• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1540-1547
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• 2013

The energy economic analysis of the standard rural house model with PV system was performed based on annual energy demand calculation using the EnergyPlus to contribute in reducing building energy which occupies 25% of national energy consumption and in developing a low-energy & eco-friendly house model. Two types of PV system installation was considered to cover electricity demand for cooling, electric, and heating devices. For the selected house model, heating energy demand is 7 times higher than cooling energy demand. For the Case1, it is favorable to use electricity from PV system for cooling and electric devices and to sell surplus electricity. For the Case2, it is favorable to use electricity from PV system for cooling, electricity and heating devices and to sell surplus electricity. Considering the installation cost of PV system and heat pump air conditioning system, the break-even point of Case1 and Case2 are about 13 and 11 years respectively. Although the installation cost of Case2 is more expensive, Case2 provides three times more profit than Case1 after the break-even point. Because the expected average life time of the selected PV system is 25 years, Case2 is more favorable option for the given standard rural house model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.228-234
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• 2021

Real estate market participants need to have a sense of predicting real estate prices in decision-making. Commonly used methodologies, such as regression analysis, ARIMA, and VAR, have limitations in predicting the value of an asset, which fluctuates due to unknown variables. Therefore, to mitigate the limitations, an artificial neural was is used to predict the price trend of apartments in Seoul, the hottest real estate market in South Korea. For artificial neural network learning, the learning model is designed with 12 variables, which are divided into macro and micro factors. The study was conducted in three ways: (Ed note: What is the difference between case 1 and 2? Is case 1 micro factors?)CASE1 with macro factors, CASE2 with macro factors, and CASE3 with the combination of both factors. As a result, CASE1 and CASE2 show 87.5% predictive accuracy during the two-year experiment, and CASE3 shows 95.8%. This study defines various factors affecting apartment prices in macro and microscopic terms. The study also proposes an artificial network technique in predicting the price trend of apartments and analyzes its effectiveness. Therefore, it is expected that the recently developed learning technique can be applied to the real estate industry, enabling more efficient decision-making by market participants.

• Journal of the Korean association of regional geographers
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• v.22 no.3
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• pp.599-614
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• 2016

Urban centers have been recognized as problem regions so far. However, urban centers of metropolises take a new aspect in recent years as much as the negative influence of gentrification becomes a social issue. This paper analyzes the declining trend of urban centers in six metropolises - Seoul, Busan, Daegu, Incheon, Gwangju and Daejun from 1995 to 2010. As results of analysis, it is identified that the urban centers' shrinkage got moderated recently in the metropolises, even though their resurgence is not evident. Especially it is difficult to say longer that Jongro-Gu and Jung-Gu of Seoul are declining urban centers. Easing shrinkage is most outstanding in Jung-Gu, Daegu among local metropolises. Nevertheless, a serious obstacle such as high price of housing is in the process of obvious resurgence of urban center differently from the United States, Europe and Japan.

• Journal of Distribution Science
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• v.13 no.8
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• pp.61-71
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• 2015

Purpose - Before the year 2000, the housing prices in Korea were increasing every decade. After 2000, for the first time, Korea experienced a decrease in housing prices, and the repetitive cycle of price fluctuation started. Such a "boom and bust cycle" is a worldwide phenomenon. The current study proposes a mathematical model to explain price fluctuation cycles based on the theory of consumer psychology. Specifically, the model incorporates the effects of buyer expectations of future prices on actual price changes. Based on the model, this study investigates various independent variables affecting the amplitude of price fluctuations in housing markets. Research design, data, and methodology - The study provides theoretical analyses based on a mathematical model. The proposed model uses the following assumptions of the pricing mechanism in housing markets. First, the price of a house at a certain time is affected not only by its current price but also by its expected future price. Second, house investors or buyers cannot predict the exact future price but make a subjective prediction based on observed price changes up to the present. Third, the price is determined by demand changes made in previous time periods. The current study tries to explain the boom-bust cycle in housing markets with a mathematical model and several numerical examples. The model illustrates the effects of consumer price elasticity, consumer sensitivity to price changes, and the sensitivity of prices to demand changes on price fluctuation. Results - The analytical results imply that even without external effects, the boom-bust cycle can occur endogenously due to buyer psychological factors. The model supports the expectation of future price direction as the most important variable causing price fluctuation in housing market. Consumer tendency for making choices based on both the current and expected future price causes repetitive boom-bust cycles in housing markets. Such consumers who respond more sensitively to price changes are shown to make the market more volatile. Consumer price elasticity is shown to be irrelevant to price fluctuations. Conclusions - The mechanism of price fluctuation in the proposed model can be summarized as follows. If a certain external shock causes an initial price increase, consumers perceive it as an ongoing increasing price trend. If the demand increases due to the higher expected price, the price goes up further. However, too high a price cannot be sustained for long, thus the increasing price trend ceases at some point. Once the market loses the momentum of a price increase, the price starts to drop. A price decrease signals a further decrease in a future price, thus the demand decreases further. When the price is perceived as low enough, the direction of the price change is reversed again. Policy makers should be cognizant that the current increase in housing prices due to increased liquidity can pose a serious threat of a sudden price decrease in housing markets.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.4
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• pp.665-680
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• 2009

