• The Journal of the Korea Contents Association
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• v.15 no.12
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• pp.525-533
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• 2015

The evolution of spectrum sharing technology enables the creation of many business scenarios and business models such as TV white space service. Business models considering spectrum sharing should guarantee economic feasibility for service providers and increasing benefit for service users. In addition, new business models should contribute to economic activation in the wireless telecommunication service industry. It is therefore necessary to design quantitative evaluation methods for selection of the best business models. The methods should reflect the various points of view of valuation. Our research addresses evaluation method for business models considering spectrum sharing. We define evaluation indicators to reflect the distinct characteristics of spectrum sharing. Also, we adopt analytic hierarchy process(AHP) to derive the weights of each indicator to evaluate business models considering spectrum sharing.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.89-97
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• 2016

Intellectual property rights play a key role in employment creation and income generation plays an important role, especially in the creative economy. Many companies are ultimately increasing efforts to boost the company's financial performance, such as maximizing profits by building a strong brand assets amid committed to brand management in this paradigm. Reasonable evaluation and commercialization of technology transactions, financial assistance, investment decisions, trademark brand value for the reactivation (revitalizing) for the purposes of M & A, litigation, brand strategy will be said to be very important. In spite of the importance, the awareness of the property and the capabilities to assess are hardly sufficient. Thus, this study, targeting companies with valid trademarks for value assessment, conducted case analysis by cost method and income approach; the analysis presented the result from 2.05 million by the cost method to 2.7 million by the income approach applied to a variable discount rate and adjustment contribution. However, now that the implication was drawn from a single company, further studies covering case study and application plan according to scale and type of diverse company groups should be continued.

• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.119-138
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• 1998

This paper aims to evaluate the regional development model related regional cooperative system, especially, with the governmental-educational-industrial mutual cooperative establishment plan for regional development to propose the basic direction pursued by engineering colleges, regional development policy and policy of science and technology. It proceeds through the analysis of the distinctive qualities of modern scientific technique and the system to pursue it's policy, and the study of the necessity and concepts of regional cooperative system. For this, the present condition and main issues regarding the cooperative research system among the government, education and industry complex such as the regional consortium projects and the regional cooperative research center etc, are analyzed and examined. Besides these, questionnaire survey method for experts on regional development is used concerning the regional cooperating system, their ongoing cooperative research, main issues and the roles of the mutual cooperative system. In conclusion, it proposed evaluating methods for solidifying cooperation and development of mutual relations between regional development and regional cooperative system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5465-5475
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• 2013

In this study, when to invest in real estate abroad, to present a real option in the way of decision-making. Thus, by using the binomial option model of one of the real thing and DCF, we compared the choice of real estate investment in China and South Korea. Research concerns the real estate market of Shanghai and Seoul, Analyzed the data between 2001-2009. Results were calculated NPV investment period (Net Present Value), Seoul appears in 435.44, Shanghai was 398.26. Investment decision by NPV method will select Seoul. However, as a result of calculating the value using the real option, it was found that for Seoul appear in 615.4, Shanghai has been shown to 626.1, and is suitable for investment in Shanghai. Assuming on the basis of this, that it has invested in practice, and compare the results, Seoul is intended for since 2010, real estate prices fell to 2013 currently, damage has occurred, profit's occurred Shanghai. This ensures that when making decisions in real estate investment and to use the real option than the existing DCF is appropriate.

• Journal of Korea Technology Innovation Society
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• v.12 no.1
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• pp.189-211
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• 2009

The importance of searching the weak signal has been increasingly recognized to cope with rapidly changing circumstances as an environmental analysis technique. This study proposed the NEST process for the searching for the weak signal. The NEST (New & Emerging Signals of Trends) is a micro environmental analysis process based on both quantitative and qualitative method. For this, the weak signal Searching Board is developed and traditional methods as global monitoring, trend analysis, brainstorming and delphi method are implemented to NEST. The NEST process is consists of three stage modules; the global monitoring stage in search of seeds information related to the environmental change, the weak signal analysis stage using the weak signal Tracking Board, and the delphi valuation stage for objectifying the final result. The NEST provides the weak signal of the promising technology which can bring new paradigm and the Up-Coming Trends which can lead new trend in the future. These outputs can be used to select promising technology from firm level to national level. The NEST system can be effectively operated as well as in small group so that small and medium innovative firms can develop and execute their own NEST process individually.

