Quantitative classification and evolution analysis of construction safety climate

doi:10.16265/j.cnki.issn1003-3033.2025.01.0396

Abstract

Abstract:

In order to explore the evolution mechanism and the best joint strategy for improvement of construction safety climate, with the help of the Mobius ring structure, a three-factor structure model of construction safety climate based on cognition-behavior-environment was constructed from three dimensions of construction workers' cognition, behavior and environment. According to the classification standard of the three-dimensional spatial structure model of construction safety climate, the grading standard of safety climate was divided. The DBN was used to study the changes of the construction safety climate with time. The results show that in terms of influencing factors, safety incentives have the greatest impact on enterprise safety climate and its evolution. In terms of dimensions, the behavioral dimension has the greatest impact. The best joint strategy to improve the construction safety climate is to strengthen the control of safety incentives, safety supervision, workers' safety response, safety consciousness and workers' learning and communication in turn.

Key words: construction, safety climate, quantitative classification, evolution analysis, dynamic Bayesian network (DBN)

CLC Number:

X948

LEI Tian, TIAN Zhen. Quantitative classification and evolution analysis of construction safety climate[J]. China Safety Science Journal, 2025, 35(1): 32-39.

Figures/Tables 12

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维度	影响因素
认知	安全思想和理念(Safety Thoughts and Ideas, STI)
	安全意识(Safety Conscious, SCS)
	安全知识(Safety Knowledge, SKL)
环境	自然环境(Natural Environment, NE)
	施工现场环境(Construction Site Environment, SE)
	人文环境(Humanistic Environment, HE)
行为	安全管理承诺(Safety Management Commitment, SMC)
	安全激励(Safety Incentive, SIC)
	安全督查(Safety Supervision, SSV)
	安全教育和培训(Safety Education and Training, SET)
	工人安全响应(Worker Safety Response, WSR)
	工人间学习与交流(Workers' Learning and Communication, WLC)

变量	项数	Cronbach's alpha	CR	AVE
STI	3	0.863	0.864	0.680
SCS	5	0.815	0.849	0.531
SKL	3	0.763	0.764	0.520
SMC	3	0.931	0.936	0.830
SIC	3	0.815	0.817	0.600
SSV	3	0.916	0.916	0.785
SET	3	0.768	0.769	0.526
WSR	3	0.803	0.812	0.595
WLC	3	0.705	0.781	0.543
NE	3	0.752	0.785	0.550
SE	3	0.824	0.821	0.605
HE	3	0.907	0.908	0.768

等级	范围	描述
Weak	[1, 3)	不符合现状,十分欠缺
Medium	[3, 4)	一般符合现状
Strong	[4, 5]	非常符合现状,总体令人满意

等级	x、y、z取值范围	R²取值范围	描述
R1	[1, 2)	3≤ R² <12	弱
R2	[2, 3)	12≤ R² <27	中等
R3	[3, 4)	27≤ R² <48	良好
R4	[4, 5]	48≤ R² ≤75	强

变量	安全氛围处于R4等级的概率		差值	排名
变量	T=1	T=12	差值	排名
SCS	0.212 957 520	0.349 560 859	0.136 603 339	4
STI	0.203 120 337	0.334 687 890	0.131 567 554	6
SKL	0.243 165 453	0.324 387 491	0.081 222 038	12
SE	0.248 495 839	0.365 837 177	0.117 341 338	9
NE	0.226 459 047	0.356 309 466	0.129 850 419	8
HE	0.268 948 384	0.356 384 091	0.087 435 707	11
SMC	0.194 261 337	0.324 387 491	0.130 126 155	7
SET	0.210 530 704	0.324 387 491	0.113 856 787	10
SIC	0.191 799 130	0.344 000 426	0.152 201 296	1
WLC	0.218 688 844	0.351 393 905	0.132 705 061	5
SSV	0.202 825 719	0.354 167 239	0.151 341 521	2
WSR	0.198 796 673	0.344 180 214	0.145 383 541	3