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Healthcare organizations have been facing challenges due to high costs and low efficiency in health services. The growth of costs and losses caused by avoidable mistakes lead to the search for solutions, and Health Lean Management appears as a potential solution to help in solving service quality problems, as well as reducing risks. This study aims to analyse the state of the art in the literature centred on the Lean approach in the context of risk management in healthcare organizations, and to identify new research opportunities, highlighting possible lines of future research.

Following a systematic literature review approach, 51 papers were considered relevant for this research, and reviewed to explore the development of literature in this area.

Based on the results, five main research streams were identified: (1) risk management oriented towards patient safety; (2) risk management oriented towards employee safety; (3) importance of attitudes and behaviours in risk reduction projects; (4) Lean tools used in healthcare risk management and (5) Integration of approaches. Moreover, several shortcomings were identified in literature.

Identified shortcomings represent significant opportunities for further research development.

In alignment with the European Union’s Vision Zero initiative to eliminate road fatalities by 2050, leveraging technological advancements becomes crucial for addressing the challenges of vulnerable road users (VRUs), and for mitigating the impact of human error. Despite increasing scholarly interest in applications of extended reality (XR), a research gap persists, particularly in the role of XR in transportation safety. Therefore, the aim of the study was to fill this gap through a systematic literature review to evaluate comprehensively the potential scope and practical applicability of XR technologies in enhancing the safety of VRUs.

A systematic review was undertaken, following PRISMA guidelines meticulously, in which 80 relevant articles from databases, such as Scopus and Science Direct, were identified and analysed.

The results of the analysis revealed the potential of XR beyond pedestrians and cyclists, and highlighted a lack of research about the impact of XR with regard to the personal traits or abilities of VRUs. The results of a thorough analysis confirmed the potential of XR as a promising solution for an approach to collaborative co-creation in addressing the safety challenges of VRUs. In addition, the integration of eye-tracking with virtual reality emerged as a promising innovation for enhancing the safety of vulnerable road users.

Theoretical implications include enhancing the understanding of applications of XR in VRUs’ safety and providing insights into future research possibilities and methodological approaches. Valuable insights into search strategies and inclusion-exclusion criteria can guide future research methodologies.

Practically, the findings from the study offer insights to assist urban planners and transportation authorities in incorporating XR technologies effectively for VRUs safety. Identifying areas for further development of XR technology could inspire innovation and investment in solutions designed to meet the safety needs of VRUs, such as enhanced visualisation tools and immersive training simulations.

The findings of previous research underscore the vast potential of XR technologies within the built environment, yet their utilisation remains limited in the urban transport sector. The intricacies of urban traffic scenarios pose significant challenges for VRUs, making participation in mobility studies hazardous. Hence, it is crucial to explore the scope of emerging technologies in addressing VRUs issues as a pre-requisite for establishing comprehensive safety measures.

Computer vision (CV) offers a promising approach to transforming the conventional in-person inspection practices prevalent within the construction industry. However, the reliance on centralized systems in current CV-based inspections introduces a vulnerability to potential data manipulation. Unreliable inspection records make it challenging for safety managers to make timely decisions to ensure safety compliance. To address this issue, this paper proposes a blockchain (BC) and CV-based framework to enhance safety inspections at construction sites.

This study adopted a BC-enhanced CV approach. By leveraging CV and BC, safety conditions are automatically identified from site images and can be reliably recorded as safety inspection data through the BC network. Additionally, by using this data, smart contracts coordinate inspection tasks, assign responsibilities and verify safety performance, managing the entire safety inspection process remotely.

A case study confirms the framework’s applicability and efficacy in facilitating remote and reliable safety inspections. The proposed framework is envisaged to greatly improve current safety inspection practices and, in doing so, contribute to reduced accidents and injuries in the construction industry.

This study provides novel and practical guidance for integrating CV and BC in construction safety inspection. It fulfills an identified need to study how to leverage CV-based inspection results for remotely managing the safety inspection process using BC. This work not only takes a significant step towards data-driven decision-making in the safety inspection process, but also paves the way for future studies aiming to develop tamper-proof data management systems for industrial inspections and audits.

Effective voice behavior in healthcare workers is critical for patient safety, quality improvement and workforce well-being. A review of the literature on voice behavior in healthcare highlights that little is known about the voice behaviors of new graduates in allied health and that current theory, from medical and nursing research, does not adequately apply to this sector. New knowledge about voice behavior for this sector of the workforce will support education and healthcare institutions in building and sustaining a healthy voice behavior culture.

This paper reports on phase two of a two-phase study looking at the voice behavior experiences of new allied health graduates over one year. Using a realist perspective and narrative analysis, we uncover and illustrate what works, with whom and under what conditions.

Four synthesized narratives outline the contexts and mechanisms that result in different voice behavior outcomes – speaking up effectively, speaking up with unmet expectations, not speaking up and a reduction in speaking up over time. Experiences of positive interprofessional collaboration and reflective supervision supported effective voice behavior.

