The effectiveness of subsidies in improving the performance of renewable energy firms has aroused significant research attention in recent years. As subsidy modes may affect corporate financial performance,we have chosen companies specializing in wind and solar energy in the Shanghai and Shenzhen stock markets as samples.The relationships between the subsidy modes and financial performance of these two types of companies are investigated with a panel data model. Results of the total sample indicate that both indirect and non-innovative subsidy have significant effects on the financial performance of renewable energy companies. The regressive coefficient of the former,however, is a negative value, which illustrates that taxation, bonus, and other market-based mechanisms impair corporate profitability. Moreover, the influence of innovative subsidy is weak, which means that the subsidy used for research and development, technical demonstration, and other innovations of renewable energy enterprises have failed to effectively enhance corporate financial performance. In terms of sub-industries, the direct subsidy for wind energy companies has achieved a significant effect. Incomparison, the indirect subsidy and innovative subsidy acquired by solar energy companies have notably reduced corporate profitability. Thissuggests an urgent reform of subsidy policy for this industry is needed. The government should consider differences in the effects subsidies have for wind and solar energy companies when improving subsidy policy. In addition, market-based subsidy mechanisms should be perfected, and the structure of innovative subsidies should be ameliorated.

To ensure the hierarchical structure of complex system illustrative and reasonable, the new method is presented to build and adjust hierarchical structure of complex system through integration of decision making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) models. First of all, the rationale and procedures of integrating DEMATEL and ISM are analyzed; then the method to perfect system's hierarchical structure with dummy nodes is proposed, which can be viewed as the images of the original nodes in system's hierarchical structure; at last, a material example is given to verify the methods mentioned above

The decision on the location of a straw-based power generation plant has a great influence on the plant’s operation and performance. This study explores traditional theories for site selection. Using integer programming, the study optimizes the economic and carbon emission outcomes of straw-based power generation as two objectives, with the supply and demand of straw as constraints. It provides a multi-objective mixed-integer programming model to solve the site selection problem for a straw-based power generation plant. It then provides a case study to demonstrate the application of the model in the decision on the site selection for a straw-based power generation plant with a Chinese region. Finally, the paper discusses the result of the model in the context of the wider aspect of straw-based power generation.