• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.133-143
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• 2021

In government procurement programs, cost estimation and analysis support funding decisions and are the basis for other major decisions, too. Such estimating and analyzing the cost of the weapon systems are crucial in execution of the defense budget. However, existing cost estimations and analyses have focused on domestic R&D projects, thus those are not valid in application to foreign weapon acquisitions. This study aims at foreign weapon systems that are acquired from Direct Commercial Sales. Because the data for price estimation of a foreign weapon is usually not available, we suggest a price estimation model based on performance factors of the weapon. In this study, the proper price of the weapon system is estimated using the parametric cost estimating model. Using the data of helicopter-launched anti-tank guided missiles worldwide, we analyze the effect of each performance factor on the weapon system price by regression analysis, and use step-wise and ridge regression analysis to remove multi-collinearity. This study hopefully contributes to more reasonable decision making on proper price of weapons.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.274-283
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• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.955-962
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• 2002

Commercial internet auction systems have been successfully used recently. In those systems, because reserve prices of auction items are given by sellers only, the success bid rate can be decreased due to the large difference between the reserve price and the normal price. In this paper, we propose an agent that generates reserve prices to sellers based on past auction data and item prices gathered from the web. Through performance experiments, we show that the successful bid rate increases by preventing sellers from making unreasonable reserve prices. Using the pricing agent, we design and implement an XML-based auction system on the web.

• The Journal of Industrial Distribution & Business
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• v.7 no.3
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• pp.27-36
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• 2016

Purpose - Considering the importance of housing needs to real estate market, domestic studies on real estate prices from the perspective of demand are basically based on macro-data, but relatively few are associated with micro-data of urban real estate demand. We try to find a reliable relation of elasticity of demand and commercial housing market. Research design, data, and methodology - In this paper, we have derived housing demand theoretic method and have utilized micro-data of residential family housing survey of downtown area in Kunming City in October, 2015 to estimate income elasticity and price elasticity of housing demand respectively and make a comparative analysis. Results - The results indicate that income elasticity and price elasticity of families with owner-occupied housing are both larger than those of families with rental housing. Income elasticity of housing demand of urban residential families in Kunming is far below the foreign average and eastern coastal cities level, however, the corresponding price elasticity is far higher. Conclusions - We suggest that housing affordability of urban families in western China are constrained by the level of economic development, and the current housing price level has exceeded the economic affordability and psychological expectation of ordinary residents. Furthermore, noticing the great rigidity of housing demand, the expansion space of housing market for improvement and for commodity is limited.

• Proceedings of the KIEE Conference
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• 2005.11b
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• pp.168-170
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• 2005

At present Cournot model is one of the most commonly used theories to analyze the gaming situation in oligopoly market. But there exist several problems to apply this model to electricity market. The representative one is to obtain the inverse demand curve able to be induced from the relationship between market price and demand response. In Cournot model, each player offers their generation quantity to accomplish maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears on the long-term basis through the statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium

• The Journal of Information Systems
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• v.14 no.2
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• pp.55-74
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• 2005

In order to purchase a product cheaper, a lot of customers have been trying to search one or more marketplaces. Ever since the commercial use of the Internet, several types of marketplaces have been operating successfully on the Internet. Some of them are online shopping malls, auction markets, and group-buying markets. They have the price settlement mechanisms of their own. Online shopping malls where many stores are located support a customer to purchase the product that matches his/her requests such as price, function, design, and so forth. In online auction market, a customer can buy the product by making bids sequentially and competitively until a final price is reached. In online group-buying market, a customer can purchase the product by aggregating the orders from several buyers so that cheaper prices can be negotiated. The cheaper customers could purchase the same product item, the more satisfied they would be. However, it is very difficult for the customer to determine the marketplace to purchase, considering different kinds of marketplaces at the same time. Even though the purchasing price is cheapest in one marketplace, it is very difficult for customers to convince it the cheapest for all marketplaces. Therefore, rules and methods have been developed for purchase decision making in multiple marketplaces to reach the optimal purchase decision as a whole. They can maximize customer's utility and resolve the conflicts with other marketplaces through multi-agent negotiation.

• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.2
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• pp.67-78
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• 2021

This study aims to analyze how students' design work functions affect consumer attitudes and purchase intentions toward clothes designed by students, while exploring the moderating effect of price sensitivity in such a relationship. Data was acquired from 351 responses of an online questionnaire (www.sojump.com). A two-step approach was employed to analyze our hypotheses using structural equation modeling (SEM) in SPSS 22.0 and AMOS 22.0 statistical packages. First, significant empirical evidence was secured regarding the effects of design functions (assurance, fashion, camouflage, individuality, and comfort) on consumer attitudes toward clothes, which can lead to purchasing intention. Fashion, individuality, and comfort functions can enhance consumer attitude significantly, but assurance and camouflage have no significant influence. Among the functions, comfort has the greatest effect on consumer attitudes, indicating that when students market works as commodities, comfort should be highlighted in their designs. In this way, such products can draw the interest of many consumers. Second, empirical evidence showed that price sensitivity negatively moderates the association between attitude and purchase intention. Thus, design courses should be careful when setting student works' prices given consumer sensitivity. The optimization of the student works' cost structure can help minimize price sensitivity. Overall, the findings and their implications can serve as a basis for the commercial application of design curriculum works and provide feasible support for developing student design curriculum in the future.

• Journal of Energy Engineering
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• v.24 no.2
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• pp.9-16
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• 2015

As electricity is an indispensable input to human's existence and industrial production, economic benefits arise from consumption. The economic benefits of the electricity consumption are useful information in various fields of electricity-related policy. Therefore, this study attempts to value the economic benefits from electricity use. The economic benefit of electricity consumed is the area under the demand curve which made of the sum of the actual consumer expenditure and the consumer surplus. Consumer expenditure can be easily observed but the information on price elasticity of demand is necessarily required to compute consumer surplus. This study derives the estimates for price elasticities through literature review. The price elasticities of the electricity demand for residence, industry, and commercial are estimated to be -0.332, -0.351, and -0.263, respectively. Because the consumer surplus of the electricity consumption for residence, industry, and commercial are computed to be 191.54, 143.44, and 231.91 won per kWh, respectively. Given that average prices of electricity use were 127.02, 100.70, and 121.98 won per kWh for the year 2013, the economic benefit are calculated to be 318.56, 244.14, and 353.89 won per kWh, respectively. We can convert the values to 321.96, 246.75, and 357.67 won per kWh in 2014 constant price, respectively, using consumer price index. They can be used in the economic feasibility analysis of a new electricity supply project.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1627-1636
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• 2014

In real-time electricity price environment, the energy management system can provide the significant advantage to the residential, commercial and industrial customers since it can reduce the electricity charge by controlling the load operation effectively in response to time-varying price. However, the earlier studies for load management mainly focus on the residential and commercial customers except for the industrial customers because most of load operations in industrial sector are intimately related with production schedule. So, it is possible that the inappropriate control of loads in industrial sector causes huge economic loss. In this paper, therefore, we propose load control algorithm for factory energy management system(F-EMS) to achieve not only minimizing the electricity charges but also maintaining production efficiency by considering characteristics of load operation and production schedule. Considering characteristics of load operation and production schedule, the proposed load control algorithm can reflect the various characteristics of specific industrial customer and control their loads within the range that the production efficiency is maintained. Simulation results show that the proposed load control algorithm for F-EMS leads to significant reduction in the electricity charges and peak power in industrial sector.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.8_spc
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• pp.1233-1243
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• 2019

Asia hosts more than half of the world's 1 billion goats and is also where domestication of wild goats began. Goats, including dairy goats, are adapted to a wide variety of harsh environments and thus play key roles as providers of nutrition, food security and socio-economic status to their human owners in many low-income Asian countries. In many countries in Southeast and East Asia, medium and large scale commercial dairy goat farming can be profitable enterprises because of the high price of goat milk, and good demand due to its health and medicinal properties. In some Asian countries, dairy goats play important roles in non-commercial activities, including use as educational animals in elementary schools in Japan and show animals in Indonesia. Dairy goat farmers in Asia are faced with numerous challenges, such as a shortage of high producing animals adapted to the local environment, lack of quality feeds during a prolonged dry season, many diseases and difficulty getting their product to market, however, the increasing demand for goat milk in the newly developed and developed economies in Asia provides an optimistic future for dairy goat production in this region.