• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.94-101
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• 2020

This study examined the effect of the sale price by excluding the PHC-pile cost from the construction costs for basic type (CCsBT) as an additional cost. The Ministry of Land, Infrastructure, and Transport excluded the PHC-pile cost in the CCsBT and new method so that only the designed pile quantity was recognized as an additional cost. The effect on the sale price was analyzed by comparing the pile cost of the existing and new methods. For this purpose, seven cases were selected, and the PHC-pile cost was estimated. The existing method was estimated as the ratio of the pile cost to CCsBT. The new method was estimated based on the bill of quantity. As a result, the CCsBT decreased by approximately 2-3% when the PHC-pile cost was calculated in the new method. Furthermore, as a result of comparing the sale price, excluding the PHC-pile cost with the sale price, the CCsBT decreased by approximately 1%. These results are expected to help improve the understanding of the CCsBT. Also, this paper contributes to promoting national housing stability through institutional improvement.

• Korean Journal of Construction Engineering and Management
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• v.6 no.6 s.28
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• pp.98-106
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• 2005

The construction cost index and the forecasting model of apartment house can be efficient for evaluating the validness of the fluctuating price, and for making guidelines for construction firms when calculating their profit. In this study the previous construction cost index of apartment house was improved, and the forecasting model based on X-12 ARIMA was developed. According to the result, during the last five years the construction cost, excluding labor expense, has risen approximately to 22.7%. And during next three years, additional 16.8% rise of construction cost is expected. Those quantitative results can be utilized for evaluating the apartment house's selling price in an indirection, and be helpful to understand the variation pattern of the price.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.13-22
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• 2016

Remodeling of multi-family house (MFH) has emerged as a major issue in the construction industry. Many decision-makers are struggling to determine whether to conduct a remodeling because of insufficient information including standard or method for projecting the price of their facilities after remodeling works. In this context, this research has conducted for analyzing how the price of the MFH is shifted by remodeling works. To achieve this research goal, (i) fourteen MFH remodeling cases were collected and (ii) price variation for the collected cases was analyzed in order to figure out how remodeling work affects the price of MFH cases. Finally, this research suggested the factors determining price of the MFH, wherein remodeling work has been conducted. From the results of this research, it is expected that the decision-makers can understand what is the crucial factors for determining the price of their MFH when they plans remodeling, and further this research can be a corner stone for developing a model for predicting the price of MFH if remodeling would be performed.

• Korean Journal of Construction Engineering and Management
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• v.25 no.4
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• pp.45-52
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• 2024

Estimating the sales price of a residential building development project is difficult because of it has many complex variables such as location, environment, and economic conditions. Many previous studies related to influence factors of the sales price is to identify by survey of experts and it is few studies by comparing with actual sales price. Accordingly, the purpose of this study is to identify the factors influenced on the projects by using correlation analysis from collected actual data in this study. For the purpose, first, the factors such as economy, location, housing, financial environmental factors were identified from previous studies. Second, data were collected on actual sale prices and selected factors. Finally, the actual sales price and factors were compared and analyzed by using correlation analysis. As a result, the R² values of economy, location, housing and financial environmental factors were over 0.5 respectively. Therefore, it was confirmed that these factors were significantly correlated with actual sales price. The results of this study are expected to be utilized as basic data for research and development of a new sale prices prediction model.

• Korean Journal of Construction Engineering and Management
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• v.16 no.1
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• pp.74-81
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• 2015

As one of urban infrastructure system, the electricity substation is critical for urban life and industrial activity as the electricity demands get higher than ever. However the substation is generally regarded as unpleasant or dangerous facility, which finally results in the continuous opposition movement by resident due to the belief of unidentified negative effect in apartment prices. Accordingly, as the scientifically objective and quantitative analysis is required to solve the social conflict, this study intends to examine the variation affected by urban infrastructure system, expecially for substation. After the independent variable defining the price of apartment and the dependent variable, which is apartment price, are identified and their spatial data has been filed, the forecasting model has been developed through the hedonic price function as well as artificial neural networks system. The research finding indicated that the spatial range affected by substation is not notable and the range of some case was applicable for less than 600m. It is expected that these research findings can be applied for establishing the one of solid cases for the analysis of economical effect to local housing market by the urban infrastructure system.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.89-97
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• 2017

The number of Aged Apartment units is expected to increase as time went on. Living standards are getting better and they want a new apartment space as the economy progresses. Therefore, it is necessary to prepare for the increasing remodeling market through the feasibility evaluation method that can be applied to the remodeling project of the apartment house. The purpose of this study is to analyze the social pricing factors affecting the Officially assessed individual House Price for the analysis model of commercial house remodeling. The collected samples were analyzed using multiple regression analysis of 350 prices included in 127 lots. Middle school level, high school level, total number of households, and floor area ratio were extracted. As a result of comparing the Officially assessed individual House Price by applying to the remodeling case, the difference between the existing Officially assessed individual House Price and the improvement Officially assessed individual House Price is different. The accessibility with the subway station is included in the land price, and there is no change in the number of stories and directions because it is customized remodeling. There was a difference in the disclosure price depending on the type of factor extraction by the evaluator in a batch application of the disclosure price factors. The research can be used as a model for future remodeling business feasibility analysis.

