This study highlights a theoretical dilemma about the mixed implications of a firm’s R&D alliance network for its innovation performance. That is, knowledge sharing among R&D alliance partners can both benefit the focal firm with access to external knowledge and skill sets and expose it to potential risks of knowledge leakage and misappropriation, thus both advancing and hampering the focal firm’s innovation performance. Drawing on the network pluralism perspective, we address this dilemma by highlighting the interplay between the network embeddedness forces exerted by a firm’s R&D alliance network and other networks the focal firm participates in. Specifically, we find that a strong industrial network built upon the coalition and associations among peer firms in the focal firm’s industry can intensify the nonmonotonic (inverted U-shaped) effect of an R&D alliance network on the firm’s innovation performance, while the firm’s strong political connections with governments can weaken the effect of an R&D alliance network. In addition, such interplay between different networks tends to be strengthened by the focal firm’s technological capability.

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Background The health sector plays an important part in adapting to climate change; however, the sector is also responsible for significant greenhouse gas (GHG) emissions. In high-income countries, the carbon footprints of health-care systems have been estimated to be 3-10% of the total national GHG emissions, but no in-depth investigation has been done for China. This study aims to examine the carbon footprint of the Chinese health-care system and identify emission hotspots. MethodsEnvironmentally extended input-output analysis and structural path analysis were used to assess the lifecycle GHG emissions of the Chinese health-care system. A satellite account of GHG emissions was constructed for 46 economic sectors in China using energy data from the National Bureau of Statistics based on the numbers reported by a large number of enterprises. Data on health expenditure for medical institutions, pharmaceuticals, construction, administration, and research were obtained from multiple Chinese official statistics yearbooks and the national input-output table. Findings In 2012, China spent CNY 2539 billion on health care, leading to emissions of 315 (68% CI 267-363) megatonnes CO 2 equivalent. Health care accounted for 2·7% (68% CI 2·3-3·1) of China's total GHG emissions. The major contributors of GHG emissions in the health-care system were public hospitals (148 megatonnes [47%]), nonhospital purchased pharmaceuticals (56 megatonnes [18%]), and construction (46 megatonnes [15%]). In medical institutions, energy use for buildings and transport accounted for only 16% of the total carbon footprint, whereas 84% was embodied in the purchased goods and services.Interpretation China has a much smaller health-care carbon footprint per capita than developed countries, such as the USA and Australia. However, its carbon emissions per unit of health expenditure are relatively high because of the expenditure structure and the carbon intensity of the country's entire economy. The results suggest the need for a nationwide carbon-efficient target for health care and use of low-carbon alternatives in making supply chain choices to achieve reductions in the carbon footprint.

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The overabundance of carbon emissions is widely considered as a serious world problem. This paper focuses on analyzing the influence of economic factors on carbon emissions. Based on the traditional STIRPAT model, in terms of the "pollution haven hypothesis" and "pollution halo hypothesis", this paper employs the dynamic panel data model to explore the impact of economic elements such as economic growth, population, foreign direct investment and others on carbon emissions. Based on our research, China's urban carbon emissions do not follow the inverted U-shaped hypothesis of the traditional EKC curve theory and presents an inverted N-type. Moreover, current foreign direct investment increases the carbon emissions of Chinese cities due to the "implicit trade carbon". However, during the lagging period of one phase, it significantly reduced urban carbon emissions. In addition, the lag of one period of carbon emissions statistically led to carbon emissions at the current stage. According to the empirical analysis results, this paper proposes some reasonable improvements for carbon dioxide emission reduction, which have certain reference values for other developing countries facing similar carbon emission reduction challenges.

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