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dc.contributor.author서선덕-
dc.date.accessioned2018-06-20T05:51:17Z-
dc.date.available2018-06-20T05:51:17Z-
dc.date.issued2017-06-
dc.identifier.citationENGINEERING COMPUTATIONS, v. 34, No. 1, Page. 164-173en_US
dc.identifier.issn0264-4401-
dc.identifier.issn1758-7077-
dc.identifier.urihttps://www.emeraldinsight.com/doi/full/10.1108/EC-10-2015-0323-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/72176-
dc.description.abstractPurpose - The purpose of this study is to model risks in financial analysis. These risks associated with uncertainties in the projects should be properly addressed to ensure proper decision regarding the projects. Performance indicators should be developed and assessing risks has high priority. All these activities comprise appraisal, and based on these, a proper course of action should be recommended. Design/methodology/approach - To analyze the attractiveness of a project for foreign regional railroad investment or participation, the project should be analyzed in a systematic way. First, the project's goals and objectives should be evaluated for compatibility. Also, criteria of acceptability for stakeholders should be checked against output from the project. Usually, a project can have many alternatives, and impacts of each alternative should be analyzed in terms of quantitative and qualitative forecasts of impacts. Benefits and costs need to be counted in proper units of measurement per goals and objectives. Findings - This paper shows that risk modeling can reflect uncertainty in decision-making and provide robustness of modeling process and improved communication. Also, challenges are presented in using risk analysis. Originality/value - To overcome the shortcomings of traditional mathematical optimization model in identifying best sets of projects for private application, the proposed model finds ways to incorporate risk management components for the optimization procedure. Based on simulation results, a brute force solution procedure using enumeration can be used. Another approach is recommended to use the genetic algorithm process to reduce the number of alternatives to search to reach an optimal solution.en_US
dc.description.sponsorshipPreparation of this article was sponsored by a grant NRF-2014R1A1A2054793 and Transportation & Logistics Research Program ID-97344 of Korean Government.en_US
dc.language.isoen_USen_US
dc.publisherEMERALD GROUP PUBLISHING LTDen_US
dc.subjectRisk analysisen_US
dc.subjectFinancial analysisen_US
dc.subjectRegional railroad investmenten_US
dc.subjectRisk modelen_US
dc.titleRisk analysis model for regional railroad investmenten_US
dc.typeArticleen_US
dc.identifier.doi10.1108/EC-10-2015-0323-
dc.relation.page164-173-
dc.relation.journalENGINEERING COMPUTATIONS-
dc.contributor.googleauthorSuh, Sunduck-
dc.contributor.googleauthorSuh, Wonho-
dc.contributor.googleauthorKim, Jung In-
dc.relation.code2017010763-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF ENGINEERING SCIENCES[E]-
dc.sector.departmentDEPARTMENT OF TRANSPORTATION AND LOGISTICS ENGINEERING-
dc.identifier.pidsunduck-
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COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > TRANSPORTATION AND LOGISTICS ENGINEERING(교통·물류공학과) > Articles
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