• The Journal of Industrial Distribution & Business
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• v.9 no.11
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• pp.39-54
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• 2018

Purpose - To success, in spite of deficient resources, a start-up company has to check various circumstances. Many researchers proposed different appraisal methods for technology commercialization. But everybody agrees Merrifield is the first one, who is a pioneer of an appraisal model of technology commercialization. After he proposed it, many researchers and field workers developed a more complicated model, which called a BMO model. In this research, considering the circumstances of start-ups that lack available resources, it proposes a new appraisal method for technology commercialization, which is named a weighted-BMO model. Research design, data, and methology - For the new BMO-model, it studied the preceding studies. And it found that the success factors for start-ups were correlated with technology commercialization. After comparing the success factors for technology commercialization of start-ups with BMO appraisal factor, it withdraws the net BMO appraisal model: which we are calling the weighted-BMO model. Results - This study found a few things. First, actually, the BMO appraisal factors related with the success factors of technology commercialization. Second, the weighted-BMO model, which included the entrepreneur ability factor, was more accurately estimated the success of technology-based start-ups than the BMO model. Third, it overcame the weakness of the BMO-model, which did not include quantitative factors. In addition to evaluating the feasibility of the BMO model, we also presented a strategy for the future direction. But, still, it included a few shortcomings, which we are calling the arbitrage of weighted value. Sometimes, the intentional weighted value can deliberate the different valuation. Conclusitons - Due to this study, the weighted-BMO model included appraisal factors related with the success factors of technology commercialization and the entrepreneur ability factor, and quantitative factors. When evaluating the combined score of the existing Merrified BMO components, 35 points of the first pass criterion accounted for 29.17% of the total score, and 80 points of the merit score of the second rank criterion were 66.67% Considering that the weighted sum is taken into account, the baseline score of the weighted summing method for each component of the modified BMO model is 2.92 points, which is 29.17% of the weighted sum total of 10 points. The evaluation score was 6.67 points, 66.67% of the weighted total score of 10 points.

• Journal of the Korean Society for Marine Environment & Energy
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• v.16 no.3
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• pp.217-225
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• 2013

It is time to develop new renewable energy that could fundamentally replace fossil fuel, which has been increasingly needed due to environmental pollution and energy security. Korean marine bio-energy development project is planned to produce 50% of total bioenergy. This study attempts to measure the greenhouse gas emission reduction benefits of marine bio-energy development project through contingent valuation method. Single bounded dichotomous choice (SBDC) is applied with spike model. The results show that the average willingness to pay are estimated to be KRW 4,190 at SBDC, per household per year. If the result has been expanded to the region which is survey conducted, KRW 50.1 billion annually. These quantitative information can be usefully utilized in the cost benefit analysis to implement project and policy-making for the industrialization of marine bio-energy development project.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.121-128
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• 2019

Computing systems have various vulnerabilities to cyber attacks. In particular, various cyber attacks that are intelligent in the information society have caused serious social problems and economic losses. Traditional security systems are based on misuse-based technology, which requires the continuous updating of new attack patterns and the real-time analysis of vast amounts of data generated by numerous security devices in order to accurately detect. However, traditional security systems are unable to respond through detection and analysis in real time, which can delay the recognition of intrusions and cause a lot of damage. Therefore, there is a need for a new security system that can quickly detect, analyze, and predict the ever-increasing cyber security threats based on machine learning and big data analysis models. In this paper, we present a IDS model that combines machine learning and big data technology.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.1-22
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• 2017

Analysis of future business or investment opportunities, such as business feasibility analysis and company or technology valuation, necessitate objective estimation on the relevant market and expected sales. While there are various ways to classify the estimation methods of these new sales or market size, they can be broadly divided into top-down and bottom-up approaches by benchmark references. Both methods, however, require a lot of resources and time. Therefore, we propose a data-based intelligent demand forecasting system to support evaluation of new business. This study focuses on analogical forecasting, one of the traditional quantitative forecasting methods, to develop sales forecasting intelligence systems for new businesses. Instead of simply estimating sales for a few years, we hereby propose a method of estimating the sales of new businesses by using the initial sales and the sales growth rate of similar companies. To demonstrate the appropriateness of this method, it is examined whether the sales performance of recently established companies in the same industry category in Korea can be utilized as a reference variable for the analogical forecasting. In this study, we examined whether the phenomenon of "mean reversion" was observed in the sales of start-up companies in order to identify errors in estimating sales of new businesses based on industry sales growth rate and whether the differences in business environment resulting from the different timing of business launch affects growth rate. We also conducted analyses of variance (ANOVA) and latent growth model (LGM) to identify differences in sales growth rates by industry category. Based on the results, we proposed industry-specific range and linear forecasting models. This study analyzed the sales of only 150,000 start-up companies in Korea in the last 10 years, and identified that the average growth rate of start-ups in Korea is higher than the industry average in the first few years, but it shortly shows the phenomenon of mean-reversion. In addition, although the start-up founding juncture affects the sales growth rate, it is not high significantly and the sales growth rate can be different according to the industry classification. Utilizing both this phenomenon and the performance of start-up companies in relevant industries, we have proposed two models of new business sales based on the sales growth rate. The method proposed in this study makes it possible to objectively and quickly estimate the sales of new business by industry, and it is expected to provide reference information to judge whether sales estimated by other methods (top-down/bottom-up approach) pass the bounds from ordinary cases in relevant industry. In particular, the results of this study can be practically used as useful reference information for business feasibility analysis or technical valuation for entering new business. When using the existing top-down method, it can be used to set the range of market size or market share. As well, when using the bottom-up method, the estimation period may be set in accordance of the mean reverting period information for the growth rate. The two models proposed in this study will enable rapid and objective sales estimation of new businesses, and are expected to improve the efficiency of business feasibility analysis and technology valuation process by developing intelligent information system. In academic perspectives, it is a very important discovery that the phenomenon of 'mean reversion' is found among start-up companies out of general small-and-medium enterprises (SMEs) as well as stable companies such as listed companies. In particular, there exists the significance of this study in that over the large-scale data the mean reverting phenomenon of the start-up firms' sales growth rate is different from that of the listed companies, and that there is a difference in each industry. If a linear model, which is useful for estimating the sales of a specific company, is highly likely to be utilized in practical aspects, it can be explained that the range model, which can be used for the estimation method of the sales of the unspecified firms, is highly likely to be used in political aspects. It implies that when analyzing the business activities and performance of a specific industry group or enterprise group there is political usability in that the range model enables to provide references and compare them by data based start-up sales forecasting system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.2
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• pp.177-186
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• 2017

