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In the face of environmental degradation, sustainable development has become a common goal across the globe. Making a scientifically based investment scheme is of great significance to promote the sustainable development of China's economy. However, there is scarce research related to such an investment scheme of sustainable development. This paper proposes a new inverse data envelopment analysis method with undesirable outputs to make several scientifically based investment schemes from different perspectives, namely, the natural, regulation, and optimal perspectives. By this method, decision makers can scientifically forecast the specific amount of investment based on their actual sustainable development objectives, which is conducive for reducing the blindness of investment in the future. In addition, a new ideal perspective is defined to guide a definite direction for improving the level of sustainable development. Combined with the gray forecasting model GM(1,1), the methods proposed by this paper were then applied to analyze the investment problem for China's sustainable development during the 2015–2024 period. The results show that: the unbalanced distribution of labor investment and the excessive investment in capital and energy are serious barriers to China's sustainable development in the short term; and in the long term, the demand for investment in labor and capital will continue to increase along with a lower demand for energy investment, and that appropriately strengthening environmental regulations will not affect the overall demand for investment. Meanwhile, improvement directions for improving China's sustainable development are discussed, and the results show that most of developing and undeveloped regions in China have great potential for improvement. Finally, some suggestions are proposed in order to create better conditions for China's sustainable development. [ABSTRACT FROM AUTHOR]

Rapid economic growth and urbanization in China have resulted in the dual threats of shortage of water and pollution of water. It is increasingly acknowledged that the efficiency of water resource system is influenced by not only the Water Use (WU) process, but also the process of Wastewater Treatment (WT). This paper considers both WU and WT as an integrated two-stage WUWT system to provide more comprehensive efficiency evaluation. In the first stage (WU subsystem), there are two parallel units, economic and social WU sub-minors, which consume water and capital to produce economic and social benefits. Meanwhile, the undesirable wastewater inevitably arises, which is treated in the second stage (WT subsystem). In order to assess the performance of the integrated WUWT system, an extended mixed network structure two-stage Slacks-Based Measure (SBM) Data Envelopment Analysis (DEA) model is developed to measure the detailed efficiencies and spot the weak link of the system. For case study, the provincial panel data during 2006–2015 of China are selected to verify the applicability of the proposed approach. Discussion is made from both time- and region-perspectives: over the ten years, the WU efficiencies are often higher than the WT efficiencies, so more actions should be carried out to improve the process of WT; from 2006 to 2011, social WU efficiencies are often lower than economic WU efficiencies, but the social WU efficiency has been improved after 2012; in terms of the overall efficiencies, the economically and socially developed provinces also have the higher efficiencies. Furthermore, the results demonstrate that the integrated WUWT system is efficient if and only if both WU and WT subsystem are both efficient, and the WU subsystem is efficient if and only if both economic and social WU sub-minors are efficient. [ABSTRACT FROM AUTHOR]

Abstract: The rapid economic development of China has intensified the country's environmental problems such as pollution and waste. As industry is the main contributor to environmental deterioration, the development mode of industry has attracted attention from the government and the public. In this paper, we have assumed that the industry is permitted a fixed total amount of pollution in order to avoid excessive pollution. If one province shows increased pollution, other provinces are required to reduce pollution by the same amount to maintain the total level of pollution. However, so far, few studies have considered such competition over outputs. This paper presents a new data envelopment analysis approach, which considers both the fixed and the variant sum desirable outputs in the performance improvement of a decision making unit, to evaluate the environmental efficiencies of China's industry from 2007 to 2011. The analysis results demonstrate that some economically developed provinces have better performance than less developed provinces; in particular, all efficient provinces are the developed ones. The Chinese government should focus on the increasing differences in environmental efficiencies among regions and take measures to address them. [Copyright &y& Elsevier]