• The Research Journal of the Costume Culture
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• v.7 no.6
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• pp.54-67
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• 1999

The purpose of this study were (1) to segment the female college students according to apparel shopping orientation and (2) to create a profile for each group with regard to impotance of store attributes, use of information sources, and self-image. The questionnaire were administered to the female college students living in Seoul and data were analyzed by frequency, percentage, factor analysis, cluster analysis, one-way ANOVA(analysis of variance), and MANOVA(multivariate analysis of variance). By cluster analysis of apparel shopping orientation factors, four groups are identified : (1) highly involved apparel shopper (44.34%), (2) brand-loyal shopper (24.43%), (3) planned / practical shopper, and (4) apathetic shopper (18.10%) Four groups were then compared through MANOVA on importance of store attributes, use of information, and self-image. Significant differences were found among four groups on three variables. In general. highly involved shopper tend not to be price conscious, enjoy shopping and use the information sources most actively and apathetic shoppers tend to be indifferent to apparel shopping and do not actively use the information sources.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.4
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• pp.33-53
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• 2010

When purchase prices of a raw material fluctuate over time, the total purchasing cost is mainly affected by reordering time. Existing researches focus on deciding the right time when the demand for each period is replenished at the lowest cost. However, the decision is based on expected future prices which usually turn out to include some error. This discrepancy between expected prices and actual prices deteriorates the performance of inventory models dealing with fluctuating purchase prices. In this paper, we propose a new inventory model which incorporates not only cost but also risk into making up a replenishment schedule to meet each period's demand. For each replenishment schedule, the risk is defined to be the variance of its total cost. By introducing the risk into the objective function, the variability of the total cost can be mitigated, and eventually more stable replenishment schedule will be obtained. According to experimental results from crude oil inventory management, the proposed model showed better performance over other models in respect of variability and cost.

• Journal of the Korean Statistical Society
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• v.35 no.2
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• pp.115-142
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• 2006

This paper studies the problem of option hedging when the underlying asset price process is a compound Poisson process. By adopting an asymptotic approach to let the security price converge to a continuous process, we find a closed-form hedging strategy that improves the classical Black-Scholes hedging strategy in a quadratic sense. We first show that the scaled Black-scholes hedging error has a limit in law, and that limit is decomposed into a part that can be traded away and a part that is purely unreplicable. The Black-Scholes hedging strategy is then modified by adding the replicable part of its hedging error and by adding the mean-variance hedging strategy to the nonreplicable part. Some results of simulation experiment s are also provided.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.566-573
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• 2014

This paper presents the results of an integrated navigation performance analysis for selecting the sensor of an unmanned underwater vehicle (UUV) using Monte Carlo numerical simulation. An inertial measurement unit (IMU) and Doppler velocity log (DVL) are considered to build the integrated navigation system. The position error and price of the sensor are selected as performance indices to evaluate the volunteer integrated navigation systems. Monte-Carlo simulation is introduced to analyze the circular error probability (CEP) and its variance. Simulation results provide the proper sensor combination for integrated navigation in relation to the performance and price.

• East Asian Economic Review
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• v.22 no.3
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• pp.337-370
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• 2018

This paper discusses the design of monetary policy in a New Keynesian small open economy framework by introducing nominal wage rigidities and incomplete exchange rate pass-through on import prices. Three main findings are summarized. First, with the existence of an incomplete exchange rate pass-through and nominal wage rigidities, the optimal policy is to seek to minimize the output gap, the variance of domestic price and wage inflation, as well as deviations from the law of one price. Second, the CPI inflation targeting Taylor rule is welfare enhancing when there is a technological shock to the economy. The exception occurs when there is a foreign income shock, which minimizes welfare losses under the domestic inflation targeting Taylor rule. Last, two stylized Taylor rules turn out to be a bad approximation, but the modified Taylor rules that respond to the unemployment gap rather than the output gap are a closer approximation to the optimal policy.

