How would big data support societal development and environmental sustainability? Insights and practices

The theme of this Special Volume (SV) focuses on improving natural resource management and human health to ensure sustainable societal development. Natural resources have been exploited unduly regardless of the consequences, which has resulted in inappropriate management natural resources and has caused severe environmental degradation. Contributions in this SV addressed improved environmental management, utilization, and allocation of natural resources; evaluation of sustainable natural resource management; pollution prevention and treatment; and evaluation and suggestions for improved natural resource-related policies. The authors presented an inspiring panorama of the initiatives that have been developed throughout the world for sustainable natural resource management and improve societal development. Theoretically, new approaches to bridge the gaps between the economic development and environmental protection were increasingly dominant. Empirically, many of the papers provided case studies of regions in China and other regions. The authorship reflected growing collaboration between researchers from many different countries or universities. While the great diversity of contributions on the topic reflected the wealth of insights generated on the topic in recent years, there is much more that must be done to achieve societal sustainability in natural resource management.No Full Tex

Environmental Regulation and Green Productivity of the Construction Industry in China

There are few studies analyzing whether different types of environmental regulation have differential impacts on the efficiency of the construction industry. Using 2012-2016 panel data from 30 provinces in China, the green total factor productivity (GTFP) of the construction industry is measured with a global Malmquist Luenberger productivity index based on the epsilon measure (EBM-GML) model. Thereafter, a panel Tobit regression model is proposed to explore the relationship between three types of environmental regulation and the GTFP of the construction industry. The results show that: (1) from 2012 to 2016, the GTFP of the Chinese construction industry grew slowly at an average annual rate of 0.14%; (2) both one-phase lagged command-and-control and current phase market-based environmental regulation had a positive linear relationship with GTFP. One-phase lagged voluntary environmental regulation on the other hand, had an inverted U-shaped relationship with GTFP; (3) the three types of environmental regulation can be combined to establish a suitable environmental regulation system. The findings of this study provide guidance for the sustainable development of the construction industry by combining the actions of different types of environmental regulation

A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries

This paper aims to address the problem of allocating the CO2 emissions quota set by government goal in Chinese manufacturing industries to different Chinese regions. The CO2 emission reduction is conducted in a three-stage phases. The first stage is to obtain the total amount CO2 emission reduction from the Chinese government goal as our total CO2 emission quota to reduce. The second stage is to allocate the reduction quota to different two-digit level manufacturing industries in China. The third stage is to further allocate the reduction quota for each industry into different provinces. A new inverse data envelopment analysis (InvDEA) model is developed to achieve our goal to allocate CO2 emission quota under several assumptions. At last we obtain the empirical results based on the real data from Chinese manufacturing industries

CO2 emissions reduction of Chinese light manufacturing industries:a novel RAM-based global Malmquist-Luenberger productivity index

Climate change has become one of the most challenging issues facing the world. Chinese government has realized the importance of energy conservation and prevention of the climate changes for sustainable development of China's economy and set targets for CO2 emissions reduction in China. In China industry contributes 84.2% of the total CO2 emissions, especially manufacturing industries. Data envelopment analysis (DEA) and Malmquist productivity (MP) index are the widely used mathematical techniques to address the relative efficiency and productivity of a group of homogenous decision making units, e.g. industries or countries. However, in many real applications, especially those related to energy efficiency, there are often undesirable outputs, e.g. the pollutions, waste and CO2 emissions, which are produced inevitably with desirable outputs in the production. This paper introduces a novel Malmquist-Luenberger productivity (MLP) index based on directional distance function (DDF) to address the issue of productivity evolution of DMUs in the presence of undesirable outputs. The new RAM (Range-adjusted measure)-based global MLP index has been applied to evaluate CO2 emissions reduction in Chinese light manufacturing industries. Recommendations for policy makers have been discussed

Influence of agglomeration and selection effects on the Chinese construction industry