This study aims at analyzing the performance of Real Estate Investment Trusts(REITs) by Risk Adjustment Model. The main results are as follows. Firstly, most property types of REITs gain positive(+) excess overall returns at first and second period. On the contrary, most property types of REITs gain negative(-) excess overall returns and their standard deviations are larger at financial crisis period. Secondly, lodging, regional mall and commercial mortgage show lower risk-lower return, and freestanding, apartment and specialty show higher risk-higher return than average REITs, according to the CAPM results of . Moreover CAPM results of show the characteristics of REITs as investment commodities changes into higher risk-higher return for financial crisis period. Lastly, risk adjusted demanded returns of REITs are affected positively(+) by systemic risks and negatively(-) by unsystemic risks, according to the Risk Adjustment Model results of both and . Comparing risk adjusted demanded returns of REITs with their realized returns, healthcare reveals the largest outperformance.

• Land and Housing Review
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• v.3 no.1
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• pp.59-68
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• 2012

The current land development cost price system is classified as the creating land by construction price and composition changes that occur sporadically in the process of completion at the source of the factors by incurred cost price. Housing for land cost price system is a lack of objectivity which scheme of the such a gap due to the land in accordance construction and incurred cost price system so far. Therefore, in order to increase the objectivity of costing the costing of predictable surprises should be reflected in the process. Under such a background, this study defined the effective differential ratio as the predictable, estimated them for various characteristics of each business district to reflect. For this, set the properties category of five types to attributes and making the complex category and Look-up table. Which result of model validation is showed a high reliability. Therefore, Continuous accumulation of material in the future, when them to reflect the construction cost, will contribute to the bridge the gap the construction cost between incurred them.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.3
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• pp.263-285
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• 2011

Despite the process of neoliberalization has made a decisive influence on our society as a whole, there seems little interests in neoliberal urbanization and entrepreneurial urban projects promoting it. This study is to see relationships between neolibealization process and recent urbanization and urban policies in terms of entrepreneurial city mediating them. In particular, this paper tries to reconceptualize entrepreneurial city as corresponding to privatization and commodification, financialization, state redistribution, and management and manipulation of crises which Harvey(2005) suggests as four main features of neoliberalization process in general and 'accumulation by dispossession' in particular, and to characterize it in terms of 'creative destruction' and of 'entrepreneurial governance'. As examined in the later part of this paper, recent cases of these entrepreneurial urban projects in S. Korea include volatility of land and housing price in the Capital region and urban regeneration and newtown projects, project for free economic zones construction in Incheon and other 5 regions, project for SOC construction heavily relying on private investment, in particular project financing pursued nationwidely including Daegu, and project of urban cultural marketing to promote capital inflow tacitly as well as to enhance urban imagine explicitly.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.13-25
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• 2016

High-speed railway (Korea Train Express) has had a deep impact on the regional economy of Korea. Current high-speed rail research is mostly theoretical, there is a lack of quantitative research using a precise algorithm to study the effect of high-speed railway on the regional economy. This paper analyses the influence of high-speed rail on the regional economy, with a focus on the Daegu area. Quantitative analysis using department store indexes and regional medical records is performed to calculate the economic influence of high-speed rail. The result shows that high-speed railway effects the regional economy though regional consumption growth and medical care trends.