• Journal of agriculture & life science
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• v.46 no.2
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• pp.179-190
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• 2012

This study was performed to obtain a heat saving effect and enhance the efficiency of a greenhouse by using a hot water piping in order to minimize the operating costs of a greenhouse as oil prices continue to rise. This method also reduces the likelihood of accidents caused by snowdrifts in regions with heavy snowfall. In general, the experimental plot was $2.0{\sim}6.0^{\circ}C$ higher than the control plot. When the skylight felt was opened, the minimum temperature was in the range of $3.0{\sim}12.0^{\circ}C$. Therefore, we judged that damage caused by snowdrifts may be prevented partly by active heating. The temperature difference inside of the greenhouse by height was insignificant. The maximum heating load of the greenhouse according to crop was respectively about $37,000kcal{\cdot}h^{-1}$ and $41,700kcal{\cdot}h^{-1}$. During the experiment, the heat value of each designed temperature in the range of the minimum ambient temperature $-11.9{\sim}4.0^{\circ}C$ was about 95,000~322,000 kcal and it was in the range of $6,050{\sim}20,900kcal{\cdot}h^{-1}$. If it is compared with the maximum heating load, it can be shown that about 15~56% of the heating energy can be supplied. The total heat value and the amount of power consumption were 2,629,025 kcal and 677.3 kWh respectively during the experiment. If it is heated with diesel, a fossil fuel, the consumption during the experiment was 291 L and the cost was 331,700won. Total cost of using electric power was about 24,400 won and it is shown that it is about 7.5% of the cost of diesel consumption. Also, if the total amount of power consumption is converted into energy, it is approximately 582,200 kcal and the energy was just about 22% of the total heat value.

• Asia Marketing Journal
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• v.12 no.2
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• pp.83-110
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• 2010

Dissatisfied customers may express their dissatisfaction behaviorally. These behavioral responses may impact the firms' profitability. How do we model the impact of self regulatory orientation on emotions and subsequent customer behaviors? Obviously, the positive and negative emotions experienced in these situations will influence the overall degree of satisfaction or dissatisfaction with the service(Zeelenberg and Pieters 1999). Most likely, these specific emotions will also partly determine the subsequent behavior in relation to the service and service provider, such as the likelihood of complaining, the degree to which customers will switch or repurchase, and the extent of word of mouth communication they will engage in(Zeelenberg and Pieters 2004). This study investigates the antecedents, consequences of negative consumption emotion and the moderate effect of attribution processing in an integrated model(self regulatory mode → specific emotions → behavioral responses). We focused on the fact that regret and disappointment have effects on consumer behavior. Especially, There are essentially two approaches in this research: the valence based approach and the specific emotions approach. The authors indicate theoretically and show empirically that it matters to distinguish these approaches in services research. and The present studies examined the influence of two regulatory mode concerns(Locomotion orientation and Assessment orientation) with making comparisons on experiencing post decisional regret and disappointment(Pierro, Kruglanski, and Higgins 2006; Pierro et al. 2008). When contemplating a decision with a negative outcome, it was predicted that high (vs low) locomotion would induce more disappointment than regret, whereas high (vs low) assessment would induce more regret than disappointment. The validity of the measurement scales was also confirmed by evaluations provided by the participating respondents and an independent advisory panel; samples provided recommendations throughout the primary, exploratory phases of the study. The resulting goodness of fit statistics were RMR or RMSEA of 0.05, GFI and AGFI greater than 0.9, and a chi-square with a 175.11. The indicators of the each constructs were very good measures of variables and had high convergent validity as evidenced by the reliability with a more than 0.9. Some items were deleted leaving those that reflected the cognitive dimension of importance rather than the dimension. The indicators were very good measures and had convergent validity as evidenced by the reliability of 0.9. These results for all constructs indicate the measurement fits the sample data well and is adequate for use. The scale for each factor was set by fixing the factor loading to one of its indicator variables and then applying the maximum likelihood estimation method. The results of the analysis showed that directions of the effects in the model are ultimately supported by the theory underpinning the causal linkages of the model. This research proposed 6 hypotheses on 6 latent variables and tested through structural equation modeling. 6 alternative measurements were compared through statistical significance test of the paths of research model and the overall fitting level of structural equation model and the result was successful. Also, Locomotion orientation more positively influences disappointment when internal attribution is high than low and Assessment orientation more positively influences regret when external attribution is high than low. In sum, The results of our studies suggest that assessment and locomotion concerns, both as chronic individual predispositions and as situationally induced states, influence the amount of people's experienced regret and disappointment. These findings contribute to our understanding of regulatory mode, regret, and disappointment. In previous studies of regulatory mode, relatively little attention has been paid to the post actional evaluative phase of self regulation. The present findings indicate that assessment concerns and locomotion concerns are clearly distinct in this phase, with individuals higher in assessment delving more into possible alternatives to past actions and individuals higher in locomotion engaging less in such reflective thought. What this suggests is that, separate from decreasing the amount of counterfactual thinking per se, individuals with locomotion concerns want to move on, to get on with it. Regret is about the past and not the future. Thus, individuals with locomotion concerns are less likely to experience regret. The results supported our predictions. We discuss the implications of these findings for the nature of regret and disappointment from the perspective of their relation to regulatory mode. Also, self regulatory mode and the specific emotions(disappointment and regret) were assessed and their influence on customers' behavioral responses(inaction, word of mouth) was examined, using a sample of 275 customers. It was found that emotions have a direct impact on behavior over and above the effects of negative emotions and customer behavior. Hence, We argue against incorporating emotions such as regret and disappointment into a specific response measure and in favor of a specific emotions approach on self regulation. Implications for services marketing practice and theory are discussed.

