• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.674-679
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• 2006

The public research and development (R&D) funds for construction engineering is one of the key elements for the advancement of construction industry. Korean Ministry of Construction and Transportation is currently planning to produce approximately US$ 500 millions of research funds every year in Korea from year 2007. Along with the prospect for increasing R&D investment, there is of increasing pressures on the development of quantitative methodologies for assessing the performance of construction R&D results. Although there have been some general R&D project evaluation methods, they are not readily used for construction R&D research assessment due to the distinct characteristics of construction R&D. This paper presents a simple methodology that can make quantitative assessments of construction R&D performances. The proposed methodology is expected to assist government officials in objectively evaluating construction R&D performances and identifying the areas that require more R&D investment.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.75-89
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• 2015

This study examines 31 import and export cargo items handled in each port to investigate which items face the most competition among the ports and how many of them are transited to other ports. The study aims to suggest implications for the future port policy of Incheon Port. It was found that the volume concentration in the Western Coast region from 2005 to 2014 became increasingly decentralized. The decentralization began in earnest in 2009 in particular, and the value was 0.448 in 2014, indicating fierce competition among the regions. According to the static and dynamic positioning analyses results for Incheon Port, Pyeongtaek and Dangjin Port, and Gunsan Port, using BCG Matrix, the static positioning analysis showed that Incheon Port belongs to the 3rd quadrant (Cash Cows), Pyeongtaek and Dangjin Port belongs to the 2nd quadrant (Question Marks), and Gunsan Port belongs to the (Dogs) group. This implies that Incheon Port has maintained its position with large shares compared to those of other ports, despite its low growth rate. However, the market position and growth rate of Incheon Port decreased according to the dynamic positioning analysis results. The shift-share analysis results indicated that the volumes of Incheon Port and Gunsan Port were shifting to Pyeongtaek and Dangjin Port. Moreover, the ratio of absolute growth to potential growth of Incheon Port and Gunsan Port turned out to be significantly lower than that of Pyeongtaek and Dangjin Port, implying that Incheon Port and Gunsan Port are declining as compared to Pyeongtaek Port and Dangjin Port. According to the LQ index analysis results, specialized items from Incheon Port that do not overlap with other ports included the following ten items: meat, fish and crustaceans, bituminous coals, crude oil and petroleum, petroleum-refined products, plastic rubber and products, textiles, nonferrous metal and products, electric machinery, and aircrafts and ships. In particular, it was confirmed that the bulk cargo of Incheon Port was actually shifting to Pyeongtaek and Dangjin Port following the policy of re-establishing port functions.