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Virtual care is any interaction between a patient and clinician or clinicians, occurring remotely using information technologies. Like many international services, United Kingdom (UK) ambulance services use paramedics and nurses to undertake telephone assessments of patients calling the 999 emergency service line. Using their clinical knowledge, experience, and, at times, computer decision support software, these clinicians assess patients from a range of clinical acuities to confirm the need for an emergency response or identify and support those patients who can be cared for with remote treatment advice and referral. The Covid-19 pandemic saw UK ambulance services change and adapt their operating models to meet social distancing requirements, increase clinical staff numbers and mitigate staff becoming unavailable for work due to self-isolation. One such strategy was moving clinicians from Emergency Operations Centres (EOCs) to working at home. Staff utilised digital phone systems, remote computer-aided dispatch modules, remote clinical decision support software and video platforms, which allowed close to full functionality compared to inside typical EOCs. There is a dearth of literature exploring the comparative practice of clinicians from home rather than from EOCs. Therefore, this study reports the findings of a qualitative analysis of these effects from the clinician's perspective. The authors hope that the findings from this study will inform the operating, education and leadership practices of those delivering such services.

A convenience sample of telephone nurses and paramedics from one UK ambulance service in which home working had been implemented were contacted. 15 clinicians with recent home working experience responded to the invite out of a possible 31 (48%). All participants had previously practised remote assessment from within an EOC. Semi-structured interviews took place via video conferencing software and were recorded, transcribed and thematically analysed. An inductive approach was taken to generating codes and both researchers separately reading the transcripts before re-reading them, assigning initial themes and determining frequency.

Four main themes were identified with further associated sub-themes: (1) performance, (2) support, (3) distractions and interruptions and (4) confidence in decision-making.

There are very few studies exploring the practice of remote clinicians in emergency EOCs. This study identified that home working clinicians felt their productivity had increased, making them more satisfied in their practice. However, there were mixed feelings over the level of support they perceived they now received, despite the mechanisms of support being largely the same. Supervisors found it especially challenging to provide support to practitioners; and employers might need to clarify the support mechanisms they provide to homeworkers. The elimination of distractions and interruptions was seen as a largely positive result of homeworking; however, these interruptions were not seen as inappropriate, thus, identifying a need for role clarity and task coordination rather than interruption elimination. Finally, clinicians felt that they become more confident when working from home, researching more, trusting themselves more and relying less on others to reach safe outcomes. However, there were missed opportunities to learn from listening to others' clinical practice.

This study explores how a small minority of social entrepreneurs break free from third sector constraints to conceive, create and grow non-profit organisations that generate social value at scale in new and innovative ways.

Six narrative case histories of innovative social enterprises were developed based on documents and semi-structured interviews with founders and long serving executives. Data were coded “chrono-processually”, which involves locating thoughts, events and actions in distinct time periods (temporal bracketing) and identifying the processes at work in establishing new social ventures.

This study presents two core findings. First, the paper demonstrates how successful social entrepreneurs draw on their lived experiences, private and professional, in driving the development and implementation of social innovations, which are realised through application of their capabilities as analysts, strategists and resources mobilisers. These capabilities are bolstered by personal legitimacy and by their abilities as storytellers and rhetoricians. Second, the study unravels the complex processes of social entrepreneurship by revealing how sensemaking, theorising, strategizing and sensegiving underpin the core processes of problem specification, the formulation of theories of change, development of new business models and the implementation of social innovations.

The study demonstrates how social entrepreneurs use sensemaking and sensegiving strategies to understand and address complex social problems, revealing how successful social entrepreneurs devise and disseminate social innovations that substantially add value to society and bring about beneficial social change. A novel process-outcome model of social innovation is presented illustrating the interconnections between entrepreneurial cognition and strategic action.

Overcrowding continues to afflict emergency departments (EDs), and its attendant consequences are becoming increasingly severe. The burden of the COVID-19 pandemic is further escalating the situation worldwide. One of the most critical questions is how to adequately quantify what constitutes overcrowding and determine implications for operations management in improving service efficiency. This paper aims to discuss the aforementioned.

The authors propose the time and class complexity measures for ED service systems, taking into account important patient-level and system characteristics. Using an extensive data set from a Canadian ED, the authors investigate the performance of complexity-based measures in predicting service delays.

The authors find that the complexity measure is potentially more important than some well-known crowding metrics. In particular, EDs can improve service efficiency by managing the level of complexity within a desirable interval. Furthermore, complexity exposes how the interplay between demand-side behavioral changes and supply-side responses affects operational performance. Moreover, the results suggest that arrival patterns—the number of patients of each class arriving per time and times between events (arrivals and service completions)—increase the risk of service delays more than the demand volume.

This paper is the first to provide an extensive investigation into the application of the complexity-based measure for ED crowding. The study demonstrates potential values to be gained in ED service systems if complexity measure is incorporated into their operations management decisions.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

Major incidents in tunnel environment will pose several challenges for the emergency service organisations in terms of heat, visibility and lack of experiences from working in confined environments. These aspects, in turn, could pose challenges to establish collaboration. This study aims to contribute to the field of collaborative tunnel responses by exploring how “common knowledge” (Edwards, 2011) is built by the emergency services organisations, that is, what the organisations consider important while working on a potentially common problem, and their motives for the interpretations and actions if a major tunnel incident occurs.

Participants from the road traffic control centre, emergency dispatch centre, emergency medical service, rescue service and police were included in the study. Data from four focus group sessions was analysed using thematic analysis.

