The significance of SMEs (small and medium-sized enterprises) is gradually highlighted as we have entered the age of "New Normal." The South Korean government support these enterprises to boost economic growth and create more jobs. It also releases numerous policies such as national R&D projects and expanding tax incentive services particularly aiming at promoting dramatic investment in R&D and technological innovation. There is a sharp contrast regarding the efficiency of direct or indirect supports for encouraging R&D investment launched by SMEs depending on researchers. However, there has been little attempt to explore the optimal combination of two policy tools. Amid promoting affiliated governmental departments in charge of SMEs policies and constantly growing R&D investment, it is an appropriate time to discuss the medium and long-term direction for the optimal policy mix of direct and indirect supports. In this study, the author obtained 32 relevant studies published earlier in the domestic journals, explored literatures more systematically, and further conducted a meta-analysis. It is dedicated to summarizing relevant controversies and organizes them empirically beyond merely verifying whether policy support stimulates private R&D investment by SMEs. The meta-analysis showed that it would be effective to support as tax for large enterprises, while subsidiary support for SMEs. However, indirect support needs to be progressively increased as direct support primarily accounts for the entire R&D support for South Korean SMEs.
The purpose of this study is to present meaningful information and policy implications concerning the determinants of royalties of technology transfer to stakeholder. To identify key determinants of royalties in technology transfer, this study conducted AHP survey analysis (Survey period: 01/09~31/10, 2016) of 96 government-funded research centers and 85 companies which were participants of the R&D project "Next Generation BioGreen21" of R.D.A in the "N" center from 2011 to 2015. Research results show that both parties acknowledge 'Technical considerations for determining the profitability of the technologies' and 'The interest and willingness of the management group' as critical factors for the determinants of royalties. The difference of each party is that private companies acknowledge 'Available budget plan' as a critical factor while the government-funded research centers value 'Market competitiveness'. These findings suggest four main policy implications which are the investigation of technological demands reflecting specific needs of industrial sites, the diversification of royalty payments for private companies, the differentiated research evaluation system for the purpose of technology transfer and the planning of public R&D project reflecting research time span of private companies.
Recently, due to the primary emphasis of health industry and to the restriction of budget, setting the priorities for effective and efficient investment on the medical device and material products has been one of the critical issues in the government sector. This paper shows how an Analytic Hierarchy Process (AHP) model can be used for assessing selected medical device and material products for grant of the Ministry of Health & Welfare. The final results show that unabsorbable suture is the most attractive medical device product among 88 evaluated products, followed by IV cannula, central venous catheter.
The purpose of this research investigates the determinant factors of the joint technology development project performance between SMEs and universities. Reviewing existing papers we could categorize independent variables into three groups of partner characteristics, process management variables and relationship characteristics between partners. Three measures of satisfaction with the cooperation result, the intention of continuing relationship and the utilization of developed technology and product were used as dependent variable considering that we studied the joint projects of SMEs' involvement, short period and small scale. The data was collected by questionnaire survey mailed to the 1082 SMEs and university professors which executed the joint projects sponsored by Small Business Administration in 2009. We received 200 responses from SMEs, and 305 cases from professors among which 55 responses of each partner were on the same project. We analyzed the data sets individually, data of SMEs and that of universities with multiple regression analysis technique and also analyzed the common responses of 55 projects. Analysis results of the data from SMEs indicated that partners' expertise, facilities and equipment, communications, strategic importance, and trust were significant variables for the project performance. Analysis results of the data from universities showed that previous links, definition of objectives, strategic importance, trust and commitment were significant variables. Analysis results of combined data of 55 projects from SMEs and universities indicated that facilities and equipment, project management proficiency and commitment were significant variables.
The purpose of this paper is to figures out the impact on the business performance based on the case studies about the establishment of automated smart factories supported by the government. In this study, the effectiveness of supporting business is verified by comparing supported company with non-supported ones using methods such as T-test and ANOVA. The PSM method was used to solve the selection bias issue between the experimental group and the controlled group. The research results have shown that the effect of the supporting business to the automated system was tenuous, and the amount of sales and research and development costs was increased after a certain schedule passed in case of the supporting project to the smart factory. There is some time lag to appear the effect of the government supporting businesses and the supporting business to the automated system leads to long term sales increase by increasing parameters like research and development costs rather than direct influence. Therefore, this research will be useful information for the process of establishing useful basic data and policies which helps to secure new budget Government Supporting Businesses and find ways improve the business.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
/
v.12
no.2
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pp.105-115
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2017
Innovative cluster theory promotes cluster growth as the tacit knowledge and know-how approach becomes easier through industry-academia cooperation. Industry-academia cooperation is an innovation network policy that supports joint research between industry and academia. In this respect, The Flow of recent government policy is activating I-U support office in university & research institute for enable I-U Cooperation ecosystem. Then SMB Administration was first performed "research village support program", to support SMEs in industry-university cooperative research capabilities by integrating the research, development and commercializatin of the university or research institution with excellent research base in 2013. However, I-U Cooperation R&D must be based the link strategy of Localization in order to be better composition at research village. In the case of research villages where specialized discovery strategies are well reflected, integration of similar companies in specialized fields will naturally create clusters and create synergy of research. This study searching and summarizing through a recent Hanbat National University research village. Finally, we propose the implications of government policy.
