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Railways are a well-known example of complex critical infrastructure, incorporating socio-technical systems with humans such as drivers, signallers, maintainers and passengers at the core. The technological evolution including interconnectedness and new ways of interaction lead to new security and safety risks that can be realised, both in terms of human error, and malicious and non-malicious behaviour. This study aims to identify the human factors (HF) and cyber-security risks relating to the role of signallers on the railways and explores strategies for the improvement of “Digital Resilience” – for the concept of a resilient railway.

Overall, 26 interviews were conducted with 21 participants from industry and academia.

The results showed that due to increased automation, both cyber-related threats and human error can impact signallers’ day-to-day operations – directly or indirectly (e.g. workload and safety-critical communications) – which could disrupt the railway services and potentially lead to safety-related catastrophic consequences. This study identifies cyber-related problems, including external threats; engineers not considering the human element in designs when specifying security controls; lack of security awareness among the rail industry; training gaps; organisational issues; and many unknown “unknowns”.

The authors discuss socio-technical principles through a hexagonal socio-technical framework and training needs analysis to mitigate against cyber-security issues and identify the predictive training needs of the signallers. This is supported by a systematic approach which considers both, safety and security factors, rather than waiting to learn from a cyber-attack retrospectively.

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

Errors are inevitable, resulting from the human condition itself, system failures and the interaction of both. It is essential to know how to deal with their occurrence, managing them. However, the negative tone associated with them makes it difficult for most organizations to talk about mistakes clearly and transparently, for fear of being harmed, preventing their detection, treatment and recovery. Consequently, errors are not managed, remaining accumulated in the system, turning into successive failures. Organizations need to recognize the inevitability of errors, making the system robust, through leadership and an organizational culture of error management. This study aims to understand the role of these influencing variables in an error management approach.

In this paper, the authors applied the methodology of a quantitative nature based on a questionnaire survey that analyses error management, leadership and the organizational culture of error management of 380 workers in Portuguese companies.

The results demonstrate that leadership directly influences error management and indirectly through the organizational culture of error management, giving this last variable a mediating role.

The study covers companies from different sectors of activity on a topic that is little explored in Portugal, but part of the daily life of organizations, which should deserve greater attention from directors and managers, as they assume a privileged position to promote and develop error management mechanisms. Error management must be the daily work of leaders. This study contributes to theoretical knowledge and business practice on error management.

The article discusses the current relevance of artificial intelligence (AI) in research and how AI improves various research methods. This article focuses on the practical case study of systematic literature reviews (SLRs) to provide a guideline for employing AI in the process.

Researchers no longer require technical skills to use AI in their research. The recent discussion about using Chat Generative Pre-trained Transformer (GPT), a chatbot by OpenAI, has reached the academic world and fueled heated debates about the future of academic research. Nevertheless, as the saying goes, AI will not replace our job; a human being using AI will. This editorial aims to provide an overview of the current state of using AI in research, highlighting recent trends and developments in the field.

The main result is guidelines for the use of AI in the scientific research process. The guidelines were developed for the literature review case but the authors believe the instructions provided can be adjusted to many fields of research, including but not limited to quantitative research, data qualification, research on unstructured data, qualitative data and even on many support functions and repetitive tasks.

AI already has the potential to make researchers’ work faster, more reliable and more convenient. The authors highlight the advantages and limitations of AI in the current time, which should be present in any research utilizing AI. Advantages include objectivity and repeatability in research processes that currently are subject to human error. The most substantial disadvantages lie in the architecture of current general-purpose models, which understanding is essential for using them in research. The authors will describe the most critical shortcomings without going into technical detail and suggest how to work with the shortcomings daily.

The purpose of this paper is to investigate the medical incident responses from two public hospitals in Hong Kong, namely, Kowloon Hospital and Caritas Medical Centre, in order to improve the strategic preparation for crisis management in hospitals.

The paper analyses two medical incidents using Situational Crisis Communication Theory by Coombs (2007). The two case studies presented herein demonstrate the importance of consistency in terms of crisis responses.

For the first case, the crisis responses from different parties after the incident, including Hospital Authority, the doctor and the nurses from Kowloon Hospital, are contradicting to each other. First, Hospital Authority confirmed that the incident is solely an accident which is a denial response. Second, the doctor passed the responsibility to the nurses which is a scapegoating response. Third, the nurses tend to reduce the responsibility for the death of patient by excusing strategy. As a whole, their responses are inconsistent to each other. For the second case, Caritas had initially denied the responsibilities, but finally had given partial apology under public pressure. That makes people think that Caritas does not really regret.

Rebuilding posture should be used instead of denial and diminishment posture. However, public organization and civil servants are reluctant to use a full apology due to possible legal consequences. The apology ordinance would ease the pressure to express regret and sympathy.

Aerospace is a demanding technological and industrial sector. Several regulations and policies via innovative digital transformation have been integrated to impact production systems and supply chains, including safety measures. Studies demonstrated that the Fourth Industrial Revolution (4IR) technologies could enhance productivity growth and safety measures. The 4IR role in influencing airlines’ growth is yet to receive in-depth studies in South Africa. Thus, this study aims to investigate the role of 4IR technologies in influencing airlines’ growth in South Africa.

This research used a qualitative research method. Primary data were compiled via 56 face-to-face semi-structured interviews with major stakeholders. The study achieved saturation. A thematic method was used to analyse the collected data.

Findings reveal the nine major factors influencing South African airlines’ growth in the 4IR era. This includes investment in ergonomics applications and research, governance is driven by 4IR, collaboration and incorporation of 4IR concepts, partnership with drone technology and high precision and efficiency with 4IR. Others are reskilling and upskilling, investment in 4IR software, policies to promote 4IR usage in the industry and policies to reduce human interface.

