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As an efficient way to deal with the exhaustion of traditional fossil fuels, new energy power generation has obtained much attention from the Chinese Government. In this context, more and more new energy power generation groups that consist of large numbers of regional enterprises have been founded and developed rapidly. However, researches related to comprehensive benefit evaluation of group-affiliated new energy power generation enterprises is still blank in China, which will hinder the benefit growth and sustainable development of such enterprises. A novel hybrid evaluation indicator system is proposed from both perspectives of sustainability and the internal management within the groups. Considering the preference information given on each of the indicators is featured by multi-source and multi-form, an evaluation framework to integrate the blended and complex evaluation information is designed. In addition, different from previous studies, this paper employs a combined technique of Stochastic Transformation for Blended Information (STBI) method and the Technique for Order Preference by Similar to Ideal Solution (TOPSIS) to simulate the evaluation process and rank the comprehensive benefit of evaluation objects. It can efficiently handle the comprehensive evaluation problems with blended and complex evaluation information and preserve the initial evaluation information to the utmost simultaneously. Finally, this paper applied the evaluation model to empirical research and the results show that the model meets the actual situation of the new energy power generation group and can provide a certain reference value

sustainability

Evaluating the Comprehensive Benefit of Group-Affiliated New Energy Power Generation Enterprises for Sustainability: Based on a Combined Technique of STBI and TOPSIS