风险倾向对新生代建筑工人危险感知的影响机制

doi:10.16265/j.cnki.issn1003-3033.2023.05.2044

摘要/Abstract

摘要：

为探究不同风险倾向新生代建筑工人危险感知水平的差异性,个性化提高不同风险倾向群体的危险感知水平,首先精选39张包含施工现场安全隐患的图片素材,借助固定式眼动仪,测试并收集45名被试在观看图片过程中的危险感知数据;然后编制风险倾向量表,开展风险倾向问卷调查,收集数据后,运用置换检验、注意力热点图和搜索轨迹图分析并检验数据,研究风险倾向对新生代建筑工人危险感知的影响机制。结果表明:不同风险倾向的新生代建筑工人危险感知水平存在显著性差异;相较于高风险倾向群体,低风险倾向群体表现出更少的感知危险数量、更短的首次注视时间、更长的停留占比和更多的眼跳次数;尽管低风险倾向的新生代建筑工人感知危险数量较少,但是对已识别危险的重视程度明显高于高风险倾向群体。

关键词: 风险倾向, 新生代建筑工人, 危险感知, 影响机制, 眼动试验, 置换检验

Abstract:

In order to explore the differences in hazard perception levels among the new generation of construction workers with different risk propensities and enhance the risk perception level of different risk propensity groups in a personalized manner, 39 pictures containing hazards in the workplace were selected carefully, hazard perception data from 45 subjects was tested and collected by fixed eye-tracking device, and their risk propensity data was collected by questionnaire. Then permutation test, the heat map and the scan path map were used to analyze and verify data. Finally, the influencing mechanism of risk propensity on hazard perception of the new generation of construction workers was clarified. The results show that there are significant differences in the hazard perception level of the new generation of construction workers with different risk propensity. Compared with the high-risk propensity group, the low-risk propensity group exhibits fewer perceived quantity of hazards, shorter first fixation time, longer dwell percentage and more run counts. Although the number of hazards perceived by the new generation of construction workers with low-risk propensity is lower, they pay more attention to the identified hazards than those with high-risk propensity.

Key words: risk propensity, new generation of construction workers, hazard perception, influencing mechanism, eye movement experiment, permutation test

倪国栋, 方亚琦, 张琦, 丁志华. 风险倾向对新生代建筑工人危险感知的影响机制[J]. 中国安全科学学报, 2023, 33(5): 221-229.

NI Guodong, FANG Yaqi, ZHANG Qi, DING Zhihua. Influencing mechanism of risk propensity on hazard perception of new generation of construction workers[J]. China Safety Science Journal, 2023, 33(5): 221-229.

