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In recent years, the rapid development of the rare earth industry has had a serious impact on the environment. Some enterprises have taken measures to improve the production process. In order to explore the sustainability of this industry and these improvements’ environmental benefits, this paper combines emergy analysis and lifecycle assessment to evaluate and compare the production process of rare-earth oxides considering the three aspects of emergy flow, pollutant emissions, and emergy-based indicators. Changes in the emergy of pollutant emissions before and after improvement of the production process are discussed. The results show that the greatest inputs in the mining and beneficiation stage and smelting separation stage are labor force and service and non-renewable resources, respectively. These two production stages are highly dependent on external input and have weak competitiveness. Both stages place great pressure on the environment, so the bastnasite production process would be unsustainable in the long term. After the improvement, the environmental impact of the production process for bastnaesite changed significantly, indicating that the improvement effect of the wastewater treatment facilities and the change of fuel from coal to natural gas is remarkable.

Innovation ability has become one of the core elements in the pursuit of China’s green growth, and high-tech industries are playing a leading role in technological innovation in China. With the rapid development of China’s high-tech industries, their innovation efficiency has attracted widespread attention. This article aims to illustrate a shared inputs two-stage network Data Envelopment Analysis (DEA), to measure the innovation efficiency of high-tech industries in China’s 29 provinces from 1999 to 2018. The results indicate that there are obvious differences in the innovation efficiency of the provinces. The technology development efficiency, the technical transformation efficiency, and the overall innovation efficiency of the developed east coast provinces are generally higher than those of the backward central and western provinces. This article further applies the spatial econometrics model to analyze the factors influencing the innovation efficiency of high-tech industries. We have found that government support, R&D input intensity, industries aggregation, economic extroversion, and the level of development of the modern service industries cause varying degrees of impact on innovation efficiency.

With rapid progress in the corporate social responsibility (CSR) theories and the up-gradation of the global market information disclosure system, enterprises have increased their attention toward relevant stakeholders and social responsibility. CSR exerts a substantial impact on the sustainable development of enterprises and markets in the economic and social fields. On the one hand, the increasingly perfect supporting facilities promote the financial growth of the entire society. While on the other hand, the profit-seeking trend of capital is also on the rise. The incongruity between the rapid progress of enterprises and the lack of social responsibility limits the benign development of the market. This study discusses the antecedents of CSR from the variable combination perspective using the fuzzy-set qualitative comparative analysis. It also investigates which combination of characteristics has better CSR performance. After the configuration analysis, it is identified that four paths lead to high CSR performance. These include the market-developed type, political link type, financial performance type, and state-owned enterprise subsidy type, and the level of each type is explained in-depth. Finally, this study provides management inspiration for the government and enterprises to formulate a sound social responsibility strategy and improve CSR performance by optimizing the matching of CSR activities and business objectives.

Accurate measurement of the shadow price of carbon dioxide (CO2) is fundamental to the scientific assessment of the carbon emission reduction cost and the formulation and execution of China’s carbon emission mitigation policies. Underpinned by the directional distance function, this research uses a parametric linear programming method and a Bayes bootstrap estimation method to estimate the marginal CO2 emission reduction cost of the industrial sector in China and to quantify the related influencing factors. The results revealed that the marginal reduction cost of industrial CO2 is CNY 4565/ton. The marginal reduction cost of CO2 varies by industry, with the textile industry being the highest and the petroleum, coking and nuclear fuel processing industries the lowest. Meanwhile, an increasing number of industries are shifting to cleaner production. Furthermore, the marginal reduction cost of industrial CO2 has an “inverted U-shaped” relation with carbon intensity. Carbon emission reduction can be accomplished effectively if the carbon intensity is kept below the threshold value of 0.41 tons/CNY 10,000.

