The application of intelligent technology has an important impact on the green total factor productivity of China’s manufacturing industry. Based on the provincial panel data of China’s manufacturing industry from 2008 to 2017, this article uses the Malmquist–Luenburger (ML) model to measure the green total factor productivity of China’s manufacturing industry, and further constructs an empirical model to analyze the impact mechanism of intelligence on green total factor productivity. The results show that intelligence can increase the green total factor productivity of the manufacturing industry. At the same time, mechanism analysis shows that intelligence can affect manufacturing green total factor productivity by improving technical efficiency. However, the effect of intelligence on the technological progress of the manufacturing industry is not significant. In addition, the impact of intelligence has regional heterogeneity. It has significantly promoted the green total factor productivity in the eastern and central regions of China, while its role in the western region is not obvious. The research in this article confirms that intelligence has a significant positive impact on the green total factor productivity of the manufacturing industry, and can provide suggestion for the current further promotion of the deep integration of intelligence and the green development of the manufacturing industry to achieve the strategic goal of industrial upgrading.

The purpose of this study is to investigate the mechanisms of big data on consumer behavior on the models of C2C e-commerce. From the beginning of the following five aspects: recommendation system, information search, reputation system, virtual experience and security system, the paper discusses some factors that affect buying intention in C2C e-commerce under big data. It fully considers the characteristics of big data, and then constructs the behavioral decision-making model of C2C ecommerce consumers, especially the factors of perceived usefulness, perceived risk and trust are integrated into the model of this research. We conduct the survey method and collect 245 valid questionnaires on consumers in each area in Shanghai and online using the quota sampling method. The empirical data show that it has six hypotheses being rejected, and others are supported in 20 hypotheses. According to the results, the paper also discusses why these hypotheses are not supported and give some marketing countermeasures in order to help the e-commerce enterprises better respond to the challenges of big data.

Aim: Through the supply and demand of China's human resources for health status, age structure, educational level of existing health professionals and other aspects of statistical analysis to understand the current situation of China's health human resources, so as to put forward the healthy development of health human resource allocation optimization suggestions, and provide the basis for the formulation of relevant policies.Method: Using the software of SPSS and EXCEL software to descriptive analysis on human resources for health in China.Results: The lack of health human resources and inequalities exist at the same time, the distribution is greater than demand contradictions; Health care professionals degree level needs to improve; And so on. Therefore recommends the development of relevant policies to encourage aspiring young professionals to apply for health institutions for sustainable development reserve personnel and health services, and improve health care professional's career in medicine motivation to improve their social status. And should accelerate structural adjustment, increase academic and professional skills training human resources for health professionals in relatively poor areas, efforts to improve service levels.Keywords: human resources for health, human structure, allocation Human resources for health refers to all staff engaged in the provision of health services in the health departments and units, the status of human resources for health is one of the critical indicators to look at a country or a region's health service level, is a very important factor in health services system. Deepening medical and health system, improve China's medical and health services, fundamentally speaking, is to rely on the tireless efforts of the medical and health care workers. "CPC Central Committee and State Council on deepening the medical and health system" has been clear about the task to strengthen the construction of health human resources. Human resources for health is the key to implement health care reform and the development of health services. This requires us to focus on the strategy research of talent team construction and development further around the main steps of human resource management.

It is of great significance to study the spatial network of the new energy vehicle (NEV) industry innovation efficiency and its factors to promote the rational allocation of innovative resources and the coordinated development of Chinese NEV industry. First, the Super Efficiency Data Envelope Analysis model is used to measure innovation efficiency in the NEV industry in Chinese provinces, and based on the results, the improved gravity model is applied to construct a spatial correlation network. Then, by applying social network analysis (SNA) to study NEV industry development node spatial correlations, we conclude that there is no overall hierarchical structure. The SNA are applied to examine spatial correlations with respect to NEV industry innovation efficiency in each province, and to analyze the role and position of each province in the spatial correlation network. Finally, the influencing factors of spatial correlation of the innovation efficiency of China’s NEV industry has been discussed. The result shows that the difference in spatial distance and R&D investment has a significant impact on the spatial correlation of the NEV industry.

Serious environmental pollution due to the economic boom in China has forced the government to implement environmental regulations. This paper examines the relationship between environmental regulations and technological development in different regions of China. Industry data from 1999 to 2012 using the DEA (Data Envelopment Analysis)-Malmquist productivity index were analyzed. It was found that total productivity growth is mainly caused by the change in technological progress. The environmental regulations of industry had a positive effect on technical progress at the national level. However, the relationship between environmental regulation and technological progress showed significant differences at the regional level. Results showed that for every 1% increase in strength of environmental regulation, there was a corresponding 7.04% increase in technology progress in eastern China. However, in central and western China, results showed that for every 1% increase in strength of environmental regulation, technology progress declined by 4.91% and 1.08%, respectively. It is concluded that the Porter hypothesis is well supported by data from the advanced eastern regions, while not fully supported by data from the underdeveloped central and western regions. For the central and western regions, various reasons for deviation from the Porter Theory have been determined by using the Environmental Kuznets Curve (EKC). Policy implications such as using government allowances and bank loans to import well educated staff, to enhance production technologies, to implement environmental solutions, and to set up strict regulations are recommended for the policy makers.