• Environmental and Resource Economics Review
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• v.18 no.2
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• pp.217-239
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• 2009

As gas hydrate is recently emerging as a new energy source to solve environmental and exhaustion problems caused by fossil energy, Korea is working on a gas hydrate development project under a 10-year plan from 2005 to 2014. Gas hydrate is expected to have a big effect on the economy and society of Korea, which is largely depending on energy imports besides water energy and atomic energy. However, it is uncertain whether the project will produce successful results. Thus, it is very important to improve its validity and to propose effective execution strategies by evaluating the value of the project in advance. Thus, this study intended to include new information, which had not been evaluated in existing methods, and to reduce biases or errors in value evaluation results by applying a fuzzy risk analysis to the real option model in order to evaluate the value of a gas hydrate development project. It is advantageous that the real option model based on the fuzzy risk analysis modelizes the vagueness and inexactness of intangible element judgment into an appropriate language scale so as to evaluate these elements clearly and integrate them with estimated financial performance results. The application of the fuzzy risk analysis makes it possible to conduct an analysis by dissolving a decision-making issue with complicated and various attributes into several simplified problems. With the continuing high oil prices and today's demand of clean energy, the necessity of energy resources and technology development projects keeps growing. Amid this situation, it is expected that these study results will contribute to proposing a guideline not only for gas hydrate projects but also for policy decision-making related to future energy industries.

• Korean small business review
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• v.42 no.1
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• pp.19-41
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• 2020

In Korea, punitive damages were introduced in the 2011 Fair Transactions in Subcontracting Act(FTSA), and in 2019 the Patent Act, Trade Secret Protection Act(TSPA), Industrial Technology Protection Act(ITPA), and Mutually Beneficial Cooperation Act(MBCA). In punitive damages, the judgment of 'intentional' is especially important, and it is necessary to refer to US precedents since there is no accumulated case. Major Company can avoid intentional counseling through the advice of lawyers, but SMEs may have to punish punitive damages due to a lack of awareness of the system. In the case of TSPA, ITPA, FTSA, and MBCA, except for Patent Act, the provisions related to proof of damage have not been well maintained yet. Therefore, the data submission order system of these laws needs to be revised to the level of patent Act need to be. TSPA needs to be amended in the future to estimate the amount of the royalties in estimating the amount of damages so that it can receive the 'reasonably' estimated amount rather than the usual amount. On the other hand, ITPA, FTSA, and MBCA do not have any provisions for the estimation of damages. Besides, it is difficult to evaluate the technology value in the case of leakage or deodorization of new technologies. Therefore, valuation needs to be carried out by a credible institution along with the development of a model for calculating damages.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Nutrition Research and Practice
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• v.10 no.1
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• pp.56-66
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• 2016