• 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.

• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.89-94
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• 2012

The objective of this study was to estimate the genetic parameters and breeding value of swine using their economic traits. The traits considered were age at 90 kilograms body weight (D90 kg), backfat thickness (BF) and eye muscle area (EMA). Estimation of genetic parameters and breeding value from 18,668 heads considering the economic traits were based on farm performance data from May 2007 to April 2011. Estimation of genetic parameters based on economic traits revealed that the single best model was fitted after finding source of variance on fixed and random effects and estimated by a multiple trait model using DF-REML (Derivative-FREE Restricted Maximum Likelihood). In this study, the estimated heritabilities of Duroc, Berkshire, Landrace and Yorkshire were about 0.22-0.59 for the D90 kg, 0.47-0.62 for the BF and 0.23-0.37 for the EMA. Genetic correlation of D90 kg with BF and EMA of the four breeds were -0.01-0.24 and -0.35--0.23, respectively. Moreover, the genetic correlation of BF with EMA was -0.68--0.17. On the other hand, the phenotypic correlation of D90 kg with BF and EMA of the four breeds were about 0.01-0.11 and -0.37--0.21, respectively, while the phenotypic correlation of BF with EMA was -0.68--0.17. Results showed that the genetic trends of breeding value every year were decreasing for D90 kg, increasing for BF while for EMA inconsistent values were obtained.

• Journal of Animal Science and Technology
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• v.54 no.2
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• pp.83-87
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• 2012

The purpose of this study was to estimate genetic parameters for productive traits in swine. Productive traits were considered on average daily gain (ADG), body height (BH) and body length (BL). Genetic analysis was consisted of 18,668 heads for productive traits which were based on on-farm performance tested from May, 2007 to Apr, 2011. For estimating genetic parameters on productive traits, single best model was fitted after finding source of variance on fixed and random effects and estimated with a multiple trait animal model by using DF-REML (Derivative-Free Restricted Maximum Likelihood). The estimated heritabilities of Duroc, Berkshire, Landrace and Yorkshire 0.22-0.58 for the average daily gain, 0.34-0.41 for the body height and 0.4-0.52 for the body length, respectively. Phenotypic correlations of average daily gain with body height and body length for the four breeds were 0.42-0.48, 0.53-0.58, 0.34-0.46 and 0.47-0.56, respectively. Phenotypic correlations of body height with body length were 0.41, 0.57, 0.52, 0.59, respectively. The estimated genetic correlation coefficients of average daily gain with body height and body length estimated for the four breeds were 0.34-0.47, 0.70-0.75, 0.17-0.38 and 0.50-0.53, respectively. The estimated genetic correlation coefficients of body height with body length were 0.57, 0.69, 0.61 and 0.71, respectively.

• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.29-38
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• 2006

After the first opening of the KTX in April 2004, travel time between major cities has been dramatically reduced. The reduction rates range from 32% to 47%. Considering travel time reduction between major cities, this study concerned about the intercity travel impact of the KTX operation. This study aimed to analyze intercity mode choice behavior of Daegu Citizens according to the first opening of the KTX. This study takes place in two sections. These are (i) the section of KTX between Daegu and Seoul, and (ii) the section of KTX between Daegu and Daejeon. This study estimated empirical models for analyzing intercity mode choice behavior according to the first opening of the KTX. This study makes use of the data from travel survey from Daegu metropolitan area. The main part of the survey was carried out in the KTX Dong-Daegu station. The survey data includes the information on travel from Daegu to Daejeon and from Daegu to Seoul. In order to analyze intercity choice behavior according to the frist opening of the KTX, multinomial model structure is used. For the model specification, a variety of behavioral assumptions about the factors which affect the mode choice, were considered. From the empirical model estimation, it is found that OVTT(Out-of-Vehicle Travel Time), OVTC(Out-of-Vehicle Travel Cost), IVTT(In-Vehicle Travel Time), IVTC(In-Vehicle Travel Cost), travel frequency, travel purpose, sex, age, occupation. household income, individual income are significant in choosing intercity travel mode. However, it is found that the intercity nde choice behavior is different between (i) the section of KTX between Daegu and Seoul, and (ii) the section of KTX between Daegu and Daejeon. Furthermore, some policy implications are discussed in conclusion.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.27-57
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• 2008