This paper used individual establishment level data to estimate the effects of government support for the research and development of 'small and medium enterprises'(SMEs). We analyzed, on the establishment level, the degree of technical advancement, strength of private R&D incentives, and the effect on employment levels of firms which participated in the 2010 government R&D support project. The results of this study are as follows. First, the size and frequency of government investment in the R&D of SMEs were both positively correlated with the amount of patent registrations. Furthermore, we found that the amount of patent registrations were positively correlated with the size of the establishments, but the average level of technological advancement for the firms running the research was lower than the average level of technological advancement for the firms merely participating in the project. Second, the government's R&D policy was found to be complementary to private R&D incentives, and a 1% increase in government R&D investment resulted in an inelastic increase (0.193~0.245%) of the firms' post-program R&D spending. Third, we found that R&D support from the government contributed to an increase of employment by the participating firms. Additionally, we found that the impact of R&D support on job creation varied for the firm size and technological characteristics. Therefore, it is important for governments to take into consideration each type of small business, when setting R&D policies.
From a point of knowledge based view, IUI(Industry-University-Institute) R&D collaboration is recognized as an important way to acquire lacking technology and knowledge. In this study, we investigated firm performance of IUI R&D collaboration on national R&D project. That is, we identified whether a collaborative research really affects firm performance, and whether firm performance is differed by types of collaboration. To test our hypotheses, we selected 250 Korean SMEs(Small and Medium Enterprises) which were funded from government R&D for 2006-2009, and we verified relations between the ratio and/or types of R&D collaboration and firm performance. Firm performance was measured by number of patent applied and ROA(Return on Assets) after completion of the project (in year t+1). Findings showed that the relationship between the ratio of R&D collaboration and technological performance was inverted U-shape. Among types of R&D collaboration, though inter-industry collaborative research was negatively related to technological performance, IUI collaborative research was positively related to technological performance. However, the ratio and types of R&D collaboration had no relation to economic performance. The results of this study will contribute to the strategy of SMEs as well as the policy of a government with regard to IUI R&D collaboration.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.19
no.2
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pp.215-235
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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.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.13
no.1
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pp.61-72
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2018
In a rapidly changing environment, such as globalization, technology-based startups are attracting attention as a new growth engine that creates jobs and added value and promotes national competitiveness. At present, countries around the world recognize the development of technology-based start-up companies as a major policy task and strive to make policy efforts to revitalize start-ups and strengthen innovation capabilities of companies. Especially, in order to secure superiority in the fierce market competition, it is becoming more and more important for the growth and development of technological start-up companies that pioneer new markets and energize the economy based on original and innovative technologies. Therefore, it is necessary to study systematically and plan for survival and growth of technology start-up companies. The purpose of this study is to investigate the entrepreneurial spirit of Innovation, Entrepreneurship, Risk Sensibility and Technology Innovation Capacity, R&D ability, Technology Accumulation Capacity, Technology Innovation System, The results of this study are as follows. the effects of marketing ability on technical performance and financial performance are examined. First, the CEO 's entrepreneurial spirit has an effect on the technical performance and financial performance of the management performance. Second, the technology accumulation ability and the R & D capability have a positive effect on the technical performance. Finally, it was found that the ability to commercialize the technology commercialization capacity affects both technical performance and financial performance. The policy implications that can be gained through this are as follows. First, by strengthening cooperation between universities and research institutes, related technology entrepreneurship education programs should be upgraded so that technology entrepreneurs or preliminary entrepreneurs can capture business opportunities and secure market price competitiveness. Secondly, R & D for the purpose of start-up should be developed and marketable technology should be developed and linked to direct start-up. Third, it is necessary to activate the program to match the company with the honorary retirement manpower of large enterprises and SMEs, which have more experience in field experience than the founders.
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