Enterprise Energy-saving Emission Reduction Project Decision-making Research

With people's increasing awareness on environmental problems, energy-saving and the reduction of green house gas emissions will be an important measure on the government's part. Relevant laws and regulations will be promulgated one after one, hence placing stricter guidelines on enterprises. But as the executive bodies of such measures, enterprises can rarely come up with sound, scientific strategies to do so. This, of course, puts themselves in a passive position in which they make decisions that are profitable in the short term but not necessarily so in a longer one. Hence the need to search for ways of reducing green house gas emissions from the perspective of enterprises.Adopting ANP comprehensive assessment method and utilising the "supper decision" software, this paper explores the various approaches to energy-saving and emission-reducing. The main results of this paper include: establishing a system of parameters; optimizing "supper decision " software; setting up the strategy model, settling the elements and element groups, comparing and contrasting the different approaches, establishing a fuzzy assessment system; as well as a sensativity analysis of the parameters found on the Internet.the main achievements of this paper:1 It establishes a system of parameters against which all appoaches of energy-saving and emission-reducing are measured. It not only expands the current system of parameters but also gives an analysis of the relationship between different parameters and the relevant feedbacks from each parameter.2 It gives the organization and computation design for the "supper decision " software, which is specifically designed to suit the characteristics of energy-saving and emission-reducing strategy.3 It establishes the strategy model for energy-saving and emission-reducing using the optimalized 'supper decision' software. The whole decision then comes to 'to do' or 'not to do', which leads to a 0.54-0.46 division.4 Through the sensativity analysis, not only are the controlling parameters made clear, but the relationship between the sub-controlling parameters and other parameters obtained from the Internet is also brought to light. The changing pattern of the interdependent parameters is achieved as well.The parameters we chose from the Internet for sensativity analysis are those which can be regulated by the government, therefore they may serve as an enlightenment for the government's quantitative analysis of the energy-saving and emission-reducing effect.All these lead us to the conclusion that the research of this paper will contribute greatly to the strategy-making approaches of the government and provide some technical support. It is also enlightening with respect to the government's quantitative analysis of the validity of variousparameters. Therefore, this paper is of high value in terms of theoretical significance as well aspractical application.