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Contains reliable cross-country data on aspects of private sector development, crucial in planning for economic recovery and growth. In targeting increased exports and investment, many governments prioritize an improved climate for business as a basis to attract capital, create jobs, and provide basic services. The availability of cross-country data on the business environment has rapidly expanded in recent years, including data from the World Bank Group's Doing Business project, Enterprise Surveys, and the Entrepreneurship Snapshots. Included in this guide are indicators on the economic and social context, the investment climate, private sector investment, finance and banking, and infrastructure. Though a pocket guide cannot include all relevant variables, the included indicators provide users with a general understanding of the private sector in each country. Indicators displayed in the tables are defined in the glossary, which also lists data sources.

The Coronavirus Disease 2019 (COVID-19) pandemic has changed many social, economic, environmental and healthcare determinants of health. We applied an ensemble of 16 Bayesian models to vital statistics data to estimate the all-cause mortality effect of the pandemic for 21 industrialized countries. From mid-February through May 2020, 206,000 (95% credible interval, 178,100–231,000) more people died in these countries than would have had the pandemic not occurred. The number of excess deaths, excess deaths per 100,000 people and relative increase in deaths were similar between men and women in most countries. England and Wales and Spain experienced the largest effect: ~100 excess deaths per 100,000 people, equivalent to a 37% (30–44%) relative increase in England and Wales and 38% (31–45%) in Spain. Bulgaria, New Zealand, Slovakia, Australia, Czechia, Hungary, Poland, Norway, Denmark and Finland experienced mortality changes that ranged from possible small declines to increases of 5% or less in either sex. The heterogeneous mortality effects of the COVID-19 pandemic reflect differences in how well countries have managed the pandemic and the resilience and preparedness of the health and social care system. Application of Bayesian models to vital statistics data from 21 industrialized countries shows that approximately 206,000 additional people died than if the COVID-19 pandemic had not occured. The heterogeneous distribution of excess deaths across the countries reflects differences in how the pandemic has been managed as well as the resilience of healthcare systems in these nations.

Evaluation of tourism competitiveness is useful for measuring the level of regional tourism development. It is of great importance to understand the advantages and disadvantages of tourism development correctly and formulate corresponding development strategies. To investigate tourism competitiveness, this paper established an evaluation index system, including tourism development competitiveness, tourism resource competitiveness, and tourism-support competitiveness, for 14 prefectures and cities in Xinjiang in China. The characteristics and laws of spatial differentiation were analyzed. Factor analysis was applied to examine the spatial differentiation of regional tourism competitiveness. The results showed an obvious spatial differentiation in tourism competitiveness among the 14 prefectures and cities. In terms of development competitiveness, Yili and Urumqi constituted the spatial center, followed by Changji, Altay, and Ba Prefecture. As the provincial capital, Urumqi has political, economic, cultural, transportation, and geographic advantages, but its competitiveness is not prominent in terms of monopoly and efficiency. In terms of resource competitiveness, Yili is the core attraction, while Urumqi, Kashgar, Altay, and Ba Prefecture are dominant attractions. With respect to supporting competitiveness, Bo Prefecture has high value, followed by Urumqi City and Aksu. Hetian and Ke Prefecture have the lowest values. The comprehensive competitiveness of tourism is centered on Yili. Urumqi and Bo Prefecture are subcenters, and Changji, Altay, Ba Prefecture, Aksu, and Kashgar are characterized as multi-polar competition areas. Using the KMO and Bartlett’s sphericity tests, the cumulative contribution variance of the eigenvalues of the eight factors extracted by the maximum variance rotation method was found to be 92.714%. Socio-economic conditions, tourism resources, infrastructure construction, regional cultural influence, ecological environment carrying capacity, tertiary industry development, tourism service level, and living security system are the main driving factors affecting the spatial differentiation of tourism competitiveness in Xinjiang. Analyzing the spatial evolution characteristics and the driving factors of the regional tourism competitiveness in Xinjiang, this paper seeks to promote the optimal allocation of tourism production factors in the macro regional system, and provide theoretical guidance and an empirical basis for the comprehensive and harmonic development of regional tourism.

Air quality in China has gradually been improving in recent years; however, the Beijing-Tianjin-Hebei (BTH) region continues to be the most polluted area in China, with the worst air quality index. BTH and its surrounding areas experience high agglomeration of heavy-polluting manufacturers that generate electric power, process petroleum and coal, and carry out smelting and pressing of ferrous metals, raw chemical materials, chemical products, and non-metallic mineral products. This study presents evidence of the air pollution impacts of industrial agglomeration using the Ellison–Glaeser index, Herfindahl–Hirschman index, and spatial autocorrelation analysis. This was based on data from 73,353 enterprises in “2+26” atmospheric pollution transmission channel cities in BTH and its surrounding areas (herein referred to as BTH “2+26” cities). The results showed that Beijing, Yangquan, Puyang, Kaifeng, Taiyuan, and Jinan had the highest Ellison–Glaeser index among the BTH “2+26” cities; this represents the highest enterprise agglomeration. Beijing, Langfang, Tianjin, Baoding, and Tangshan also showed a low Herfindahl–Hirschman index of pollutant emissions, which have a relatively high degree of industrial agglomeration in BTH “2+26” cities. There was an inverted U-shaped relationship between enterprise agglomeration and air quality in the BTH “2+26” cities. This means that air quality improved with increased industrial agglomeration up to a certain level; beyond this point, the air quality begins to deteriorate with a decrease in industrial agglomeration.