BACKGROUND/OBJECTIVES: Despite successes recorded in combating iodine deficiency, more than 2 billion people are still at risk of iodine deficiency disorders. Rural landlocked and mountainous areas of developing countries are the hardest hit, hence the need to explore and advance novel strategies such as biofortification. SUBJECTS/METHODS: We evaluated adoption, purchase, and consumption of iodine biofortified vegetable legumes (IBVL) using the theory of protection motivations (PMT) integrated with an economic valuation technique. A total of 1,200 participants from three land-locked locations in East Africa were recruited via multi-stage cluster sampling, and data were collected using two, slightly distinct, questionnaires incorporating PMT constructs. The survey also elicited preferences for iodine biofortified foods when offered at a premium or discount. Determinants of protection motivations and preferences for iodine biofortified foods were assessed using path analysis modelling and two-limit Tobit regression, respectively. RESULTS: Knowledge of iodine, iodine-health link, salt iodization, and biofortification was very low, albeit lower at the household level. Iodine and biofortification were not recognized as nutrient and novel approaches, respectively. On the other hand, severity, fear, occupation, knowledge, iodine status, household composition, and self-efficacy predicted the intention to consume biofortified foods at the household level; only vulnerability, self-efficacy, and location were the most crucial elements at the school level. In addition, results demonstrated a positive willingness-to-pay a premium or acceptance of a lesser discount for biofortification. Furthermore, preference towards iodine biofortified foods was a function of protection motivations, severity, vulnerability, fear, response efficacy, response cost, knowledge, iodine status, gender, age. and household head. CONCLUSIONS: Results lend support for prevention of iodine deficiency in unprotected populations through biofortification; however 'threat' appraisal and socio-economic predictors are decisive in designing nutrition interventions and stimulating uptake of biofortification. In principle, the contribution is threefold: 1) Successful application of the integrated model to guide policy formulation; 2) Offer guidance to stakeholders to identify and tap niche markets; 3) stimulation of rural economic growth around school feeding programmes.

• Asia pacific journal of information systems
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• v.17 no.2
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• pp.123-137
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• 2007

The advent of the Internet and related Web technologies has created an easily accessible link between a firm and its customers, and has provided opportunities to a firm to use information technology to support supplementary after-sale services associated with a product or service. It has been widely recognized that supplementary services are an important source of customer value and of competitive advantage as the characteristics of the product itself. Many of these supplementary services are information-based and need not be co-located with the product, so more and more companies are delivering these services electronically. Net-based customer service, which is defined as an Internet-based computerized information system that delivers services to a customer, therefore, is the core infrastructure for supplementary service provision. The importance of net-based customer service in delivering supplementary after-sale services associated with product has been well documented. The strategic advantages of well-implemented net-based customer service are enhanced customer loyalty and higher lock-in of customers, and a resulting reduction in competition and the consequent increase in profits. However, not all customers utilize such net-based customer service. The digital divide is the phenomenon in our society that captures the observation that not all customers have equal access to computers. Socioeconomic factors such as race, gender, and education level are strongly related to Internet accessibility and ability to use. This is due to the differences in the ability to bear the cost of a computer, and the differences in self-efficacy in the use of a technology, among other reasons. This concept, applied to e-commerce, has been called the "e-commerce divide." High Internet penetration is not eradicating the digital divide and e-commerce divide as one would hope. Besides, to accommodate personalized support, a customer must often provide personal information to the firm. This personal information includes not only name and address, but also preferences information and perhaps valuation information. However, many recent studies show that consumers may not be willing to share information about themselves due to concerns about privacy online. Due to the e-commerce divide, and due to privacy and security concerns of the customer for sharing personal information with firms, limited numbers of customers adopt net-based customer service. The limited level of customer adoption of net-based customer service affects the firm profits and the customers' welfare. We use a game-theoretic model in which we model the net-based customer service system as a mechanism to enhance customers' loyalty. We model a market entry scenario where a firm (the incumbent) uses the net-based customer service system in inducing loyalty in its customer base. The firm sells one product through the traditional retailing channels and at a price set for these channels. Another firm (the entrant) enters the market, and having observed the price of the incumbent firm (and after deducing the loyalty levels in the customer base), chooses its price. The profits of the firms and the surplus of the two customers segments (the segment that utilizes net-based customer service and the segment that does not) are analyzed in the Stackelberg leader-follower model of competition between the firms. We find that an increase in adoption of net-based customer service by the customer base is not always desirable for firms. With low effectiveness in enhancing customer loyalty, firms prefer a high level of customer adoption of net-based customer service, because an increase in adoption rate decreases competition and increases profits. A firm in an industry where net-based customer service is highly effective loyalty mechanism, on the other hand, prefers a low level of adoption by customers.