China’s Mega Supply Chains

This chapter explains the development and significance of China’s mega supply chains and their position in the global division of labour. It explains the importance of modularity, standardization, and complementarity in supply chains. It analyses how efficiencies and resilience are achieved and balanced in supply chains and the importance of platforms, both geographical clusters, such as industrial bases in Shenzhen, Chengdu, and Suzhou, and digital platforms, such as Alibaba and Pinduoduo. The chapter also argues that China’s mega supply chains have become regional hubs supplying intermediate products to manufacturing facilities in countries with lower labour costs. It discusses the extent to which China is progressing towards Industry 4.0, with smart supply chains, and how the country is responding to the challenges from growing global trade tensions.

A Tale in Three Parts: The Success of California’s Life Science Clusters

With the seventh largest GDP in the world, California has the economic heft of a country. One of the largest drivers of economic growth in California is the life science industry. In fact, it is a cornerstone of California’s innovation ecosystem, and is characterized by three distinct geographical clusters. There’s San Diego’s entrepreneurial energy, Los Angeles’ emerging incubators and the Bay Area’s unique tech influence. All of these clusters drive growth and distinct opportunities for institutes, universities, businesses and entrepreneurs. This article focuses on: how did California become a life science powerhouse, and what do each of these regions have to offer to the industry?

Geospatial evaluation of trade-offs between equity in physical access to healthcare and health systems efficiency

IntroductionDecisions regarding the geographical placement of healthcare services require consideration of trade-offs between equity and efficiency, but few empirical assessments are available. We applied a novel geospatial framework to study these trade-offs in four African countries.MethodsGeolocation data on population density (a surrogate for efficiency), health centres and cancer referral centres in Kenya, Malawi, Tanzania and Rwanda were obtained from online databases. Travel time to the closest facility (a surrogate for equity) was estimated with 1 km resolution using the Access Mod 5 least cost distance algorithm. We studied associations between district-level average population density and travel time to closest facility for each country using Pearson’s correlation, and spatial autocorrelation using the Global Moran’s I statistic. Geographical clusters of districts with inefficient resource allocation were identified using the bivariate local indicator of spatial autocorrelation.ResultsPopulation density was inversely associated with travel time for all countries and levels of the health system (Pearson’s correlation range, health centres: −0.89 to −0.71; cancer referral centres: −0.92 to −0.43), favouring efficiency. For health centres, negative spatial autocorrelation (geographical clustering of dissimilar values of population density and travel time) was weaker in Rwanda (−0.310) and Tanzania (−0.292), countries with explicit policies supporting equitable access to rural healthcare, relative to Kenya (−0.579) and Malawi (−0.543). Stronger spatial autocorrelation was observed for cancer referral centres (Rwanda: −0.341; Tanzania: −0.259; Kenya: −0.595; Malawi: −0.666). Significant geographical clusters of sparsely populated districts with long travel times to care were identified across countries.ConclusionNegative spatial correlations suggested that the geographical distribution of health services favoured efficiency over equity, but spatial autocorrelation measures revealed more equitable geographical distribution of facilities in certain countries. These findings suggest that even when prioritising efficiency, thoughtful decisions regarding geographical allocation could increase equitable physical access to services.

Geographical clusters and social risk factors for suicide in the city of São Paulo, 2006–2015: An ecologic study

Background: To identify geographical clusters of suicide in São Paulo, Brazil (2006–2015) and to verify the associations of suicide with sociocultural characteristics of its 96 districts. Methods: Spatial scan test was used to detect the geographical clusters. Correlation and multiple regression techniques were used to estimate the association of socioeconomic and cultural variables with suicide. Results: The mean suicide rate was 4.8/100,000. Three clusters were identified which are as follows: one of increased risk in downtown and two of decreased risk in the South and in the Southeast. The mean suicide rate of the high-risk clustered districts (7.99/100,000) presented significantly higher average incomes per household, higher proportion of formally educated, of no religious affiliation, of recent migrants, of all-times migrants and lower proportion of married. The multiple model selected two independent risk factors – people with no religious affiliation (β = 0.182) and of recent migrants (β = 0.278) – and two protective factors – the proportion of married (β = –0.185) and of total migrants (β = –0.075), which jointly explained 58.4% of the variance. Conclusion: Durkheimian social and cultural risk factors for suicide were confirmed. Compared to a previous study period (1996–2005), suicide rates and geographical clusters remained relatively stable in the subsequent decade (2006–2015).

The role of geographical clusters in the success of reward-based crowdfunding campaigns

Crowdfunding is a relatively new phenomenon, which disrupted the classic way to fund a venture. It consists in retrieving the capital needed to start an entrepreneurial activity drawing funds from a large base of small investors – generally common people – rather than from the traditional financial sources. Although many studies have been conducted on this topic, little focus has been put on the geography of this phenomenon. This article addresses this issue analysing whether regions characterized by the presence of geographical clusters are able to raise the probability of a successful crowdfunding campaign for projects located there. Drawing on a data set of 792 crowdfunded projects, we conduct an empirical study aimed at studying the role played by geographical clusters in fostering the crowdfunding of new entrepreneurial ventures. The results offer insights into the phenomenon of crowdfunding and shed light on the role of geographical clusters in the success of reward-based crowdfunding campaigns of early-stage entrepreneurial projects.

