• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.474-477
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• 2013

As the market-based spectrum policy is introduced, an interest in the economic value of the frequency is increasing. Research and practical applications concerning the methodology for the estimation of the economic value of the frequency and its determinants are actively engaged, which are used for setting a reserve price and bid price of spectrum auction and a spectrum clearance cost. In this study, by the analysis of the spectrum valuation methodology, we derive the changes in the factors affecting the valuation and propose to apply improved. In the model frequency value is consist of technical value, commercial value and strategic value, we find the dynamics of fluctuation factors and suggest how to apply them to spectrum policy.

• The Korean Journal of Franchise Management
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• v.14 no.4
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• pp.35-50
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• 2023

Purpose: This study aims to uncover the mechanism of how initial fees are determined in the restaurant franchise business. Since the initial fees can be considered as a price of utilizing business models and operational knowledge of a certain franchise brand, it is critical to understand the fee decision-making process based on the strategic pricing theories. Therefore, this study investigates the influence of operational value on the determination of initial franchise fees grounded on a value-based pricing strategy. The Operational value is specifically categorized into profitability, growth, and stability of the franchise system. Research design, data, and methodology: The data used were collected through franchise disclosure documents and brand equity index provided by Korea Management Association Consulting. Data from 44 franchise restaurants during 2018 to 2021 are included in the sample. The panel dataset was analyzed by using generalized least squares estimation with R-Studio. Results: Profitability and stability positively influence initial franchise fees. However, growth did not influence initial franchise fees. Conclusions: The results of the study demonstrate that the operational value plays a critical role in determining the franchise fees. Specifically, franchisees recognize how much revenue a franchise system generates for them (i.e., profitability) and how stable the entire system is for operating business (i.e., stability) when they make purchasing decisions for franchise. The findings extend the pricing literature by applying pricing theories in the franchise fee context. Also, the study contributes to franchising and restaurant management literature by providing knowledge of how franchise fees are determined.

• Electronics and Telecommunications Trends
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• v.27 no.6
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• pp.38-48
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• 2012

최근 주요 IT 업체의 마케팅 전략은 하드웨어적인 성능 및 가격 위주의 시장전략에서 제품 및 서비스에 대한 사용자의 편의성과 만족도를 극대화시키는 감성 UI(User Interface)/UX(User eXperience)에 바탕을 둔 소비자 감성 지향형 전략으로 이동해 가고 있다. 스마트 시대의 핵심은 감성과 기술의 소통이며, 미래의 정보 서비스는 보고 듣는 것에서 만지고, 느끼고, 기기와 소통하게 함으로써 제품과 서비스의 가치가 결정되는 감성 기반의 서비스가 될 것이다. 감성정보 서비스 기술은 사용자와 기기가 교감하는 디지털 인터페이스를 통해 새로운 형태의 의사 소통 방식과 감성전달 메커니즘으로 소비자의 현재 정서를 인지하고 감정의 정화/승화/억제를 보조하여 보다 사실적이고 실감적인 미디어 소비를 지원할 것이다. 본고에서는 미래 감성 ICT 생태계의 기반이 되는 감성 UX에 대하여 방송 통신망을 바탕으로 한 감성정보 서비스의 현재 모습과 기술동향에 대해 기술한다.

• Korean Journal of Construction Engineering and Management
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• v.15 no.4
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• pp.58-67
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• 2014

The proportion of investment in national R&D projects in construction and transportation has been increasing continuously; in terms of the size of R&D projects, there are many medium- to large-sized projects of over KRW 10 billion. However, in spite of such continuous increase in R&D investments, there are many technologies developed but not commercialized, i.e., the quiescence of technology. Accordingly, it is necessary to link the R&D results to commercialization by expanding the scope of R&D projects. In this context, this study presented objective reference prices to be used in contracting/transacting technology and implementing commercialization strategy by conducting technology valuations against on-going research projects with earnings approach, and by estimating value of patented technology. Sum of free cash flow (business value) that can be generated during the life of the technology was estimated as KRW 512 million by reflecting a discount rate of 16.34% to convert it into the present value. In addition, the technology value was computed as KRW 227million by applying a technology factor of 44.39% to the above value. Based on the technology value estimated in this way, it is necessary to establish industrialization and commercialization strategy of the technology.

• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.57-74
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• 2017

The Electronic Shelf Label (ESL) is an alternative to the paper price label attached to merchandise shelves and is attracting attention as a retail IoT infrastructure that will lead the innovation of offline retail outlets. In general, when introducing a substitute product, the company tends to consider the financial factors such as the efficiency of the investment cost compared to the existing product or the reduction of the operating cost. However, considering only financial factors in the decision-making process, it may not properly reflect the various values associated with corporate strategy and the requirements of stakeholders. In this study, 8 evaluation items (Investment Cost, Operating Cost, Quality Level, Customer Management, Job Efficiency, Maintenance, Functional Expandability, and Store Image) based on BSC's 4 perspectives (Financial, Customer, Internal Business Process, Learning & Growth), and using AHP (Analytic Hierarchy Process) to measure the priorities of evaluation items for domestic small supermarket employees. As a result of the research, priority was given in order of Customer, Learning & Growth, Internal Business Process, and Financial aspects among the evaluation items for adopting the price label, and the electronic price label was supported with higher importance than the paper price label. In contrast to the priorities of the financial aspects of most prior studies, the items of Learning & growth and customer perspectives have relatively high priorities. In particular, respondents classified by job group, The priorities of the 8 evaluation items were different among the groups. These results are expected to provide implications for both companies (retail outlets) and ESL providers (manufacturers and service providers) who are considering the introduction of ESL.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.168-175
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• 2020

Recently, there has been an increasing need to expand the supply of renewable energy as a solution to greenhouse gas emissions. Therefore, as a measure to promote domestic renewable energy investment and gradual expansion, this study analyzed the investment value of renewable energy projects utilizing the unoccupied spaces of public enterprise's facilities and presented a strategic decision-making framework to support efficient national land development and government measures. The NPV was estimated to be 286 million won if the expansion of the facility was not considered, but it is reasonable to postpone the expansion decision because the value of -130 million won was calculated if the expansion was considered. On the other hand, the real-option value was estimated to be 444 million won, taking SMP uncertainty, expansion, and abandonment options into account, and an additional value of 288 million won was calculated from an analysis of the expansion project using the existing NPV analysis.

• The Proceeding of the Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.3 s.59
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• pp.63-73
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• 2006

Auctions have been traditionally used to find the current price of goods when little is known about their true value. A special auction methodology, called a 'simultaneous multiple round auction', is available to auction radiofrequency spectrum where all lots are simultaneously on of for over multiple rounds of bidding. This type of auction is especially useful when there are lots that are of essentially equal value and substitutable, except that different bidders may prefer different combinations of lots. By using multiple rounds, a bidder has the opportunity to gather information concerning the value of individual lots and can change strategy by shifting the bidding to another preferred combination if one combination becomes too expensive. Information is released in three main ways during an auction: Bidder Status; High Bids; and Bandwidth Value.

• Management & Information Systems Review
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• v.33 no.1
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• pp.45-63
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• 2014

A trading system is a computer trading program that automatically submits trades to an exchange. Mechanical a trading system to execute trade is spreading in the stock market. However, a trading system to trade a single asset might occur instability of the profit because payoff of this system is determined a asset movement. Therefore, it is necessary to develop a trading system that is trade two assets such as a pair trading that is to sell overvalued assets and buy the undervalued ones. The aim of this study is to propose a relative value based trading system designed to yield stable and profitable profits regardless of market conditions. In fact, we propose a procedure for building a trading system that is based on the rough set analysis of indicators derived from a price ratio between two assets. KOSPI 200 index futures and S&P 500 index futures are used as a data for evaluation of the proposed trading system. We intend to examine the usefulness of this model through an empirical study.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.37-52
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• 2011

Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.