• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.30 no.2
• /
• pp.89-98
• /
• 2007

In this paper the economic value of weather forecasts is valuated for profit-oriented enterprise decision-making situations. Value is estimated in terms of monetary profits (or benefits) resulted from the forecast user's decision under the specific payoff structure, which is represented by a profit/loss ratio model combined with a decision function and a value score (VS). The forecast user determines a business-related decision based on the probabilistic forecast, the user's subjective reliability of the forecasts, and the payoff structure specific to the user's business environment. The VS curve for a meteorological forecast is specified by a function of the various profit/loss ratios, providing the scaled economic value relative to the value of a perfect forecast. The proposed valuation method based on the profit/loss ratio model and the VS is adapted for hypothetical sets of forecasts and verified for site-specific probability of precipitation forecast of 12 hour and 24 hour-lead time, which is generated from Korea meteorological administration (KMA). The application results show that forecast information with shorter lead time can provide the decision-makers with great benefits and there are ranges of profit/loss ratios in which high subjective reliability of the given forecast is preferred.

• The Journal of Asian Finance, Economics and Business
• /
• v.6 no.1
• /
• pp.321-328
• /
• 2019

The purpose of the study is to analyze the main approaches to assessing human capital and develop proposals for its most objective assessment of it at the different levels of manifestation - individual, microeconomic and macroeconomic. The article considers the basic approaches to the evaluation of human capital, used in practice: retrospective (costly) and prospective (income based). Cost based methods involve measuring the value of human capital based on the total costs associated with its formation. The proposed additional evaluation criteria, in particular, the use of the expert approach and the developed indicators of a qualitative assessment of the human capital of the enterprise will allow development that is more efficient and use of available human resources. Human capital is becoming a major factor in the formation and development of an innovative economy and knowledge economy. Accordingly, the proposed additions to the assessment of human capital at the country level are aimed at assessing it from a new angle, taking into account the current global trends in the formation of an innovative economy and digitalization. They meet qualitatively new requirements for human capital as the main productive factor in the creation of new highly efficient technologies that promote the active development of the social sphere, science, education, health, etc.

• Knowledge Management Research
• /
• v.22 no.2
• /
• pp.247-268
• /
• 2021

Investors mainly use PER and PBR among financial ratios for valuation and investment decision-making. I conduct an analysis of two basic financial ratios from a statistical perspective. Financial ratios contain key accounting numbers which reflect firm fundamentals and are useful for valuation or risk analysis such as enterprise credit evaluation and default prediction. The distribution of financial data tends to be extremely heavy-tailed, and PER and PBR show exceedingly high level of kurtosis and their extreme cases often contain significant information on financial risk. In this respect, Extreme Value Theory is required to fit its right tail more precisely. I introduce not only GPD but exGPD. GPD is conventionally preferred model in Extreme Value Theory and exGPD is log-transformed distribution of GPD. exGPD has recently proposed as an alternative of GPD(Lee and Kim, 2019). First, I conduct a simulation for comparing performances of the two distributions using the goodness of fit measures and the estimation of 90-99% percentiles. I also conduct an empirical analysis of Information Technology firms in Korea. Finally, exGPD shows better performance especially for PBR, suggesting that exGPD could be an alternative for GPD for the analysis of financial ratios.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.15 no.6
• /
• pp.1-26
• /
• 2020

The term 'Unicorns' in the corporate ecosystem was firstly introduced by Aileen Lee in 2013. It has been actively discussed in South Korea particularly to compare the level of the 'start-up ecosystem' from a global perspective. Accordingly, the Korean government has recently set a policy goal 'to nurture 20 Korean unicorn companies by 2022'. While the phenomenon of 'Unicorn Club Company' has been brought to the level of policy objectives and spread more widely to the public, existing academic research to understand its substantial and underlying implications has been insufficient. First, in this study, the characteristics of 479 'Unicorn Club' companies in 2019 were analyzed in-depth. Previous research has focused on the general status and trend by analyzing the number of unicorn companies by country and industry classifications. However, this study conducted a qualitative exploratory analysis by investigating descriptive statistics about unicorn companies, including their investors, while providing case studies. Also, cluster analysis, ANOVA, and multi-level regression were employed for quantitative exploration. The characteristics of individual companies were examined based on the "ERIS Model (Entrepreneur - Industry(Market) - Resource - Strategy Model)". Secondly, factors influencing its valuations were examined in connection with the previously analyzed characteristic variables and investor characteristics. Finally, based on these, the future direction of the "Unicorn Phenomenon" from the perspective of "Enterprise Ecosystem" and productively using it from the perspective of the public policy is suggested.

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