• Title/Summary/Keyword: 가산자료모형

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Demand Estimation for Art Museum using Travel Cost Method : A Case of National Museum of Modern and Contemporary Art (여행비용접근법을 적용한 미술관 방문수요함수 추정 : 국립현대미술관을 사례로)

  • Eom, Young-Sook;Kim, Jin-Ok;Park, In-Sun
    • Review of Culture and Economy
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    • v.19 no.2
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    • pp.29-50
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    • 2016
  • This paper is to apply an individual travel cost method(TCM) to estimate demand functions for cultural services enjoyed by visiting 3 branches of the National Museum of Modern and Contemporary Art located in the Seoul Metropolitan area. This paper extends the standard TCM by incorporating opportunity costs of leisure time and two different data generating process - 398 respondents from an on-site survey and 600 respondents from a general household survey. Negative binomial models reflecting the non-negative integer nature of visiting frequency with over-dispersed variance were best fitted for demand functions, in which residents of Seoul metropolitan area surveyed from on the site exhibited higher visitation demand for the national art museum. Price elasticity and income elasticity differed by respondents' residency. Price elasticity of long distance visitors (-0.21) was more inelastic from those of Seoul residents (-0.34 ~ -0.5). Moreover, regional residents outside of Seoul area seemed to consider that services from the national art museum is a normal good with income elasticity of 0.5, whereas the Seoul residents seemed to perceive it to be an inferior good with income elasticity of -0.05.

Urban Runoff According to Rainfall Observation Locations (강우 측정 지점에 따른 도시 유역 유출량 변화 분석)

  • Hyun, Jung Hoon;Chung, Gunhui
    • Journal of Wetlands Research
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    • v.21 no.4
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    • pp.305-311
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    • 2019
  • Recently, global climate change causes abnormal weather and disaster countermeasures do not provide sufficient defense and mitigation because they were established according to the historical climate condition. Repeated torrential rains, in particular, are causing damage even in the robust urban flood defense system. Therefore, in this study, the change of runoff considering the spatial distribution of rainfall and urban characteristics was analyzed. For rainfall concentrated in small catchment, rainfall in the watershed must be accurately measured. This study is based on the rainfall data observed with Automated Surface Observing System (ASOS) and Automatic Weather Stations (AWS) provided by the Seoul Meteorological Administration. Effluent from the pumping station was estimated using the EPA-SWMM model and compared and analyzed. Catchments with rainwater pumping station are small with large portion of impermeable areas. Thus, when the ASOS data where is located from from the chatchment, runoff is often calculated using rainfall data that is different from rainfall in the catchment. In this study, the difference between rainfall data observed in the AWS near the catchment and ASOS away from the catchment was calculated. It was found that accurate rainfall should be used to operate rainwater pumping stations or forecast urban flooding floods. In addition, the results of this study may be helpful for estimating design rainfall and runoff calculation.

High-Risk Area for Human Infection with Avian Influenza Based on Novel Risk Assessment Matrix (위험 매트릭스(Risk Matrix)를 활용한 조류인플루엔자 인체감염증 위험지역 평가)

  • Sung-dae Park;Dae-sung Yoo
    • Korean Journal of Poultry Science
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    • v.50 no.1
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    • pp.41-50
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    • 2023
  • Over the last decade, avian influenza (AI) has been considered an emerging disease that would become the next pandemic, particularly in countries like South Korea, with continuous animal outbreaks. In this situation, risk assessment is highly needed to prevent and prepare for human infection with AI. Thus, we developed the risk assessment matrix for a high-risk area of human infection with AI in South Korea based on the notion that risk is the multiplication of hazards with vulnerability. This matrix consisted of highly pathogenic avian influenza (HPAI) in poultry farms and the number of poultry-associated production facilities assumed as hazards of avian influenza and vulnerability, respectively. The average number of HPAI in poultry farms at the 229-municipal level as the hazard axis of the matrix was predicted using a negative binomial regression with nationwide outbreaks data from 2003 to 2018. The two components of the matrix were classified into five groups using the K-means clustering algorithm and multiplied, consequently producing the area-specific risk level of human infection. As a result, Naju-si, Jeongeup-si, and Namwon-si were categorized as high-risk areas for human infection with AI. These findings would contribute to designing the policies for human infection to minimize socio-economic damages.