Vulnerability and resilience analysis of safety behavior of organizations participating in bridge engineering based on GRA-SD

doi:10.16265/j.cnki.issn1003-3033.2024.09.0079

Abstract

Abstract:

To effectively implement safety production investment in bridge construction projects, GRA was used to analyze the correlation between the influencing factors of construction safety behavior from both the project supervision organization and construction units, and then the core causal factors were determined. Subsequently, a SD model was proposed to investigate the interaction mechanisms among the core causal factors. Finally, the vulnerability and resilience of the core causal factors affecting construction safety behavior were analyzed. The results indicated that extreme fines imposed by construction units, high supervision costs for project monitoring organizations, and low initial proportions between parties were the key vulnerability factors of the safety behavior in bridge construction. Reasonable economic fines, appropriate supervision costs, and enhanced training to improve frontline personnel's safety awareness significantly improved the construction safety behavior resilience.

Key words: grey relational analysis (GRA), system dynamics (SD), bridge engineering, main particip ants, safety behavior, vulnerability, resilience, construction unit, project supervision organization

CLC Number:

ZHANG Siyuan, YU Bo, LI Ruipu, WANG Qun. Vulnerability and resilience analysis of safety behavior of organizations participating in bridge engineering based on GRA-SD[J]. China Safety Science Journal, 2024, 34(9): 41-49.

Figures/Tables 12

Fig.1

Table 1

Table 2

Fig.2

Table 3

Table 4

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Fig.8

References 16

[1]	周海怡, 鲍全贵, 叶茂, 等. 基于组合赋权法的城市桥梁可靠性模糊综合评价[J]. 中国安全科学学报, 2023, 33(增1): 156-161.
	ZHOU Haiyi, BAO Quangui, YE Mao, et al. Fuzzy comprehensive evaluation of urban bridge reliability based on combination weighting method[J]. China Safety Science Journal, 2023, 33(S1): 156-161. doi: 10.16265/j.cnki.issn1003-3033.2023.S1.2494
[2]	李海文, 鲍学英. 基于动态权重-二维云模型的川藏铁路桥梁施工风险评估[J]. 铁道科学与工程学报, 2021, 18(6): 1650-1660.
	LI Haiwen, BAO Xueying. Risk assessment of Sichuan-Tibet railway bridge construction based on dynamic weight and 2-D cloud model[J]. Journal of Railway Science and Engineering, 2021, 18(6): 1650-1660.
[3]	王飞球, 黄健陵, 符竞, 等. 基于BP神经网络的跨既有线高速铁路桥梁施工安全风险评估[J]. 铁道科学与工程学报, 2019, 16(5): 1129-1136.
	WANG Feiqiu, HUANG Jianling, FU Jing, et al. Risk assessment of construction safety of high-speed railway bridge across existing lines based on BP neural network[J]. Journal of Railway Science and Engineering, 2019, 16(5): 1129-1136.
[4]	CHEN Fangyu, WEI Yongchang, JI Hongchang, et al. A multiplex network based analytical framework for safety management standardization in construction engineering[J]. Advanced Engineering Informatics, 2024, 59:DOI:10.1016/j.aei.2023.102278.
[5]	王志强, 刘硕, 马婷婷, 等. 风险偏好视角下地铁施工安全群体行为博弈研究[J]. 中国安全生产科学技术, 2020, 16(3): 138-144.
	WANG Zhiqiang, LIU Shuo, MA Tingting, et al. Study on behavioral game of metro construction safety groups under perspective of risk preference[J]. Journal of Safety Science and Technology, 2020, 16(3): 138-144.
[6]	陈述, 任亚萍, 席炎, 等. 动态惩罚机制下企业安全生产行为演化分析[J]. 中国安全科学学报, 2022, 32 (1): 51-57. doi: 10.16265/j.cnki.issn1003-3033.2022.01.007
	CHEN Shu, REN Yaping, XI Yan, et al. Evolutionary analysis on work safety behavior in firms under dynamic punishment Mechanism[J]. China Safety Science Journal, 2022, 32 (1): 51-57. doi: 10.16265/j.cnki.issn1003-3033.2022.01.007
[7]	LI Xinhong, MA Jie, HAN Ziyue, et al. Application of game theory in risk management of urban natural gas pipelines[J]. Journal of Loss Prevention in the Process Industries, 2023, 83: DOI:10.1016/j.jlp.2023.105037.
[8]	张跃斌, 易欣, 宋璋玉, 等. 基于SD的装配式建筑施工安全监管演化博弈研究[J]. 中国安全生产科学技术, 2022, 18(3): 149-155.
	ZHANG Yuebin, YI Xin, SONG Zhangyu, et al. Research on evolutionary game of safety supervision for prefabricated building construction based on SD[J]. Journal of Safety Science and Technology, 2022, 18(3): 149-155.
[9]	GU Shengyu, ZHANG Pan, YANG Jianying. System dynamics model based on evolutionary game theory for quality supervision among construction stakeholders[J]. Journal of Civil Engineering and Management, 2018, 24(4): 318-330.
[10]	张仕廉, 聂李琴. 基于DEMATEL方法的建筑施工安全管理行为影响因素分析[J]. 安全与环境工程, 2017, 24(1): 121-125.
	ZHANG Shilian, NIE Liqin. Influence factors of safety management behaviors of building construction by using DEMATEL method[J]. Safety and Environmental Engineering, 2017, 24(1): 121-125.
[11]	申玲, 孙其珩, 吴立石. 基于博弈关系的建筑安全投入监管对策研究[J]. 中国安全科学学报, 2010, 20(7): 110-115.
	SHEN Ling, SUN Qiheng, WU Lishi. Study on supervision strategies for construction safety investment based on game theory[J]. China Safety Science Journal, 2010, 20(7): 110-115.
[12]	王志强, 张樵民, 有维宝. 装配式建筑政府激励策略的演化博弈与仿真研究:基于政府补贴视角下[J]. 系统工程, 2019, 37(3): 151-158.
	WANG Zhiqiang, ZHANG Qiaomin, YOU Weibao. Evolutionary game and simulation of government incentive strategies for prefabricated buildings: from the perspective of government subsidies[J]. Systems Engineering, 2019, 37(3): 151-158.
[13]	陈雍君, 王璐琳, 王卫东, 等. 高铁四电建设工程信息共享演化博弈分析[J]. 铁道科学与工程学报, 2023, 20(1): 44-52.
	CHEN Yongjun, WANG Lulin, WANG Weidong, et al. Analysis and research on evolutionary game of information sharing in railroad electrification construction engineering[J]. Journal of Railway Science and Engineering, 2023, 20(1): 44-52.
[14]	MJAKUSKINA S, KAVOSA M, LAPINA I. Achieving sustainability in the construction supervision process[J]. Journal of Open Innovation: Technology, Market, and Complexity, 2019, 5(3):DOI:10.3390/joitmc5030047.
[15]	PENG Wang, YANG Weijun. Research on safety accidents in bridge construction based on safety rheology and mutation[J]. Applied Mechanics and Materials, 2012, 204/205/206/207/208: 2162-2166.
[16]	龙彦江, 彭鹏, 马羚, 等. 安全管理行为对安全管理绩效影响分析方法[J]. 工程管理学报, 2020, 34(3): 103-108.
	LONG Yanjiang, PENG Peng, MA Ling, et al. Analysis for impact of safety management behaviors on safety management performance[J]. Journal of Engineering Management, 2020, 34(3): 103-108.

