Financing mode of energy performance contracting projects with carbon emissions reduction potential and carbon emissions ratings

被引:22
|
作者
Shang, Tiancheng [1 ]
Yang, Lan [1 ]
Liu, Peihong [2 ]
Shang, Kaiti [3 ]
Zhang, Yan [1 ]
机构
[1] Tianjin Univ, Coll Management & Econ, Tianjin 300072, Peoples R China
[2] Tianjin Univ Tradit Chinese Med, Coll Culture & Hlth Commun, Tianjin 301617, Peoples R China
[3] Bournemouth Univ, Fac Management, Poole BH12 5BB, Dorset, England
关键词
Energy performance contracting projects; Energy service company; Carbon emissions rating; Fuzzy binary tree model; Pre-transaction; Post-transaction; SERVICE COMPANIES; BUSINESS MODELS; CHINA; EPC; PRICE; RISK;
D O I
10.1016/j.enpol.2020.111632
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper focuses on energy performance contracting (EPC) projects that can potentially reduce carbon emissions. Based on the reasons for financing difficulties in China's EPC projects, the paper delineates opportunities for the energy-saving service industry as well as the ownership of carbon emissions. According to the transaction cost and resource dependence theories, this paper constructs a financing mode for EPC projects based on the total amount of control and quota trading. Financing mode is divided into two types according to the carbon emissions objectives noted by emissions demanders: self-use and non-self-use. Each financing mode is then categorized as either preor post-transaction given the differences in carbon emissions trading periods, and their characteristics are compared. Regarding carbon emissions ratings, a parabolic fuzzy number is used to describe how carbon emissions trading prices fluctuate and how the risk-neutral probability and weighted interval of European call option prices are obtained. The option price interval is then converted into a certain value by defuzzification. The financing mode this paper designs not only improves the possibility of EPC projects' financing and profitability, but also expands energy service companies' scope in choosing projects. This paper's carbon emissions rating method enables participants' understanding of the magnitude of uncertainty, obtains more accurate market price forecasts, and helps investors choose their acceptable confidence levels to guide investment strategies.
引用
收藏
页数:11
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