Cracking the Achilles’ heel of energy performance contracting projects: the credit risk identification method for clients

References

• Bao, X. Z., and Y. Yang. 2013. Early warning of financial distress using clustering-rough sets-neural networks. Journal of Systems & Management 22 (3):359–65.
   Google Scholar
• Barbara, F., and Y. M. Hui. 2007. New progress in energy efficiency projects in California. Power Demand Side Management 9 (1):66–67.
   Google Scholar
• Berghorn, G. H., and M. Syal. 2019. Risk model for energy performance contracting in correctional facilities. Journal of Green Building 14 (2):61–82. doi:10.3992/1943-4618.14.2.61.
   Web of Science ®Google Scholar
• Chen, X., and M. X. Xie. 2009. Application of logistic model in credit risk identification of listed companies in iron and steel industry. Statistics and Decision-making 19:82–85.
   Google Scholar
• Chen, Y., and X. H. Li. 2017. Decision-theoretic rough set model based on weighted multi-cost. Computer Science 44 (12):239–44.
   Google Scholar
• Gao, S., L. Dong, Y. Gao, and X. Liao. 2012. Mid-long term wind speed prediction based on rough set theory. Proceedings of the Chinese Society of Electrical Engineering 32 (1):32–37.
   Google Scholar
• Garbuzova-Schlifter, M., and R. Madlener. 2016. AHP-based risk analysis of energy performance contracting projects in Russia. Energy Policy 97 (97):559–81. doi:10.1016/j.enpol.2016.07.024.
   Web of Science ®Google Scholar
• Geng, J. 2014. The application and risk identification of the energy performance contracting in the hotel industry. Resource Conservation & Environmental Protection 10:16–17.
   Google Scholar
• Ghjuvan, A. F., M. Laurent, and M. Rania. 2017. Uncertainty quantification for energy savings performance contracting: Application to an office building. Energy & Buildings 152:61–72.
   Web of Science ®Google Scholar
• Hui, X. F., and J. P. Sun. 2004. Credit risk identification of commercial banks: An empirical study of the credit matrix. International Financial Research 25 (3):21–27.
   Google Scholar
• Jannick, T., and T. Timm. 2019. Modeling energy efficiency insurances and energy performance contracts for a quantitative comparison of risk mitigation potential. Energy Economics 80:842–59.
   Web of Science ®Google Scholar
• Jie, D., Q. Hu, L. Zhang, Y. Qian, and D. Li. 2015. Feature selection for multi-label classification based on neighborhood rough sets. Journal of Computer Research & Development 52 (1):56–65.
   Google Scholar
• Jing, G. U., and Z. F. Zhou. 2010. A study on credit risk identification in emerging technology firms based on variable precision rough sets. Journal of Industrial Engineering & Engineering Management 24 (1):70–76.
   Google Scholar
• Lee, P., P. T. I. Lam, F. W. H. Yik, and E. H. W. Chan. 2013. Probabilistic risk assessment of the energy saving shortfall in energy performance contracting projects- A case study. Energy & Buildings 66 (5):353–63. doi:10.1016/j.enbuild.2013.07.018.
   PubMed Web of Science ®Google Scholar
• Lee, P., P. T. I. Lam, and W. L. Lee. 2015. Risks in energy performance contracting (EPC) projects. Energy & Buildings 92 (92):116–27. doi:10.1016/j.enbuild.2015.01.054.
   Web of Science ®Google Scholar
• Lee, P., P. T. I. Lam, and W. L. Lee. 2018. Performance risks of lighting retrofit in energy performance contracting projects. Energy for Sustainable Development 45 (45):219–29. doi:10.1016/j.esd.2018.07.004.
   Web of Science ®Google Scholar
• Li, M., and L. Q. Chen. 2007. Empirical analysis on credit risk identification of commercial banks based on BP neural network. Nanjing Social Science 1:18–29.
   Google Scholar
• Li, Z. H., and M. Li. 2005. The credit risk identification model of China’s commercial banks and its empirical study. Economic Science 27 (5):17–22.