Understanding the relative significance of 4IR technologies’ role in airlines’ growth can assist critical stakeholders in promoting innovative policies and regulations tailored towards digitalised aerospace. Thus, the study contributes to strategies to improve digital innovation, airline growth and safety as components of the air travel demands in South Africa.

In the last decade, the Industry 4.0 paradigm had started to rapidly expand to the logistics domain. However, Logistics 4.0 is still in an early adoption stage: some areas such as warehousing are still exploring its applicability, and the technological implementation of this paradigm can become fuzzy. This paper addresses this gap by examining the relationship among influencing factors, barriers, and benefits of Logistics 4.0 technologies in warehousing contexts.

Starting from a Systematic Literature Review (SLR) approach with 56 examined documents published in scientific journals or conference proceedings, a conceptual framework for Logistics 4.0 in warehousing is proposed. The framework encompasses multiple aspects related to the potential adopter’s decision-making process.

Influencing factors toward adoption, achievable benefits, and possible hurdles or criticalities have been extensively analyzed and structured into a consistent picture. Company’s digital awareness and readiness result in a major influencing factor, whereas barriers and criticalities are mostly technological, safety and security, and economic in nature. Warehousing process optimization is the key benefit identified.

This paper addresses a major gap since most of the research has focused on specific facets, or adopted the technology providers’ perspective, whereas little has been explored in warehousing from the adopters’ view. The main novelty and value lie in providing both academics and practitioners with a thorough view of multiple facets to be considered when approaching Logistics 4.0 in logistics facilities.

After knee replacement surgery, rehabilitation is needed to recover to normal levels of mobility. A continuous passive motion (CPM) machine is usually introduced at this stage to aid rehabilitation. However, the redundant structure and complex mechanism of the existing machine has resulted in irregular use. The purpose of this paper is to redesign the current machine.

The mechanical and electrical systems of the current machine were studied alongside interviews with stakeholders. Problems with the existing machine were identified. Related information was gathered in both the engineering and medical aspects. The redesign concept of the equipment was specified following engineering analyses to develop the final model. Finite element analysis was performed to ensure the appropriate size and dimension of the equipment. The prototype of the redesigned CPM was manufactured in-house. Product testing was conducted with 40 volunteers including experienced therapists, nurses, university students and working-age people.

Compared to the previous machine, the newly designed model was improved in both functioning and manufacturing costs. The redesigned machine is more durable and consists of a less complex structure.

The redesigned machine introduces some new features and removes unnecessary functions. As a result, the model costs less and hence, is considered beneficial to the general public. More utilization is expected which could eventually reduce the therapists’ workload at the hospital. This research provides well-defined processes of the product development starting from the users’ requirement analysis to the prototype testing stage.

On shield tunnel construction (STC) site, human error is widely recognized as essential to accident. It is necessary to explain which factors lead to human error and how these factors can influence human performance. Human reliability analysis supports such necessity through modeling the performance shaping factors (PSFs). The purpose of this paper is to establish and validate a PSF taxonomy for the STC context.

The approach taken in this study mainly consists of three steps. First, a description of the STC context is proposed through the analysis of the STC context. Second, the literature which stretch across the PSF methodologies, cognitive psychology and human factors of STC and other construction industries are reviewed to develop an initial set of PSFs. Finally, a final PSF set is modified and validated based on STC task analysis and STC accidents cases.

The PSF taxonomy constituted by 4 main components, 4 hierarchies and 85 PSFs is established for human behavior modeling and simulation under the STC context. Furthermore, by comparing and evaluating the performance of STC PSF and existing PSF studies, the proposed PSF taxonomy meets the requirement for qualitative and quantitative analysis.

The PSF taxonomy can provide a basis and support for human behavior modeling and simulation under the STC context. Integrating PSFs into a behavior simulation model provides a more realistic and integrated assessment of human error by manifesting the influence of each PSFs on the cognitive processes. The simulation results can suggest concrete points for the improvement of STC safety management.

This paper develops a taxonomy of PSFs that addresses the various unique influences of the STC context on human behaviors. The harsh underground working conditions and diverse resources of system information are identified as key characteristics of the STC context. Furthermore, the PSF taxonomy can be integrated into a human cognitive behavior model to predict the worker’s behavior on STC site in future work.

The paper aims to convert into useable guidelines, the knowledge related to human factors and tasks' organisation, which are embedded in one of the most exciting maintenance actions that are carried out, the pitstop in Formula 1 races.

The paper opted for a fault tree analysis (FTA) to de-construct all the sub-tasks and their possible deviations from desirable situations and to evaluate the most relevant information needed for carrying out the pitstop operation. Besides, the SHELL model was applied in a second stage to evaluate the interaction between human being and human interfaces with other components of the system. Once this set of information was crystallised, the research translated it into useable guidelines for organising industrial maintenance actions using the same approach and possible reaching the same results.

The results of this study is a structured set of guidelines that encompasses the most paramount aspects that should be considered for setting correct maintenance actions. They represent a “guide” for including the different angles that are included during these operations.

The guidelines are potentially applicable to every maintenance operation. The guidelines should be tested on different working domains to check their applicability besides the racing world.

This study is a reverse engineering work for creating a scheme to include into maintenance operations aspects such as crew athlete-like fitness, training, technology, organisational issues, safety, ergonomics and psychology.

The value of the paper is deconstructing the results of one of the most successful and prepared maintenance action. The paper takes a different approach in proposing how to structure and create maintenance solutions. The difference in approaches between the maintenance during the pitstop of Formula 1 car and industrial applications enhances the gap that needs still to be filled for further improving maintenance actions out of the racing world.