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The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.

Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.

Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.

First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.

The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.

The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.

The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.

Building social capital between groups of people and developing social enterprises that integrate social goals into commercial business models are rapidly adopted as innovative poverty relief mechanisms across countries. Together, the translation of social relationships into increased accessibility to resources, and the entrepreneurial dynamics resulting in additional services and goods, are thought to meet the survival and developmental needs of poor families and communities. However, the socio-economic contexts, in which new public policies and initiatives have been taken, vary from country to country. In China, its strong Confucian culture, state-led development strategy, weak civil society, and hierarchical social relationships have contributed to a value structure of social capital, but decreased the efficiency of business practice in social enterprise. This chapter presents a case study of Rural Cooperative Program, a poverty relief initiative in China’s southwest Guizhou Province. With the introduction of China’s new policies in welfare and rural development, this chapter presents evaluation results of whether social enterprises and entrepreneurship can improve poor villagers’ socio-economic wellbeing and promote sustainable development of poor rural villages in China, and to what extent social capital has been mobilized to facilitate the Rural Cooperative Program.

This introductory chapter sets the overall context of global civil society in today’s global world. The authors will firstly provide a definition of civil society from social and political science perspectives. Then secondly, the authors provide a contemporary overview of global civil society debates in the current social and political environment; they also offer a short examination of COVID-19 and how this global pandemic has developed new spheres of contestation and collaboration. In the final part of the chapter, the authors present a brief overview of each chapter contributed to this volume.

By adopting retrospective evaluation theories, this study aims to explain how innovations provided by separate suppliers in the tourism value chain influence tourist’s perceived value of the overall experience and further uncover which innovative product attributes are more effective in improving tourist perceptions of the overall value.

A survey yielded 584 valid responses from tourists who had experienced specific tourist product innovations during their travels. Structural equation modelling was used to test the proposed theoretical model.

The results reveal that tourists evaluate overall travelling experience value either by recalling an intense, impressive moment (i.e. a heuristic approach) or through an evaluation of the overall utility gained from the whole trip (i.e. a normative approach). Furthermore, innovations that are perceived as increasing convenience and enabling learning contribute to tourists’ overall value perception through both normative and heuristic approaches, while immersion resulting from innovation only contributes to overall perceived value through the heuristic approach.

Given the complex service ecosystem of tourism destinations, each tourism service provider should consider how innovations contribute to the experience of the whole trip and which attributes of innovations increase tourists’ overall perceived experience value.

This study complements existing knowledge by revealing the relationship between product innovation in tourism sectors and tourists’ perceived value of the whole trip. Moreover, it offers a theoretical framework for further investigation into service product innovation in hospitality and tourism industry.

The purpose of this study was to solve the problem of most woven-fabric self-lubricating bearings that find it difficult to function at temperatures above 320°C, by designing a new type of new nuclear joint bearing. The results of this study will help designers to achieve accurate stress distribution, displacement deformation, fatigue life and damage of bearings. All of these can be a guide for designing self-lubricating joint bearings.

Finite element analysis is undertaken to simulate the new design bearings. To get the most appropriate and accurate results, the room temperature simulation (Simulation A), the modulus of elasticity that changes with temperature (Simulation B) and the thermal-structure-coupled simulation (Simulation C) are compared. The fatigue simulation is conducted to verify whether the self-lubricating method is reasonable and whether the bearing can function for over 60 years in an enclosed environment.

Stress distribution and displacement deformation of joint bearing can be accurately achieved via the thermal-structure coupled simulation. Work life and damage results have been achieved via the fatigue analysis, and the suggested working loads can be calculated via safety factors.

The newly designed joint bearing in which the graphite is laid on the outside of the inner ring functions and self-lubricates at temperatures above 320°C.

Under the pressure of environment degradation and energy consumption rises, solar photovoltaic power generation (SPPG) has been seen as a strategic emerging industry in China. However, the SPPG projects have many uncertain factors in the process of the life cycle. The purpose of this paper is to evaluate the investment risk comprehensively.

Specifically, this paper firstly identified the risk factors and consequences of SPPG project investment and constructed the investment risk factor evaluation index system. Secondly, the factor analysis method was used to reveal the key investment risk factors and risk consequences. Then, the research hypotheses and conceptual model were proposed, and the empirical analysis was conducted based on the structural equation model (SEM).