This study used a case study approach, focusing on healthcare providers within a large New Zealand city and a cohort of 10 participants. Some researchers argue that small numbers limit the generalization of findings to different populations. Realists argue that, given the way in which knowledge is developed using realist methodologies, the resultant theory is portable. Interviews were conducted online during the COVID-19 pandemic. This may have impacted the connection between the interviewer and interviewee, causing the interviewees to not express their true thoughts. However, the interviewer did take time to connect with the interviewees and build trust over the three interviews over one year. Participants did not capture the diversity in the allied health workforce – most identified as female and none identified as Māori/Indigenous. And finally, participants could inhibit or exaggerate information due to the influence of social desirability. This does not appear to be a significant limitation in this study, given the many examples shared by the participants highlighted their challenges.

This study provides an in-depth exploration of how new graduates in allied health experience speaking up. Our findings enrich the knowledge of speaking up by using synthesized narratives to provide insights into what factors can enable a healthy speaking up culture within the new graduate allied health workforce. This is new knowledge that will be of interest at the individual, team and organizational levels of healthcare. The findings will support curriculum design and new graduate support frameworks for the education and health sectors. Highlighted in this study are the importance of the following factors in supporting speaking up for allied health new graduates: the employment of reflective supervision, purposeful facilitation of team belonging and interprofessional collaboration and tailored speaking up training for allied health new graduates and leaders in healthcare.

By taking a realist perspective and using narrative analysis, we gain an understanding of the voice behavior experiences of new graduates in allied health and the contextual factors and mechanisms that activate effective voice behavior in sub-acute and rehabilitation settings. These findings differ from nursing and medicine and highlight the benefits of reflective supervision and interprofessional collaborative practice.

The purpose of this paper is to improve the understanding of the social contexts of sustainable Lean culture in healthcare by examining self-efficacy (SE) as a fundamental construct related to the value of perceived readiness, prior education of Lean and the importance of leadership’s system-level support.

A descriptive correlational study was conducted to identify the relationships between SE and Lean readiness factors, SE and prior Lean training, SE and clinical vs administrative roles and SE and perceived system-level support in a large health system.

There was a statistically significant difference in self-reported readiness to use Lean tools between individuals who had received Lean training during their academic education and those who had not; however, their level of education did not impact SE. Lastly, and perhaps most important, the learner who embodies SE also has system-level support.

Future directions of this research, in addition to assessing team readiness as other studies suggest, would be to evaluate individual team member readiness by gauging SE and addressing deficits prior to the deployment of process improvement (PI) projects to promote success and sustainability.

This contributes to the ongoing scholarship of Lean management systems, providing clinical and non-clinical leaders with a contextual understanding of their supportive role in the SE of teams.

This study demonstrates the value of understanding SE of individual team members and how it can contribute to overall improved team outcomes, directly impacting the sustainability of Lean change culture and its promotion of improved patient safety, cost efficiencies and access to care.

Construction is a risky industry. Therefore, organizations are seeking ways towards improving their safety performance. Among these, the integration of technology into health and safety leads to enhanced safety performance. Considering the benefits observed in using technology in safety, this study aims to explore digital technologies' use and potential benefits in construction health and safety.

An extensive bibliometrics analysis was conducted to reveal which technologies are at the forefront of others and how these technologies are used in safety operations. The study used two different databases, Web of Science (WoS) and Scopus, to scan the literature in a systemic way.

The systemic analysis of several studies showed that the digital technologies use in construction are still a niche theme and need more assessment. The study provided that sensors and wireless technology are of utmost importance in terms of construction safety. Moreover, the study revealed that artificial intelligence, machine learning, building information modeling (BIM), sensors and wireless technologies are trending technologies compared to unmanned aerial vehicles, serious games and the Internet of things. On the other hand, the study provided that the technologies are even more effective with integrated use like in the case of BIM and sensors or unmanned aerial vehicles. It was observed that the use of these technologies varies with respect to studies conducted in different countries. The study further revealed that the studies conducted on this topic are mostly published in some selected journals and international collaboration efforts in terms of researching the topic have been observed.

This study provides an extensive analysis of WoS and Scopus databases and an in-depth review of the use of digital technologies in construction safety. The review consists of the most recent studies showing the benefits of using such technologies and showing the usage on a systemic level from which both scientists and practitioners can benefit to devise new strategies in technology usage.

The purpose of this study is to determine propeller damage based on acoustic recordings taken from unmanned aerial vehicle (UAV) propellers operated at different thrust conditions on a test bench. Propeller damage is especially critical for fixed-wing UAVs to sustain a safe flight. The acoustic characteristics of the propeller vary with different propeller damages.

For the research, feature extraction methods and machine learning techniques were used during damage detection from propeller acoustic data. First of all, sound recordings were obtained by operating five different damaged propellers and undamaged propellers under three different thrusts. Afterwards, the harmonic-to-noise ratio (HNR) feature extraction technique was applied to these audio recordings. Finally, model training and validation were performed by applying the Gaussian Naive Bayes machine learning technique to create a diagnostic approach.

