TY - JOUR
T1 - A comprehensive analysis of the causal factors in repair, maintenance, alteration, and addition works
T2 - A novel hybrid fuzzy-based approach
AU - Mohandes, Saeed Reza
AU - Karasan, Ali
AU - Erdoğan, Melike
AU - Ghasemi Poor Sabet, Pejman
AU - Mahdiyar, Amir
AU - Zayed, Tarek
N1 - Funding Information:
This research is financially supported by the project entitled –Postdoc Matching Fund Scheme provided by the Hong Kong Polytechnic University, under the Project Number: 1-W15K.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/12/1
Y1 - 2022/12/1
N2 - Despite the recent improvements made to the area of occupational health and safety (OHS) within the construction sector, the Repair, Maintenance, Minor alteration, and Addition (RMAA) works have been given scant attention. In this study, given the significance of the injuries reported in the RMAA sector, a meticulous investigation is conducted into the causal factors contributing to the related accidents by capturing their causal interrelationships together with their importance levels. To this end, first, a comprehensive list of factors contributing to RMAA accidents was obtained through an extensive literature review and experts’ interviews. Then, through the lenses of qualified relevant experts in Hong Kong, the proposed interval-valued intuitionistic fuzzy (IVIF) DEMATEL and IVIF analytic network process were employed to respectively uncover the cause-and-effect relationships among these factors and prioritize them. The findings show that “the lack of assessment and praising of workers’ OHS understanding and performance,” “the high turnover rate of workers resulting in difficulties in providing safety training and education,” and “lack of safety training for workers” are the most critical causes to be given full attention by construction safety managers. The methodological approach proposed in this study brings about two theoretical contributions: unraveling interrelationships existing among the causal factors, and prioritization of them considering their interrelationships. The findings reported in this study also aid decision-makers in improving the critical causal factors in a way to enhance the OHS of RMAA sector.
AB - Despite the recent improvements made to the area of occupational health and safety (OHS) within the construction sector, the Repair, Maintenance, Minor alteration, and Addition (RMAA) works have been given scant attention. In this study, given the significance of the injuries reported in the RMAA sector, a meticulous investigation is conducted into the causal factors contributing to the related accidents by capturing their causal interrelationships together with their importance levels. To this end, first, a comprehensive list of factors contributing to RMAA accidents was obtained through an extensive literature review and experts’ interviews. Then, through the lenses of qualified relevant experts in Hong Kong, the proposed interval-valued intuitionistic fuzzy (IVIF) DEMATEL and IVIF analytic network process were employed to respectively uncover the cause-and-effect relationships among these factors and prioritize them. The findings show that “the lack of assessment and praising of workers’ OHS understanding and performance,” “the high turnover rate of workers resulting in difficulties in providing safety training and education,” and “lack of safety training for workers” are the most critical causes to be given full attention by construction safety managers. The methodological approach proposed in this study brings about two theoretical contributions: unraveling interrelationships existing among the causal factors, and prioritization of them considering their interrelationships. The findings reported in this study also aid decision-makers in improving the critical causal factors in a way to enhance the OHS of RMAA sector.
KW - Accident analysis
KW - Accident causation
KW - ANP
KW - DEMATEL
KW - Fuzzy logic
KW - RMAA
UR - http://www.scopus.com/inward/record.url?scp=85134588648&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2022.118112
DO - 10.1016/j.eswa.2022.118112
M3 - Journal article
AN - SCOPUS:85134588648
SN - 0957-4174
VL - 208
JO - Expert Systems with Applications
JF - Expert Systems with Applications
M1 - 118112
ER -