• Review of Culture and Economy
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• v.17 no.2
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• pp.29-62
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• 2014

Game industry, one of cultural-content industry which is considered as a typical knowledge-based industry and creative industry, is not like the overseas expansion of traditional manufacture, and has different strategy and performance of export expansion through product or project-based strategy. Therefore, it should be approached by each content unit, and necessary to look at the factors that make their decision makings of foreign market entry vary. This study focuses on discovering creativity, absorptive capacity and strategic orientation(market orientation and innovation orientation) which affect the difference of distribution's decision making of entry into foreign market in game industry This paper examined 252 cases of online games in order to investigate creativity, absorptive capacity and strategic orientations for each foreign market and what entry type(among licensing, joint distribution, exclusive distribution) they chose according to the products developed in team level. This helps us analyze the factors affecting market orientation and innovation orientation in the perspectives of creativity and absorptive capacity in comprehensive way, and notice the phenomena which use different foreign distribution strategy though there are company incorporated abroad and their results. This study supplements the limit of the existing Resource-Based View, Resource-Dependent View, and traditional international business theories such as Transaction Cost Theory or OLI Paradigm(Eclectic Framework), and proves how company could reduce asymmetry of uncertainty and information in creative industry and whether they accomplish successful overseas expansion according to strategic orientations.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.533-544
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• 2018

Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.

• Journal of IKEEE
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• v.23 no.3
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• pp.1088-1091
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• 2019

In this paper, a real-time monitoring system for environmental safety by living area is proposed. The proposed system is designed to measure radiation, fine dust and basic living information (temperature) using fixed and mobile measuring equipment, and constitutes a web database that stores data received from the equipment. It also develops web programs for displaying received data on PCs and mobile phones. The results of testing the performance of the system by an authorized testing agency showed that the radiation measurement range was measured in the range of $10{\mu}Sv/h$ to 10mSv/h, which is comparable to the world's highest level, and that the accuracy was measured between ${\pm}6.7$ and ${\pm}8.7$ percent of the measurement uncertainty was measured and normal operation at or below the international standard of ${\pm}15$ percent. In addition, the temperature test was conducted on a section of $-20^{\circ}C$ to $50^{\circ}C$ and normal operation was confirmed in response to the temperature change. Stability of radiated electromagnetic waves was ensured by a suitable judgment. The product's testing in general and high and low temperature environments for about four months after the prototype was made confirmed to be more than five years of durability. The measurement range and accuracy of fine dust sensors are compared with those of companies that measure the air environment, and the performance level is similar through the air quality measurement register.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.76-84
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• 2021

The quality assurance activities can detect the factors that affect the quality based on risk identification in the course of mass production. Risk identification is conducted with risk analysis, and the risk analysis method for the rotorcraft landing system is selected by failure mode effects analysis (FMEA). FMEA is a method that detects the factors that can affect the product quality by combining severity, occurrence, and detectability. The results of FMEA were prioritized using the risk priority number. On the other hand, these methods have certain shortcomings because the severity, occurrence, detectability are weighted equally. Dempster-Shafer evidence theory can conduct uncertainty analysis for the opinions with personal reflections and subjectivity. Based on the theory, the belief function and the plausibility function can be formed. Moreover, the functions can be utilized to evaluate the belief rate and credibility. The system is exposed to impact during take-off and landing. Therefore, experts should manage failure modes in the course of mass production. In this paper, FMEA based on the Dempster-Shafer evidence theory is discussed to perform risk analysis regarding the failure mode of the rotorcraft landing system. The failure priority was evaluated depending on the factor values. The results were derived using belief and plausibility function graphs.

• Asia Marketing Journal
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• v.15 no.3
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• pp.53-77
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• 2013

As advertising and promotions are categorized as operating expenses, managers tend to reduce marketing budget to improve their short term profitability. Gauging the value and accountability of marketing spending is therefore considered as a major research priority in marketing. To respond this call, recent studies have documented that financial market reacts positively to a firm's marketing activity or marketing related outcomes such as brand equity and customer satisfaction. However, prior studies focus on the relation of marketing variable and financial market variables. This study suggests a channel about how marketing activity increases firm valuation. Specifically, we propose that a firm's marketing activity increases the level of the firm's product market information and thereby the dispersion in financial analysts' earnings forecasts decreases. With less uncertainty about the firm's future prospect, the firm's managers and shareholders have less information asymmetry, which reduces the firm's cost of capital and thereby increases the valuation of the firm. To our knowledge, this is the first paper to examine how informational benefits can mediate the effect of marketing activity on firm value. To test whether marketing activity contributes to increase in firm value by mitigating information asymmetry, this study employs a longitudinal data which contains 12,824 firm-year observations with 2,337 distinct firms from 1981 to 2006. Firm value is measured by Tobin's Q and one-year-ahead buy-and-hold abnormal return (BHAR). Following prior literature, dispersion in analysts' earnings forecasts is used as a proxy for the information gap between management and shareholders. For model specification, to identify mediating effect, the three-step regression approach is adopted. All models are estimated using Markov chain Monte Carlo (MCMC) methods to test the statistical significance of the mediating effect. The analysis shows that marketing intensity has a significant negative relationship with dispersion in analysts' earnings forecasts. After including the mediator variable about analyst dispersion, the effect of marketing intensity on firm value drops from 1.199 (p < .01) to 1.130 (p < .01) in Tobin's Q model and the same effect drops from .192 (p < .01) to .188 (p < .01) in BHAR model. The results suggest that analysts' forecast dispersion partially accounts for the positive effect of marketing on firm valuation. Additionally, the same analysis was conducted with an alternative dependent variable (forecast accuracy) and a marketing metric (advertising intensity). The analysis supports the robustness of the main results. In sum, the results provide empirical evidence that marketing activity can increase shareholder value by mitigating problem of information asymmetry in the capital market. The findings have important implications for managers. First, managers should be cognizant of the role of marketing activity in providing information to the financial market as well as to the consumer market. Thus, managers should take into account investors' reaction when they design marketing communication messages for reducing the cost of capital. Second, this study shows a channel on how marketing creates shareholder value and highlights the accountability of marketing. In addition to the direct impact of marketing on firm value, an indirect channel by reducing information asymmetry should be considered. Potentially, marketing managers can justify their spending from the perspective of increasing long-term shareholder value.