The determination of whether market size can influence industrial agglomeration or selection is an important topic in economic development. To analyse the differential economic development of the construction industry under different market sizes, this research analyses the employment density of China’s provinces and their Total factor productivity (TFP). It also analyses whether the difference in the provinces’ productivity are explained by their agglomeration and selection effects. First, a DEA-Malmquist model is used to calculate the TFP of each construction industry sub-sector. Then, a nested model is used to measure the influence of the selection and the agglomeration effects on the TFP at different market sizes of the construction industry. Results evidence that there are significant differences in the construction productivity at different sub-sectors in different regions of China. These differences are mainly the consequence of the agglomeration effect, rather than the selection effect. Findings of this study suggest that the Chinese construction industry should optimise its structure in different provinces to achieve a balanced growth at different market sizes

The effect of strategic synergy between local and neighborhood environmental regulations on green innovation efficiency: The perspective of industrial transfer

Considering the environmental governance dilemma caused by environmental decentralization, this study aims to explore whether the strategic synergy between local and neighborhood environmental regulations can be an essential tool to improve green innovation efficiency and achieve sustainable development. Using the data of industrial firms from 2005 to 2019, and employing network slack-based measure and Tobit regression, this study provides empirical evidence that (1) the green innovation efficiency shows an upward trend in fluctuations but still has great room for improvement; (2) the direct impact of local environmental regulation on green innovation is positive, but the indirect impact through forcing firms to transfer into the neighborhood with loose regulation is negative, that is, the industrial transfer plays a suppression effect; (3) the strategic synergy of environmental regulations has U-shaped and direct effect on green innovation and also has a positive indirect effect through inhibiting the firm's behavior transferring into the neighborhood. This study reveals the influence mechanism of the strategic synergy of local-neighborhood environmental regulations and offers empirical evidence to explain the reason why synergistic environmental governance can effectively promote green innovation, which provides the theoretical guidance for government to formulate environmental policies and construct an environmental governance system

Exploring the affecting mechanism between environmental regulation and economic efficiency: new evidence from China's coastal areas

China's commitment to building the country into a maritime power has seen a rapid growth in its marine economy in recent years. In the meantime, increasing concern over environmental degradation and sustainability has made the government to shift attention from marine development to marine ecosystem protection by formulating more environmental policies. There has been a long-standing debate between traditional views and well-known Porter Hypothesis (PH) over the impact of environmental regulation on the competitiveness and efficiencies of firms and industries. Aiming to obtain empirical evidence of the possible impact, this paper uses the Super-Efficiency Slacks-Based Measure (SE-SBM) model to calculate economic efficiency considering undesired outputs and the system Generalized Moment Method (GMM) to examine the relationship between the two variables, using data from 11 provinces and cities in China's coastal areas. The results seem to support the presence of the PH in Chinese marine economy and show a U-shaped relationship between environmental regulation and economic efficiency. In addition, it is also found optimization of industrial structure can impose a positive effect on economic efficiency, while capital investment and science and technological innovations may have a negative effect. Based on these results, the paper puts forward some recommendations for policy makers

Energy Efficiency Transitions in China: How persistent are the movements to/from the frontier?

This study examines the energy efficiency transitions in China using provincial data covering the period 2003–2015. Sustainable progress in energy efficiency achievements is beneficial to energy insecurity and the achievement of the Paris Agreement. This article combines the stochastic frontier method with the panel Markov-switching regression to model energy efficiency transitions. Estimated energy efficiency scores showed significant regional and provincial heterogeneity. Also, while human capital development, urbanization, and foreign direct investment promote energy efficiency, price and income per capita reduce it. The transition probabilities indicate that the high energy-efficient state is less sustainable, and the movement towards the frontier seems less persistent than movement from the frontier. Thus, it appears that China is not making sustainable progress in energy efficiency. The unsustainable nature of the high energy-efficient state suggests that in China, there are weak energy efficiency efforts and energy efficiency policies lack robustness