• Culinary science and hospitality research
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• v.13 no.2
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• pp.123-135
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• 2007

This study intended to determine how price-ending types used for menu products affected consumers' price evaluation and value perception and such behavioral intentions as purchase intention and search intention. The collected data went through statistical processing, including frequency analysis, factor analysis, T-test and ANOVA using an $SPSS/PC^+$ 12.0 statistical package. The results can be summarized as follows: First, as for differences in internal reference price by ending, internal reference price was lower if menu ending was an odd number than it was an even number, which indicates that consumers tend to consider the price of the menu products to be lower if the ending of menu products is an odd number. Second, menu price-ending was found to have significant differences on consumers' purchase intention, search intention, and value perception. But the results of two-way ANOVA showed that price ending by restaurant types had no effect on consumers' search intention and restaurant type. This study suggested a desirable external reference price-ending type for menu products as one of sales promotion strategies to menu products planners and drew up a concrete plan to determine which price-ending type is useful by consumers' personal properties.

• The Research Journal of the Costume Culture
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• v.27 no.5
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• pp.524-537
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• 2019

The aim of this study was to explore the effect of combinations of diverse methods notifying price discounts (i.e., reference price, odd price, and discount rate signs) and the relationships among product attribute perception, discount perception, attitude toward product, and purchase intention of product. Experiments were conducted where 12 stimuli of different price discount information notifications regarding T-shirt advertisements were presented to 352 informants. The results showed that notification of each type of discount information increased discount perception, whereas no effect due to the size of letters used in the discount rate notification was found. As more price discount information notifications were used, discount perception tended to become stronger. The results of ANOVA analysis show that both product attribute perception and discount perception affected attitude toward the product. In addition, product purchase intention was determined by attitude toward the product as well as price discount perception. Based on these findings, marketers may want to use a combination of methods of price discount notifications in advertisements to deliver price discount information clearly to consumers. Confirmation of discount information using multiple cues would help consumers to notice and perceive price discount information provided by retailers more effectively. Discount information is crucial for increasing both purchase intention and favorable attitude, therefore, diverse strategies regarding discount information presentations should be developed, tested and applied in the real world of retailing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.67-75
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• 2020

This paper proposes a methodology for gantry route optimization in order to maximize the productivity of a odd-type surface mount device (SMD). A odd-type SMD is a machine that uses a gantry to mount electronic components on the placement point of a printed circuit board (PCB). The gantry needs a nozzle to move its electronic components. There is a suitability between the nozzle and the electronic component, and the mounting speed varies depending on the suitability. When it is difficult for the nozzle to adsorb electronic components, nozzle exchange is performed, and nozzle exchange takes a certain amount of time. The gantry route optimization problem is divided into the mounting order on PCB and the allocation of nozzles and electronic components to the gantry. Nozzle and electronic component allocation minimized the time incurred by nozzle exchange and nozzle-to-electronic component compatibility by using an mixed integer programming method. Sequence of mounting points on PCB minimizes travel time by using the branch-and-price method. Experimental data was made by randomly picking the location of the mounting point on a PCB of 800mm in width and 800mm in length. The number of mounting points is divided into 25, 50, 75, and 100, and experiments are conducted according to the number of types of electronic components, number of nozzle types, and suitability between nozzles and electronic components, respectively. Because the experimental data are random, the calculation time is not constant, but it is confirmed that the gantry route is found within a reasonable time.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.70-74
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• 2004

There are many researches being in process to develop the information storage devices applying to the portable devices recently. Based on this need, the information storage devices have to be satisfied with the fast access time, the robustness of the system, high data transfer rate and lower media price. The total size of the drive must design to adapt the portable devices such as CF II card or PC II card size. This paper proposes the swing arm type actuator to insert the designed actuator in the drive of the CF II size. Hereafter the research will be going on to be suitable to the physical standard and design the focus magnetic circuit newly. The swing arm type actuator including this circuit is designed to have the dynamic characteristic satisfying the mechanical specification as well as the BD 1x. Finally, the adaptability to the portable devices was demonstrated by the finite element analysis and optimization of structural part.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.