• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.17-23
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• 2019

IaaS is well known as a very cost effective computing service which enables required infrastructures to be rented on demand without ownership of real hardwares. It is very suitable for price sensitive services due to pay-per-use style. Operators of such services would want to adjust utilization policy quickly by estimating costs for cloud infrastructures as soon as possible. However, swift response is not possible due to that cloud service providers provide a dozen or so hours delayed billing information. Our work proposes a realtime IaaS cost estimation model based on usages monitored by virtual machine instance. We operate PC laboratory service on a public cloud during full semester to validate our suggested model. From that experiment, an averaged disparity between estimation and actual cost is less than 5.2%.

• Journal of Distribution Science
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• v.14 no.11
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• pp.129-138
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• 2016

Purpose - The ICT(information and communications technologies) development is affecting consumer behaviors on selecting channel or distribution system. This study aims to advance our knowledge about the factors influencing omni-channel behaviors. This study considers the positive brand experience as the moderating variable into the relationship between omini-channel use intention and consumer brand relation. Also, the effect of positive brand experience on consumer-brand relation is researched. Research design, data, and methodology - This study conducted an empirical test with the subject as customers who purchase goods or service through on-off cross channel simultaneously. The research model is developed from prior literatures about influencing variables on channel selection. The structure of this study is designed to identify causal relationships between the variables. 268 survey data from the questionnaire survey which is conducted to target customers who use online and offline channels, is used for empirical analysis. This study validates generality with descriptive statistics and data reliability with Cronbach's alpha value. The exploratory factor analysis is used for value purification. Then, the confirmatory factor analysis is conducted for structural equation modeling. Finally, the execute structural equation modeling is analyzed to confirm the hypotheses Results - First, the two causal influences between perceived performance risk and the propensity of omni-channel and between price consciousness and the propensity of omni-channel are verified through the empirical test. Second, the result identifies that the propensity of omni-channel is influenced on consumer-brand relationship. Third, the AMOS analysis proves that the moderating variable, positive brand experience, has significant positive impact on consumer-brand relationship. This significant relationship is highly supported by the regression analysis between brand experience and propensity of omni-channel because it results that positive brand experience has positive impact on the propensity of omni-channel. All hypotheses are verified to be true. Conclusions - Based on the empirical result, this study confirms that perceived performance risk and price consciousness are the important factors influencing propensity of omni-channel. According to the additional analysis, the moderating variable and positive brand experience plays important role between the propensity of omni-channel and consumer-brand relationship. Furthermore, positive brand experience influences more on consumer-brand relationship than non-positive brand experience.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.3
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• pp.405-418
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• 2017

SHIFT is public rental housing policy introduced by Seoul Metropolitan in 2007, which works as Chonsei(korean unique deposit rental system). This paper examines the effect of SHIFT on Chonsei prices of neighborhood apartments. To estimate the change in prices of Chonsei after the provision of SHIFT, I collect data on Chonsei prices of apartments within a 5km radius from the SHIFT housings. Summary of main results are following. Chonsei prices of the apartments within a 2-3km radius decreased by 4.4% after the provision of SHIFT housings. In contrast, when it comes to apartments within a 1-2km radius, I can't find the stochastic relationship between the provision of SHIFT hosing and price changes. This results can be explained by "Offset effects" caused by real estate development. Provision of SHIFT can sequentially induce nearby area's development, which plays a factor in the effect of price increases. And this offset effects varies in each apartment complex depending on demand for Chonsei and supply of the SHIFT.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.139-148
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• 2014

In recent years, computational models using parametric estimation method have been developed and used widely for efficient cost analysis. In this research, by applying experienced data from Guidance and Control Systems in Missile System field, the cost analysis for engineering model and commercial computational model(Price H, HL, M, S) are conducted and its result is analysed, so that the difference between two models and its grounds are apprehended. Comparing the calibrated value of computational model based on the data base of similar equipment and the cost from the engineering estimation, the two results are very close. It means that the credibility of data is enhanced through calibration. Also, for cost analysis of similar components in the future, the method for calibration of the computational models is also examined. When estimating development cost in this research, although many parts have been estimated through uncertain elements, the reliability could have been enhanced by applying computational model which secures objectivity. It is a very reasonable estimation method by utilizing calibration of the computational models based on existing accumulated development data.

• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.93-104
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• 2022

In forecasting realized volatility of the major US stock price indexes (S&P 500, Russell 2000, DJIA, Nasdaq 100), internet search volume reflecting investor's interests and implied volatility are used to improve forecast via a deep learning method of the LSTM. The LSTM method combined with search volume index produces better forecasts than existing standard methods of the vector autoregressive (VAR) and the vector error correction (VEC) models. It also beats the recently proposed vector error correction heterogeneous autoregressive (VECHAR) model which takes advantage of the cointegration relation between realized volatility and implied volatility.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.27-38
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• 2002

VTIS(Value-added Traffic Information System), among the sub-systems of ATIS, is an Advanced Traffic System which innovates efficiency and safety. And this system, having marketability and publicness, is very important. Moreover, This system offers definite traffic information according to the demand of specified users. And it is expected to produce additional spread effects because of high participation rate of private sector. However, the VTIS service media are varied and there are varied optimal Prices and payment methods according to each medium. Because of that, there needs the study on these problems or optimal criteria. But because existing studies were devoted to estimate the optimal route, the study toward the optimal price which was considered part of user and service use demand do not exist. Accordingly, we surveyed under imaginary alternative pricing scenarios and forecasted the use demand of VTIS by using Binary Logit model. Also, for the users who answered that they would use VTIS service in survey, we classified their use's behaviors as four categories and estimated the use ratio to each category by using Ordered Probit model. Last, using sensitivity analysis for results form above, we derived the optimal price that is 2800won in monthly. 145won in payment per call. Then, VTIS service use rate is respectively 65%, 75%.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Korean Journal of Agricultural Science
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• v.20 no.2
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• pp.221-236
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• 1993

Economic conditions of Korean agriculture have been aggravated since farmers experienced the shortage of labor, instability of farm product price, lack of capital and pressure of opening domestic market. Nevertheless, agriculture must be maintained because structure of national economy can not be progressed without balanced growth of food industry. So the problem that we must solve is to keep agriculture competitive. In that case technology is important in terms of improving productivity, overcoming labor shortage and stabilizing price. This paper is to study the technology adoption on the farm level, focusing on the theories of technology adoption, their empirical test and effect of technology adoption on the farm household income. In this study five theories-independent model, linear model, middle class conservation model, modified middle class conservation model, basic needs and wealfare model- were introduced concerning differentiated technology adoption rate by farmers' class. Based on the survey of controlled strawberry farming in Nonsan County, Chungnam Province, who adopted six kinds of technology, modified middle class conservation model was found to explain five kinds of technology adoption pattern and linear model was useful to explain one kind of technology, that is, irrigation method, These results may mean that controlled strawbary cultivators of middle class were reluctant to accept new technology. There are many variables to effect on the technology accepting rate, that is, farmer's age, labor capacity, education level, cultivation career, size of total cultivated land, and size of strawberry farming land. LOGIT model was used to find which variable influence the technology adoption rate. Results of estimation showed that variables of cultivation career and total land size, of which coefficients were statistically significant at the 5 percent level, might be main influential factors in accepting more than three farming techniques. There was a significant income difference between farm households accepting new methods and those rejecting them. Especially in case of low class of farming group, income of farmers who was adopting new technology was examined to be much higher than that of farmers who did not adopt. This result suggests that new technology play an important role in increasing farm household income. Finally this study emphasized that there is a need to develop proper measure of technology transfer considering various socioeconomic conditions of farm households.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.329-338
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• 2019

In this study, we analyze consumer preferences based on the agricultural box scheme attributes, and make a suggestion for business revival. We estimate the marginal willingness to pay (MWTP) for box scheme attributes using a choice experiment. Attributes include the bundle method, the delivery method, and price. To select an efficient model for statistical analysis, we evaluate the conditional logit model, heteroscedastic extreme value model(HEV model), multinomial probit model, and mixed logit model under different assumptions. The results of these four models show that the bundle method, the delivery method, and price are statistically significant in explaining the probability of participation in a box scheme. The results of likelihood ratio tests show that the heteroscedastic extreme value model is the most appropriate for our survey data. The results also indicate that MWTP for a change from fixed type to selection type is KRW 7,096.6. MWTP for a change from parcel service to direct delivery and cold-chain delivery are KRW 3,497.5 and KRW 7,532.7, respectively. The results of this study may contribute to the government's local food policies.

• KDI Journal of Economic Policy
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• v.27 no.1
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• pp.185-209
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• 2005

This study examines ERPT with asymmetric response and both import and export market shares, using wool trade data. The study found that, asymmetric response may be as common as symmetric response. In addition, the responses (both in price and quantity demanded) to the changes in exchange rate are considerably different across goods, and even for the homogenous goods, across countries. In case of depreciation, the export price changes more than appreciation case in general, and as a result the destination price changes less. It is also found that the cases of excessive or perverse pass-through are found more frequently than reported by previous studies. This finding points out that strategic behavior of firms or unexpected response to exchange rate fluctuation takes place more frequently than we commonly expect or take, in particular at disaggregated levels. When the model considers asymmetric responses of the export price to appreciation and depreciation (of exporter's currency), the estimation provided that for 39 trade cases out of 83, export price responded to appreciation and depreciation in different fashions, although the normal response was the dominating phenomenon with 99 cases or about 60% out of 166 cases. Market shares affected the extent and direction of responses in select cases. These findings will have important implications for policy makers and traders.