• Title/Summary/Keyword: 리스크 위계

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Evaluating and Suggesting Key Risk Factors according to Risk Hierarchy of Occurrence Field in the Overseas Development Projects (발생영역별 리스크 위계에 따른 투자개발형 해외건설사업의 핵심 리스크 인자 도출 및 평가)

  • Lee, Jeong-Seok;Ahn, Byung-Ju;Kim, Jae-Jun
    • Korean Journal of Construction Engineering and Management
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    • v.13 no.2
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    • pp.70-79
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    • 2012
  • The Korean Government recently has been focused on strengthening competitiveness of order and stimulating construction market in the international construction industry. It has planned to extend the ODPs (overseas development projects) in order to diversifying the international construction market of which is domestic construction companies, placing too much emphasis on plant projects of the Middle East. However, literature review of risk analysis in the ODPs shows that the number of case study is several. Therefore, Authors asserted the necessity of risk analysis in the ODPs. The purpose of this study is to suggest a methodology that find KRFs (key risk factors) in the ODPs and analyze them, using AHP and Fuzzy theory. As a result, the 37 KRFs are selected and explained characteristics of them. A future direction of this study is to suggest a risk management model in the ODPs and prove feasibility of it.

Classification of Public Perceptions toward Smog Risks on Twitter Using Topic Modeling (Topic Modeling을 이용한 Twitter상에서 스모그 리스크에 관한 대중 인식 분류 연구)

  • Kim, Yun-Ki
    • Journal of Cadastre & Land InformatiX
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    • v.47 no.1
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    • pp.53-79
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    • 2017
  • The main purpose of this study was to detect and classify public perceptions toward smog disasters on Twitter using topic modeling. To help achieve these objectives and to identify gaps in the literature, this research carried out a literature review on public opinions toward smog disasters and topic modeling. The literature review indicated that there are huge gaps in the related literature. In this research, this author formed five research questions to fill the gaps in the literature. And then this study performed research steps such as data extraction, word cloud analysis on the cleaned data, building the network of terms, correlation analysis, hierarchical cluster analysis, topic modeling with the LDA, and stream graphs to answer those research questions. The results of this research revealed that there exist huge differences in the most frequent terms, the shapes of terms network, types of correlation, and smog-related topics changing patterns between New York and London. Therefore, this author could find positive answers to the four of the five research questions and a partially positive answer to Research question 4. Finally, on the basis of the results, this author suggested policy implications and recommendations for future study.