   Google Scholar
• Liu, X., T. Cen, W. Zheng, and Z. Q. Mi. 2014. Neural network wind speed prediction based on fuzzy rough set and improved clustering. Proceedings of the Chinese Society of Electrical Engineering 34 (19):3162–69.
   Google Scholar
• Liu, X. J. 2015. The transaction cost theory of the relationship between government and market. Based on the Economic Research Guide 2:5–7.
   Google Scholar
• Liu, Y. L., and S. L. Gao. 2013. Credit risk identification of small enterprises under the supply chain financial model- An Empirical Study Based on the credit data in Beijing region. New Finance 1:45–49.
   Google Scholar
• Miao, D. Q. 2008. The rough set theory, algorithm and application. Beijing: Tsinghua University Press.
   Google Scholar
• Nie, R. X., Z. P. Tian, J. Q. Wang, H. Y. Zhang, and T. L. Wang. 2018. Water security sustainability evaluation: Applying a multistage decision support framework in industrial region. Journal of Cleaner Production (196):1681–704. doi:10.1016/j.jclepro.2018.06.144.
   Web of Science ®Google Scholar
• Peng, H. G., K. W. Shen, S. S. He, H. Y. Zhang, and J. Q. Wang. 2019. Investment risk evaluation for new energy resources: An integrated decision support model based on regret theory and ELECTRE III. Energy Conversion and Management (183):332–48. doi:10.1016/j.enconman.2019.01.015.
   Web of Science ®Google Scholar
• Qian, D., G. Q. Zhu, and J. Guo. 2019. Research on value and factors of the guarantee payment in the energy performance contracting in China. Energy Efficiency 12 (6):1547–75. doi:10.1007/s12053-019-09776-0.
   Web of Science ®Google Scholar
• Ruan, H. Q., X. Gao, and C. X. Mao. 2018. Empirical study on annual energy saving performance of energy performance contracting in China. Sustainability 10 (5):1–25. doi:10.3390/su10051666.
   PubMed Web of Science ®Google Scholar
• Shang, T. C., H. Wang, P. Liu, X. X. Li, and J. Q. Gao. 2014. Energy-consuming enterprises’ reputation risk identification. Journal of Tianjin University 16 (1):26–29.
   Google Scholar
• Shang, T. C., K. Zhang, P. H. Liu, and Z. W. Chen. 2017. A review of energy performance contracting business models: Status and recommendation. Sustainable Cities & Society 34 (34):203–10. doi:10.1016/j.scs.2017.06.018.
   Web of Science ®Google Scholar
• Shang, T. C., K. Zhang, P. H. Liu, Z. W. Chen, X. P. Li, and X. Wu. 2015. What to allocate and how to allocate?—Benefit allocation in shared savings energy performance contracting projects. Energy 91 (91):60–71. doi:10.1016/j.energy.2015.08.020.
   Web of Science ®Google Scholar
• Shang, T. C., and Z. N. Pan. 2007. Energy performance contracting project risk in modern business administration. Journal of Tianjin University 9 (3):214–17.
   Google Scholar
• Shang, T. C., Z. W. Chen, P. H. Liu, and K. Zhang. 2016. Recent progress on the critical success factors of energy performance contracting projects. Journal of Beijing Institute of Technology 18 (3):30–35.
   Google Scholar
• Tan, B. 2019. Design of balanced energy savings performance contracts. International Journal of Production Research 1–24. doi:10.1080/00207543.2019.1641240.
   Web of Science ®Google Scholar
• Wang, G. 2006. The interactive behavior, private information and win-win idea- The development of contemporary economic behavior to and scientific. Social Sciences in Tianjin 5:66–71.
   Google Scholar
• Wang, L., H. Y. Zhang, J. Q. Wang, and L. Li. 2018. Picture fuzzy normalized projection-based VIKOR method for the risk evaluation of construction project. Applied Soft Computing 64:216–26. doi:10.1016/j.asoc.2017.12.014.
   Web of Science ®Google Scholar
• Wang, L., J. J. Peng, and J. Q. Wang. 2018. A multi-criteria decision-making framework for risk ranking of energy performance contracting project under picture fuzzy environment. Journal of Cleaner Production 191:105–18. doi:10.1016/j.jclepro.2018.04.169.
