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Improving accident analysis in construction – Development of a contributing factor classification framework and evaluation of its validity and reliability
Construction industry is still one of the most dangerous industries and its fatal work injuries is almost three times higher than the average across all sectors. Previous researchers have attempted to apply more systemic models and methods to improve accident analysis in construction, but few studie...
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| Format: | Default Article |
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2021
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| Online Access: | https://hdl.handle.net/2134/14472900.v1 |
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| author | Anastacio Pinto Goncalves Filho Patrick Waterson Gyuchan Thomas Jun |
| author_facet | Anastacio Pinto Goncalves Filho Patrick Waterson Gyuchan Thomas Jun |
| author_sort | Anastacio Pinto Goncalves Filho (10699750) |
| collection | Figshare |
| description | Construction industry is still one of the most dangerous industries and its fatal work injuries is almost three times higher than the average across all sectors. Previous researchers have attempted to apply more systemic models and methods to improve accident analysis in construction, but few studies have fully encompassed upstream factors such as decisions and actions at the level of the government and regulator in accident analysis. More importantly, no previous study has evaluated the validity and reliability of systemic accident analysis methods in construction. The present study, therefore, has two main aims: to develop a contributing factor classification framework to support systemic accident investigation in construction and to carry out an assessment of its validity and reliability. The classification framework was developed and assessed in two phases. The phase one involved generating a list of contributing factors from the review of 26 articles and the analysis of 532 construction accident reports. Five federal inspectors with expertise in accident investigation were involved in refining the list into 61 contributing factors and categorizing them into six levels of the Accimap framework. The phase two involved in assessing the validity and reliability of the framework with five practitioners in construction sector using three real construction accidents. This study contributes to the development of a contributing factors classification system framework for construction with acceptable validity and reliability. |
| format | Default Article |
| id | rr-article-14472900 |
| institution | Loughborough University |
| publishDate | 2021 |
| record_format | Figshare |
| spelling | rr-article-144729002021-04-23T00:00:00Z Improving accident analysis in construction – Development of a contributing factor classification framework and evaluation of its validity and reliability Anastacio Pinto Goncalves Filho (10699750) Patrick Waterson (1255566) Gyuchan Thomas Jun (1251018) Construction Accimap Classification system Accident Investigation Construction industry is still one of the most dangerous industries and its fatal work injuries is almost three times higher than the average across all sectors. Previous researchers have attempted to apply more systemic models and methods to improve accident analysis in construction, but few studies have fully encompassed upstream factors such as decisions and actions at the level of the government and regulator in accident analysis. More importantly, no previous study has evaluated the validity and reliability of systemic accident analysis methods in construction. The present study, therefore, has two main aims: to develop a contributing factor classification framework to support systemic accident investigation in construction and to carry out an assessment of its validity and reliability. The classification framework was developed and assessed in two phases. The phase one involved generating a list of contributing factors from the review of 26 articles and the analysis of 532 construction accident reports. Five federal inspectors with expertise in accident investigation were involved in refining the list into 61 contributing factors and categorizing them into six levels of the Accimap framework. The phase two involved in assessing the validity and reliability of the framework with five practitioners in construction sector using three real construction accidents. This study contributes to the development of a contributing factors classification system framework for construction with acceptable validity and reliability. 2021-04-23T00:00:00Z Text Journal contribution 2134/14472900.v1 https://figshare.com/articles/journal_contribution/Improving_accident_analysis_in_construction_Development_of_a_contributing_factor_classification_framework_and_evaluation_of_its_validity_and_reliability/14472900 CC BY-NC-ND 4.0 |
| spellingShingle | Construction Accimap Classification system Accident Investigation Anastacio Pinto Goncalves Filho Patrick Waterson Gyuchan Thomas Jun Improving accident analysis in construction – Development of a contributing factor classification framework and evaluation of its validity and reliability |
| title | Improving accident analysis in construction – Development of a contributing factor classification framework and evaluation of its validity and reliability |
| title_full | Improving accident analysis in construction – Development of a contributing factor classification framework and evaluation of its validity and reliability |
| title_fullStr | Improving accident analysis in construction – Development of a contributing factor classification framework and evaluation of its validity and reliability |
| title_full_unstemmed | Improving accident analysis in construction – Development of a contributing factor classification framework and evaluation of its validity and reliability |
| title_short | Improving accident analysis in construction – Development of a contributing factor classification framework and evaluation of its validity and reliability |
| title_sort | improving accident analysis in construction – development of a contributing factor classification framework and evaluation of its validity and reliability |
| topic | Construction Accimap Classification system Accident Investigation |
| url | https://hdl.handle.net/2134/14472900.v1 |