• Journal of Climate Change Research
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• v.5 no.2
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• pp.95-107
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• 2014

The 'Green Start Movement' is a practical movement of green living to efficiently reduce the greenhouse gases originating from non-industrial fields such as household, commerce, transportation, etc. for the 'materialization of a low carbon society through green growth (Low Carbon, Green Korea)'. When the new government took office, following the Lee Myeongbak Administration that had presented 'Low Carbon, Green Growth' as a national vision, it was required to set up the direction of the practical movement of green life to respond to climate change persistently and stably as well as to evaluate the performance of the green start movement over the past 5 years. A questionnaire survey was administered to a total of 265 persons including public servants, members of environmental and non-environmental NGOs, participants of the green start movement and professionals. In the results of the questionnaire survey, many opinions have indicated that the awareness of the green start movement is increasing and the green start movement has had a positive impact on individual behavior and group behavior in terms of green living. The result shows, however, that the environmental NGOs don't cooperate sufficiently to create a 'green living' effect on a national scale. Action needs to be taken on the community level in order to generate a culture of environmental responsibility. The national administration office of the Green Start Movement Network should play the leading role between the government and environmental NGOs. The Green Start National Network should have greater autonomy and governance of the network needs to be restructured in order to work effectively. Also the Green Start Movement should identify specific local characteristics to support activities that reduce greenhouse gas emissions. Best practices can be shared to reduce greenhouse gas emissions by a substantial amount.

• Korean Journal of Construction Engineering and Management
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• v.22 no.4
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• pp.59-65
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• 2021

Since the 2016 "Housing Act Partial Amendment" and the "2018 Housing Comprehensive Amendment Plan", interest in the pre sale system and post sale system of apartment houses has been on the rise. In order to compare the advantages and disadvantages of the pre sale system and the post sale system of apartment houses, and to establish the basis for the institutional policy of the post sale system, a questionnaire survey method was used for tenants of the apartment house from the public side, and issues of time and cost. The time series analysis method is intended to suggest an appropriate time for payment of contributions. Accordingly, through a review of existing theories and literature, the post sale system of public and private institutions was organized, and through a questionnaire survey, the path to securing pre sale money, product information of the model house, and the degree of awareness of the effect of the post sale system were investigated. For the post sale fund support and payment method, it is necessary to increase the commercial line for existing financiers from the user's point of view, and it is necessary to operate in consideration of the economic power of the pre sale market by region. Both 60% post sale and 80% post sale have a price range of up to KRW 10 million, and the total interest rate is 5.0%, and the annual interest rate is about 2.8% for 60% post sale, and about 2.1% for 80% post sale, which is lower than the current 3.1%. I need an interest rate. The research is a perception survey targeting a total of 5,213 households in a sample of after sale apartments in public institutions. As the actual values are analyzed using a time series on the effects of market supply and demand and market prices, there is a limit to applying them to prospective residents of private apartments. In addition, to respond to first time tenants, a questionnaire survey was conducted on five complexes that have moved in within the last five years.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.95-118
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• 2017

Recent centrally the downtown area, the transaction between the row housing and multiplex housing is activated and platform services such as Zigbang and Dabang are growing. The row housing and multiplex housing is a blind spot for real estate information. Because there is a social problem, due to the change in market size and information asymmetry due to changes in demand. Also, the 5 or 25 districts used by the Seoul Metropolitan Government or the Korean Appraisal Board(hereafter, KAB) were established within the administrative boundaries and used in existing real estate studies. This is not a district classification for real estate researches because it is zoned urban planning. Based on the existing study, this study found that the city needs to reset the Seoul Metropolitan Government's spatial structure in estimating future housing prices. So, This study attempted to classify the area without spatial heterogeneity by the reflected the property price characteristics of row housing and Multiplex housing. In other words, There has been a problem that an inefficient side has arisen due to the simple division by the existing administrative district. Therefore, this study aims to cluster Seoul as a new area for more efficient real estate analysis. This study was applied to the hedonic model based on the real transactions price data of row housing and multiplex housing. And the K-Means Clustering algorithm was used to cluster the spatial structure of Seoul. In this study, data onto real transactions price of the Seoul Row housing and Multiplex Housing from January 2014 to December 2016, and the official land value of 2016 was used and it provided by Ministry of Land, Infrastructure and Transport(hereafter, MOLIT). Data preprocessing was followed by the following processing procedures: Removal of underground transaction, Price standardization per area, Removal of Real transaction case(above 5 and below -5). In this study, we analyzed data from 132,707 cases to 126,759 data through data preprocessing. The data analysis tool used the R program. After data preprocessing, data model was constructed. Priority, the K-means Clustering was performed. In addition, a regression analysis was conducted using Hedonic model and it was conducted a cosine similarity analysis. Based on the constructed data model, we clustered on the basis of the longitude and latitude of Seoul and conducted comparative analysis of existing area. The results of this study indicated that the goodness of fit of the model was above 75 % and the variables used for the Hedonic model were significant. In other words, 5 or 25 districts that is the area of the existing administrative area are divided into 16 districts. So, this study derived a clustering method of row housing and multiplex housing in Seoul using K-Means Clustering algorithm and hedonic model by the reflected the property price characteristics. Moreover, they presented academic and practical implications and presented the limitations of this study and the direction of future research. Academic implication has clustered by reflecting the property price characteristics in order to improve the problems of the areas used in the Seoul Metropolitan Government, KAB, and Existing Real Estate Research. Another academic implications are that apartments were the main study of existing real estate research, and has proposed a method of classifying area in Seoul using public information(i.e., real-data of MOLIT) of government 3.0. Practical implication is that it can be used as a basic data for real estate related research on row housing and multiplex housing. Another practical implications are that is expected the activation of row housing and multiplex housing research and, that is expected to increase the accuracy of the model of the actual transaction. The future research direction of this study involves conducting various analyses to overcome the limitations of the threshold and indicates the need for deeper research.