Wafa Boulagouas

Purpose: Despite efforts to improve safety management practices in industrial companies, major accidents seem to be inevitable. Many accidents still occur because companies are unable to learn from past occurrences due to ineffective incident and accident learning processes. This study proposes a learning-based framework for industrial accidents investigation and contributes to accident prevention research.Design/methodology/approach: The proposed learning process includes the analysis of the industrial accident using the Event Tree Analysis (ETA) method, capitalisation of causative factors using the Swiss Cheese Model (SCM), and finally modelling the relationships among the accident causative factors and analysing their causality using the Fuzzy Cognitive Mapping (FCM) technique and running learning scenarios.Findings: The proposed learning process was applied to an industrial accident, and the results showed that human unsafe behaviours and unsafe supervision were the principal causative factors of the blowout accident.Practical implications: The proposed learning-based framework provides a structured approach for oil and gas companies to systematically analyse and learn from past accidents, enhancing their prevention strategies. Theoretically, the framework bridges the gap between theory and practice by demonstrating how established accident analysis methods can be combined and applied in a real-world industrial context.Originality/value: The proposed learning process combines accident analysis and investigation techniques with simulations for an in-depth and robust learning-based framework for accident prevention.

Purpose: Improvements to health and safety at work constantly involve organizational changes (OCs). However, the OC initiatives often fail at achieving their intended goals despite efforts to draw knowledge from various disciplines, such as sociology, psychology and information sciences, to guide the change implementation. This paper proposes a temporality approach to manage the resistance during an OC project based on the capitalization of the actors' behaviors (i.e. alignment/resistance) for successful OC implementation.Design/methodology/approach: Employees in an industrial company (N = 186) undergoing an OC answered a questionnaire survey. The statistical analysis approach was used to measure the influence of the constructs of the proposed temporality capitalization approach on the OC conduct.Findings: Results indicate that the considered constructs have positive and significant correlations with OC development. It has also been found that the employees' alignment is highly correlated with the opportunities they might gain from the OC.Practical implications: The proposed temporality capitalization approach shows that providing the employees with clear objectives is not sufficient to support the change, and it is suggested that the change management has to move a step further and seek to target the perspectives of the employees to energize them around the OC and maximize their alignment.Originality/value: In this paper, change management is approached through the temporality capitalization that confirms the importance of monitoring the change development through the alignment. In other terms, the curve of the adaptation of the change receivers matters and should attract more attention rather than the change implementation speed.

Multitasking while driving negatively affects driving performance and threatens people’s lives every day. Moreover, technology-based distractions are among the top driving distractions that are proven to divert the driver’s attention away from the road and compromise their safety. This study employs recent data on road traffic accidents that occurred in Spain and uses a machine-learning algorithm to analyze, in the first place, the influence of technology-based distracted driving on drivers’ infractions considering the gender and age of the drivers and the zone and the type of vehicle. It assesses, in the second place, the impact of drivers’ infractions on the severity of traffic accidents. Findings show that (i) technology-based distractions are likely to increase the probability of committing aberrant infractions and speed infractions; (ii) technology-based distracted young drivers are more likely to speed and commit aberrant infractions; (iii) distracted motorcycles and squad riders are found more likely to speed; (iv) the probability of committing infractions by distracted drivers increases on streets and highways; and, finally, (v) drivers’ infractions lead to serious injuries.

The use of communication technologies, e.g., mobile phones, has increased dramatically in recent years, and their use among drivers has become a great risk to traffic safety. The present study assessed the workload and road ordinary violations, utilizing driving data collected from 39 young participants who underwent a dual-task while driving a simulator, i.e., respond to a call, text on WhatsApp, and check Instagram. Findings confirmed that there are significant differences in the driving performance of young drivers in terms of vehicle control (i.e., lateral distance and hard shoulder line violations) between distracted and non-distracted drivers. Furthermore, the overall workload score of young drivers increases with the use of their mobile phones while driving. The obtained results contribute to a better understanding of the driving performance of distracted young drivers and thus they could be useful for further improvements to traffic safety strategies.

Road traffic plays a vital role in countries’ economic growth and future development. However, traffic accidents are considered a major public health issue affecting humankind. Despite efforts by governments to improve traffic safety, the misalignment between the policy efforts and on-ground infringements, distractions and breaches reflect the regulatory failure. This paper uses the Bayesian network method to investigate unsafe behaviors and traffic accidents involving unlicensed drivers as a perspective for the regulatory alignment assessment. The findings suggest that: (1) unlicensed drivers are more likely to have unsafe driving behaviors; (2) the probability of being involved in a severe traffic accident increases when the drivers are unlicensed and decreases in the case of licensed drivers; (3) young drivers are noticeably more likely to engage in unsafe behaviors, usually leading to serious injuries and deaths, when their driving licenses are invalid; (4) women are more likely to engage in right-of-way violations and to have collisions with no serious injuries, contrary to unlicensed men drivers, who are involved in other types of traffic accidents resulting in serious injuries.

Purpose: Decoupling of pressures ranging from regulatory compliance and stakeholders expectations to business competitiveness and sustainability, companies need to align their environmental strategies with a broader consideration of these influences. This paper aims at developing a dynamic alignment model to enhance the environmental performance that considers the influential pressures based on a multi-criteria decision-making process.Design/methodology/approach: Authors have proposed a dynamic model for the alignment of the environmental performance based on a hybrid multi-criteria decision-making approach combining the analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This model considers contemporary strategic dynamism of the environmental performance and provides a methodology to assist companies prioritizing the environmental aspects based on the influential pressures and deciding on the enhancement pathways.Findings: The proposed model based on a hybrid multi-criteria decision-making process allows prioritizing the environmental aspects considering the allocated weights to the alignment-triggered pressures and draw the way to develop different pathways to improve the alignment.Practical implications: The proposed dynamic alignment model presents an instrument for the continuous alignment of the environmental performance and an effective management of changes and contributes to minimize gaps and divergences.Originality/value: In this paper, the environmental performance has been approached through the contemporary strategic dynamism with the deployment of the multi-criteria decision-making techniques to yield an alignment framework for the environmental decision that combines the internal and external approaches for an effective and sustainable improvement of the environmental performance.

Purpose: The purpose of this paper is to deal with the allocation requirements of the dependability of the multiphase systems. Design/methodology/approach: It consists of a proposal for a combined methodology based on the simultaneous use of decomposition systems and reliability allocation method. Findings: In the developed methodology, the authors use the principles of risk assessment and propose a new formulation of weight allowance with reference to the structural‒functional dependence. Practical implications: The suggested methodology provides invaluable help to implementation process analysis. Originality/value: The adopted allocation approach is based on the use of a three-dimensional model: temporal, structural and functional decomposition of systems.