   Web of Science ®Google Scholar
• Wang, Z. F., G. Y. Xu, R. J. Lin, H. Wang, and J. Z. Ren. 2019. Energy performance contracting, risk factors, and policy implications: Identification and analysis of risks based on the best-worst network method. Energy 170:1–13.
   Web of Science ®Google Scholar
• Wu, B. 2015. A summary of research on credit risk prevention in energy performance contracting. Enterprise Reform and Management 22:34–36.
   Google Scholar
• Wu, D. S., and L. Liang. 2004. Research of credit score based on v-fold cross-validation and Elman neural networks. Systems Engineering-theory & Practice 24 (4):92–98.
   Google Scholar
• Wu, H., Y. Wu, and J. Luo. 2009. An interval type-2 fuzzy rough set model for attribute reduction. IEEE Transactions on Fuzzy Systems 17 (2):301–15. doi:10.1109/TFUZZ.2009.2013458.
   Web of Science ®Google Scholar
• Wu, S. Z., and P. Z. Gou. 2011. Attribute reduction algorithm on rough set and information entropy and its application. Computer Engineering 37 (7):56–55.
   Google Scholar
• Wu, Y., and J. L. Zhou. 2019. Risk assessment of urban rooftop distributed PV in energy performance contracting (EPC) projects: An extended HFLTS-DEMATEL fuzzy synthetic evaluation analysis. Sustainable Cities and Society 47:1–22.
   Web of Science ®Google Scholar
• Wu, Z. J., X. C. Dong, and G. L. Pi. 2017. Risk evaluation of China’s petrochemical energy performance contracting (EPC) projects: Taking the Ningxia petrochemical company as an example. Natural Gas Industry 37:112–19.
   Google Scholar
• Xu, F., S. Yao, X. Ji, P. Zhao, and J. Wang. 2017. Uncertainty measurement method on flor information system based on fuzzy neighborhood rough set. Journal of Nanjing University 5:926–36.
   Google Scholar
• Yan, R. J., and S. Q. Yin. 2018. Micro-blog credit evaluation model based on selective neural network ensemble. Computer Engineering and Design 39 (5):1478–83.
   Google Scholar
• Yao, S., J. Wang, F. Xu, and J. Chen. 2017. Uncertainty measurement and attribute reduction in incomplete neighborhood rough set. Computer Application 38 (7):97–103.
   Google Scholar
• Yu, H., G. Y. Wang, and Y. Y. Yao. 2015. Research status and prospect of rough set theory of decision making. Journal of Computer Science 8:1628–39.
   Google Scholar
• Yuan, H. Z., X. J. Gao, C. Q. Yang, and X. P. Zhang. 2011. The current situation, existing problems and countermeasures of China’s energy performance contracting. Energy Technology and Economy 23 (1):58–61.
   Google Scholar
• Zhang, M. S., M. J. Wan, W. Jin, and C. Xia-Bauer. 2018. Managing energy efficiency of buildings in China: A survey of energy performance contracting (EPC) in building sector. Energy Policy 114 (114):13–21. doi:10.1016/j.enpol.2017.11.065.
   Web of Science ®Google Scholar
• Zhang, S. L., H. N. Cai, and G. F. Piao. 2009. Energy performance contracting project credit loss and countermeasures research. Construction Economy 23 (1):55–58.
   Google Scholar
• Zhang, W. J., and H. P. Yuan. 2019. Promoting energy performance contracting for achieving urban sustainability: What is the research trend? Energies 12:1–18.
   Google Scholar
• Zhang, W. J., and H. P. Yuan. 2019. A bibliometric analysis of energy performance contracting research from 2008 to 2018. Sustainability (11) (11) 11:1-23. doi:10.3390/su11133548.
   Web of Science ®Google Scholar
• Zhao, J., G. Y. Wang, W. U. Zhong-Fu, H. Tang, and L. I. Hua. 2004. Method of data discretization based on rough set theory. Mini-micro Systems 25 (1):60–64.
   Google Scholar
• Zhu, J. 2012. Comparison of EMC operating model based on risk analysis. Cooperative Economy & Technology 7:32–34.
   Google Scholar