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ÀúÀÚ¸í ¾È¼ºÁø½Äº°ÀúÀÚ ; ±èÅÂÈñ ; ³²°æ¿ë½Äº°ÀúÀÚ ; ±èÁö¸í
¹ßÇà»ç Çѱ¹°ÇÃà½Ã°øÇÐȸ
¼ö·Ï»çÇ× Çѱ¹°ÇÃà½Ã°øÇÐȸ ³í¹®Áý, Vol.19 No.1 (2019-02)
ÆäÀÌÁö ½ÃÀÛÆäÀÌÁö(77) ÃÑÆäÀÌÁö(10)
ISSN 15982033
ÁÖÁ¦ºÐ·ù ½Ã°ø(Àû»ê)
ÁÖÁ¦¾î Ç÷£Æ® °Ç¼³ ; ¸®½ºÅ© Æò°¡ ; ȸ±ÍºÐ¼® ; ¼Õ½Ç ºñÀ² ; ¸®½ºÅ© ¸ðµ¨¸µ ; plant construction ; risk assessment ; regression analysis ; loss ratio ; risk modelling
¿ä¾à1 Ç÷£Æ® °Ç¼³ ÇÁ·ÎÁ§Æ®¿¡ ´ëÇÑ ¼ö¿ä°¡ Áõ°¡ÇÏ°í º¹ÀâÇØÁü¿¡ µû¶ó ¿¹±âÄ¡ ¸øÇÑ À§Çè ¿ä¼Ò°¡ Áõ°¡ÇÏ°í ÀÖ´Ù. ÀÌ¿¡ Ç÷£Æ® °Ç¼³ ÇÁ·ÎÁ§Æ®¿¡ ´ëÇÑ ÁßÁ¡ ¸®½ºÅ© ¿äÀÎÀ» ¹ÙÅÁÀ¸·Î Á¤·®Àû ¸®½ºÅ© ºÐ¼® ¹× Æò°¡ ¸ðµ¨ °³¹ßÀÌ ¿ä±¸µÇ°í ÀÖ´Ù. º» ¿¬±¸´Â º¸Çè ȸ»ç¿¡¼­ ¼öÁý ÇÑ º¸Çè±Ý Áö±Þ µ¥ÀÌÅ͸¦ »ç¿ëÇÏ¿© Ç÷£Æ® °Ç¼³ ÇÁ·ÎÁ§Æ®ÀÇ ½ÇÁ¦ ÀçÁ¤Àû ¼Õ½ÇÀ» À§Çè Æò°¡ ¸ðµ¨ÀÇ Á¾¼Ó º¯¼ö·Î ¹Ý¿µÇÏ¿´À¸¸ç ¹®Çå °ËÅä ¹× µ¥ÀÌÅÍ ºÐ¼®À» ¹ÙÅÁÀ¸·Î , ÁöÇü, ½Ã¿îÀü, °øÁ¤·ü, ÃÑ °ø½Ãºñ ¹× ÃÑ °ø»ç±â°£À» µ¶¸³º¯¼ö·Î äÅÃÇÏ¿´´Ù. Á¦¾ÈµÈ ¼Õ½ÇÀ² ¸ðµ¨Àº Ç÷£Æ® ÇÁ·ÎÁ§Æ® ¸®½ºÅ© ºÐ¼®°ú ½Ã°ø/½Ã¿îÀü ´Ü°èÀÇ ¸®½ºÅ© ºÐ¼® °¡À̵å¶óÀÎÀ¸·Î È°¿ëµÉ ¼ö ÀÖ´Ù.
¿ä¾à2 Due to the increasing demand for and complexity of plant construction projects, unpredictable risk factors are on the consequent increase. For that reason, the quantitative risk analysis is being called for, in order for the development of a risk assessment model using risk indicators for the plant construction projects. This study used the claim payout data collected at a global insurance company to reflect the actual financial losses in plant construction projects as dependent variables in the risk assessment model. In terms of independent variables, the geographic information, i. e., landform, and the construction information including test-run, schedule rate, total cost and duration are adopted. In addition, this study suggests that the regression model containing such independent variables that are statistically significant can be applied to as a foundational guideline for the plant construction project risk analysis during the phase of construction and commissioning.
¼ÒÀåó Çѱ¹°ÇÃà½Ã°øÇÐȸ
¾ð¾î Çѱ¹¾î
DOI https://doi.org/10.5345/JKIBC.2019.19.1.077
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