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Tourism, as a system, develops strategies for risk prevention and mitigation. The shock generated by the COVID-19 pandemic is different when compared with previous events because it is more intense and prone to structural changes. Tourists' perceptions condition their behaviour and decisions, with adverse results on travel and tourism consumption; and hygiene and health risks generate a cause-effect relationship on destination specificities.

From globalisation to risk perception and crisis management, in a framework where technology, communication and digital content represent undeniable importance, we are facing circumstances especially conducive to the redesign of the collective future, where the sustainability of tourism is a collective goal, arising from the right balance between the competitiveness of destinations and climate action.

Given the prospects for the next decade, health and hygiene are structural factors to be considered in decision-making processes. Thus, so the proposed approach contributes to the awareness, by the various stakeholders, of its importance and the need to implement methods and processes compatible with more inclusive and responsible tourism.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.

Emerging technologies are becoming vital in the very process of innovation. Companies need to be updated to the latest technologies to offer their premium services to customers as well as meet their expectations. In the medical sector, it is a challenge to sustain superiority in service due to a high level of competition and the challenges arising from different forces. Liberty Dental Clinic (LDC), a premium clinic in dental services and solutions, based in the UAE, was able to maintain a premium presence in Dentistry due to a series of developmental thoughts and efforts. It was able to invest and utilize new innovative technologies which many organizations lacked such as implementing the most contemporary Artificial Intelligence “4 Robots” in the Clinics. Creating a pathway for a satisfactory customer journey was embedded at all levels of the hierarchy in the Clinic and customer touchpoints. Using a case study methodology, the drivers behind the success and uniqueness of LDC have been discussed including Leadership, Quality Management, Risk Management, Internal & External Marketing Strategy, Corporate Social Responsibility, Sustainability, Technology and Innovation.

It is now well-established that good water quality is associated with economic prosperity, reduced incidence on public health and the good functioning of the various ecosystems found in our environment. Water contamination is mostly related to both diffused (agricultural lands and geologic rock degradations) and point sources of pollution. Mauritius has many water resources which depend solely on precipitation for their replenishment. Water parameters which are of relevance include total dissolved solids (TDS), temperature, pH, electrical conductivity, turbidity, dissolved oxygen, dissolved and particulate organic carbon and major cations and anions. The traditional methods of analysis for these parameters are mostly using electrical and optical methods (probes and sensors in the field), while chemical titrations, Flame AAS and High-Performance Liquid Chromatography techniques are carried out in the laboratory. Image Classification techniques using neural networks can also be used to detect the presence of contaminants in water. In addition to basic water quality parameters, the field sensors range have been extended to cover important major ions and can now be integrated with Artificial Intelligence (AI)-based models for the prediction of variations in water quality to better protect human health and the environment, reduce operation costs of water and wastewater treatment plant unit processes.

Recent socio-economic trends have made Artificial intelligence (AI) a vital institutional force driving development among countries with optimal opportunities and costs. Among researchers in this domain, the benefit of AI is highly espoused, having been underexplored in Africa. However, the outbreak of the COVID-19 pandemic has highlighted the need to strengthen the education sector, given that many schools have migrated their teaching and learning online. While face-to-face teaching was the norm, the transition to online teaching has brought about the need to rethink the use of Information Technology to strengthen teaching and learning. To proffer solutions for the implementation of AI in Africa, there is the need to understand the challenges. Therefore, in this chapter, we explore the possible challenges that hinder the implementation of AI in Africa. Further, we propose solutions for the implementation of AI in the education sector, especially in this era of the COVID-19 pandemic. The solutions stem from rethinking the role of AI in the education sector. Finally, a conceptual framework that synthesises the problems and the proposed solution is developed. We envision that the proffered solutions can mitigate the deepening misconceptions and challenges bedevilling AI implementation in Africa.

Natural Law philosophy asserts that there are universally binding and universally evident principles that can be determined to guide the actions of persons. Moreover, many of these principles have been enshrined in both statute and common law, thus ensuring their saliency for staff and institutions charged with palliative care. The authors examine the often emotive and politicized matter of (non-voluntary) euthanasia – acts or omissions made with the intent of causing or hastening death – with reference to Natural Law philosophy. This leads us to propose a number of important public policy remedies to ensure dignity in dying for the patient, and their associates.

Introduction: Coronavirus-19 (COVID-19) global outbreak poses a danger to millions of people’s health and the uncertainty and financial prudence around the world. Without a doubt, the sickness will place a tremendous strain on healthcare systems, which existing or traditional-based treatments cannot adequately handle. Only intelligence derived from diverse data sources can provide the foundation for rigorous clinical and social responses that optimise the use of constrained healthcare resources, create tailored patient treatment plans, educate policy-makers, and accelerate clinical trials

Purpose: This chapter aims to incorporate innovative practices of artificial intelligence (AI) into local, national, and global healthcare systems that can save lives of people and as well helps in human capital management ways that may be deployed rapidly and effectively with minimal errors.

Methodology: AI technologies and tools play a crucial part in COVID-19 crisis response by assisting with the virus discovery, early detection, and the development of effective medications and therapies. In this chapter, significant issues related to COVID-19 and how they may be addressed by applying HRM practices with recent advances in AI. Also, through a literature review of the recent studies implemented in a similar context, an AI solution is proposed by formulating a conceptual model.

Findings: This chapter offers that the latest AI techniques can assist policy-makers in implementing modern human capital management practices to fight against COVID-19. The goal is to remotely monitor patients utilising gadgets that are embedded with state-of-the-art medical technology. To limit hospital visits, or at least cut them down to a minimum, on the one hand, the health clinic also wants to deliver reliable health information to the doctors before or during virtual consultations.

At present, the whole hospitality and tourism sector is severely impacted by the COVID-19 pandemic, and related lockdowns have been producing severe transformations in the industry. Several business reports and academic studies have highlighted that, compared to before the COVID-19 outbreak, tourists will likely choose to visit less crowded tourism destinations, and will tend to prefer accommodation facilities that can deliver their services with reduced face-to-face interactions and guaranteeing fair levels of physical and social distancing. This said, there is only a limited number of scientific studies dealing with this topic so far. This, coupled with the extremely dynamic and turbulent environment we are currently experiencing, urges scholars to further intensify the academic discussion on this area of research. Further examination would give practitioners knowledge to assist them in their decision-making in an era of tourism where everyone seems to be moving towards a ‘new normal’ of unknown duration. The present study was thus conducted to make a contribution to this debate by providing and discussing the results of a factor analysis on a sample of 200 German respondents, to dig into the criteria that travellers use to select the destination and the accommodation for their vacation. Findings contribute to deepen the scientific debate about how tourist behaviour is transformed by the COVID-19 pandemic and, potentially, by any other type of virus that could replicate a similar emphasis on hygiene and safety, as well as on social distancing. Meanwhile, our results will provide policy makers, destination marketers, and accommodation managers with useful information on effectively planning and implementing their service design in order to meet tourists' expectations and needs.