This paper attempts to quantitatively assess the public value that has been assigned to this government plan by employing a contingent valuation technique. Data gathering performed that professional research firm administrated a face-to-face national survey of 1,000 randomly-selected households. A one-and-one-half-bound model was adopted to elicit willingness to pay (WTP) responses, and the payment vehicle used was income tax. The WTP model used in this study is based on a utility difference approach and the spike model. The results showed that the public value of conserving green turtles was estimated to be 2,570 Korean Won per household over the next 10 years as of 2016, statistically significant at the 1% level. Expanding the values considered to include the national population gives a public value of 48.7 billion Korean Won. Thus, the public value of rescuing, rehabilitating, and releasing green turtles that have been caught by fishermen, collided with fishing boats, and died in nets through the government program is not small.

• Proceedings of the Technology Innovation Conference
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• 2004.02a
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• pp.222-245
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• 2004

This paper has an intention of proposing useful parametric tables of each industry group within Korea. These parametric tables can be insightful criteria for those who are dealing with the exact valuation of company, technology or industry through Real Option Analysis (ROA) since the identification of the movement of underlying asset is the very first step to be done. To give the exact estimations of parameters and the most preferred model in each industry group, we cover topics on ROA, stochastic process, and parametric estimation method like Generalized Method of Moments (GMM) and Maximum Likelihood Estimation (MLE). Additionally, specific industry groups, such as, Internet service group and mobile telecommunication service group defined independently in this paper are also examined in terms of its property of movement with the suggesting of the most fitting stochastic model.

• 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 Information Technology
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• v.5 no.1
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• pp.79-98
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• 2002

This study examines the association between valuation and accrual information. According to accounting based valuation model, firm's value consists of net book value and abnormal earnings. Net book value and abnormal earnings are determined as the manager's accounting policy. Discretionary accruals may signal the manager's value expectation or be noisy factor of accounting variables. The results of this study are as follows; First discretionary accruals are associated to stock prices negatively but non-discretionary accruals are not to stock prices. This result suggests that discretionary accruals and non-discretionary accruals are the differential factors of the firm value. Second, the product term of discretionary accrual and net book value are associated to the stock price negatively but the product term of non-discretionary accrual and net book value are not associated to the stock price. the results indicate that discretionary accruals are noisy factors of net book value information. Third, the product term of discretionary accrual and net income are associated to the stock price negatively and the product tenn of non-discretionary accrual and net income are also associated to the stock price negatively, the results suggest that discretionary accruals are noisy factors of earnings.

• Journal of Energy Engineering
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• v.24 no.3
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• pp.40-47
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• 2015

Integrated gasification combined cycle (IGCC) power plants not only emit less greenhouse gases and air pollutants than conventional coal-fired power plants, but also use low-price, low-quality, and internationally easily procurable coal. Thus we can benefit from safeguarding energy security through building the IGCC power plant. This paper attempts to value the benefits of energy security enhanced by IGCC power plant. To this end, we report here the results from a contingent valuation survey of randomly selected 600 households. A combination of a double-bounded model and a spike model is applied for the purpose of increasing statistical efficiency and dealing with zero(0) willingness to pay data, respectively. The results show that the respondents are additionally willing to pay 6.05 won for 1kWh of electricity generated from IGCC power plant. In other words, the benefits from safeguarding energy security through building the IGCC power plant are 6.05 won per kWh. Given that the expected amount of generation from the Taean IGCC power plant that is scheduled to be built in late 2015 is 2.27 TWh per year, the benefits are estimated to be 13.74 billion won per year.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.1
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• pp.101-111
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• 2018

The Korean government has been trying to conserve a marine ecosystem that has been shifting due to climate change. As part of this effort, the government designated seventy-seven marine species that have been disappearing and deserve to be protected as endangered managing them specially. To generate basic data to guide policy for these endangered species, their value must be measured. OOf the species declared endangered, coral is particularly threatened by climate change, and its management is important. Accordingly, understanding the potential value of reefs, can be an effective way of proving the benefits of continuous management to decision makers and the general public alike. To this end, we have applied the contingent valuation method (CVM), an economic technique of for valuing a environmental and non-market goods such as a coral reef. A national face-to-face survey of 1,000 randomly selected households was conducted in order to determine the public's willingness to pay (WTP) for conserving coral reefs. A one-and-one-half-bound (OOHB) model was adopted to interpret WTP responses, and a spike model was employed to deal with zero WTP responses. The results show that the conservation value of a coral reef can be estimated at 3,016 won per household per year, statistically significant at the 1 % level. Expanding values to the national population gives an annual value of 58.9 billion won. We can conclude that the public is willing to pay a significant amount to conserve coral reefs.