• Korean Journal of Construction Engineering and Management
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• v.23 no.5
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• pp.108-116
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• 2022

Started in 1989 as Public Permanent Rental Housing scheme, public rental housing lease policy is increasing target residents and supply in each government by introducing new supply types. However, public housing business entities have difficulties in expanding the supply due to cumulated deficit. The research suggested long-term public rental housing reconstruction business as a method to preserve the cumulated deficit from the previous. Minimum floor area ratio mathematical model was suggested by defining the floor area ratio of reconstruction business as minimum, since housing sales profit after reconstruction could preserve aggregated deficit, and mathematically approached by considering the traits of long-term public rental housing reconstruction. The determinant for minimum floor area ratio mathematical model comprise cumulated deficit of the existing long-term public rental housing, land size of reconstructed sale housing, housing sales price per unit area, and business cost per unit area. Minimum floor area ratio mathematical model is expected to be the milestone for supporting decision making regarding the economic part of old long-term public lease housings' reconstruction scale, and expanding housing supply within urban area.

• Management & Information Systems Review
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• v.37 no.3
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• pp.27-47
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• 2018

In this study, we examine how land use zoning affects the land price controlling other variables such as road-facing condition of the land, land form, land age after its development and land size. We employ geographically weighted regression analysis which reflects spatial dependency as methodology with a data sample of land transaction price data of Jangyu, a new town, in Korea. The results of our empirical analysis show that the respective coefficients of traditional regression and geographically weighted regression are not significantly different. However, after calculating Moran's Index with residuals of both OLS and GWR models, we find that Moran's Index of GWR decreases around 26% compared to that of OLS model, thus improving the problem of spatial autoregression of residuals considerably. Unlike our expectation, though, in both traditional regression and geographically weighted regression where residential exclusive area is used as a reference variable, the dummy variable of the residential land for both housing and shops shows a negative sign. This may be because the residential land for both housing and shops is usually located in the level area while the residential exclusive area is located at the foot of a mountain or on a gentle hill where the residents can have good quality air and scenery. Although the utility of the residential land for both housing and shops is higher than its counterpart's since it has higher floor area ratio, amenity which can be explained as high quality of air and scenery in this study seems to have higher impact in purchase of land for housing. On the other hand, land for neighbourhood living facility seems to be valued higher than any other land zonings used in this research since it has much higher floor area ratio than the two land zonings above and can have a building with up to 5 stories constructed on it. With regard to road-facing condition, land buyers seem to prefer land which faces a medium-width road as expected. Land facing a wide-width road may have some disadvantage in that it can be exposed to noise and exhaust gas from cars and that entrance may not be easy due to the high speed traffic of the road. In contrast, land facing a narrow road can be free of noise or fume from cars and have privacy protected while it has some inconvenience in that entrance may be blocked by cars parked in both sides of the narrow road. Finally, land age variable shows a negative sign, which means that the price of land declines over time. This may be because decline of the land price of Jangyu was bigger than that of other regions in Gimhae where Jangyu, a new town, also belong, during the global financial crisis of 2008.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.57-65
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• 2019

If aging apartments are left unimproved through remodeling, the city will be eventually slum. As the government recognizes remodeling as an alternative to reconstruction, the law has been revised mainly to increase the housing area, increase the number of house and allow the vertical extension for making remodeling costs. However, the remodeling is still not activated yet in the market. Therefore, this study analyzes the decision factors of apartment remodeling in Seoul metropolitan area based on Heckman two-stage analysis considering sampling error. Research findings indicate that the decision for remodeling is determined by the characteristics of the household, housing, and time-lapse variables. And also the number of household members, net assets, housing satisfaction, the 11-20, 21-30, and more than 30 years of building are identified as the significant variables as a result of remodeling choice probability analysis. It is noteworthy that the significant variables from then remodeling cost analysis are net assets, area, more than 30 years of building, and unit housing price. It is also notable that the policy, which extend the housing area to cover remodeling cost, are not actually effective to activate the remodeling, and the age in the case of elderly people in Seoul and Gyeonggi-do who are expected to have high net assets and income is not significant variables. This study is expected to provide more objective and reliable implication to the policy makers, the home owner and the investors on the decision making process related to the remodeling project.

• 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.