• Title/Summary/Keyword: The building total floor area

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University Green Campus Policy & Evaluation Criteria -Focus on Comparison of Korea, US AASHE, UNEP & ISCN-GULF- (대학 그린캠퍼스 정책과 평가기준에 관한 연구 -한국, 미국 AASHE, UNEP & ISCN-GULF 간 비교를 중심으로-)

  • Oh, Joon-Gul;Yeom, Dae-Bong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.5
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    • pp.577-586
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    • 2018
  • In Korea, sustainability is mandatory in every field. University campuses are educational facilities that consume considerable amounts of energy. Therefore, many universities have tried to take advantage of the last opportunity to prepare students with sustainability and leadership. This study compared the green campus policy and evaluation criteria among Korea, US AASHE, UNEP, and ISCN-GULF to vitalize the green campus movement and suggest recent research data for the Korea green campus accreditation. The results are as follows: 1. new evaluation criteria need to be added to the certified green building total floor area ratio instead of adapting the G-SEED system in the Campus Resource & Environments category; 2. Korean Green Campus Evaluations need to be improved when expressing the campus individuality by choosing an increased number of credits and criteria; and 3. new evaluation criteria are required to secure the result, feedback, and products from curriculum updates in the Campus Education category.

Determinants of Apartment Prices in Busan: A Spatial Quantile Regression (공간적 분위수 회귀분석에 의한 부산 아파트 가격 결정요인 분석)

  • Yoon, Jong-Won;Park, Sae-Woon;Jeong, Tae-Yun
    • Management & Information Systems Review
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    • v.37 no.1
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    • pp.155-175
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    • 2018
  • Lots of previous researches on determinants of apartment prices in Korea consider spatial dependence while few studies regard endogeneity of spatial lag by adding a spatial lag to an OLS regression. Thus, this study intends to include this spatial lag in its analysis of determinants of apartment price in Busan by using a two-stage quantile regression. The empirical results are : the coefficient of spatial lag variable is more than 0.5 and is statistically significant at 1% level. From this result we can confirm that the effect of the price of nearby apartment on that of another apartment is very big. We also find that apartment buyers prefer larger size, height in both the total floors and living floor, south-facing living room with a ocean view, and proximity to metros, high school and coast. Unlike our expectation, however, mountain view is less favored than building view, which we can guess is because apartments with mountain views are mostly located in the low-priced apartment area where some of their living rooms face north. Quantile regression also explains the effect of hedonic characteristics on apartment price better than OLS estimation. For instance, the effect of south facing living room variable on the price is twice larger in high-price apartments than in low-price counterparts. And the effect of vicinity to the coast or the ocean is ten times bigger in high priced apartments.