Industrialization has been widely regarded as a sustainable construction method in terms of its environmental friendliness. However, existing studies mainly consider the single impact of greenhouse gas emissions or material consumption in the construction process of industrialized buildings, and pay less attention to ecological pollution and community interest, which leads to an insufficient understanding. There is an urgent need to systematically carry out accurate assessment of comprehensive construction environmental impact within industrialized building processes. Various methods, including face-to-face interviews, field research and building information modeling (BIM), were used for data collection. Four categories selected for the study included resource consumption, material loss, ecological pollution, and community interest. A life cycle assessment (LCA) model, namely input-process-output model (IPO), is proposed to analyze the construction environmental impact of the standard layer of industrialized buildings from four life cycle stages, namely, transportation, stacking, assembly and cast-in-place. The monetization approach of willingness to pay (WTP) was applied to make a quantitative comparison. Results reveal that the assembly stage has the largest impact on the environment at 66.13% among the four life cycle stages, followed by transportation at 16.39%, stacking at 10.29%, and cast-in-place at 7.19%. The key factors include power consumption, noise pollution, material loss, fuel consumption and component loss, which altogether account for more than 85% of the total impact. Relevant stakeholders can conduct their project using the same approach to determine the construction environmental performance and hence introduce appropriate measures to mitigate the environmental burden.

Ecologically sensitive suburban areas provide important ecosystem services and protect urban ecological security because of their multiple functions in natural and human systems. The research on the ecological environment effects of land use activities in ecologically sensitive suburban areas is important in guiding the healthy and sustainable development of cities. Taking the west suburbs of Hangzhou in China as a case study, we quantified land use changes from Landsat satellite imagery and calculated the value of ecosystem services using the well-established equivalent factor table for land use/cover change (LUCC) and ecosystem services value (ESV). The impacts of LUCC on the ecological environment were analyzed using the transfer matrix of land use and coefficient of elasticity. Results revealed the following. (1) The total ESV in the western suburban area of Hangzhou decreased from$109.95 million in 2000 to $ 87.09 million in 2016. Moreover, the ESV of gas regulation, climate regulation, soil formation and protection, as well as biodiversity conservation presented a large decrease of more than 25%, especially between 2010 and 2016. (2) The spatial distribution of ESV was high in the west and low in the east. The regions with a significant reduction in ESV were mainly distributed in the eastern town of Wuchang and in Jincheng Town located in the midwest valley. (3) Industrial agglomeration activities in the ecologically sensitive suburban area emerged as the primary factor influencing ESV for various land uses. The elasticity indicator for assessing the responses to ESV changes relative to LUCC showed that 1% of the land conversion in this area resulted in average changes in ESV of 4.1% after the establishment of the industrial agglomeration area. (4) The increase in construction land was associated with a significant decrease in forest area because of the policy of cultivated land requisition–compensation balance and development strategies for low-slope hilly lands. Consequently, the ESV in the ecologically sensitive suburban areas rapidly declined.

Currently, many large Chinese cities have entered the postindustrial era, leaving a large amount of vacant, inefficiently utilized industrial land and buildings in the inner cities. Industrial land redevelopment (ILR) can benefit cities in multiple ways, such as by increasing urban public space, improving the quality of life of citizens, and improving the environment, and is considered an effective approach to enhance people’s wellbeing. However, large-scale ILR projects often raise a series of social issues in practice, such as injustice and inequality. To address complex urban issues, ILR requires multifaceted, coordinated, and comprehensive strategies involving multitudinous stakeholders. A profound understanding of diverse stakeholders in the decision-making of ILR is a vital step in enhancing the sustainability of ILR. The aim of this paper is to use Shanghai as a case study to understand the diverse stakeholders and their participation during the decision-making of ILR in China. Interviews and questionnaires were used to collect data. Stakeholder analysis (SA) and social network analysis (SNA) were used as complementary research methodologies in this paper. First, stakeholders who participated in the decision-making of ILR were identified. Then, the characteristics of various stakeholders, including power, interests, and knowledge, were analyzed. Following this, the interactive relationships among stakeholders were explored, and their network structure was examined. Finally, policy recommendations were presented regarding stakeholder participation problems in the decision-making of ILR in China.

Fuelled by the medicalisation of life and an ever-expanding remit, healthcare has become industrialised and unsustainable. Sustainable healthcare requires a shift from industrial healthcare to careful and kind care as well as addressing the social and environmental determinants of health. Caring for, about, and with each other is a social determinant of health, writes Victor Montori

Construction industrialization (CI) has been adopted worldwide because of its potential benefits. However, current research shows the incentives for adopting CI may differ in different regions. While the promotion of CI in China is still at the initial stage, a systematical analysis of the driving factors would help decision makers get a comprehensive understanding of CI development and select proper strategies to promote CI. This research combines qualitative and quantitative methods to explore the construction industrialization driving factors (CIDFs) in China. The grounded theory method (GTM) was employed to explore CI concepts among 182 CI-related articles published in 10 top-tier journals from 2000 to 2017. A total of 15 CIDFs were identified, including one suggested by professionals during a pre-test questionnaire survey. The analysis showed that the development of CI in China is pushed by macrodevelopment and pulled by the government and is also a self-driven process. The major driving factors for CI adoption in China are the transformation and upgrade of the conventional construction industry and the solution of development dilemmas. Our study also suggests that pilot programs are, currently, the most effective method to promote CI in China and to accumulate experience so to gain recognition by the society. This research is also of value for CI promotion in other developing countries.