The study revealed that the tunnel environment presents specific aspects of how common knowledge was produced related to lifesaving and safety. The themes structuring mechanisms to reduce uncertainty, managing information for initial priorities, aligning responsibilities without hampering each other's work and adjusting actions to manage distance, illustrated how common knowledge was produced as crucial aspects to a collaborative response. Organising management sites, grasping and communicating risks, accessing the injury victims, was challenged by the confined environment, physical distances and imbalance in access to information and preparedness activities in tunnel environments.

This study offers new insights of common knowledge, by illustrating a motive perspective on collaborative responses in tunnel incidents. Creating interoperability calls not just for readiness for action and tunnel safety, but also training activities acknowledging different interpretations and motives to further develop tunnel responses.

Vehicle allocation problems (VAPs), which are frequently confronted in many transportation activities, primarily including but not limited to full truckload freight transportation operations, induce a significant economic impact. Despite the increasing academic attention to the field, literature still fails to match the needs of and opportunities in the growing industrial practices. In particular, the literature can grow upon the ideas on sustainability, Industry 4.0 and collaboration, which shape future practices not only in logistics but also in many other industries. This review has the potential to enhance and accelerate the development of relevant literature that matches the challenges confronted in industrial problems. Furthermore, this review can help to explore the existing methods, algorithms and techniques employed to address this problem, reveal directions and generate inspiration for potential improvements.

This study provides a literature review on VAPs, focusing on quantitative models that incorporate any of the following emerging logistics trends: sustainability, Industry 4.0 and logistics collaboration.

In the literature, sustainability interactions have been limited to environmental externalities (mostly reducing operational-level emissions) and economic considerations; however, emissions generated throughout the supply chain, other environmental externalities such as waste and product deterioration, or the level of stakeholder engagement, etc., are to be monitored in order to achieve overall climate-neutral services to the society. Moreover, even though there are many types of collaboration (such as co-opetition and vertical collaboration) and Industry 4.0 opportunities (such as sharing information and comanaging distribution operations) that could improve vehicle allocation operations, these topics have not yet received sufficient attention from researchers.

The scientific contribution of this study is twofold: (1) This study analyses decision models of each reviewed article in terms of decision variable, constraint and assumption sets, objectives, modeling and solving approaches, the contribution of the article and the way that any of sustainability, Industry 4.0 and collaboration aspects are incorporated into the model. (2) The authors provide a discussion on the gaps in the related literature, particularly focusing on practical opportunities and serving climate-neutrality targets, carried out under four main streams: logistics collaboration possibilities, supply chain risks, smart solutions and various other potential practices. As a result, the review provides several gaps in the literature and/or potential research ideas that can improve the literature and may provide positive industrial impacts, particularly on how logistics collaboration may be further engaged, which supply chain risks are to be incorporated into decision models, and how smart solutions can be employed to cope with uncertainty and improve the effectiveness and efficiency of operations.

Based on the 5th wave/tomorrow age theory, we are living in the world that is in necessity to change. Rapid urbanization causes global challenges such as economic problems and recessions, environmental challenges, climate change, social instability, health diseases, biological attached, and crisis caused by technological dominations. These challenges threaten the world, humanity, and human beings. Therefore, it is vital to tackle and struggle with them in order to maintain the world and improve quality of livability and quality of life to achieve sustainability. Generally, modern Blue-Green urban areas and smart cities with high quality of livability and life are proposed to deal with urbanization challenges to maintain the world and improve quality of human life. Based on Prof. Doost's 5th wave theory, related theories, concepts and models like Doost Risk Mitigation Method (DRMM), and also his experience on sustainability as best practice such as cooperating with Danish Sustainable Platforms Company, working as an academic leader at IoE/EQ EU Erasmus Plus project in Germany during 2017–2020, cooperating with former mayor of Copenhagen, consulting the German MV State Minister of Energy, Digitalization, and Infrastructure to cooperate with Iran in 2016, more than 15 years holding lecture and research internationally about risk and risk management on mobility in different universities like (TU Berlin) Technical University of Berlin (EUREF Campus, Sustainable Mobility Management and Sustainability Building) and also achieving a honorary doctorate in sustainable development management, a practical model concerned on risk management in mobility to provide comprehensive global Blue-Green clean sustainable urban mobility risk mitigation strategic plan is given. Therefore, in this chapter, impact of risk management on mobility to provide sustainable global urban mobility plan in order to create modern Blue-Green sustainable urban area and future smart cities through the 5th wave theory are explored. Fundamentally, the main goal of the research is to have an applied study about mobility risk mitigation and utilize it as a key to create comprehensive global urban mobility risk mitigation plan toward Blue-Green sustainable clean mobility technologies to create modern sustainable smart cities through the tomorrow age theory in order to create livable urban area with high quality of livability and life. In addition, the risks in mobility through the DRMM are measured to analyze the risk and to do risk mitigation and mobility project improvement to move to sustainable mobility and high sustainability in future smart cities.

Given the unprecedented scale of the climate emergency and the need for swift and radical change in how we travel, it is important for local authorities to consider how best to use their ‘authority’ to initiate sustainable change. However, without collective decision-making, longstanding issues around equity, real, and perceived injustices will trump any good intentions and policies. In this chapter, I attempt to make sense of why the initial stages of the Emergency Active Travel Fund (EATF) a mobility scheme designed to tackle two emergencies – the pandemic and the climate – largely failed in the eyes public, even though it was designed with their benefit in mind.