(1) Background: Public satisfaction with the health system is a very important comprehensive indicator. Given the limited healthcare resources in a society, it is always important for policymakers to have full information about the priority and the ranking order of the factors of healthcare resources for improving public satisfaction. (2) Methods: Grey Relational Analysis (GRA) is advantageous for satisfaction analysis because satisfaction is a “grey concept” of “having a clear boundary but vague connotation”. The data were from the CGSS and the China Health Statistics Yearbook (2013 and 2015), with a total of 15,969 samples (average satisfaction score = 68.5, age = 51.9, female = 49.4%). (3) Results: The government’s percentage of total expenditure on healthcare was ranked as the most important factor for public satisfaction with the health system in China in both 2013 and 2015. The second most important factor changed from “Out-of-pocket percentage of individuals” in 2013 to “Hospital beds per thousand populations” in 2015. Meanwhile, “Healthcare workforce per thousand populations” increased from the least important factor in 2013 to the 3rd in 2015. Disparities in the ranking orders of the factors among regions of China were identified too. (4) Conclusions: The analysis results suggest that during recent years the priority of Chinese residents’ healthcare satisfaction for healthcare resources has shifted on the national level from economic affordability to more intensive “people-centered” services, while the regional disparities and gaps need to receive more attention and be further improved in the healthcare reform of next round.

Background: As China pursues better social equality and improvement in public services (healthcare), public satisfaction has been considered as a key performance indicator. There is a great need to better understand the disparities and inequalities in the public satisfaction with its healthcare system. Methods: Based on Chinese General Social Survey (CGSS) 2015 ( a set of nationally representative survey data, the most recent wave containing information about public satisfaction with the healthcare system), this study utilizes the quantile regression method to analyze how the public satisfaction at high or low quantile of the score distribution varies according to the socio-economic status and healthcare system performance indicators, especially in rural areas. Results: This study found that, at the highest percentile, better Self-Reported-Health (SRH) is associated significantly with a lower satisfaction score (coefficient -4.10, P < 0.01). High socioeconomic status (especially "above average" group) has higher satisfaction scores at both mean (coefficient 3.74, P<0.01) and median (coefficient 3.83, P<0.01). This effect is also significant across the lower quantiles of the satisfaction levels. West and Middle region (the less developed regions) tended to be more satisfied, whereas those in Northeast reported a large negative effect (coefficient -7.07, P < 0.01) at the median. While rural residents generally reported higher levels of satisfaction, rural residents’ preference regarding hospital beds and primary care access seems generally to be opposite to that of urban residents. Conclusion: Our findings suggest that the ongoing healthcare reform needs to integrate more preventive care to meet the healthy residents’ expectation and demands. More attention should be guided to the vulnerable healthcare system in the Northeast region, which has a stagnant local economy. Outcome-based quality care is especially preferred in rural healthcare, in addition to improvement of utilization and access. In addition, the “pro-rich” inequality is an ongoing concern about the system.

Considering the low-carbon supply chain led by one manufacturer and followed by one retailer, market demand is influenced by the investment of low-carbon product promotion and the degree of emission reduction. Stackelberg game theory is used to construct the game models with no-incentive model and three incentive models, respectively. The equilibrium solutions of the degree of low-carbon products promotion, the degree of low-carbon products emission reduction, the market demand, the cost-sharing ratio of the manufacturer to the retailer’s low-carbon products promotion, the degree of government’s incentive to the manufacturer’s low-carbon products, as well as the manufacturer’s and retailer’s profit are obtained in the four models. Finally, with the results, we provide some policy suggestions for the management and practice of a low-carbon supply chain.