• Management & Information Systems Review
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• v.29 no.4
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• pp.23-44
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• 2010

This study examines the value-relevance of accruals and discretionary accruals. Also, by examining the effects of the corporate life-cycle on these relationship, this study is able to provide evidence of the value-relevance of accruals and discretionary accruals measures in the economic context of life-cycle theory. This study uses results based on life-cycle classification methods developed by Anthony and Ramesh(1992), adjust Jones model and Dechow Dechev(2002) model. We classify firms using individuals variables(sales growth, capital expenditure growth, employee growth) and then use a composite score obtained from all variables for classification. Our sample consists of 272 firms listed in the Korean Stock Exchange during 14 years(1996-2009). Our final sample for regression variables consists of 2,448 firm-year observations. This evidence implies that the value-relevance of accruals and discretionary accruals in the growth and mature stage can have positive impact on the price but in the decline the value-relevance of accruals and discretionary accruals can have negative impact on the price. The results mean that discretionary accruals communicate managements' private information in the growth stage, but. earnings management in the decline stage. The results of this study suggest that corporate life cycle stages influence the value-relevance of accruals and discretionary accruals measures.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.3
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• pp.307-324
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• 2011

The culture industry is viewed as a driving industry in the 21th century. Korea has experienced the rapid growth rate of the cultural industry in terms of sale amounts for the period of 2004-2009. The purposes of this study are to analyze the spatial pattern of the cultural industry and to empirically examine the effect of municipalities' cultural industries on regional economy using SUR model. The major findings are as follows: First, cultural industries are concentrated in the capital region and several metropolitan areas. Secondly, the estimated result of SUR model shows that there is inter-relationship between cultural industry and regional economy. The effect of the cultural industry on GRDP is that the cultural industry increased 1%, GRDP increased by 0.46%. In turn, GRDP increased 1%, cultural industry increased by 0.75%. Thirdly, the elasticity of the cultural industry on GRDP is much higher than that of labor or capital stock, showing that the cultural industry has a more powerful influence on its regional economy. Fourth, the elasticity of the cultural industry on GRDP of Gun is higher than that of shi, indicating that it is rational for Gun to develop strategies to promote competitive power of the cultural Industry for regional economic growth.

• Korean Journal of Construction Engineering and Management
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• v.18 no.4
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• pp.3-16
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• 2017

Forecasting cash flow is very important but is difficult and complicated to analysis in high-rise development projects. And An expected value which was forecasted on the early stage is likely to fluctuate due to uncertainties around such complicated huge project to consider the probable uncertainty. There are not objectified method which are able to cope with uncertainty of project, and feasibility study based on selected financial analysis does not include liquidity of cash flow. Through such a stochastic method, developer can cope with cash flow fluctuation and set up a financial plan. Also this study is meaningful for laying the foundation for high-rise development project and feasibility study as well as the suitability and accuracy of feasibility study. Analysis showed that NPV and IRR include residential apartments shows surplus revenue as return of apartments offset deficit of hotel and office. Factors influencing the project feasibility for high-rise development project are sales account of $1^{st}$ year and annual vacancy rate of office.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.6 no.1
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• pp.23-37
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• 2011

This paper is brought to carry out an empirical study whether evolution process of venture firm's scale is following the Gibrat's law; random evolution process, or Pareto law; self-organizing process. The empirical test, as attaching theoretical explanation, of this research utilize the serial data samples of 92 KOSDAQ listed companies from the year of 2005 through 2008. Summarizing the research results are as followed. First, Gini Coefficients representing the density of venture firm's scale has been constantly reduced since the year of 2005 in terms of number of employee, while these index increased during the same time period from the perspective of sales volume. Second, the evolution process of Korea venture firm's scale is following the Power Law related to Pareto Law. In particular, estimated Pareto coefficient, ${\alpha}$, is shown lower than 1 which is significant result. Third, the probability of joining in the top tier group of firm starting from the early stage growing is forecasted into 6.9%, the result which emphasize the starting scale of venture firm play an important role in long term evolution of venture firm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.135-142
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• 2017

This study employs an analytical mathematical model to estimate the optimal debt ratio of Korean agricultural corporations, more sensitive to the government debt ratio policy compared to other industries, and the estimation of the optimal debt ratio based on objective data. The analytical model utilizes the equation for ROE, with the debt ratio as an independent variable, and related parameters include ROS, TAT, and NFCL. Regarding the NFCL, the optimal debt ratio standard is defined as the debt ratio that maximizes the ROE by analytical procedures such as adding an equation concerning the debt ratio and a linearity relationship to the analytical model, and from these equations, a quadratic equation with the debt ratio as an independent variable describes the ROE. This methodemploys fourteen years of corporate data. Results show that 138% of debt ratio is the optimal debt ratio to increase the ROE of the corporations, which implies that the existing debt ratio of Korean agricultural corporations is higher than optimal. Consequently, it is required for authorities to change future debt ratio policies in view that the purpose of debt ratio management is to maintain safety and increase profitability.Management should emphasize characteristics of the specific industry rather than standardized judgements based on numerical indexes.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.103-109
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• 2019

The purpose of this study is to examine various existing models that analyze the economic value of meteorological information, to present a new analysis model, a market model, and to quantitatively analyze the economic value of meteorological information in the Korean service industry using the market model. The research method of this paper will basically use empirical analysis along with the theoretical approach to critically examine the existing analytical model of economic value of meteorological information and to suggest a new analytical model. The analysis results are as follows. Theoretically, the marginal cost of firms is reduced by providing the amount of weather information, and social welfare is increased by the increase of consumer and producer surplus. In this paper, the marginal cost of 1% increase in the amount of weather information decreases by 0.101% and the increase in social welfare increases by 1,247billion Won in 2017. On the other hand, in the accommodation and restaurant sectors, the marginal cost due to a 1% increase in weather information decreased by 0.218%, and the social welfare increase increased by 308billion Won in 2017.

