methodologies have been used such as expert-panel discussion method and portfolio analysis with expert valuation method in order to explore future technologies. These experts-based qualitative methodologies are well defined but lacking in some objectivity because size of expert-panels has limitations. We suggest a quantitative methodology, science mapping method to compensate this shortcoming in this study. There is another limitation related governmental R&D strategy which is that general R&D portfolios are static until a point of technology realization. We also propose a dynamic R&D investment portfolio which present different portfolios at a intermediate point and a point of technology realization. We expect this try with science mapping method and a dynamic R&D portfolio could strengthen strategic aspect of government R&D policy.
Journal of Information Technology Applications and Management
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v.22
no.3
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pp.83-103
/
2015
The rapid development of internet technologies and social media over the last few years has generated a huge amount of unstructured text data, which contains a great deal of valuable information and issues. Therefore, text mining-extracting meaningful information from unstructured text data-has gained attention from many researchers in various fields. Topic analysis is a text mining application that is used to determine the main issues in a large volume of text documents. However, it is difficult to identify related issues or meaningful insights as the number of issues derived through topic analysis is too large. Furthermore, traditional issue-clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be recognized using traditional issue-clustering methods, even if those issues are strongly related in other perspectives. Therefore, in this research, a methodology to reorganize social issues from a research and development (R&D) perspective using social network analysis is proposed. Using an R&D perspective lexicon, issues that consistently share the same R&D keywords can be further identified through social network analysis. In this study, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Issue clustering can then be performed based on the analysis results. Furthermore, the relationship between issues that share the same R&D keywords can be reorganized more systematically, by grouping them into clusters according to the R&D perspective lexicon. We expect that our methodology will contribute to establishing efficient R&D investment policies at the national level by enhancing the reusability of R&D knowledge, based on issue clustering using the R&D perspective lexicon. In addition, business companies could also utilize the results by aligning the R&D with their business strategy plans, to help companies develop innovative products and new technologies that sustain innovative business models.
The national economic policy paradigm is constantly changing according to the global business environment. Among them, fostering SMEs is a core policy of many developed countries. The growth of SMEs contributes to the creation of jobs and the development of local communities in the era of employment-free growth. In particular, the growth of SMEs is the foundation for growth into mid-sized and large enterprises. Therefore, the growth of SMEs plays an important role in the national economy. Information and communication technology (ICT) became important much more with the emergence of the 4th industrial revolution. Among them, the growth of ICT SMEs is the nation's future asset. Therefore, this study examines and verifies the main factors affecting the performance of ICT SMEs from the view of their R&D resources. On the basis of 1,999 SMEs dataset, empirical analysis was performed to investigate the influence of R&D resources on their corporate performance. Its results are as follows. First, based on theresource-based theory, ICT SMEs' R&D investment, R&D manpower, and government support policies were found to have a positive effect on securing a company's competitive advantage. Second, it was found that the level of product has a positive effect on the company's performance. Finally, it was found that M&A and technology acquisition method strategies differ according to the growth stage of the company. Therefore, in order to achieve technological innovation and corporate performance of ICT SMEs, the government support policy and investment into internal R&D personnel play as main factors. In addition, it was found that technology acquisition strategies differ depending on the growth stage of the company.
Soyean Lim;Hyun-Chul Lee;Woo-Sung Yoon;Seong-Seok Go
International conference on construction engineering and project management
/
2009.05a
/
pp.876-882
/
2009
With overall opening of global construction market by World Trade Organization (WTO) agreements, importance of management efficiency of construction industry which considers both tangible and intangible assets is recently being recognized in our nation. That is, efforts for reinforcement of competitiveness must be placed through maximization of values of internal and external intangible assets of construction industry such as management innovation, information, investment in technology and R&D and intellectual property. Accordingly in this study, evaluation criteria for intangible assets of construction industry were investigated and classified. Using such criteria, evaluation index and model were established based on the degree of importance of each criterion. The purpose of this study is to review importance of intangible assets in terms of competitiveness and management efficiency of construction industry and to provide basic data for establishment of intangible assets and revitalization of investment.
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