• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.315-326
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• 2020

Corporate efforts to build strong brands have made consumers interested in brand love. In the field of brand love, however, there is a lack of systematic research on the multidimensionality of the concept of brand love and on the scale development to measure it. Thus, based on the methodological research design of Churchill(1979) and DeVellis(1991), this study explored properties of brand love and classified them into two levels - 'emotion' and 'relationship' - and generated corresponding measurement items. To do this, the research was conducted in a total of eight stages, including preliminary studies such as literature review, open surveys, and in-depth interviews, as well as the main study process in which the factors were analyzed step by step. As a result, the level of emotion appeared to have five subcomponents (self-esteem, warmth, interest, responsibility, pleasure) with 19 items, and the level of relationship - three subcomponents (unchanging, sharing/supporting, understanding) with 11 items, adding up to a total of 30 measurement items for brand love with reliability, convergent and discriminant validity, and nomological validity. Additionally, we intended to expand the scope of research related to brand love by presenting the result model of organic interaction between the concepts that constitute brand love and proposing '4 categories of brand love strength' based on it.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.175-182
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• 2021

As road noise became an issue, low-noise pavement (LNP) has emerged. The noise difference from general asphalt pavement (GAP) is a measure to explain the noise reduction of LNP. On the other hand, even for GAP, noise varies with the performance years (PY) and pavement condition. This study evaluated the representative noise value (RNV) by the speed and PY of GAP. Sections of 49selected from the National Road Pavement Management System, and the noise was measured at speeds from 50km/h to 80km/h at every 10km/h using the Close Proximity Method (CPX). Because the noise immediately after construction differed from the other, it was treated separately, and some outliers were removed. The noise increased with increasing PY. In addition, the noise increase by speed showed a reliable trend at all noise levels. The RNV for each speed and PY was obtained through analyses of the PY and speed. The average noise difference between the initial construction and the six-year-paced pavement was approximately 6dB. When evaluating the noise reduction of LNP, it is necessary to use RNV rather than the noise of old pavement. The RNV of GAP is necessary for a relative comparison with LNP and studying the road noise characteristics for each GAP type.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.238-245
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• 2011

For introduction of local autonomy system, local government enabled efficient supply of public service by local resident's request. Specially, local governments is doing effort of that organize various policy and a lot of budgets for social welfare promotion, but is interested relatively little in efficient use of social welfare finance and operation. According to these problem, this study measured efficiency of social welfare facility in local governments. The purpose of this analysis is to measure the efficiency of community welfare in local governments by data envelopment analysis(DEA), using data from 16 local governments in Korea. Input variance is GDP per capita in local, rate of welfare budget, rate of financial independence and local public official per 10,000 capita. Output variance is social welfare facility per 100,000 capita and park area per 1,000 capita, The results of the study are summarized as follows : First, There was differential in efficiency about social welfare facilities operation in local governments. 7 local governments(Busan, etc.) was an in efficiency. Second, some local governments(Incheon, etc.) must increase scale of input variance, and some local governments(Busan, etc.) must improve efficiency of input variance.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.340-347
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• 2012

In Korea, the game software and service industry is the core cultural industry from it's significant academic and policy. However, recent growth is slowing down because of increasing competition in the industry. In other words, most of the companies growth have reached limit caused by focusing only on short-term revenue-generating management, Therefore, the game software and service companies are needed to emphasize strategic planning of R&D and product development based on the long-term perspective. The purpose of this analysis is to measure the efficiency of management by data envelopment analysis(DEA), using data from 20 companies in the game software and service industry. Input variances are number of labor, total asset, and total investment and output variances are total sale and enterprise value. The results are followings: First, There was a different efficiency between the companies in the game software and service industry. The eight companies was inefficiency. Second, six inefficiency companies were excessive number of the employees and investment assets. third, four companies were CRS, five companies were IRS and eleven companies were DRS. From the result, five companies have to increase the scale of input variance and eleven companies also have to improve efficiency of input variance.

• Korean Journal of Food Science and Technology
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• v.24 no.2
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• pp.165-170
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• 1992

The creep behavior of gels made with $30{\sim}45%$ gelatinized rice starch was measured over a wide range of temperature. Compressive creep curves of rice starch gels conformed to a six element mechanical model consisting of one Hookean, two Voigt and one Newtonian component. The creep compliance of gels decreased with increasing starch concentrations. Among viscoelastic constants of the mechanical model, elastic modulus was mainly influenced by the change of starch concentrations. The concentration-invariant compliance curve was obtained by reduction to 38% using reduction parameter $a_{c}$. The creep compliance curves of 45% starch gels increased with temperature, which indicated that rice starch gels became softer and less rigid with increasing temperature. When the compliance at $20^{\circ}C$ was set as a reference curve, creep compliance data for 45% gels at various temperature could be superimposed as a continuous smooth curve. The apparent activation energies of 45% rice starch gels calculated by the modified WLF equation were not intrinsic, but decreased as temperature increased.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.