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RISS 인기검색어
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- 저자 : 황석원(Seogwon Hwang) (검색결과 14 건)
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우리나라 도시재생 R&D사업의 델파이 조사에 관한 연구
황석원(SeogWon Hwang),권성훈(Seong-hoon Gwon),이민규(Minkyu Lee) 한국기술혁신학회 2009 한국기술혁신학회 학술대회 발표논문집 Vol.2009 No.5
본 연구에서는 도시재생 R&D사업의 델파이 조사를 실시하여. 각 세부과제의 중요성, 실현가능성과 실현시기, 정부의 지원방안과 사업추진의 장애요인에 대해 분석했다. 조사결과를 바탕으로, 합의 분석을 통해 추가 라운드의 필요성을 판단했다. 또한, 기술수준과 중요도에 의한 포트폴리오를 구성하여 각 세부과제에 대한 평가를 실시했다. 본 연구는 우리나라 도시재생 R&D사업 전체에 대한 대규모 기술예측기술수준 조사연구로서, 향후 동 사업의 수행과 평가에 중요한 근거자료를 제공할 것으로 기대된다.
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‘국가 R&D 혁신 방안’모니터링을 위한 프레임워크 구축
황석원(Seogwon Hwang),박기범,정기철,조용래,안형준,우청원,장훈,강민지,나다영 과학기술정책연구원 2019 정책연구 Vol.- No.-
It is a very important task to check whether the national science and technology projects for next growth engine and job creation through innovation are being implemented properly, and to reflect them in future policy-making. As the function of the deliberation was transferred to PACST(Presidential Advisory Council on S&T), PACST plays a role in as entrusted with the role of comprehensively reviewing and monitoring policies and execution of the government department. If PACST works closely with the ministries, it is expected to contribute to policy implementations, which have frequently reached an impasse due to conflicts among ministries. Like the context above, STEPI conducted a policy research in cooperate with PACST to monitoring the national S&T projects and to support policy implementation. Above all, we tried to examine the implementation of the national projects and to suggest improvements from the viewpoint of policy consumers, ie, field researchers, companies, and the people. This research focused on how specific the national S&T projects are being implemented and the changes in the field as a policy consumers perspective by avoiding policy-maker centered thinking. For this purpose, new methodologies were used, such as organizing the demand system for science and technological innovation policies. In addition to the sense of change, also we examined the effectiveness of policy implementation and suggested future improvement measures. As a result of the FGI and several expert meetings while maintaining a policy consumer’s perspective, the policies pursued by the government are very diverse and well-intentioned, but have not yet reached the point of creating a change that can be felt on the field. For policy implementation to be fully effective, the critical scale of policy implementation will also be considered and long-term continuous implementation will be paramount. The long-term implementation of a policy with a critical scale means that the policy implementation system must be simplified. How it should be changed will require much research and discussion in the future. This research also emphasized policy-demanding views, we hope that policy consumers, who are participate in industries, academies, research institutions, citizens and media sectors, will actively state their opinions and suggest policies during the course of the upcoming wide-ranging discussions.
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황석원(Seogwon Hwang),양승우(SeungWoo Yang),안두현(Doo Hyun Ahn),이세준(Sejun Lee),신은정(Eunjung Shin),양현채(Hyeonchae Yang),한웅규(Ungkyu Han),강희종(Hee Jong Kang),이다은(Daeun Lee),진성만(Seongman Jin),송충한(ChoongHan Song),김해도 과학기술정책연구원 2020 정책연구 Vol.- No.-
In the era of digital transformation, the government is pushing for R&D system integration. The goals of this study are as follows. It presents theories and methodologies for innovation in data-driven R&D management. Second, we propose an innovation policy plan for data-driven R&D management. According to previous studies, data-driven R&D has recently become important due to evidence-based science and technology policy, science of science policy, the 4th industrial revolution, and big data. In 2013, the OECD announced Data-driven Innovation. Korea is linking and integrating R&D databases (e.g. NTIS ; National Science & Technology Information Service). The vision and framework of this study is as follows. The vision of this research is to build a ‘national science and technology data platform’ for data-driven R&D. The ‘national science and technology data platform’ is the most important to meet the needs of data users. Therefore, the framework of this study identifies the user needs of the R&D process. The R&D process consists of five fields (planning / selection / execution / performance evaluation / performance utilization / infrastructure). First, Planning Innovation for Data-driven R&D. R&D planning refers to an activity that prepares efficient means to achieve R&D goals. R&D planning methods is largely divided into Qualitative Method and Quantitative Method. The Qualitative Method is a method of utilizing the experience and opinion of experts. Quantitative Method is a method that utilizes statistics and trend analysis. Recent R&D Planning uses a mixture of Qualitative Method and Quantitative Method (e.g. technology roadmap, DelpHi, Technology Life Cycle, Cross Impact Analysis, etc.). The planning innovation policy task for data-driven R&D suggests building a platform for integrating and providing R&D planning information, constant monitoring, establishing a BERA (Big-data based Early-stage R&D Analysis) centers, and providing consulting services. Second, Selection and Implementation Innovation for Data-driven R&D. As a result of the survey, there is a problem with fairness in the selection and implementation of R&D. To solve the problem of selection and implementation, it is necessary to build a big data platform. The selection and implementation innovation policy task suggests step-by-step intelligence, the establishment of an R&D big data ecosystem, and the use of advanced technologies. Third, Performance Evaluation Innovation for Data-driven R&D. Performance Evaluation refers to an activity that evaluates R&D according to indicators. Performance evaluation lacks autonomy, strategy, expertise, and openness. Therefore, the Performance Evaluation Innovation policy tasked to suggest accumulation, linkage, and sharing with evaluation information, utilization of evaluation results, and establishment of a policy monitoring system. Fourth, Research Utilization Innovation for data-driven R&D. Research Utilization lacks user supported services (supplier-centered management), connectivity/openness, technical/policy basis, information protection standards, and compensation system. Therefore, the Research Utilization Innovation policy task was to propose user-oriented information provision, activation of DB-linked services, reinforcement of access to research data, and establishment of rules for using research information. Fifth, Data Infrastructure Innovation for Data-driven R&D. Data Infrastructure is the most important to collect data that can be utilized. Therefore, it should be reorganized centering on the users (organizations) used. In conclusion, this study proposes the establishment of a ‘national science and technology data platform’ for the development of data-driven R&D innovation policies. The ‘national science and technology data platform’ should be developed step by step (1st to 3rd steps).
