我国地铁乘客事件频发,提示有必要探讨乘客行为的分类、影响及其与事件介入的关系。地铁乘客行为问卷(MPBQ)和地铁站员工问卷(MSSQ),两者都包括32个行为项目,在地铁乘客(N=579)和地铁工作人员(N=99)的样本上进行了开发和调查。使用MPBQ,测量每个异常行为的自我报告频率,并进行解释性因子分析,它揭示了对28个保留行为项目的三因素解决方案:越轨行为,任性的疏忽和突然的侵犯。ANOVA用于检查人口统计学和骑行概况变量对不同类型行为的影响。MSSQ用于收集地铁工作人员对行为频率的意见,严重性和可能受影响的实体,鉴于发生了特定的行为。在32个识别行为上建立了重要性层次结构,以确定最重要的骑行行为。最后,Logistic回归显示,骑行时间,乘客经历的停车次数,更重要的是,违反和突然违反,是事件参与的重要预测因子。研究结果的可能解释和含义可能有助于理解乘客行为并以促进更安全运营的方式针对地铁安全干预措施。
The frequent
incidents caused by metro passengers in
China suggest that it is necessary to explore the classification and effects of passenger behaviors and their relations to incident involvement. A metro passenger behavior questionnaire (MPBQ) and a metro station staff questionnaire (MSSQ), both comprising 32 behavior items, were developed and surveyed on a sample of metro passengers (N=579) and metro staff (N=99). Using the MPBQ, the self-reported frequency of each aberrant behavior was measured and subjected to explanatory factor analysis, which revealed a three-factor solution on the 28 retained behavior items: transgressions, self-willed inattentions and abrupt violations. ANOVA was used to examine the effects of demographic and riding profile variables on different types of behaviors. The MSSQ was used to collect metro staff opinions on behavior frequency, severity and entities that might be affected, given that a specific behavior occurred. An importance hierarchy was established over the 32 identified behaviors to determine the most important riding behaviors. Finally, logistic regression showed that riding time, number of stops experienced by a passenger and, more importantly, transgressions and abrupt violations, were significant predictors of incident involvement. The possible explanations and implications of the findings might help in understanding passenger behaviors and targeting metro safety interventions in ways that promote safer operations.