• Title/Summary/Keyword: 준로그모형

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A Study on the Factors Determining Officetel Price in Busan (부산지역 오피스텔 가격 결정요인 분석)

  • Choi, Yeol;Kim, Hyeong Jun;Yeo, Jung Hoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.35 no.3
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    • pp.725-735
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    • 2015
  • The aim of this study is to specifically understand the officetel market by empirical analysis for the determining factors that affect determining the price of the officetel in Busan. In my opinion, it can help officetel providers to select the appropriate size and location that analysis for the factors determining officetel price with market price, and also it can help customers officetel to choice depending on the purpose. So I was conducting this study. In this study, I analyzes the factors determining the price of Officetel using a OLS linear regression, semi-log model, and a robust regression-Busan area Officetel Real Transaction Price as the dependent variable and factors representing the physical characteristics, locational characteristics and regional characteristics as independent variables.

A Study on the Factors Affecting the Arson (방화 발생에 영향을 미치는 요인에 관한 연구)

  • Kim, Young-Chul;Bak, Woo-Sung;Lee, Su-Kyung
    • Fire Science and Engineering
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    • v.28 no.2
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    • pp.69-75
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    • 2014
  • This study derives the factors which affect the occurrence of arson from statistical data (population, economic, and social factors) by multiple regression analysis. Multiple regression analysis applies to 4 forms of functions, linear functions, semi-log functions, inverse log functions, and dual log functions. Also analysis respectively functions by using the stepwise progress which considered selection and deletion of the independent variable factors by each steps. In order to solve a problem of multiple regression analysis, autocorrelation and multicollinearity, Variance Inflation Factor (VIF) and the Durbin-Watson coefficient were considered. Through the analysis, the optimal model was determined by adjusted Rsquared which means statistical significance used determination, Adjusted R-squared of linear function is scored 0.935 (93.5%), the highest of the 4 forms of function, and so linear function is the optimal model in this study. Then interpretation to the optimal model is conducted. As a result of the analysis, the factors affecting the arson were resulted in lines, the incidence of crime (0.829), the general divorce rate (0.151), the financial autonomy rate (0.149), and the consumer price index (0.099).

Analyses on Related Factors with Fire Damage in Korea (한국에서의 화재 피해 관련요인 분석)

  • Chang, Eunmi;Kang, Byungki;Park, Kyeong
    • Journal of the Korean Geographical Society
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    • v.50 no.3
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    • pp.355-373
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    • 2015
  • In this study the factors of fire damage are analyzed through previous research reviews. Local environmental factors as well as those factors attributed to fire damage (number of fire events, number of injured, number of death, economic loss) were selected to compose mutual relationship model. In order to verify this relationship model, official statistics concerning fire damage were collected from 228 local governments and compared with results from previous research. As a result of this comparison four dependent variables and 22 independent variables that affect fire damage were analyzed. Independent variables are divided into human vulnerability factors, physical vulnerability factors, economic vulnerability factors, mitigating factors and local characteristics. To analyze a relationship between selected dependent variables and independent variables, we applied a semi-logarithm model and performed regression analysis. Among the 22 independent variables, the number of the weak to disaster, social welfare service workers, workers in manufacturing industry, and the number of workers in restaurants and bars per 10,000 people show the significant correlation with the number of fire incidence. The number of death from fire is significantly related to two variables which are the number of social welfare service workers per 10,000 and the ratio of commercial area. Damage cost is significantly dependent on the property taxes per 10,000 people. These factors were included in the research model as vulnerability factors (human, physical, economic) and mitigating factors and local characteristics, and the validity of research model was verified. The result could contribute to fire-fighting resource allocation in Korea or they can be utilized in establishing fire prevention policy, which will enhance the national level of fire safety.

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Estimation of the Value of Road Traffic Noise within Apartment Housing Prices (아파트가격에 내재된 도로교통소음가치 추정)

  • 임영태;손의영
    • Journal of Korean Society of Transportation
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    • v.19 no.4
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    • pp.19-33
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    • 2001
  • In the developed countries, traffic noise is one of most serious problems faced by people's lives. So the importance of the traffic noise is quite well recognized by the infrastructure planners as well as the people. The traffic noise is valued in monetary terms in some countries and it is reflected in estimating the net present value or benefit/cost ratio. On the contrary, the effects of traffic noise are not reflected in the assessment of infrastructure in most cases in Korea. However, as the income level has been increasing, more people have been becoming to put more importance on their living conditions. The purpose of this paper is to estimate the value of traffic noise in the Seoul metropolitan area. The housing price were surveyed to use the quasi-hedonic price technique. By this way, two housing prices at the same floor level in different 128 complexes in the Seoul metropolitan area were surveyed. the actual traffic noise level was also measured. The differences of housing prices and noise levels were analyzed using the various types of regression models. The value is quite different by size of house. The value of large house is higher than that of small house. Since the income level of people in large house is higher than that in small house. it might be said that value of traffic noise for high income people is higher than that for low income people. Moreover, the increase of 1dB(A) noise affects the house price by about 0.3% in Seoul metropolitan area.

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