The role of geographical clusters in the success of reward-based crowdfunding campaigns

This article studies whether some salient characteristics of the geographical area in which a crowdfunding campaign is launched affect its success. Drawing on a data set of 792 crowdfunded projects, we conduct an empirical study aimed at studying the role played by geographical clusters (GCs) in fostering the crowdfunding of new entrepreneurial ventures. The results offer insights into the phenomenon of crowdfunding and shed light on the role of GCs in the success of reward-based crowdfunding campaigns of early-stage entrepreneurial projects.

No man is an Island: spatial clustering and access to primary care as possible targets for the development of new community mental health approaches.

Background: to understand if patients seen at Centro Hospitalar Psiquiátrico de Lisboa (CHPL) live in geographical clusters or randomly throughout the city, as well as determine their access to the psychiatric hospital and primary care facilities (PCF). Methods: spatial autocorrelation statistics were performed (queen criterion of contiguity), regarding all patients observed at CHPL in 2017 (at the census subsection level), and considering not only their overall number but also main diagnosis, and admission to the psychiatric ward - voluntary or compulsory. Distance to the hospital and to the closest PCF was measured (for each patient and the variables cited above), and the mean values were compared. Finally, the total number of patients around each PCF was counted, considering specified radius sizes of 656 and 1000m. Results: All 5161 patients (509 psychiatric admissions) were geolocated, and statistical significance regarding patient clustering was found for the total number (p-0.0001) and specific group of disorders, namely Schizophrenia and related disorders (p-0.007) and depressive disorders (p-0.0002). Patients who were admitted in a psychiatric ward live farther away from the hospital (p-0.002), with the compulsory admissions (versus voluntary ones) living even farther (p-0.004). Furthermore, defining a radius of 1000m for each PCF allowed the identification of two PCF with more than 1000 patients, and two others with more than 800. Conclusions: as patients seem to live in geographical clusters (and considering PCFs with the highest number of them), possible locations for the development of programs regarding mental health treatment and prevention can now be identified.

Prevalence and Socioeconomic inequalities trends in child health comparing within and between group inequalities: Food insecurity and malnutrition in Zimbabwe

BackgroundGlobally nations are advocating for universal health coverage which argues for health access for all however, inequalities in child health remain a threat to this global initiative. Even though malnutrition and food insecurity are now dominating the global development agenda, there are substantial gaps on literature about patterns and trends of socioeconomic inequalities in food insecurity and malnutrition in many developing countries. Globally an estimated 3.1 million children die annually as a result of undernutrition, shockingly sub-Saharan Africa accounts for majority of the most nutritionally insecure and food insecure children in the world. In previous decades’ prevalence of stunting in Zimbabwe has been erratic. This paper assessed socioeconomic inequalities in child health focusing on malnutrition and food insecurity in Zimbabwe.MethodsThe study used Demographic Health Survey (DHS) data sets of 2010\11 and 2015. Food insecurity in children was determined based on the WHO dietary diversity score. The study adopted the WHO dietary diversity score informed by the Infant and Young Child Feeding (IYCF) practices. Minimum dietary diversity as an indicator for food security is defined by a cut- off point of >4, therefore for this study children with less than 3 of the 13 food groups were defined as food insecure. Malnutrition was assessed using weight-for-age Z-scores, with children whose weight-for-age Z-score below minus two standard deviations (-2 SD) from the median considered malnourished. Concentration indices were computed to understand if malnutrition was dominant among the poor or rich. The paper used the Theil index, which is a generalized entropy measure and decomposed the indices by population subgroups (geographical clusters and socioeconomic status) so as to separate total inequality in the distribution between the selected groups and remaining within-group inequalities.ResultsFor the period under review malnutrition prevalence increased by 1.03 percentage points (p.p) [2010/11(3.73%); 2015(4.76%)], while food insecurity prevalence decreased by 4.35p.p [2010/11(78.29%);2015(73.94)]. Prevalence of malnutrition and food insecurity increased by; 9.6p.p and 2p.p among poor children & 10.23p.p and 0.5p.p among rural children. Concentration indices showed that; children from wealthy households were more likely to be food secure (pro-rich) while, children from poor households were more likely to be nutritious (pro-poor). For nutrition status socioeconomic inequality gaps appear to be widening as the concentration indices between the two time periods increased, while for food security status socioeconomic inequality gaps appear to be contracting as the concentration indices between the two time periods reduced. Decomposed Theil indices by geographical clusters (urban & rural) for; food security status shows contracting socioeconomic inequality gaps in both geographical clusters (urban & rural), while for nutrition status the Theil indices reflect widening socioeconomic inequality gaps among urban children and contracting socioeconomic inequality gaps among rural children.ConclusionThe study concluded within-group inequalities to be driving most of the socioeconomic inequalities in nutritional status and food security status of children in Zimbabwe. Therefore, Zimbabwean government should design policies that focus on addressing within-group inequalities and direct food security interventions for food insecure children through availing food aid.