• KIEE International Transactions on Power Engineering
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• v.4A no.3
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• pp.159-166
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• 2004

Forecasting prices in electricity markets is critical for consumers and producers in planning their operations and managing their price risk. We utilize the generalized autoregressive conditionally heteroskedastic (GARCH) method to forecast the electricity prices in two regions of New York： New York City and Central New York State. We contrast the one-day forecasts of the GARCH against techniques such as dynamic regression, transfer function models, and exponential smoothing. We also examine the effect on our forecasting of omitting some of the extreme values in the electricity prices. We show that accounting for the extreme values and the heteroskedactic variance in the electricity price time-series can significantly improve the accuracy of the forecasting. Additionally, we document the higher volatility in New York City electricity prices. Differences in volatility between regions are important in the pricing of electricity options and for analyzing market performance.

• Korean journal of food and cookery science
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• v.30 no.3
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• pp.360-367
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• 2014

This study analyzed the Importance-Performance Analysis of selective attributes of Ethnic Food Restaurant. A total of 369 questionnaires were analyzed. Five factors were obtained from factor analysis of Importance variance of selective attributes of Ethnic food restaurant: Factor 1 "Quality", Factor 2 "Service", Factor 3 "Physical environment", Factor 4 "Uniqueness", Factor 5 "Health". Also, "Quality", "Physical environment", "Uniqueness" factors influenced overall satisfaction. In addition, according to the IPA results, selective attributes with low satisfaction and high importance in the second quadrant were 'Sanitation that comfort hospitality', 'Level of service' and 'Price'. These results suggest that when customers select Ethnic food restaurant, they consider 'food price' and 'food quality'. Therefore, manager of ethnic food restaurant should take these improvement factors into consideration in order to meet consumer's expectations.

• East Asian Economic Review
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• v.18 no.3
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• pp.301-335
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• 2014

In this paper, we consider a small open economy under the New Keynesian model with unemployment of Gal$\acute{i}$ (2011a, b) to discuss the design of the monetary policy. Our findings can be summarized in three parts. First, even with the existence of unemployment, the optimal policy is to minimize variance of domestic price inflation, wage inflation, and the output gap when both domestic price and wage are sticky. Second, stabilizing unemployment rate is important in reducing the welfare loss incurred by both technology and labor supply shocks. Therefore, introducing the unemployment rate as an another argument into the Taylor-rule type interest rate rule will be welfare-enhancing. Lastly, controlling CPI inflation is the best option when the policy is not allowed to respond to unemployment rate. Once the unemployment rate is controlled, however, stabilizing power of CPI inflation-based Taylor rule is diminished.

• The Journal of Fisheries Business Administration
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• v.30 no.2
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• pp.25-37
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• 1999

Some multi echelon inventory systems carry perishable products. The value of these product reduces as the period of time they spend in the system. In this paper We derive the necessary condition to determine optimal quantity, service level for a perishable product. The systems considered consist of two echelons and carry single item. To determine the optimal order quantity, the demand is assumed to be constant, the holding costs may be different in the echelons, and it allows no shortages. I assumed the price of product decreases by negative exponential function. To determine service level, following assumptions used in the model ㆍlead time is constant. ㆍdemand is normal distribution. ㆍthe product starts to perish at the second echelon. Service level is computed for different levels of lead times and for different variance of demands and for different price functions. The experimental results indicate that the service level in cost is a function of service level in demand and perishability of product. Results of the models exhibit that perishability and the age of the product are critical to determine the lot sizing and service level.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.287-297
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• 2009

In terms of generalized autoregressive conditional heteroscedastic(GARCH) model, estimation of prediction interval based on likelihood is quite sensitive to distribution of error. Moveover, it is not an easy job to construct prediction interval for conditional variance. Recent studies show that the bootstrap method can be one of the alternatives for solving the problems. In this paper, we introduced the bootstrap approach proposed by Pascual et al. (2006). We employed it to Korean stock price data set.