4.7 Article

A risk assessment framework of PPP waste-to-energy incineration projects in China under 2-dimension linguistic environment

期刊

JOURNAL OF CLEANER PRODUCTION
卷 183, 期 -, 页码 602-617

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.02.077

关键词

Risk assessment; PPP; WTE; 2-dimension linguistic information; Cloud model

资金

  1. Fundamental Research Funds for the Central Universities [2017XS099, 2016MS70, 2018ZD14]
  2. Special Project of Cultivation and Development of Innovation Base [Z171100002217024]
  3. NCEPU Double First-Class Graduate Talent Cultivation Program
  4. Research Funds of Beijing Social Science [16GLC069]

向作者/读者索取更多资源

Risk assessment is critical to insuring the success of waste-to-energy (WTE) projects under public private partnership (PPP) model as risks are accompanied with the life-cycle of the projects. Uncertainty composed of fuzziness and randomness is an important issue in the risk assessment under increasingly complex environments. The 2-dimension linguistic information is a powerful tool to express the fuzziness of information, and meanwhile, the cloud model perfectly depicts the randomness of information with three numerical characteristics. Combining them together, this paper puts forward a risk assessment framework of PPP WTE incineration projects. Firstly, an evaluation index system for risk assessment of China's PPP WTE incineration projects is constructed, which includes 14 criteria involved in four dimensions of construction and operation risk, macro-economic risk, legal and socio-political risk, and government risk; secondly, a conversion model between 2-dimension linguistic variables and clouds is developed; thirdly, the cloud Choquet integral (CCI) operator is utilized to handle the correlations among risk factors; fourthly, a risk assessment framework is established to assess the overall risk level of several China's PPP WTE incineration projects. From the empirical demonstration and comparison analysis, the proposed framework can effectively deal with such a complicated problem and lead to an outstanding result. (C) 2018 Elsevier Ltd. All rights reserved.

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