Risk assessment in straw-based power generation public-private partnership projects in China: A fuzzy synthetic evaluation analysis
Risk assessment in straw-based power generation public-private partnership projects in China: A fuzzy synthetic evaluation analysis
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DOI：
10.1016/j.jclepro.2017.06.008
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发表时间：
2017-09
影响因子：
11.1
通讯作者：
Yunna Wu;Lingwenying Li;Ruhang Xu;Kaifeng Chen;Yong Hu;Xiaoshan Lin
中科院分区：
文献类型：
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作者：
Yunna Wu;Lingwenying Li;Ruhang Xu;Kaifeng Chen;Yong Hu;Xiaoshan Lin
随着中国对节能减排和环保要求的不断提高，秸秆发电发展迅速，不仅可以提供清洁能源，还可以直接解决农民焚烧秸秆造成的严重环境问题。目前，政府正在利用私营部门的资金和技术优势，逐步将公私合作模式应用于这一领域。为评估中国公私合作秸秆发电项目的风险，采用问卷调查的方法，确定了44个风险因素，筛选出19个关键风险因素，并将其分为4类。然后，通过模糊综合评价法，计算出各灾害发生的可能性（LO）、影响程度（MI）、综合风险等级（IRL）、灾害总风险。CRF“政府发明”是最关键的风险因素，CRG“项目参与者风险”是最关键的风险因素组。总体而言，最终的模糊综合结果表明，中国公私合作秸秆发电项目的IRL较高。最后，对每个CRF给出了一些建议。本文建立的评价指标体系、多准则模糊综合评价框架、所得结论和风险应对措施，可以帮助政策制定者和项目决策者做出适当的决策，将有限的资源配置到更值得关注的风险上。同时，本文可以为私营部门规避风险过大的项目提供参考，同时也有利于公共部门采取有效措施降低项目风险，从而吸引更多优质的民间资本。此外，秸秆发电公私合作项目的风险评估还没有得到足够的讨论和重视。因此，本研究扩充了知识，为文献做出了贡献。
With the increasing requirement on energy saving, emission reduction and environmental protection in China, the straw-based power generation is developing rapidly, which can not only provide clean energy, but also address the serious environmental problems caused by farmers’ burning straw directly. Currently, the government is gradually applying Public-Private-Partnership model to this field making use of private sectors’ capital and technological advantages. To assess the risks in public-private partnership straw-based power generation projects in China, 44 risk factors were identified and 19 critical risks factors (CRFs) were selected and classified into 4 groups (CRGs) based on a questionnaire survey in this paper. Then, the likelihood of occurrence (LO), magnitude of impact (MI), the integrated risk level (IRL) of each CRF, CRG and the overall risk were calculated through the fuzzy synthetic evaluation method. The CRF “government invention” was the most critical risk factor and the CRG “project participant risk” was the most critical risk factor group. Overall, the final fuzzy synthesis result indicated that the IRL of the public-private partnership straw-based power generation projects in China was high. Finally, some recommendations were given for each CRF. The evaluation index system, the multi-criteria fuzzy synthetic evaluation framework, the obtained conclusions and the risk response measures in this paper can help policy makers and project decision makers make appropriate decisions and allocate the limited resources to the risks worthy more attention. Simultaneously, this paper can provide a reference for the private sector to avoid too risky project and at the same time facilitate the public sector to take effective measures reducing project risks so as to attract more high-quality private capital. In addition, the risk assessment in public-private partnership straw-based power generation projects has not been discussed and paid enough attention yet. Thus, this study expands the knowledge and contributes to the literature.