• Korean small business review
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• v.41 no.1
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• pp.53-73
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• 2019

Recently, as the number of shopping facilities has increased, such as complex shopping malls, warehouse type superstores, large fashion outlets, and so on, the conflicts over the opening of large stores between neighboring municipalities are increasing. However, current regulations on the opening of large-scale stores, such as the impact analysis on commercial area, do not adequately reflect the characteristics of new type shopping facilities. In this study, we tried to suggest a rational policy alternative with more realistic suitability by analyzing the characteristics of 'regional shopping facilities' beyond the scope of the municipalities, and analyzing the impact on the regional merchants. The main results of the study are summarized as follows. First, unlike previous researches, which are limited to small business sector, this study presents the results of comprehensively comparing and analyzing the impact on the detailed sectors of the whole distribution market, including the large distribution sector and online distribution sector. Second, in this study, we calculated the total (average) amount of market penetration rate of existing shopping facilities by the entire regional shopping facilities in the Seoul metropolitan area, and this is considered to be of great value in relation to the recognition of problems at the whole level of the metropolitan area and the search for alternative solutions.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.17-35
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• 2015

Demand forecasting is the activity of estimating the quantity of a product or service that consumers will purchase for a certain period of time. Developing precise forecasting models are considered important since corporates can make strategic decisions on new markets based on future demand estimated by the models. Many studies have developed market growth curve models, such as Bass, Logistic, Gompertz models, which estimate future demand when a market is in its early stage. Among the models, Bass model, which explains the demand from two types of adopters, innovators and imitators, has been widely used in forecasting. Such models require sufficient demand observations to ensure qualified results. In the beginning of a new market, however, observations are not sufficient for the models to precisely estimate the market's future demand. For this reason, as an alternative, demands guessed from those of most adjacent markets are often used as references in such cases. Reference markets can be those whose products are developed with the same categorical technologies. A market's demand may be expected to have the similar pattern with that of a reference market in case the adoption pattern of a product in the market is determined mainly by the technology related to the product. However, such processes may not always ensure pleasing results because the similarity between markets depends on intuition and/or experience. There are two major drawbacks that human experts cannot effectively handle in this approach. One is the abundance of candidate reference markets to consider, and the other is the difficulty in calculating the similarity between markets. First, there can be too many markets to consider in selecting reference markets. Mostly, markets in the same category in an industrial hierarchy can be reference markets because they are usually based on the similar technologies. However, markets can be classified into different categories even if they are based on the same generic technologies. Therefore, markets in other categories also need to be considered as potential candidates. Next, even domain experts cannot consistently calculate the similarity between markets with their own qualitative standards. The inconsistency implies missing adjacent reference markets, which may lead to the imprecise estimation of future demand. Even though there are no missing reference markets, the new market's parameters can be hardly estimated from the reference markets without quantitative standards. For this reason, this study proposes a case-based expert system that helps experts overcome the drawbacks in discovering referential markets. First, this study proposes the use of Euclidean distance measure to calculate the similarity between markets. Based on their similarities, markets are grouped into clusters. Then, missing markets with the characteristics of the cluster are searched for. Potential candidate reference markets are extracted and recommended to users. After the iteration of these steps, definite reference markets are determined according to the user's selection among those candidates. Then, finally, the new market's parameters are estimated from the reference markets. For this procedure, two techniques are used in the model. One is clustering data mining technique, and the other content-based filtering of recommender systems. The proposed system implemented with those techniques can determine the most adjacent markets based on whether a user accepts candidate markets. Experiments were conducted to validate the usefulness of the system with five ICT experts involved. In the experiments, the experts were given the list of 16 ICT markets whose parameters to be estimated. For each of the markets, the experts estimated its parameters of growth curve models with intuition at first, and then with the system. The comparison of the experiments results show that the estimated parameters are closer when they use the system in comparison with the results when they guessed them without the system.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.1
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• pp.99-112
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• 2014

This paper addresses an assessment model for selecting PL(Private Level) product companies. The proposed model extracts the weights of evaluation elements based on AHP(Analytic Hierarchy Process). These evaluation elements are from real-world instances in a domestic hyper market. Especially, the model points at food products which constitute a large portion of entire profits in the market. In this model, we first classify the 54 evaluation elements into 4 layers and secondly carry out a survey with relevant specialists based on them. We also estimate the weights of evaluation elements according to pairwise comparisons from the survey, and propose them as a quantitative alternative which can be applied in real-world problems. Finally, the pilot-study is conducted to compare the proposed model with the existing simple summation method. From this study, HACCP system assessment and Review(0.279281), Transportation(0.117706) and Fundamental law observance(0.066392) are presented as the key evaluation elements for selecting PL product companies. The proposed model facilitates the company selection among those candidate companies which is not easy to determine the superiority by reflecting the importance of evaluation elements.