Chapter
Nov 30, 2023

Prediction of Unsafe Behavior for Construction Workers Based on Logistics Regression

ABSTRACT

Construction industry is one of the pillar industries of China’s national economy. The benign development of the construction industry plays a vital role in the construction of China’s socialist market economy and the development of the national economy. But for a long time, the construction industry has also been one of the industries with frequent production accidents in China. Once a safety accident occurs in the project construction, it will cause more serious casualties and property losses, and seriously hinder the national construction and social development. The unsafe behavior of construction workers is a common cause of safety accidents. Therefore, it is helpful to predict whether construction workers will make unsafe behaviors in the construction process and make timely prevention to reduce the occurrence of safety accidents. The study will use the perception of risk and knowledge and behavioral control perception as dependent variables to predict the generation of unsafe behaviors among workers.

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REFERENCES

Gui, Y. (2016). “Study on the mechanism of unsafe behavior of construction workers.” China Safety Production Science and Technology, 12(03):181-186. (in Chinese)
Gui, Y. (2021). “Study on quantitative classification of unsafe behavior of construction workers.” Journal of Safety and Environment, 21(06):2617-2627. (in Chinese)
Shan, F. (2014). “Comparative analysis of Logistic regression model and discriminant analysis method.” Journal of Yangtze University, 11(04):19-22+2. (in Chinese)
Zhou Z. (2022). “Analysis of critical path of unsafe behavior of construction workers and intervention countermeasures.” Journal of Engineering Management, 36(06):127-132. (in Chinese)

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Go to ICCREM 2023
ICCREM 2023
Pages: 230 - 238

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Published online: Nov 30, 2023

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Feiyan Zhao [email protected]
Associate Professor, Zhonghuan Information College, Dept. of Economics and Management, Tianjin Univ. of Technology, Tianjin, China. Email: [email protected]
Zhonghuan Information College, Dept. of Economics and Management, Tianjin Univ. of Technology, Tianjin, China (corresponding author). Email: [email protected]

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