This study proposes a slack-based endogenous directional distance function model (SBEDDF) to assess the environmental impact of China's power generation industry. By selecting directional vectors according to slac...
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This study proposes a slack-based endogenous directional distance function model (SBEDDF) to assess the environmental impact of China's power generation industry. By selecting directional vectors according to slack values and endowing them with norms, this model guarantees that unit invariance and efficiency value measures are suitable for economic interpretation. The results of this study indicate that the environmental efficiency of China's power generation industry is low and varies considerably from one region to another. The optimal approach to reduction of emissions is unique for each region. For example, in Guangxi, reducing SO2 emissions is the priority, while in Shanxi, NOx emissions need to be targeted. The results of the Tobit regression analysis indicate that the power function of unit elasticity fits the environmental Kuznets curve of the power industry well. These results demonstrate that it is prudent for environmental administrators to tailor emission reduction standards and incentive policies to the prevailing circumstances in a region. (C) 2018 Elsevier Ltd. All rights reserved.
Along with the rapid growth of the coastal economy as well as the broadening and deepening of ocean exploration, the extensive growth pattern of China's marine economy led to such problems as more consumption of m...
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Along with the rapid growth of the coastal economy as well as the broadening and deepening of ocean exploration, the extensive growth pattern of China's marine economy led to such problems as more consumption of marine resources, more waste emissions, and the deterioration of the marine ecological system. Therefore, the study of marine economic efficiency has great significance for achieving cleaner production and sustainable development of China's marine economy. Based on the global Malmquist-Luenberger index model, this paper brings undesirable output into the measurement of total factor productivity to evaluate the green efficiency of China's marine economy under environmental constraints. In order to better depict the dynamic nature of marine economic efficiency, eleven coastal regions in China were selected as the objects of this study, with data collected from 2006 to 2014. The results indicate that total factor productivity of China's marine economy without considering undesirable output is markedly higher than that considering it. China's coastal regions differed in the green efficiency of the marine economy. The green efficiency of the marine economy in Tianjin rose the fastest, while in Guangxi it dropped the fastest, and the average annual growth rate varied by 8.18% between the two provinces. Moreover, the green efficiency of the East China Sea Economic Circle is the highest in the three coastal regions followed by the Bohai Economic Rim, while that of the South China Sea Economic Circle is the lowest. The improvement of the green efficiency of China's marine economy mainly stems from technological progress, while the improvement of technical efficiency has little influence on it, sometimes even adversely affecting it. Based on these findings, we discuss the corresponding policy suggestions on the sustainable development of China's marine economy. (C) 2018 Elsevier Ltd. All rights reserved.
Data envelopment analysis (DEA) models appear in envelopment and multiplier forms, which are in a primal-dual relationship. In this paper, we derive the general multiplier form of path-based models, encompassing radia...
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Data envelopment analysis (DEA) models appear in envelopment and multiplier forms, which are in a primal-dual relationship. In this paper, we derive the general multiplier form of path-based models, encompassing radial, directionaldistancefunction, and hyperbolic distancefunctionmodels as special cases. We investigate the economic interpretation of the multiplier models and uncover the link between shadow profit inefficiency and technical inefficiency provided by path-based models. Using the optimality conditions for the primal-dual pair, we precisely describe the two-way relationship between the optimal solutions of the multiplier model and the supporting hyperplanes of the technology set at the projection. This relationship serves as a mathematical justification for extending one of the early approaches to measuring returns-to-scale (RTS) onto the entire class of path-based models. Moreover, we demonstrate the eligibility of this method by revealing the fact that the set of all strongly efficient benchmarks for the assessed unit in path-based models does not need to belong to a single strongly efficient face of technology set. This finding changes the view on traditional approaches to RTS measurement that rely on supporting hyperplanes encompassing a single strongly efficient face of the technology set. In this new perspective, we propose two methods for RTS measurement. The first is based on the hyperplanes at the projection, and the second method adapts the minimum face method to be suitable for path-based models. Both methods are fully justified and brought to an algorithmic form.
This paper explores the relationship between environmental regulation, innovation, and competitiveness using environmental patent data. The analysis is conducted in two stages. First, a non-parametric frontier analysi...
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This paper explores the relationship between environmental regulation, innovation, and competitiveness using environmental patent data. The analysis is conducted in two stages. First, a non-parametric frontier analysis is implemented to estimate efficiency scores, including a measure of technological innovation based on patent stocks. Second, econometric methods are applied to analyse the role of policy stringency and policy design on efficiency. Our estimation sample covers thermal power plant sectors in 20 countries from 1990 to 2009. The results show that the stringency of environmental regulations is a significant determinant of productive efficiency with respect to pollutant emissions as well as fuel use. However, these effects turn negative once the level of stringency leaps over a certain threshold. In addition, the paper concludes that the positive effect of regulatory stringency can be diminished by a negative effect of regulatory differentiation with measures which vary in stringency across plant size and age having negative consequences, and these effects are increasing over time. Finally, it is found that integrated approaches to environmental innovation are more likely to bring about efficiency improvements than end-of-pipe technologies. (C) 2017 Elsevier B.V. All rights reserved.
In traditional multi-attribute group decision-making (MAGDM) methods, the aggregation of expert evaluation information, the normalization of attribute scales, and the determination of attribute prior weights can lead ...
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In traditional multi-attribute group decision-making (MAGDM) methods, the aggregation of expert evaluation information, the normalization of attribute scales, and the determination of attribute prior weights can lead to information loss and inconsistent results. In addition, these methods cannot identify and improve the shortcomings of non-optimal alternatives. Considering these, this paper proposes a MAGDM method based on data envelopment analysis (DEA) by setting up a parallel expert evaluation system, thus integrating the initial opinions of all experts to rank the alternatives from a global perspective. First, we construct the multi-expert evaluation process as a parallel system from the global perspective so that the decision-making process is based on the initial expert evaluation information. Then, a new directional distance function model based on endogenous projection directions is proposed to measure the alternatives under each expert subsystem, eliminating data processing and artificial weight assignment. The non-optimal alternatives can be improved to an efficient state by adjusting the attribute levels to target values. Next, we propose a DDF super-efficiency model to perform a full ranking of the alternatives. Finally, a case study is provided to demonstrate the rationality and effectiveness of the proposed method.
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