2022UNSWorks (UNSW Sydney)Open access

An Evidence-based safety management system for heavy truck transport operations

Lori Mooren

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Abstract

The aim of this thesis research was to find ways to improve safety in the heavy vehicle transport industry through the development of an evidence-based safety management system. This research was undertaken in light of disproportionate crash and injury risks associated with the heavy vehicle transport industry in comparison with other industries and other road users. No research to date has attempted to identify a set of safety management characteristics that are likely to reduce this risk. Although in recent years, work related road safety research has occurred, the problem of heavy vehicle crash related injury has largely been analysed as a public road safety road safety problem and largely dealt with through encouraging compliance to transport regulations. The nature of the trucking industry presents some unique challenges for safety management at an organisational level. This thesis argues that a “systems approach” with evidence-based safety management elements can be developed into an intervention program that is likely to improve safety outcomes in the heavy vehicle transport sector. Drawing from the knowledge from prior workplace safety and road safety research (Study 1), a study of safety management characteristics comparing those in good safety performing heavy vehicle operators and poor safety performers sought to synthesise the distinguishing features between them. Two empirical studies were conducted (Studies 2 and 3). The first was a survey of senior managers of Australian heavy vehicle operating companies. The second was an in-depth investigation of a sample of the survey participants to validate the self-reported survey, and to learn more about the reported characteristics and non-reported characteristics in situ. The findings of these studies provided the basis upon which to build a safety management system (SMS) suitable for heavy transport vehicle operations. This process resulted in the identification of 14 safety management practices that have strong research evidence for inclusion in a safety management system (SMS) for heavy truck operations. These findings, together with analysis of sound theoretical models to underpin the SMS, were used to shape the SMS. The SMS features three spheres of management practices – risk assessment and management, driver risk management and safety culture management. Drawing from the literature, a dynamic model of a safety management system is presented and explained. The original aim of this thesis research has been met, providing an evidence-based safety management system that is likely to reduce crash and injury risk when applied to heavy vehicle transport operations.

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The aim of this thesis research was to find ways to improve safety in the heavy vehicle transport industry through the development of an evidence-based safety management system. This research was undertaken in light of disproportionate crash and injury risks associated with the heavy vehicle transport industry in comparison with other industries and other road users. No research to date has attempted to identify a set of safety management characteristics that are likely to reduce this risk. Although in recent years, work related road safety research has occurred, the problem of heavy vehicle crash related injury has largely been analysed as a public road safety road safety problem and largely dealt with through encouraging compliance to transport regulations. The nature of the trucking industry presents some unique challenges for safety management at an organisational level. This thesis argues that a “systems approach” with evidence-based safety management elements can be developed into an intervention program that is likely to improve safety outcomes in the heavy vehicle transport sector. Drawing from the knowledge from prior workplace safety and road safety research (Study 1), a study of safety management characteristics comparing those in good safety performing heavy vehicle operators and poor safety performers sought to synthesise the distinguishing features between them. Two empirical studies were conducted (Studies 2 and 3). The first was a survey of senior managers of Australian heavy vehicle operating companies. The second was an in-depth investigation of a sample of the survey participants to validate the self-reported survey, and to learn more about the reported characteristics and non-reported characteristics in situ. The findings of these studies provided the basis upon which to build a safety management system (SMS) suitable for heavy transport vehicle operations. This process resulted in the identification of 14 safety management practices that have strong research evidence for inclusion in a safety management system (SMS) for heavy truck operations. These findings, together with analysis of sound theoretical models to underpin the SMS, were used to shape the SMS. The SMS features three spheres of management practices – risk assessment and management, driver risk management and safety culture management. Drawing from the literature, a dynamic model of a safety management system is presented and explained. The original aim of this thesis research has been met, providing an evidence-based safety management system that is likely to reduce crash and injury risk when applied to heavy vehicle transport operations.

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Available abstract

The aim of this thesis research was to find ways to improve safety in the heavy vehicle transport industry through the development of an evidence-based safety management system. This research was undertaken in light of disproportionate crash and injury risks associated with the heavy vehicle transport industry in comparison with other industries and other road users. No research to date has attempted to identify a set of safety management characteristics that are likely to reduce this risk. Although in recent years, work related road safety research has occurred, the problem of heavy vehicle crash related injury has largely been analysed as a public road safety road safety problem and largely dealt with through encouraging compliance to transport regulations. The nature of the trucking industry presents some unique challenges for safety management at an organisational level. This thesis argues that a “systems approach” with evidence-based safety management elements can be developed into an intervention program that is likely to improve safety outcomes in the heavy vehicle transport sector. Drawing from the knowledge from prior workplace safety and road safety research (Study 1), a study of safety management characteristics comparing those in good safety performing heavy vehicle operators and poor safety performers sought to synthesise the distinguishing features between them. Two empirical studies were conducted (Studies 2 and 3). The first was a survey of senior managers of Australian heavy vehicle operating companies. The second was an in-depth investigation of a sample of the survey participants to validate the self-reported survey, and to learn more about the reported characteristics and non-reported characteristics in situ. The findings of these studies provided the basis upon which to build a safety management system (SMS) suitable for heavy transport vehicle operations. This process resulted in the identification of 14 safety management practices that have strong research evidence for inclusion in a safety management system (SMS) for heavy truck operations. These findings, together with analysis of sound theoretical models to underpin the SMS, were used to shape the SMS. The SMS features three spheres of management practices – risk assessment and management, driver risk management and safety culture management. Drawing from the literature, a dynamic model of a safety management system is presented and explained. The original aim of this thesis research has been met, providing an evidence-based safety management system that is likely to reduce crash and injury risk when applied to heavy vehicle transport operations.

Key concepts: Truck, Transport engineering, Computer science, Business, Operations management, Engineering, Automotive engineering

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