• Journal of Korea Technology Innovation Society
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• v.11 no.2
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• pp.241-263
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• 2008

Within any income approach, a discount rate is used to convert some projected free cash flow to its presented value. In case of valuing companies, the most frequently used discount rate is the weighted average cost of capital(WACC) at the aggregate level. But technology valuation is different to discounting aggregate corporate cash flow since it is concerned about individual Intellectual property. Therefore, blindly applying standard discount rate such as WACC in technology valuation is unlikely to lead to the right result. The primary focus of this paper is to establish the structure of discount rate for technology valuation and to suggest the method of estimation. To determine an appropriate discount rate for technology valuation, the level of technology risk, market risk and competitive risk should be included in the structure of discount rate. This paper suggests the build-up model which consists of three components as a expansion of the CAPM. It includes (1) a risk-free rate of return, (2) general market risk premium and beta and (3) intellectual property risk premium related to technology risk and specific target market risk. However, there is no specific check list for examining the intellectual property risk until now and no specific method for quantifying its risk into risk premium. This paper developed the 10 element to determine the level of the intellectual property risk and applied estimation function such as linear function, natural log function and exponential function to transform the level of risk into risk premium. The limitation of this paper is that the range of intellectual property risk premium is inferred based on the information of foreign and domestic valuation agency. Finally, this paper explored the development of an intellectual property discount rate for technology valuation and presented the method in order to quantify the intellectual property risk premium.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.451-469
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• 2014

The purpose of this study is to implement and develop the integrated Economic Value Added (EVA) and Time-Driven Activity-Based Costing (TDABC) model to seek both improvement of Net Operating Profit Less Adjusted Tax (NOPLAT) and reduction of Capital Charge (CC). Net Operating Profit Less Adjusted Tax (NOPLAT) can be maximized by reducing the indirect cost of an unused resource capacity increased by Cost Capacity Ratio (CCR) of TDABC. On the other hand, Capital Charge (CC) can be minimized by improving the efficiency of Invested Capital (IC) considered by Weighted Average Cost of Capital (WACC) of EVA. In addition, the integrated system of TDABC using Balance Scorecard (BSC) and EVA is developed by linking between the lagging indicators and the three leading indicators. The three leading indicators include customer, internal process and growth and learning perspectives whereas the lagging indicator includes NOPLAT and CC in terms of financial perspective. When the Critical Success Factor (CSF) of BSC is cascading as a cause and an effect relationship, time driver of TDABC and capital driver of EVA can be used efficiently as Key Performance Indicator (KPI) of BSC. For a better understanding of the proposed EVA/TDABC model and BSC/EVA/TDABC model, numerical examples are derived from this paper. From the proposed model, the time driver of TDABC and the capital driver of EVA are known to lessen indirect cost from comprehensive income statement when increasing the efficiency of operating IC from the statement of financial position with unified KPI cascading of aligned BSC CSFs.

• Journal of Digital Convergence
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• v.3 no.1
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• pp.115-148
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• 2005

This study is intended to suggest a more reasonable and practical method of estimating discount & capitalization rate for valuation of closely-held culture content business, that is, to modify the Buildup Summation Model(which is recommended for the closely-held business by the NACVA) by adopting the weighted ratings in the CT Project Investment Evaluation of the Korea Culture Contents Association to risk factors of the Buildup Summation Model. This method is ease to apply for closely-held culture content business and has advantages in applying the weighted rates based on the characteristics of respective culture contents. And it can make up for the Weighted Average Cost of Capital (WACC) which shows generally low discount rates.

• 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.