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황석원(Seogwon Hwang),권성훈,김윤종,김기환,김지훈 과학기술정책연구원 2017 정책연구 Vol.- No.-
The basic plan for national science and technology corresponds to the basic starting point of science and technology policy in Korea. The monitoring and analysis of performance in the 5-year cycle is closely linked to The basic plan for national science and technology. However, there is a slight ambiguity when it comes to the performance analysis of The basic plan for national science and technology. On the one hand, it might mean a performance analysis of the overall science, technology, and innovation ecosystem of Korea, and on the other hand, it might mean an analysis of the "additional contribution" of the activity of establishing the basic plan itself compared to the time when there was no such basic plans. At present, policy makers usually interprets as the former, meaning that the overall performance of the science and technology innovation ecosystem in Korea is analyzed every five years. This report focuses on two indicators of ‘the contribution of science and technology for economic growth’ and ‘the impact on job creation of science and technology’ among all the contents of the performance analysis of the basic planning for national science and technology which is conducted under the responsibility of MSIT(Ministry of Science and ICT). We additionally propose some policy recommendations for improving performance analysis procedure itself of the basic plan for national science and technology, not limited to reporting the analysis results for the two indicators mentioned above. As a matter of course, the agenda of the science and technology innovation ecosystem in each period are different, and the vision, goals and task setting of the basic plan are changed accordingly. Therefore, it is important to review the overall performance of the ecosystem of science and technology innovation, and to establish and analyze realistic and objective performance indicators according to the agenda of the time.
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황석원(Seogwon Hwang),김지훈 과학기술정책연구원 2017 정책연구 Vol.- No.-
This study is a late study of “Impact Assessment of R&D Investment: Framework Building and a Pilot Analysis”. In the research analyzed the change of the future society based on the innovation of science and technology through the Delphi survey. This is to predict the role of science and technology innovation among the many factors that will make future social change. It also predicts how much government R&D will be contributed among by private R&D, government R&D, and overseas technology. This can be used to predict the impact of government R&D on future social change. First, The Delphi Survey in 2017 updated the observable indicators for the 70 social change indicators to the latest values, and changed, added, and deleted the contents of some indicators. Second, Delphi survey was carried out. Based on the survey results, the social change contribution of science and technology innovation, contribution by social influence source were analyzed. Third, derive the index of social change and analyzed the impact of STI on social change and the effects of government/private R&D. Based on the results of this study, we can see the priority of government R&D investment to cope with future social change based on science and technology innovation. Based on the expected impact of government R&D investment, we can look at the priorities of three perspectives: “simple prediction”, “necessity of policy”, “gap of both”. The priority of the three perspectives can be used to set one priority by weighting each. These priorities can help the government establish a R&D investment strategy. Providing information on the government’s R&D investment strategy and priority setting, but if research and development entities and enterprises’ voluntary R&D implementation lead to considerable gap and distortion due to market failure, government intervention may be required. At this time, the government can consider three options. First, the government is planning to make a very small number of super-large Top-Down projects. Second, it is to purchase R&D services from research and development executives and companies to promote public works by combining promotion of government’s public works and R&D. Third, based on simplicity and transparency business and budget structure, when selecting supported researchers and companies, it is possible to reflect some of the priorities of government strategies and investment in the evaluation items.
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배옹호(Yong-Ho Bae),황석원(Seogwon Hwang),정장훈(Jang Hoon Chung),정현주(Hyun-Ju Jung),김지수(Jisoo KIm),서병선(Byeongseon Seo),고명주(Myoung-Ju Koh) 과학기술정책연구원 2016 정책연구 Vol.- No.-
As the R&D capability of private sector increases, it is needed to change the role of the government from driving national R&D to supporting the private R&D. To rearrange the role of the government in R&D, this study focuses on analyzing R&D investment of the government and the private sector and tries to suggest policy implications. This research questions are as follows. 1) What is the optimal resource allocation between the governmnet and the private sector? 2) What are the effects of government R&D investment on private R&D investment? Are the effects of government R&D investment on the economic growth bigger than the private R&D investment? Is the government R&D investment crowding out the private R&D investment? 3) What are the effects of government R&D policy tools on private R&D investment? To answer these questions, we use the several analysis methodology such as portfolio analysis, econometric tools, survey of corporate recognition, and so on. Wrapping up the discussions, this research raised several policy implications. Firstly, the government has to raise up the efficiency of the government R&D. Secondly, the main areas of government R&D investment need to change from development technology to basic research. And the government has to try support small-meduim size enterprises(SMES), to make more highly vaule-added industry in our country. Thirdly, it is needed to change from the government led R&D system to market led R&D system. Fourthly, it is suggested the desirable technology innovation policies of the future growth engines.
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