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Business Risk Evaluation of Electricity Retail Company in China Using a Hybrid MCDM Method

Sen Guo, Wenyue Zhang and Xiao Gao
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Sen Guo: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Wenyue Zhang: State Grid Tianjin Electric Power Company, Tianjin 300010, China
Xiao Gao: Department of Finance, Accounting and Auditing Research, State Grid Energy Research Institute, Beijing 102209, China

Sustainability, 2020, vol. 12, issue 5, 1-21

Abstract: Electricity retail marketization reform is in progress in China, and many electricity retail companies (ERC) have been founded. The comprehensive evaluation of business risk for ERC can help effectively manage business risk and reduce risk loss, which is vital for its healthy and sustainable development. In this paper, a new hybrid multi-criteria decision making (MCDM) method integrating the Bayesian best-worst method (BBWM) and improved matter-element extension model (IMEEM) is proposed for business risk evaluation for an ERC. The latest group MCDM method, namely the BBWM is employed to determine risk criteria weights, and the IMEEM is used to rank the business risk of ERC. The evaluation index system is built including three aspects of economic operation risk, marketable risk and political risk. The business risk of ERC in China is evaluated by using the proposed MCDM method, and the result shows the current business risk belongs to ‘High’ grade and closer to ‘Very High’ grade more. The proposed MCDM method for business risk evaluation of ERC is effective and practical, which can provide references for risk management and sustainable development of ERC.

Keywords: electricity retail company; business risk evaluation; Bayesian best-worst method; improved matter-element extension model; sustainable development (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (13)

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