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参考文献 21

[1]	全国工程质量安全监管信息平台公共服务门户. 2017—2021年房屋市政工程生产安全事故情况[EB/OL].[2022-10-22]. https://zlaq.mohurd.gov.cn/fwmh/bjxcjgl/fwmh/pages/default/index.html.
[2]	李琰, 毛钰, 张燕. 建筑工人应急行为影响机制[J]. 中国安全科学学报, 2021, 31(10):1-7. doi: 10.16265/j.cnki.issn1003-3033.2021.10.001
	LI Yan, MAO Yu, ZHANG Yan. Influence mechanism of construction workers' emergency behavior[J]. China Safety Science Journal, 2021, 31(10): 1-7. doi: 10.16265/j.cnki.issn1003-3033.2021.10.001
[3]	黄芹芹, 祁神军, 张云波, 等. 建筑工人习惯性不安全行为干预策略的SD模型[J]. 中国安全科学学报, 2018, 28(7):25-31. doi: 10.16265/j.cnki.issn1003-3033.2018.07.005
	HUANG Qinqin, QI Shenjun, ZHANG Yunbo, et al. SD model of intervention strategies for habitual unsafe behavior of construction workers[J]. China Safety Science Journal, 2018, 28(7): 25-31. doi: 10.16265/j.cnki.issn1003-3033.2018.07.005
[4]	NI Guodong, LYU Lei, WANG Shaobo, et al. Formation mechanism and dynamic evolution laws about unsafe behavior of new generation of construction workers based on China's construction industry: application of grounded theory and system dynamics[J]. Frontiers in Psychology, 2022,13:DOI:10.3389/fpsyg.2022.888060. doi: 10.3389/fpsyg.2022.888060
[5]	HAN Yu, FENG Zhida, ZHANG Jingjie, et al. Employees' safety perceptions of site hazard and accident scenes[J]. Journal of Construction Engineering and Management, 2019, 145(1):DOI:10.1061/(ASCE)CO.1943-7862.0001590. doi: 10.1061/(ASCE)CO.1943-7862.0001590
[6]	HASANZADEH S, ESMAEILI B, DODD MICHAEL D. Measuring the impacts of safety knowledge on construction workers' attentional allocation and hazard detection using remote eye-tracking technology[J]. Journal of Management in Engineering, 2017, 33(5):DOI:10.1061/(ASCE)ME.1943-5479.0000526. doi: 10.1061/(ASCE)ME.1943-5479.0000526
[7]	NAMIAN M, ALBERT A, FENG J. Effect of distraction on hazard recognition and safety risk perception[J]. Journal of Construction Engineering and Management, 2018, 144(4):DOI:10.1061/(ASCE)CO.1943-7862.0001459. doi: 10.1061/(ASCE)CO.1943-7862.0001459
[8]	ZHANG D C, HIGHHOUSE S, NYE C D. Development and validation of the general risk propensity scale (GRiPS)[J]. Journal of Behavioral Decision Making, 2019, 32(2): 152-167. doi: 10.1002/bdm.2102
[9]	JOSEF A K, RICHTER D, SAMANEZ-LARKIN G R, et al. Stability and change in risk-taking propensity across the adult life span[J]. Journal of Personality and Social Psychology, 2016, 111(3): 430-450. doi: 10.1037/pspp0000090 pmid: 26820061
[10]	SÁMANO-RÍOS M L, IJAZ S, RUOTSALAINEN J, et al. Occupational safety and health interventions to protect young workers from hazardous work:a scoping review[J]. Safety Science, 2019, 113: 389-403. doi: 10.1016/j.ssci.2018.11.024
[11]	张泾杰, 韩豫, 马国鑫, 等. 基于BIM的建筑工人危险感知能力训练系统[J]. 土木工程与管理学报, 2017, 34(1): 88-93.
	ZHANG Jingjie, HAN Yu, MA Guoxin, et al. Training system for risk perception based on BIM for construction workers[J]. Journal of Civil Engineering and Management, 2017, 34(1): 88-93.
[12]	LIU Mei, LIAO Pinchao, WANG Xiaoyun, et al. Influence of semantic cues on hazard-inspection performance: a case in construction safety[J]. International Journal of Occupational Safety and Ergonomics, 2021, 27(1): 14-28. doi: 10.1080/10803548.2018.1541648
[13]	叶贵, 李学征, 向卿婷, 等. 建筑工人故意违章行为动机形成机制研究[J]. 中国安全科学学报, 2020, 30(8):12-17. doi: 10.16265/j.cnki.issn1003-3033.2020.08.002
	YE Gui, LI Xuezheng, XIANG Qingting, et al. Research on formation mechanism of construction workers' DVB motivation[J]. China Safety Science Journal, 2020, 30(8): 12-17. doi: 10.16265/j.cnki.issn1003-3033.2020.08.002
[14]	BISLEY J W. The neural basis of visual attention[J]. The Journal of Physiology, 2011, 589(1): 49-57. doi: 10.1113/jphysiol.2010.192666
[15]	COMU S, KAZAR G, MARWA Z. Evaluating the attitudes of different trainee groups towards eye tracking enhanced safety training methods[J]. Advanced Engineering Informatics, 2021, 49:DOI:10.1016/j.aei.2021.101353. doi: 10.1016/j.aei.2021.101353
[16]	WANG Chunmei, XU Bingbing, ZHANG Sujuan, et al. Influence of personality and risk propensity on risk perception of Chinese construction project managers[J]. International Journal of Project Management, 2016, 34(7): 1294-1304. doi: 10.1016/j.ijproman.2016.07.004
[17]	HUNG K T, TANGPONG C, LI Jin, et al. Robustness of general risk propensity scale in cross-cultural settings[J]. Journal of Managerial Issues, 2012, 24(1): 78-96.
[18]	ZHANG Jian, XIANG Pengcheng, ZHANG Rong, et al. Mediating effect of risk propensity between personality traits and unsafe behavioral intention of construction workers[J]. Journal of Construction Engineering and Management, 2020, 146(4): DOI:10.1061/(ASCE)CO.1943-7862.0001792. doi: 10.1061/(ASCE)CO.1943-7862.0001792
[19]	BHANDARI S, HALLOWELL M R, BOVEN L V, et al. Using augmented virtuality to examine how emotions influence construction-hazard identification, risk assessment, and safety decisions[J]. Journal of Construction Engineering and Management, 2020, 146(2):DOI:10.1061/(ASCE)CO.1943-7862.0001755. doi: 10.1061/(ASCE)CO.1943-7862.0001755
[20]	HAN Yu, YIN Zhenzhen, ZHANG Jingjie, et al. Eye tracking experimental study investigating the influence factors of construction safety hazard recognition[J]. Journal of Construction Engineering and Management, 2020, 146(8):DOI:10.1061/(ASCE)CO.1943-7862.0001884. doi: 10.1061/(ASCE)CO.1943-7862.0001884
[21]	郑颖琇, 陈星, 徐俞凯, 等. 施工场地内安全标志位置的有效性研究及其应用[J]. 安全与环境工程, 2022, 29(1):17-25.
	ZHENG Yingxiu, CHEN Xing, XU Yukai, et al. Research and application of the position validity safety signs in construction sites[J]. Safety and Environmental Engineering, 2022, 29(1): 17-25.