序号	致因要素	文献来源
1	监管成本J_b、安全生产投入成本S_b	张跃斌^[8]、申玲^[11]等
2	奖励J_j、罚款S_f	王志强^[5]、陈述^[6]等
3	安全人员初始比例Y (施工单位)、X(项目监理机构)	CHEN Fangyu^[4]、 GU Shengyu^[9]等
4	事故发生率P	王志强^[12]、MJAKUSKINA S^[14] 等
5	事故发生后对本单位的损失S_s(施工单位)、 J_s(项目监理机构)	陈雍君^[13]、PENG Wang^[15]等

样本量	S_b/J_b	S_f/J_j	S_s/J_s	Y/X	P
专家1	8/9	7/9	9/8	9/9	6/6
专家2	8/9	8/8	8/9	9/8	7/7
专家3	8/8	7/8	9/7	8/8	5/6
专家4	7/9	8/8	8/9	9/9	8/8
专家5	7/8	8/7	8/9	8/8	6/6
专家6	9/8	8/8	9/8	9/9	7/7
专家7	8/9	7/8	9/9	9/8	6/7
专家8	8/8	8/9	8/8	8/8	5/6
专家9	8/7	7/9	7/9	9/9	7/7
专家10	9/9	9/8	8/8	9/8	9/9

变量类型	变量名称
水平变量 (4个)	项目监理机构—严格监管;项目监理机构—形式监管; 施工单位—规范安全投入;施工单位—不规范安全投入
速率变量 (2个)	项目监理机构严格监管变化率F(x); 施工单位规范施工变化率F(y)
辅助变量 (8个)	项目监理机构对施工单位采取严格监管策略的期望收益U₁₁、采取形式监督的期望收益U₁₂、期望收益差U₁; 施工单位规范安全投入的期望收益U₂₁、不规范安全投入的期望收益U₂₂、期望收益差U₂; 影子变量(x、y)
外部变量 (17个)	施工单位按规范标准及合同要求完成施工任务的正常收益S_z; 项目监理机构按规范标准及合同要求完成监管任务的正常收益J_z; 项目监理机构对施工单位进行安全施工监管的成本J_b; 施工单位根据施工合同规定应对项目投入的安全生产费用S_b; 施工单位对项目实际投入的安全生产费用S_c; 施工单位未规范安全投入,被项目监理机构查处后受到的经济惩罚S_f; 项目监理机构严格监管得到的奖励J_j; 施工单位未规范安全投入,被项目监理机构发现的概率P₁; 项目监理机构严格监管,施工单位未规范安全投入且未被发现发生的安全事故概率P₂; 项目监理机构在P₂情况下产生的损失J_s2; 施工单位在P₂情况下产生的损失S_s2; 项目监理机构未严格监管,施工单位规范安全投入发生的安全事故概率P₃; 项目监理机构在P₃情况下产生的损失J_s3; 施工单位在P₃情况下产生的损失S_s3; 项目监理机构未严格监管,施工单位未规范施工发生的安全事故的概率P₄; 项目监理机构在P₄情况下产生的损失J_s4; 施工单位在P₄情况下产生的损失S_s4

名称		S
		y	1-y
		y	被发现P₁	未被发现(1-P₁)
项目监理机构 (J)	x	J_z-J_b, S_z-S_b	J_z-J_b+J_j, S_z-S_c-S_f	J_z-J_b-P₂×J_s2, S_z-S_c-P₂×S_s2
项目监理机构 (J)	1-x	J_z-P₃×J_s3, S_z-S_b- P₃×S_s3	J_z-P₄×J_s4,S_z-S_c-P₄×S_s4