A high recall value of 96.19% was obtained in the performance results of the model trained according to damaged and undamaged propeller acoustic data. The precision value was 73.92% as moderate. The overall accuracy value of the model, which can be considered as general performance, was obtained as 81.24%. The F1 score has been found as 83.76% which provides a balanced measure of the model’s precision and recall values.

This study include provides solid method to diagnose UAV propeller damage using acoustic data obtain from the microphone and allows identification of differently damaged propellers. Using that, the risk of in-flight failures can be reduced and maintenance costs can be lowered with addressing the occurred problems with UAV propeller before they worsen.

This study introduces a novel method to diagnose damaged UAV propellers using the HNR feature extraction technique and Gaussian Naive Bayes classification method. The study is a pioneer in the use of HNR and the Gaussian Naive Bayes and demonstrates its effectiveness in augmenting UAV safety by means of propeller damages. Furthermore, this approach contributes to UAV operational reliability by bridging the acoustic signal processing and machine learning.

This paper aims to critically evaluate the impact of empowering leadership on safety behavior and safety climate during safety monitoring at a nuclear power plant (NPP) in the United Arab Emirates (UAE).

Data were collected using questionnaires filled out by 500 participants from the UAE nuclear sector. The relationships among the variables were analyzed using structural equation modeling.

The results indicated that empowering leadership has a positive impact on safety behavior, and a positive safety climate leads to increased levels of safety behavior (compliance and participation). The results also showed that safety climate partially mediates the relationship between empowering leadership and safety behavior.

This study contributes to the existing knowledge regarding empowering leadership, safety monitoring, behavior and climate. Because limited information is available on this topic, this study extends the research on the relationship between empowering leadership and safety research at an NPP. Specifically, it outlines that safety monitoring partially mediates the relationship between empowering leadership and safety behavior. This research enables NPPs worldwide to incorporate empowering leadership to enhance safety monitoring and ensure better safety behavior and climate.

Forced labour is one of the most exploitative practices in supply chains, generating serious human right abuses. The authors seek to understand how relationships for reducing forced labour are influenced by institutional logics. The emerging supply chain efforts of social enterprises offer particularly intriguing approaches, as their social mission can spur creative new approaches and reshape widely adopted management practices.

The authors study supplier relationships in the smartphone industry and compare the evolving practices of two cases: the first, a growing novel social enterprise; and the second, a high-profile commercial firm that has adopted a progressive role in combating forced labour.

The underlying institutional logic influenced each firm's willingness to act beyond its direct suppliers and to collaborate in flexible ways that create systematic change. Moreover, while both focal firms had clear, well-documented procedures related to forced labour, the integration, rather than decoupling, of forced labour and general supply chain policies provided a more effective way to reduce the risks of forced labour in social enterprises.

As authors’ comparative case study approach may lack generalizability, future research is needed to broadly test their propositions.

The paper identifies preconditions in terms of institutional logics to successfully reduce the risk of forced labour in supply chains.

This paper discusses how social enterprises can provide a learning laboratory that enables commercial firms to identify options for supplier relationship improvement.

The study aims to build upon the Resource-based view of the firm (RBV) and Dynamic Capability Theory (DCT) to perform a meta-analysis on the eco-innovation/SMEs’ sustainable performance relationship.

Employing a psychometric meta-analytic approach with a random-effects model, the study examines a sample of 134,841 SMEs covering 99 studies and 233 study effects. Subgroup and meta-regression analysis were used to test the study`s hypotheses in Comprehensive Meta-Analysis (CMA) statistical software.

Results unveil that the average impact of eco-innovation on SMEs` sustainable performance is positively significant but moderate. Moreover, it was found that eco-process, eco-product, eco-organizational, and eco-marketing innovations positively influence SMEs’ sustainable performance, but the impact of eco-organizational innovation is the strongest. Findings further reveal that eco-innovation positively influences economic, social, and environmental performance, but its effect on social performance is the largest. Moreover, our findings reveal that contextual factors, including industry type, culture, industry intensity, global sustainable competitive index, and human development index, moderate the eco-innovation/SMEs’ sustainable performance relationship. Lastly, methodological factors, namely sampling technique, study type, and publication status, account for study-study variance.

Our findings imply that investing in eco-innovation is worthwhile for SMEs. Therefore, CEOs/managers of SMEs must adopt eco-innovation initiatives by establishing a sustainability vision, developing employee environmental development and training, building a stakeholder management system, and promoting employee engagement in sustainability activities.

The study develops a holistic conceptual framework to consolidate the distinct types of eco-innovation and their association with the sustainable performance of SMEs for the first time in this research stream, thereby resolving the anecdotal results and synthesizing the fragmented literature across culture, discipline, and contexts.