The relationship between organizational safety culture and unsafe behaviors, and accidents among public transport bus drivers using structural equation modeling

Mokarami, Hamidreza; Alizadeh, Seyed Shamseddin; Pordanjani, Tayebe Rahimi; Varmazyar, Sakineh

doi:10.1016/j.trf.2019.07.008

Cited by 54 publications

(37 citation statements)

References 32 publications

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“…Newnam, Watson, and Murray (2002) found drivers who work in organisation with a strong safety culture reported overall safer driving behaviour in a work vehicle than those with less strict safety policies in place. Mokarami et al (2019), examined the causal relationship between aberrant behaviors by public transportation drivers in Iran and organizational safety culture. Their results revealed a negative relationship between safety culture and crashes, with promotion of a safety management system likely to improve the employees' safe behaviors.…”

Section: Traffic Safety Culturementioning

confidence: 99%

Do drivers differ in their attitudes on speed limit compliance between work and private settings? Results from a group of Nigerian drivers

Etika

Merat

Carsten

2020

Transportation Research Part F: Traffic Psychology and Behaviou

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Existing evidence suggests that drivers, particularly those who work in companies with strong road safety cultures exhibit different sets of speeding attitudes and behaviours in work and private driving. Using Ajzen and Fishbein's (1980) Theory of Planned behaviour (TPB) and onroad driving experiments, this study examined the self-reported and objective behaviour of driving within posted speed limits for a sample of fleet drivers. The findings show that the TPB explained up to 24% of the variance in intention to comply with speed limits. Drivers' attitude emerged as the most significant predictor and strongest correlate with intentions to comply with the speed limit in both work and private vehicle.Further analysis revealed participants had a higher intention to comply with speed limits in their work than private vehicle. Also, investigation of the relationship between TPB variables and observed speeding behaviour suggests that participants with higher intention to comply with the speed limit or high perceived behavioural control (PBC), exceeded the speed limit less often than those with lower intention to comply with the speed limit or low PBC. The findings have important theoretical and applied implications for development of better speed limit compliance interventions to improve driving behaviour, and road safety in general.

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Section: Traffic Safety Culturementioning

confidence: 99%

Do drivers differ in their attitudes on speed limit compliance between work and private settings? Results from a group of Nigerian drivers

Etika

Merat

Carsten

2020

Transportation Research Part F: Traffic Psychology and Behaviou

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show abstract

“…The study found that the majority of bus accidents are linked to stressed drivers and fatigue is a major indicator of high level of stress. A survey study on the influence of organizational aspect on bus driver behavior in Tehran, Iran was conducted [94]. Both Driver Safety Culture Questionnaire (DSCQ) and Public Transport DBQ (PTDBQ) were utilized in the study and a strong relationship between long working hours and high level of stress and fatigue by driver was reported.…”

Section: 7) Driver Conditionmentioning

confidence: 99%

A Landscape of Research on Bus Driver Behavior: Taxonomy, Open Challenges, Motivations, Recommendations, Limitations, and Pathways Solution in Future

et al. 2021

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Driver behavior is a concerning issue in the area of intelligent transportation system (ITS). Driver behavior is a significant key player in a wide range of unpleasant events during the ride, such as accidents or crashes, traffic congestion, harsh braking, and acceleration/deceleration. Influencing factors of driver behavior have been explored in several studies. It is imperative to investigate these factors in order to provide a comprehensive analysis and to categorize them on the basis of a coherent taxonomy. With that, this study conducted a systematic review on prior studies that focused on bus driver behavior, particularly in the ITS. This study also established a taxonomy on the topic of driver behavior in multiple areas of ITS and their classifications. Different databases, namely ScienceDirect, Web of Science, and IEEE Explore, were utilized to obtain relevant articles from 2008 to 2021 (15 April). Several filtering and scanning stages were performed according to the exclusion/inclusion criteria on all 2,803 articles obtained; however, only 87 articles met the criteria. The final set of articles were categorized into a taxonomy. The first part of the taxonomy focuses on five main factors that influence driver behavior: environmental, demographic, habit, vehicle, and on-road routine factors. The second part of the taxonomy discusses the mapping of data collection methods on the basis of four categories: real-time data collection, survey, simulation, and benchmark. Discussion and analysis were provided to highlight the critical literature gaps on bus driver behavior in the ITS, involving the use of real-time data collection, which is imperative for acquiring highly accurate and sophisticated data. This multi-field systematic review has exposed new research opportunities, motivations, challenges, limitations, and recommendations and highlighted the need for the synergistic integration of interdisciplinary works. Overall, this study presented pathways solution in future direction on the basis of three sequenced phases, namely design, labeling and validation, and machine learning. This study can serve as a guide for future researchers, as it addressed the ambiguities in the ITS-driver behavior domain and provided valuable information on these ITS-driver behavior trends.

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“…Virojboonkiate et al (2019) [44] proposed a driver identification system based on acceleration sensor data for PT systems. Mokarami et al (2019) [45] investigated 336 PT bus drivers in Tehran with two questionnaires and indicated that the organizational safety culture had positive effects on decreasing the unsafe behaviours of PT drivers and reducing PT accidents. Kang et al (2019) [46] investigated 317 drivers in Malaysia online and indicated that it was necessary to develop interventions to meet the specific lifestyles and demands of PT drivers.…”

Section: Transportation Factormentioning

confidence: 99%

“…(ii) Calculating the total value. The total value of the passenger consists of various individual values for the various passenger factors during the time period t 1 ∼ t m and can be calculated by Formula (45):…”

Section: Passenger Utility Analysesmentioning

confidence: 99%

Multiple Utility Analyses for Sustainable Public Transport Planning and Management: Evidence from GPS-Equipped Taxi Data in Haikou

Gui

2020

Sustainability

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The transportation utility values calculated by traditional utility methods are not comprehensive. Some objects and factors are ignored in traditional utility methods, and this narrow perspective is their primary drawback. In intelligent transportation systems, it is necessary to calculate transportation utility for promoting public traffic planning and management. To build a sustainable intelligent transportation system, modified utility methods are essential to analyze transportation utility in a comprehensive way with innovative technologies and efficient communication systems. To solve the disadvantages of traditional utility methods, it is necessary to establish a new method to build sustainable public transport in the future. In this study, the Multiple Utility Method and Transportation Utility Method are proposed for public transport planning and management from multiple perspectives. A sample is presented to provide a better description, and 69,174 GPS-equipped taxi data in Haikou are adopted for the application of the Transportation Utility Method. The results show that the transportation utility values calculated by the Transportation Utility Method are more comprehensive than the transportation utility calculated by traditional utility methods. This indicates that it is necessary to calculate transportation utility from multiple perspectives based on the Transportation Utility Method. Future directions could include improving the methods, considering more factors, expanding the data used, and extrapolating this research to other cities around the world with similar urban metrics and urban form.

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The relationship between organizational safety culture and unsafe behaviors, and accidents among public transport bus drivers using structural equation modeling

Cited by 54 publications

References 32 publications

Do drivers differ in their attitudes on speed limit compliance between work and private settings? Results from a group of Nigerian drivers

Do drivers differ in their attitudes on speed limit compliance between work and private settings? Results from a group of Nigerian drivers

A Landscape of Research on Bus Driver Behavior: Taxonomy, Open Challenges, Motivations, Recommendations, Limitations, and Pathways Solution in Future

Multiple Utility Analyses for Sustainable Public Transport Planning and Management: Evidence from GPS-Equipped Taxi Data in Haikou

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