分组	个案数	平均值/个	标准差/个	最小值/个	最大值/个	p
低风险倾向	23	117	8	103	134	0.005
高风险倾向	22	123	4	114	129	0.005

安全隐患	AOI数量	分组	个案数	均值/ms	标准差/ms	p
高处坠落	39	低风险倾向	23	2 640.114	747.914	0.044
高处坠落	39	高风险倾向	22	3 035.424	495.630	0.044
物体打击	21	低风险倾向	23	3 642.849	840.270	0.110
物体打击	21	高风险倾向	22	4 000.697	625.906	0.110
机械伤害	33	低风险倾向	23	4 242.461	989.385	0.008
机械伤害	33	高风险倾向	22	4 929.816	630.855	0.008
场地杂乱	30	低风险倾向	23	4 339.690	1 127.835	0.342
场地杂乱	30	高风险倾向	22	4 680.518	1 265.052	0.342
触电	12	低风险倾向	23	3 830.287	1 551.486	0.662
触电	12	高风险倾向	22	3 660.363	884.011	0.662

安全隐患	AOI数量	分组	个案数	均值	标准差	p
高处坠落	39	低风险倾向	23	0.176	0.051	0.009
高处坠落	39	高风险倾向	22	0.142	0.031	0.009
物体打击	21	低风险倾向	23	0.099	0.023	0.279
物体打击	21	高风险倾向	22	0.092	0.019	0.279
机械伤害	33	低风险倾向	23	0.140	0.027	0.000
机械伤害	33	高风险倾向	22	0.110	0.015	0.000
场地杂乱	30	低风险倾向	23	0.089	0.027	0.614
场地杂乱	30	高风险倾向	22	0.085	0.015	0.614
触电	12	低风险倾向	23	0.150	0.068	0.023
触电	12	高风险倾向	22	0.114	0.036	0.023

安全隐患	AOI数量	分组	个案数	均值/次	标准差/次	p
高处坠落	39	低风险倾向	23	3.494	0.735	0.005
高处坠落	39	高风险倾向	22	2.994	0.395	0.005
物体打击	21	低风险倾向	23	2.528	0.454	0.097
物体打击	21	高风险倾向	22	2.336	0.307	0.097
机械伤害	33	低风险倾向	23	2.915	0.481	0.003
机械伤害	33	高风险倾向	22	2.537	0.308	0.003
场地杂乱	30	低风险倾向	23	2.396	0.471	0.053
场地杂乱	30	高风险倾向	22	2.171	0.246	0.053
触电	12	低风险倾向	23	2.956	0.765	0.362
触电	12	高风险倾向	22	2.763	0.625	0.362