• Asia Marketing Journal
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• v.8 no.1
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• pp.105-132
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• 2006

The major purpose of this study is to investigate the impact of environmental uncertainties and logistics resources capabilities mediated by relational norms and logistics services on logistics performance in the industrial products. The 272 data were collected from the key informants who were working at the logistics-related departments in the H Heavy Industries & Construction and HSD Engine. The following results were verified using structural equation modeling. First, environmental uncertainties such as dynamism and heterogeneity unexpectedly had insignificant effects on relational norms such as information exchange and flexibility and logistics services such as product availability and on-time delivery. Second, logistics resource capabilities showed unique effects based upon its component's characteristics. For example, Logistics Information Systems did not have direct impact on logistics services but had indirect effect on logistics services via relational norms. On the other hand, logistics resources such as logistics specific assets and transportation service competencies had direct impact on logistics services but not on relational norms. Third, relational norms between transaction partners significantly affected logistics services but had insignificant effects on logistics performance such as logistics costs reduction and delivery qualities. Fourth, consistent with several studies, excellent logistics services between industrial purchaser and suppliers based upon relational norms did have significant effect on logistics performance such as delivery consistency and delivery qualities. Finally, the empirical results in this study could be strategic logistics management guidelines based upon the theoretical relationships among the environmental uncertainties, logistics information systems, logistics resources, relational norms, logistics services, and logistics performance.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.665-679
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• 2019

Mesoscale soil moisture measurement from the promising Cosmic-Ray Neutron Probe (CRNP) is expected to bridge the gap between large scale microwave remote sensing and point-based in-situ soil moisture observations. Traditional calibration based on $N_0$ method is used to convert neutron intensity measured at the CRNP to field scale soil moisture. However, the static calibration parameter $N_0$ used in traditional technique is insufficient to quantify long term soil moisture variation and easily influenced by different time-variant factors, contributing to the high uncertainties in CRNP soil moisture product. Consequently, in this study, we proposed a modified traditional calibration method, so-called Dynamic-$N_0$ method, which take into account the temporal variation of $N_0$ to improve the CRNP based soil moisture estimation. In particular, a nonlinear regression method has been developed to directly estimate the time series of $N_0$ data from the corrected neutron intensity. The $N_0$ time series were then reapplied to generate the soil moisture. We evaluated the performance of Dynamic-$N_0$ method for soil moisture estimation compared with the traditional one by using a weighted in-situ soil moisture product. The results indicated that Dynamic-$N_0$ method outperformed the traditional calibration technique, where correlation coefficient increased from 0.70 to 0.72 and RMSE and bias reduced from 0.036 to 0.026 and -0.006 to $-0.001m^3m^{-3}$. Superior performance of the Dynamic-$N_0$ calibration method revealed that the temporal variability of $N_0$ was caused by hydrogen pools surrounding the CRNP. Although several uncertainty sources contributed to the variation of $N_0$ were not fully identified, this proposed calibration method gave a new insight to improve field scale soil moisture estimation from the CRNP.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.61-78
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• 2019

This study is about the effect of the founder's self-efficacy on the sales of the founding company by focusing on the factors that are currently emphasized in the founding education. In particular, this paper starts from the consciousness of the problem that the education that is being implemented to achieve the purpose of successful start-up among various government-based start-up support projects is failing to produce many start-up failures. Entrepreneurs cannot be assessed by objective financial data, but there is a high degree of uncertainty that should be determined based on their personal and learning abilities. In addition, many previous studies, which are likely to be successful when there is a high self-efficacy in a specific field due to the influence of factors such as personal experience or learning, will answer the direction of support for start-up companies. This study focuses on the impact of the founder's self-efficacy on the sales of the founding firms, especially the sales that are the key to the survival of the founding firms. This study has six major studies. First, to analyze whether the self-efficacy of entrepreneurs with respect to entrepreneurship affects the sales of entrepreneurs. Second, to analyze whether the self-efficacy of entrepreneurs with respect to market orientation affects the sales of entrepreneurs. Analysis of whether the founder's self-efficacy affects the sales of the founding firms. Fourth, analysis of whether the founder's self-efficiency affects the sales of the founding firms' understanding of management environment changes. An analysis of whether efficacy affects the sales of a start-up company, and sixth, an analysis of whether the founder's self-efficacy of business model building ability affects the sales of a start-up company. As a result of the empirical analysis, this study found that the self-efficacy of entrepreneurs on product differentiation capability and business model building capacity had a positive influence on the sales of entrepreneurs. The self-efficacy had a positive effect on self-efficacy, and the customer orientation had a positive effect on self-efficacy on business model building capacity. Also, it was confirmed that a path exists between the components of self-efficacy and that self-efficacy through the path has a positive effect on the sales of the start-up company. Therefore, the results of this study suggest the implications of establishing such a path and strengthening self-efficacy to create the survival and start-up performance of a start-up company if the goal of the start-up company is to survive when implementing various support projects for the start-up company.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.28-36
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• 2023

Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.