Many consumers enjoy the challenge of purchasing a brand that matches well with their own values and personalities (for example, Ko et al., 2008; Ko et al., 2006). Therefore, the personalities of consumers can impact on the final selection of a brand and its brand personality in two ways: first, the consumers may incline to purchase a brand or a product that reflects their own personalities; second, consumers tend to choose a company that has similar brand personalities to those brands that are being promoted. Therefore, the objectives of this study are following: 1. Is there any empirical relationship between a consumer's personality and the personality of a brand that he or she chooses? 2. Can a corporate brand be differentiated by the brand personality? In short, consumers are more likely to hold favorable attitudes towards those brands that match their own personality and will most probably purchase those brands matching well with their personality. For example, Matzler et al. (2006) found that extraversion and openness were positively related to hedonic product value; and that the personality traits directly (openness) and indirectly (extraversion, via hedonic value) influenced brand effects, which in turn droved attitudinal and purchase loyalty. Based on the above discussion, the following hypotheses are proposed: Hypothesis 1: the personality of a consumer is related to the brand personality of a product/corporate that he/she purchases. Kuksov (2007) and Wernerfelt (1990) argued that brands as a symbolic language allowed consumers to communicate their types to each other and postulated that consumers had a certain value of communicating their types to each other. Therefore, how brand meanings are established, and how a firm communicate with consumers about the meanings of the brand are interesting topics for research (for example, Escalas and Bettman, 2005; McCracken, 1989; Moon, 2007). Hence, the following hypothesis is proposed: Hypothesis 2: A corporate brand identity is differentiated by the brand personality. And there are significant differences among companies. A questionnaire was developed for collecting empirical measures of the Big-Five personality traits and brand personality variables. A survey was conducted to the online access panel members through the Internet during December 2007 in Korea. In total, 500 respondents completed the questionnaire, and considered as useable. Personality constructs were measured using the Five-factor Inventory (NEO-FFI) scale and a total of 30 items were actually utilized. Brand personality was measured using the five-dimension scale developed by Aaker (1997). A total of 17 items were actually utilized. The seven-point Likert-type scale was the format of responses, for example, from 1 indicating strongly disagreed to 7 for strongly agreed. The Analysis of Moment Structures (AMOS) was used for an empirical testing of the model, and the Maximum Likelihood Estimation (MLE) was applied to estimate numerical values for the components in the model. To diagnose the presence of distribution problems in the data and to gauge their effects on the parameter estimates, bootstapping method was used. The results of the hypothesis-1 test empirically show that there exit certain causality relationship between a consumer's personality and the brand personality of the consumer's choice. Thus, the consumer's personality has an impact on consumer's final selection of a brand that has a brand personality matches well with their own personalities. In other words, the consumers are inclined to purchase a brand that reflects their own personalities and tend to choose a company that has similar brand personalities to those of the brand being promoted. The results of this study further suggest that certain dimensions of the brand personality cause consumers to have preference to certain (corporate) brands. For example, the conscientiousness, neuroticism, and extraversion of the consumer personality have positively related to a selection of "ruggedness" characteristics of the brand personality. Consumers who possess that personality dimension seek for matching with certain brand personality dimensions. Results of the hypothesis-2 test show that the average "ruggedness" attributes of the brand personality differ significantly among Korean automobile manufacturers. However, the result of ANOVA also indicates that there are no significant differences in the mean values among manufacturers for the "sophistication," "excitement," "competence" and "sincerity" attributes of the corporate brand personality. The tight link between what a firm is and its corporate brand means that there is far less room for marketing communications than there is with products and brands. Consequently, successful corporate brand strategies must position the organization within the boundaries of what is acceptable, while at the same time differentiating the organization from its competitors.

• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.1-22
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• 2008

This study is to evaluate, to the extent to, which advanced currency futures and emerging currency futures markets can predict accurately the future spot rate. To this end, Johansen's the maximum-likelihood cointegration method(1988, 1991) is adopted to test the unbiasedness and efficiency hypothesis. Also, this study is to estimate and compare a quantitative measure of relative efficiency as a ratio of the forecast error variance from the best-fitting quasi-error correction model to the forecast error variance of the futures price as predictor of the spot price in advanced currency futures with in emerging currency futures market. Advanced currency futures is British pound and Japan yen. Emerging currency futures includes Korea won, Mexico peso, and Brazil real. The empirical results are summarized as follows : First, the unbiasedness hypothesis is not rejected for Korea won and Japan yen futures exchange rates. This indicates that the emerging currency Korea won and the advanced currency Japan yen futures exchange rates are likely to predict accurately realized spot exchange rate at a maturity date without the trader having to pay a risk premium for the privilege of trading the contract. Second, in emerging currency futures markets, the unbiasedness hypothesis is not rejected for Korea won futures market apart from Mexico peso and Brazil real futures markets. This indicates that in emerging currency futures markets, Korea won futures market is more efficient than Mexico peso and Brazil real futures markets and is likely to predict accurately realized spot exchange rate at a maturity date without risk premium. Third, this findings show that the results of unbiasedness hypothesis tests can provide conflicting finding. according to currency futures class and forecasts horizon period, Fourth, from the best-fitting quasi-error correction model with forecast horizons of 14 days, the findings suggest the Japan yen futures market is 27.06% efficient, the British pound futures market is 26.87% efficient, the Korea won futures market is 20.77% efficient, the Mexico peso futures market is 11.55%, and the Brazil real futures market is 4.45% efficient in the usual order. This indicates that the Korea won-dollar futures market is more efficient than Mexico peso, and Brazil real futures market. It is therefore possible to concludes that the Korea won-dollar currency futures market has relatively high efficiency comparing with Mexico peso and Brazil real futures markets of emerging currency futures markets.

• Journal of Animal Science and Technology
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• v.44 no.5
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• pp.499-506
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• 2002

This study was conducted to estimate the heritabilities and genetic and phenotypic correlations among average daily gain, age at 90kg and backfat thickness in Yorkshire pigs. The data were obtained from 2,111 heads of Yorkshire tested at National Livestock Research Institute from May, 1994 to April, 2000. Genetic parameters were estimated with a multiple trait animal model by using DF-REML (Deri- vative-Free REstricted Maximum Likelihood). The results obtained are summarized as follows ; The means of traits studied were 0.871${\pm}$0.124 kg for average daily gain, 145.397${\pm}$11.718 days for age at 90kg and 1.476${\pm}$0.241 cm for backfat thickness. The estimated heritabilities were 0.55 for average daily gain, 0.56 for age at 90kg and 0.55 for backfat thickness. The genetic correlation of average daily gain with age at 90kg and backfat thickness were －0.82, 0.10, respectively. The genetic correlation of age at 90kg with backfat thickness was －0.25. The phenotypic correlations of average daily gain(ADG) with age at 90kg and backfat thickness and age at 90kg with backfat thickness were －0.77, 0.02 and －0.05 respectively. Though phenotypic correlation of ADG and age at 90kg was low, breeding project should be carefully considered by high genetic correlation. High heritabilities on all economic traits were obtained. Therefore, it is considered that suitable selection and management is needed successful improvement.

• Journal of Animal Science and Technology
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• v.54 no.5
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• pp.331-336
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• 2012

This study was conducted to estimate genetic parameters for ultrasound and carcass traits in Hanwoo. Heritabilities and genetic and phenotypic correlations were estimated for carcass and ultrasound measurements collected from Hanwoo cows (n=312) born at Hanwoo experiment station. Traits evaluated were eye muscle area (EMA), backfat thickness (BF), marbling score (MS) from carcass, and ultrasound eye muscle area (UEMA), ultrasound backfat (UBF), and ultrasound marbling score (UMS). Parameters were estimated using multi-trait animal models byderivative-free restricted maximum likelihood procedures. Estimated heritabilities for UBF, UEMA and UMS were 0.43, 0.23 and 0.32, while heritabilities for BF, EMA and MS were 0.33, 0.13 and 0.33 in fattened cows, respectively. Genetic correlations between ultrasound and carcass measurements were estimated to -0.19, -0.61, and -0.36 for UBF: UEMA, UBF: UMS, and UEMA: UMS in fattened cows, respectively. Phenotypic correlations between ultrasound and carcass measurements were 0.03, 0.13 and 0.26 for UBF: UEMA, UBF: UMS, and UEMA: UMS in fattened cows, respectively. As for the steer, genetic correlations between ultrasound and carcass measurements were 0.36, -0.80 and 0.27 for UBF: UEMA, UBF: UMS, and UEMA: UMS in steers, respectively. Phenotypic correlations between ultrasound and carcass measurements were 0.13, 0.07 and 0.41 for UBF: UEMA, UBF: UMS, and UEMA: UMS in steers, respectively. In conclusion, this finding would be very useful to implement into Hanwoo breeding program.