Big data analysis model for predicting operational risk in overseas construction projects
In this study, a big data analysis model was developed to predict the risks associated with overseas projects and a big data analysis technique. The risk analysis model can estimate the probability-cost interval for a planned project’s final cost by forming a probability density function and project...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Taylor & Francis Group
2022-11-01
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Series: | Journal of Asian Architecture and Building Engineering |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/13467581.2021.2007100 |
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author | Jiyeong Yun Kyeongtae Jeong Jongyoung Youn Donghoon Lee |
author_facet | Jiyeong Yun Kyeongtae Jeong Jongyoung Youn Donghoon Lee |
author_sort | Jiyeong Yun |
collection | DOAJ |
description | In this study, a big data analysis model was developed to predict the risks associated with overseas projects and a big data analysis technique. The risk analysis model can estimate the probability-cost interval for a planned project’s final cost by forming a probability density function and project costs through comparative analysis of data for a planned project and data for a previous similar project. This study attempted to collect a vast amount of information from the web and social networking services (SNS) in order to verify whether this information is sufficient to support the use of the web data analysis method used in this model. To this end, it was assumed that regional traffic conditions would be indicated on the web and SNS. In addition, two regions with different traffic conditions were selected, and then traffic-related keywords and words to enable assessment of traffic conditions were examined. Text information including these words was collected and the proportions of positive and negative words were analyzed. Results confirmed that two regions with different traffic conditions also had different numbers of negative words exhibited on the web. |
first_indexed | 2024-04-11T00:49:29Z |
format | Article |
id | doaj.art-e72ae9f6eb304e5892acea0e29ff3700 |
institution | Directory Open Access Journal |
issn | 1347-2852 |
language | English |
last_indexed | 2024-04-11T00:49:29Z |
publishDate | 2022-11-01 |
publisher | Taylor & Francis Group |
record_format | Article |
series | Journal of Asian Architecture and Building Engineering |
spelling | doaj.art-e72ae9f6eb304e5892acea0e29ff37002023-01-05T12:01:26ZengTaylor & Francis GroupJournal of Asian Architecture and Building Engineering1347-28522022-11-012162524253110.1080/13467581.2021.20071002007100Big data analysis model for predicting operational risk in overseas construction projectsJiyeong Yun0Kyeongtae Jeong1Jongyoung Youn2Donghoon Lee3Hanbat National UniversityHanbat National UniversityHanbat National UniversityHanbat National UniversityIn this study, a big data analysis model was developed to predict the risks associated with overseas projects and a big data analysis technique. The risk analysis model can estimate the probability-cost interval for a planned project’s final cost by forming a probability density function and project costs through comparative analysis of data for a planned project and data for a previous similar project. This study attempted to collect a vast amount of information from the web and social networking services (SNS) in order to verify whether this information is sufficient to support the use of the web data analysis method used in this model. To this end, it was assumed that regional traffic conditions would be indicated on the web and SNS. In addition, two regions with different traffic conditions were selected, and then traffic-related keywords and words to enable assessment of traffic conditions were examined. Text information including these words was collected and the proportions of positive and negative words were analyzed. Results confirmed that two regions with different traffic conditions also had different numbers of negative words exhibited on the web.http://dx.doi.org/10.1080/13467581.2021.2007100overseas construction projectsbig datarisk managementrisk analysis modelproject risk |
spellingShingle | Jiyeong Yun Kyeongtae Jeong Jongyoung Youn Donghoon Lee Big data analysis model for predicting operational risk in overseas construction projects Journal of Asian Architecture and Building Engineering overseas construction projects big data risk management risk analysis model project risk |
title | Big data analysis model for predicting operational risk in overseas construction projects |
title_full | Big data analysis model for predicting operational risk in overseas construction projects |
title_fullStr | Big data analysis model for predicting operational risk in overseas construction projects |
title_full_unstemmed | Big data analysis model for predicting operational risk in overseas construction projects |
title_short | Big data analysis model for predicting operational risk in overseas construction projects |
title_sort | big data analysis model for predicting operational risk in overseas construction projects |
topic | overseas construction projects big data risk management risk analysis model project risk |
url | http://dx.doi.org/10.1080/13467581.2021.2007100 |
work_keys_str_mv | AT jiyeongyun bigdataanalysismodelforpredictingoperationalriskinoverseasconstructionprojects AT kyeongtaejeong bigdataanalysismodelforpredictingoperationalriskinoverseasconstructionprojects AT jongyoungyoun bigdataanalysismodelforpredictingoperationalriskinoverseasconstructionprojects AT donghoonlee bigdataanalysismodelforpredictingoperationalriskinoverseasconstructionprojects |