Weighing and prioritization of individual factors affecting the performance of industries firefighters

Heydari, Payam; Babamiri, Mohammad; Tapak, Leili; Golmohammadi, Rostam; Kalatpour, Omid

doi:10.1016/j.firesaf.2021.103512

Cited by 5 publications

(3 citation statements)

References 36 publications

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“…Situational awareness was identified by Heydari et al [ 42 ] as the most important cognitive factor influencing the performance of industrial firefighters. In particular, shared situational awareness is significant to enable team members to adapt to a (rapidly) changing environment [ 39 ].…”

Section: High Responsibility Teamsmentioning

confidence: 99%

Development and validation of a questionnaire, the REST-Q Fire, to identify teamwork-related resources and stressors in firefighting operations

Heinemann,

Aust,

Peifer

et al. 2024

PLoS ONE

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In the complex work environments of firefighting teams, it is often human error or difficulties in teamwork that lead to dangerous situations. To prevent these, it is essential to know the teamwork-related stressors and resources in firefighting operations. A measurement tool is needed to evaluate these stressors and resources. A successive instrument development process was conducted to identify the relevant teamwork-related stressors and resources in firefighting operations. First, interviews with experienced firefighters, and second, a document analysis were conducted and evaluated to provide an overview of the teamwork-related stressors and resources. Thereupon, a questionnaire, the REST-Q Fire, was developed asking about the experienced frequency and intensity of the identified teamwork-related stressors and resources in firefighting operations. Afterwards, an online study with firefighters was conducted (N = 491). CFAs confirmed the assumed structure of the REST-Q Fire and a positive correlation of the intensity of stressors with stress was shown (r = .19 - .27). Further, the resources were overall more frequently and intensively perceived than the stressors. The most important stressors were ‘behavior of leaders’ (M (SD)frequency = 2.80 (0.83), M (SD)intensity = 3.59 (1.12)), and ‘behavior of team members’ (M (SD)frequency = 2.77 (0.75), M (SD)intensity = 3.59 (1.05)). The most important resources, on the other hand, were ‘knowledge about skills and behavior of team members’ (M (SD)frequency = 3.96 (0.63), M (SD)intensity = 4.24 (0.78)), ‘watch out for/ check on each other’ (M (SD)frequency = 3.96 (0.70), M (SD)intensity = 4.20 (0.80)), and ‘reliability of team members’ (M (SD)frequency = 3.96 (0.51), M (SD)intensity = 4.16 (0.73)). As a result, training needs for trainees in the fire service and experienced firefighters were derived.

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Section: High Responsibility Teamsmentioning

confidence: 99%

Development and validation of a questionnaire, the REST-Q Fire, to identify teamwork-related resources and stressors in firefighting operations

Heinemann,

Aust,

Peifer

et al. 2024

PLoS ONE

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“…The first step involved compiling a comprehensive list of potential hazards from various sources, including a literature review and interviews with a panel of experts [ [32] , [33] , [34] , [35] , [36] ]. Table 4 shows the findings of identifying 25 important risks.…”

Section: Case Studymentioning

confidence: 99%

Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment

Soltani,

Mirzaei Aliabadi

2023

Heliyon

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“…Otherwise, making different improvements simultaneously create high costs for the companies that threaten the Sustainability of these projects. Therefore, multi-criteria decision-making (MCDM) approaches were considered by various scholars for criteria weighting and alternative ranking [3]. For instance, AHP and DEMATEL methods were used with the aim of finding the SWARA model was also considered for the same purposes [6].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Environmental Priorities for Green Project Investments Using an Integrated q-Rung Orthopair Fuzzy Modeling

et al. 2022

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Green energy projects contribute to sustainable economic development of countries with the employment of environmentally friendly energy production strategies. However, environmental priorities should be examined for this situation. Therefore, priority analysis should be executed for the environmental issues while implementing green investment projects. Accordingly, this study aims at proposing a unique decision-making model based on orthopair fuzzy sets and the golden cut degrees for the environmental priorities of green project investments. The main novelty of the study stems from its proposed integrated model by equipping the Multi-SWARA, and TOPSIS based on the q-ROFSs technique with the golden cut. A set of criteria is identified for measuring the green projects' environmental priorities while several project alternatives are also determined with the supporting literature. Appropriately, the extensions of Multi-SWARA and TOPSIS methods have been applied for weighting and ranking the factors, respectively, in the integrated approach. Additionally, a comparative evaluation is performed with the help of VIKOR method to rank the alternatives. Besides, the sensitivity analysis is applied to illustrate the coherency of the weighting results in the decision-making approach. Accordingly, 5 cases are considered to measure the effects of changing weight results. It is defined that this model is coherent and could be extended for further studies. It is concluded that the reduction of emissions is the most essential item for the environmental priorities of green project investments. Pollution control, waste management and eco-friendly transportation activities are the most critical alternatives. Therefore, this study recommends that investors of green projects should prioritize the strategies of minimizing carbon emissions problem. In this context, investing in renewable energy technologies will help green project investors solve this problem.

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Weighing and prioritization of individual factors affecting the performance of industries firefighters

Cited by 5 publications

References 36 publications

Development and validation of a questionnaire, the REST-Q Fire, to identify teamwork-related resources and stressors in firefighting operations

Development and validation of a questionnaire, the REST-Q Fire, to identify teamwork-related resources and stressors in firefighting operations

Risk assessment of firefighting job using hybrid SWARA-ARAS methods in fuzzy environment

Analysis of Environmental Priorities for Green Project Investments Using an Integrated q-Rung Orthopair Fuzzy Modeling

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