Applying systems thinking to improve the safety of work-related drivers: A systematic review of the literature

Newnam, Sharon; Louis, Renée M. St.; Stephens, Amanda N.; Sheppard, Dianne Melinda

doi:10.1016/j.jsr.2022.09.016

Cited by 6 publications

(2 citation statements)

References 61 publications

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“…Deaths at the workplace are also published country by country, but for many years also by large organizations in their sustainability reports. Road traffic crashes as origins of workplace deaths are often the dominating cause at work but are normally not separated in work accident statistics (Newnam et al, 2022;Newnam & Watson, 2011)). With the introduction and expectation of sustainability reports including traffic safety and safety footprints of large organizations (Trafikverket, 2019;Stockholm_Declaration, 2020) new challenges to collect and to analyse safety related data will arise.…”

Section: Discussionmentioning

confidence: 99%

Fatalities in value chains—an attempt to classify road traffic crashes in accordance with the United Nations General Assembly resolution 74/299

Kullgren

Stigson

Rizzi

et al. 2023

TSR

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Large corporations are today expected or obliged to report on accidental deaths and serious injuries to employed or contracted employed as a part of reporting on sustainability and workplace safety. Data about road crashes are part of such events and are therefore, but not separately, collected and presented. In Europe, 40% to 60% of all work-related accidents resulting in death has been reported to be road traffic accidents. In 2020, the Stockholm Declaration urged all corporations to report on their safety footprint including their entire value chain. The aims of the present study were to use a new definition of safety footprint and to quantify those killed as employed and at work, and those killed in a crash where the other part was at work, as so called third parties, to transports for duty with employed drivers. The Swedish Transport Administration (STA) in-depth database of fatal crashes was used, that covers all fatalities classified as road traffic related and consists of information from the police, medical journals, autopsy reports, accident analyses performed by STA, and witness statements. All fatalities excluding suicides or those caused by sickness occurring during year 2019 were investigated (n = 214). 11% (23/214) of the fatalities occurred when the killed person was at work and 16 while commuting. 37% of the fatal accidents occurred when the killed road user or the other part was at work. In total, almost half of the fatalities in the road transport system were related to work in some way when including both the fatally injured and their collision partners. A larger proportion of non-privately owned and procured vehicles was found for the vehicles of the collision partners compared to the vehicles of the fatally injured. In approximately one third of the fatal accidents a procurement of a transport service was involved. The Swedish Work Environment Authority (SWEA) identified 10 of the 23 fatalities at work investigated and none of these accidents was found to be investigated by the police as a crime related to the work environment. In conclusion, almost half of the fatalities in the road transport system in 2019 were related to work in some way, either the fatally injured or their collision partners were at work or while commuting. When including the third-party casualties, the problem becomes much bigger and more complex. In Sweden fatalities related to work are underreported, as the SWEA does not receive basic data. Efforts are needed to improve reporting of work-related road fatalities. It was found that the police did not investigate road traffic fatalities as death at workplace. It is crucial that the police start to follow the intention of regulations linked to workplace safety. If not, the possibility to collect relevant data for organizations to report on their safety footprint is limited. It is complicated to collect, classify and analyse value chain fatal crash information, mainly due to that the police do not investigate fatal road crashes as possibly work-related events. It is recommended that organizations manage their own data collection if they wish to report on their safety footprint data.

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Section: Discussionmentioning

confidence: 99%

Fatalities in value chains—an attempt to classify road traffic crashes in accordance with the United Nations General Assembly resolution 74/299

Kullgren

Stigson

Rizzi

et al. 2023

TSR

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“…Unfortunately, many managers still primarily focus on meeting requirements such as timely delivery, transport conditions, average road speed, driving, and service quality, neglecting the assessment of risks associated with road cargo transport (Naevestad et al, 2017;Newnam et al, 2022). It is worth noting that studies on road cargo transport have predominantly concentrated on accidents, particularly those involving the transportation of hazardous materials (Oggero et al, 2006;Samuel et al, 2009;Trépanier et al, 2009;Wang et al, 2005;Yang et al, 2010;Zhao et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Bayesian Modelling Applied to Evaluate Road Cargo Transport Risks

Teles¹,

Librantz

Neto³

et al. 2023

Preprint

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In recent years, applying quantitative risk analysis in Road cargo transport (RCT) has yielded successful results in assessing risks associated with industrial industries. Recent studies have highlighted the significance of different modes of transportation (such as roads, rails, pipelines, and inland waterways)for hazardous materials, emphasizing their role in determining risk levels. Among these modes, road transport via trucks stands out as a crucial component for economic development and is commonly employed for transporting various types of cargo. To effectively evaluate the risk level of a given activity within RCT, it is essential to determine the severity index for each potential situation that may arise during the transportation process. In this context, this research aims to investigate and calculate the risks associated with RCT by employing Bayesian Networks. Computational models were implemented using Bayesian Network software, and data input was carried out using Microsoft Excel®spreadsheets. The methodology employed for this study entailed field research with the involvement of experts and academic sources, along with the utilization of a systematic literature review. Additionally, the Delphi technique was applied, followed by a survey. The results pointed that the proposed model could effectively aid in identifying the level of risk involved in RCT operations across different scenarios. Furthermore, this model enables managers to evaluate the probability of one or more risk factors occurring during operations, facilitating the implementation of more efficient mitigation measures.

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