In recent years, the continuous spread of the COVID-19 epidemic has impacted the supply chain of enterprises. Mitigating the supply chain’s vulnerability has great significance for the survival and development of enterprises. Optimizing the business environment and building a digital government will help improve the external environment for enterprise development. However, its impact on the vulnerability of the enterprise supply chain has yet to be studied. Taking the impact of COVID-19 as an example, this paper uses the survey data of nearly 40,000 enterprises of the National Federation of Industry and Commerce in 2020 and “10,000 private enterprises evaluating the business environment”, to conduct systematic empirical research and fill the research gap in this area. The study indicates that the business environment and digital government can significantly mitigate the impact of COVID-19 on the supply chain. This conclusion is still valid after a series of robustness tests. Mechanism analysis demonstrates that the business environment and digital government can prompt the government to introduce effective mitigation measures promptly, better guarantee production factors and logistics, and thus improve the vulnerability of the enterprise supply chain. This study deepens our understanding of the economic outcome of the business environment and digital government and also sheds new light on supply chain management.

The energy resource is an essential input of economic growth, which has an important impact on the ecological environment and social welfare. From the perspective of social welfare, considering the radial and non-radial characteristics of different input and output indicators, and the inseparability of the energy input and undesirable output, this study employs the non-separable hybrid DEA (Data Envelopment Analysis) model to evaluate the total energy efficiency of Chinese provinces between 2012 and 2016. Furthermore, this study calculates the energy saving and emission reduction potentials of China. The results reveal that the average total factor energy efficiency in China from 2012 to 2016 is 0.694, which means that there are still 30.6% energy efficiency losses. There is great potential for China to save energy, reduce pollutant emissions, and increase the output of social welfare. There are great differences in the total factor energy efficiency among provinces. The average energy saving potential of the whole country is 60.5%. If the energy efficiency of all provinces can reach the frontier, the whole country can save more than half of the energy consumption. The highest national average emission reduction potential is SO2, followed by dust, CO2, and NOX. The implication of the conclusion is that in the development of regional economy, we cannot sacrifice the social welfare and sustainable development and take the growth rate of GDP as the only objective. Different energy saving and emission reduction policies should be put forward according to the characteristics of different provinces.

Digital financial inclusion (DFI) plays an increasingly important role in raising residents’ income levels and optimizing income structures. Using data from the 2015–2019 China Household Finance Survey (CHFS), this paper examines the impact of DFI on residents’ income and income structure from a microeconomic perspective using OLS fixed effects models and panel Tobit models. It was found that (1) DFI significantly raises residents’ income, increasing their total annual per capita household income by CNY4200, and increasing their annual per capita household wage income, business income and property income by CNY2430, CNY1030, and CNY450, respectively. In terms of different functions of DFI, the use of digital payment, digital lending and digital financing can raise the annual per capita household income of residents by CNY4250, CNY10,360 and CNY3050, respectively. (2) DFI increases wage income by enhancing residents’ household employment level, increases business income by promoting residents’ entrepreneurship, and increases property income by improving the financial market participation. (3) DFI has a more significant effect on increasing income for higher income groups as well as rural residents. The findings of this paper provide theoretical and practical support for optimizing the design of financial inclusion policies and exploring new drivers of income growth for residents.

Management of natural resources is pivotal for sustained economic growth—the increasing ecological footprints causing biocapacity deficit threaten the resource conversation agenda. The study identified the potential causes and consequences of natural resource depletion in a broad cross-section of 138 countries. Ecological footprints, international migrant stocks, industrial value-added, and population growth influenced natural resource capital across countries. The results show that ecological footprints, industrial value-added, and population growth are the detrimental factors of resource capital. In contrast, continued economic growth is helpful to conserve natural resources for future generations. The rise and fall in the natural resource degradation are evident in the wake of international migrants’ stocks to support an inverted U-shaped relationship between them. The Granger causality inferences confirmed the one-way linkages, running from international migrant stocks, economic growth, and population growth to natural resource degradation. It verifies migrants-led, affluence-led, and population-led resource degradation. Ecological footprints Granger causes industrial value-added across countries. The forecasting estimates suggested that economic growth would likely to influenced greater in magnitude to resource degradation by its innovation shocks of 4.791%, followed by international migrant stocks, population growth, ecological footprints, and industrial value added by their innovation shocks of 4.709%, 1.829%, 1.247%, and 0.700%, respectively. The study concludes that international migrant stocks should manage smartly, causing more resource degradation via a channel of increasing biocapacity deficit across countries.