• The Korean Journal of Air & Space Law and Policy
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• v.21 no.1
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• pp.169-189
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• 2006

In 2007, KSLV(Korea Small Launching Vehicle) that we made at Goheung National Space Center is going to launch and promotes of our space exploration systematically and 'Space Exploration Promotion Act' was enter into force. 'Space Exploration Promotion Act' article 3, section 1, as is prescribing "Korean government keeps the space treaties contracted with other countries and international organizations and pursues after peaceful uses of outer space." The representative international treaties are Outer Space Treaty (1967) and Liability Convention (1972) etc. In Liability convention article 2, "A launching State shall be absolutely liable to pay compensation for damage caused by its space object on the surface of the earth or to aircraft in flight. The important content of the art. 2 is the responsible entity is the 'State' not the 'Company'. According by Korean Space Exploration Act art. 14, person who launches space objects according to art. 8 and art. 11 must bear the liability for damages owing to space accidents of the space objects. Could Korean government apply the Products Liability Act which is enter into force from July 1, 2002 to space launching person? And what is the contact type between Korea Aerospace Research Institute(KARl) and Russia manufacturer. Is that a Co-Development contract or Licence Product contract? And there is no exemption clause to waive the Russia manufacturer's liability which we could find it from other similar contract condition. If there is no exemption clause to the Russia manufacturer, could we apply the Korean Products Liability Act to Russia one? The most important legal point is whether we could apply the Korean Products Liability Act to the main component company. According by the art. 17 of the contract between KARl and the company, KARl already apply the Products Liability Act to the main component company. For reference, we need to examine the Appalachian Insurance co. v. McDonnell Douglas case, this case is that long distance electricity communication satellite of Western Union Telegraph company possessions fails on track entry. In Western Union's insurance company supplied to Western Union with insurance of $ 105 millions, which has the satellite regard as entirely damage. Five insurance companies -Appalachian insurance company, Commonwealth insurance company, Industrial Indemnity, Mutual Marine Office, Northbrook Excess & Surplus insurance company- went to court against McDonnell Douglases, Morton Thiokol and Hitco company to inquire for fault and strict liability of product. By the Appalachian Insurance co. v. McDonnell Douglas case, KARl should waiver the main component's product liability burden. And we could study the possibility of the adapt 'Government Contractor Defense' theory to the main component company.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.67-88
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• 2018

Until recently, as we recognize the significance of sustainable growth and competitiveness of small-and-medium sized enterprises (SMEs), governmental support for tangible resources such as R&D, manpower, funds, etc. has been mainly provided. However, it is also true that the inefficiency of support systems such as underestimated or redundant support has been raised because there exist conflicting policies in terms of appropriateness, effectiveness and efficiency of business support. From the perspective of the government or a company, we believe that due to limited resources of SMEs technology development and capacity enhancement through collaboration with external sources is the basis for creating competitive advantage for companies, and also emphasize value creation activities for it. This is why value chain network analysis is necessary in order to analyze inter-company deal relationships from a series of value chains and visualize results through establishing knowledge ecosystems at the corporate level. There exist Technology Opportunity Discovery (TOD) system that provides information on relevant products or technology status of companies with patents through retrievals over patent, product, or company name, CRETOP and KISLINE which both allow to view company (financial) information and credit information, but there exists no online system that provides a list of similar (competitive) companies based on the analysis of value chain network or information on potential clients or demanders that can have business deals in future. Therefore, we focus on the "Value Chain Network System (VCNS)", a support partner for planning the corporate business strategy developed and managed by KISTI, and investigate the types of embedded network-based analysis modules, databases (D/Bs) to support them, and how to utilize the system efficiently. Further we explore the function of network visualization in intelligent value chain analysis system which becomes the core information to understand industrial structure ystem and to develop a company's new product development. In order for a company to have the competitive superiority over other companies, it is necessary to identify who are the competitors with patents or products currently being produced, and searching for similar companies or competitors by each type of industry is the key to securing competitiveness in the commercialization of the target company. In addition, transaction information, which becomes business activity between companies, plays an important role in providing information regarding potential customers when both parties enter similar fields together. Identifying a competitor at the enterprise or industry level by using a network map based on such inter-company sales information can be implemented as a core module of value chain analysis. The Value Chain Network System (VCNS) combines the concepts of value chain and industrial structure analysis with corporate information simply collected to date, so that it can grasp not only the market competition situation of individual companies but also the value chain relationship of a specific industry. Especially, it can be useful as an information analysis tool at the corporate level such as identification of industry structure, identification of competitor trends, analysis of competitors, locating suppliers (sellers) and demanders (buyers), industry trends by item, finding promising items, finding new entrants, finding core companies and items by value chain, and recognizing the patents with corresponding companies, etc. In addition, based on the objectivity and reliability of the analysis results from transaction deals information and financial data, it is expected that value chain network system will be utilized for various purposes such as information support for business evaluation, R&D decision support and mid-term or short-term demand forecasting, in particular to more than 15,000 member companies in Korea, employees in R&D service sectors government-funded research institutes and public organizations. In order to strengthen business competitiveness of companies, technology, patent and market information have been provided so far mainly by government agencies and private research-and-development service companies. This service has been presented in frames of patent analysis (mainly for rating, quantitative analysis) or market analysis (for market prediction and demand forecasting based on market reports). However, there was a limitation to solving the lack of information, which is one of the difficulties that firms in Korea often face in the stage of commercialization. In particular, it is much more difficult to obtain information about competitors and potential candidates. In this study, the real-time value chain analysis and visualization service module based on the proposed network map and the data in hands is compared with the expected market share, estimated sales volume, contact information (which implies potential suppliers for raw material / parts, and potential demanders for complete products / modules). In future research, we intend to carry out the in-depth research for further investigating the indices of competitive factors through participation of research subjects and newly developing competitive indices for competitors or substitute items, and to additively promoting with data mining techniques and algorithms for improving the performance of VCNS.