The results showed that the six key risk factors (political, economic, technological, management, market and natural) have a significant impact on the risks during the whole period. The influence degree of risk factors in the operational period is such that market factor > political factor > economic factor > management factor > natural factor > technical factor. In addition, the risk of constructional period has a significant impact during the risk of operational period. Except for natural factors, all risk factors are correlated among the mutual influence relationship of risk factors. Finally, this paper puts forward management implications based on the above conclusions: effectively identify investment risk factors and comprehensively improve risk management ability; (refine the risk factors of SPPG project investment and develop targeted risk prevention and control strategies; define risk management objectives and make relevant strategic plans.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further.

It can also help stakeholders propose risk prevention strategies throughout the entire process, to promote the sustainable development of SPPG projects.

This study focuses on the investment risk of SPPG projects, by building an evaluation index system to identify key risk factors, and then establishes a SEM covering constructional period risks and operational period risks to better explore SPPG project risks, in an effort to reveal the mutual influence relationship and influence path of investment risk factors of the projects.

To reduce the computational scale for quasi-magnetostatic problems, model order reduction is a good option. Reduced-order modelling techniques based on proper orthogonal decomposition (POD) and centroidal Voronoi tessellation (CVT) have been used to solve many engineering problems. The purpose of this paper is to investigate the computational principle, accuracy and efficiency of the POD-based and the CVT-based reduced-order method when dealing with quasi-magnetostatic problems.

The paper investigates computational features of the reduced-order method based on POD and CVT methods for quasi-magnetostatic problems. Firstly the construction method for the POD and the CVT reduced-order basis is introduced. Then, a reduced model is constructed using high-fidelity finite element solutions and a Galerkin projection. Finally, the transient quasi-magnetostatic problem of the TEAM 21^a model is studied with the proposed reduced-order method.

For the TEAM 21^a model, the numerical results show that both POD-based and CVT-based reduced-order approaches can greatly reduce the computational time compared with the full-order finite element method. And the results obtained from both reduced-order models are in good agreement with the results obtained from the full-order model, while the computational accuracy of the POD-based reduced-order model is a little higher than the CVT-based reduced-order model.

The CVT method is introduced to construct the reduced-order model for a quasi-magnetostatic problem. The computational accuracy and efficiency of the presented approaches are compared.

This paper aims to review the literature on carbon trading from the perspective of evolution, finds out the evolution path of these literatures and gives out the future research hotspots in this field.

Uses visualization tools (CiteSpace and HistCite) to systematically categorize the literature on carbon-trading schemes in the Web of Science core collection from 1998 to 2018, comprehensively analyzes carbon-trading schemes from four dimensions, namely, discipline evolution, keyword evolution, citation cluster evolution and citation path evolution.

Research on carbon-trading schemes has a specific development and evolution path along four dimensions, namely, in the discipline dimension, the largest change lies in the mathematics pointed to by at least four different disciplines; the keyword evolution dimension shows a gradual deepening emphasis on coordinated development; citation clusters identify three major clusters – carbon prices, China’s carbon trading, carbon market and supply chain; and citation paths identify three major evolutionary paths, the most important of which shows that “What affects carbon price?” has changed to “What is the impact of carbon prices?”

Reveals the evolution path of carbon trading research studies and proposes four possible development directions for carbon-trading scheme research, which is helpful for future carbon trading-related research and serves as a reference for the promotion of and improvements in carbon-trading schemes.

This paper aims to explore the effect of fairness concerns on supply chain members' optimal decisions and profits, to compare their profits under different policies, and to investigate the impact of each policy on members, consumers, and the environment with fairness concerns.

Considering government policies and fairness concerns in recycling management, this paper develops five recycling and remanufacturing decision models (anarchy policy model, reward-penalty mechanism model, recycling investment subsidies model, government tax model, and fund subsidy system model). In each model, the manufacturer and the online platform form the Stackelberg game. This research further discusses comprehensive environmental benefits and consumer surplus under five scenarios.

First, the fairness concerns of the online platform inhibit the recovery rate and supply chain members' profit while increasing the platform's utility. Second, fairness concerns increase the profit gap between the manufacturer and online platform, and the higher the degree of fairness concerns, the greater the profit gap; however, the four policies reduce the profit gap. Finally, when there are fairness concerns, environmental taxes damage the interests of supply chain members and consumers, but are most beneficial to the environment; recycling investment subsidies are on the contrary; the fund subsidy system depends on the relative size of the treatment fund and the subsidy fund.

This paper provides useful insights on how to regulate government policy to improve supply chain management with fairness concerns.