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• W3208556476 startingPage "105532" @default.
• W3208556476 abstract "Rapid expansion of urbanization in developing countries such as China brings explosive growth of the construction industry. It is necessary to evaluate construction performance in terms of safety, in order for sustainable development maintaining the speed of construction production without compromising safety performance. This study presents a quantitative analysis of construction safety performance in three regions of Jiangsu, Zhejiang and Shanghai, which were selected for reforming and developing modern construction industry in China. The nonparametric method of data envelopment analysis (DEA) was employed for evaluating construction safety performance in these regions from 2003 to 2019, and construction safety performance of each year in each region was deemed a decision-making unit (DMU). It is found that these regions do not maintain the state of fully BCC-efficient after achieving the optimal ratio between inputs and outputs in construction safety management. In consideration of the severity of undesirable outcomes, the construction industry performs better in the avoidance of workplace fatalities than in the prevention of non-fatal accidents. Distinct patterns of input indicators (e.g. I1 and I2) and output indicators (e.g. O1, O2 and O3) during the period can give impetus to pooling their experience for cross reference among Jiangsu, Zhejiang and Shanghai. Additionally practical experience of these regions can be referred to by other developing countries, in order for the balance between construction safety performance and industrial development in the aspects of added-value of the construction industry, completed-area of building construction, and total number of employees in construction companies." @default.
• W3208556476 created "2021-11-08" @default.
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• W3208556476 date "2022-02-01" @default.
• W3208556476 modified "2023-10-18" @default.
• W3208556476 title "Construction safety performance evaluation based on data envelopment analysis (DEA) from a hybrid perspective of cross-sectional and longitudinal" @default.
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• W3208556476 doi "https://doi.org/10.1016/j.ssci.2021.105532" @default.
• W3208556476 hasPublicationYear "2022" @default.
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