Skip to main content
SpringerLink
Log in

Evaluating the Regulatory Environment of Overseas Electric Power Market Based on a Hybrid Evaluation Model

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

This paper develops a hybrid model for evaluating the regulatory environment of overseas electric power market (OEPM), which is of great theoretical and practical significance for power grid enterprises. Power regulation and investment environment evaluation theories as well as fuzzy Delphi method (FDM) are referenced to identify the final evaluation indicators. Owing to the presence of qualitative indicators in the index system, the analytic hierarchy process (AHP) and improved gray relational analysis (IGRA) approaches are combined to determine the indicator weights so as to ensure the credibility of the weights. Considering the non-compensatory principle among primary indicators, the improved fuzzy comprehensive evaluation method (IFCEM) based on multiplicative synthesis technique is applied to evaluate the alternatives. The empirical results indicate that “Return on Investment” and “Bilateral Relationship” are the main perspectives that greatly affect the regulatory environment of OEPM, and that UK and Greece are the best and worst alternatives in terms of the regulatory environment of OEPM in the analyzed countries. Totally, the proposed hybrid framework expressed great capacity to evaluate and rank the regulatory environment of OEPM and can be also popularized in other fields to support enterprises in making decisions by evaluating the alternatives with ambiguity and uncertainty.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Uekusa, M.: Micro-economics of regulation (1992)

  2. Viscusi, W.K., Harrington, J.E., Vernon, J.M.: Economics of Regulation and Antitrust. MIT Press, Cambridge (2005)

    Google Scholar 

  3. Littlechild, S.: Electricity: regulatory developments around the world. Verfügbar unter: http://www.econ.cam.ac.uk/electricity/publications/index.htm (2001)

  4. Wang, J.: Government Regulation Economics Introduction—fundamental theory and its apply in Government Regulation practice, vol. 9, pp. 328–330. The Commercial Press, Beijing (2003)

  5. Phillips, C.F.: The Economics of Regulation: theory and practice in the transportation and public utility industries. RD Irwin (1969)

  6. The Regulatory Assistance Project. Power sector regulation purpose, authority, and practice financial regulation, pp. 27. http://www.raponline.org. Accessed 27 Sept 2005

  7. Independent Market Operator, Ontario. Market manual 2: market administration, part 2.5: maintaining surveillance data and amending the data catalogue. http://www.theimo.Com/. Accessed 25 Sept 2002

  8. Fahrioglu, M., Alvarado, F.L.: Designing incentive compatible contracts for effective demand management. IEEE Trans. Power Syst. 15(4), 1255–1260 (2000)

    Google Scholar 

  9. Berg, S.V.: Lessons in electricity market reform: regulatory processes and performance. Electr. J. 11(5), 13–20 (1998)

    Google Scholar 

  10. Peng, H., Ren, R.: Asymmetric information regulatory mechanisms under the supervision. Econ. Rev. 5, 36–39 (2003)

    Google Scholar 

  11. Visudhiphan, P., Ilic, M.D., Mladjan, M.: On the complexity of market power assessment in the electricity spot markets. In: Power Engineering Society Winter Meeting, vol. 1, pp. 440–446. IEEE, Amsterdam (2002)

  12. Lin, H., Zhou, H.: Performance based price regulation for electric power industry. Power Syst. Technol. 28(10), 28–33 (2004)

    Google Scholar 

  13. Joskow, P.L.: Restructuring, competition and regulatory reform in the US electricity sector. J. Econ. Perspect. 11(3), 119–138 (1997)

    Google Scholar 

  14. Andres, L.: Assessing the Governance of Electricity Regulatory Agencies in the Latin American and Caribbean Region: A Benchmarking Analysis. World Bank Publications, Washington (2007)

    Google Scholar 

  15. Nyoike, P.: Is the Kenyan electricity regulatory board autonomous? Energy Policy 30(11), 987–997 (2002)

    Google Scholar 

  16. Li, C., Kang, C., Jiang, J., et al.: Study on information publishing and market assessment in electricity market surveillance. Autom. Electr. Power Syst. 27(11), 1–6 (2003)

    Google Scholar 

  17. Farmer RN, Richman BM. International business: an operational theory. Cedarwood Press (1971)

  18. Schürmann, G.: A changing regulatory and political environment: what impact does it have on the analysis of a financial institution? In: Rating von Finanzinstituten, vol. 105–118. Springer Fachmedien Wiesbaden (2016)

    Google Scholar 

  19. Litvak, I.A., Banting, P.M.: A conceptual framework for international business arrangements. Mark. New Sci. Plan. 460–467 (1968)

  20. Stobaugh, R.B.: How to analyze foreign investment climates—4 techniques for dealing with tricky questions of economic and political stability. Harv. Bus. Rev. 47(5), 100–108 (1969)

    Google Scholar 

  21. Jianshu, M.: Investment Environment Assessment Method, pp. 3–21. Beijing-Hong Kong Academic Exchange Centre, Beijing (1987)

    Google Scholar 

  22. Saaty, T.L.: Analytic Hierarchy Process. Wiley, New York (1980)

    MATH  Google Scholar 

  23. Saaty, T.L.: The seven pillars of the analytic hierarchy process. In: Multiple Criteria Decision Making in the New Millennium, pp. 15–37. Springer, Berlin (2001)

    Google Scholar 

  24. Saaty, T.L.: Analytic hierarchy process. In: Encyclopedia of operations research and management science, pp. 52–64. Springer, New York (2013)

    Google Scholar 

  25. Calabrese, A., Costa, R., Levialdi, N., et al.: A fuzzy analytic hierarchy process method to support materiality assessment in sustainability reporting. J. Clean. Prod. 121, 248–264 (2016)

    Google Scholar 

  26. Zhang, B.: Assessment on China’s foreign direct investment environment: the comprehensive scoring method and its applications. Financ. Trade Econ. 2012, 2 (2012)

    Google Scholar 

  27. Liang, Z., Yang, K., Sun, Y., et al.: Decision support for choice optimal power generation projects: fuzzy comprehensive evaluation model based on the electricity market. Energy Policy 34(17), 3359–3364 (2006)

    Google Scholar 

  28. Cai, T., Dai, H.C., Song, H.X.: Research on the evaluation model of brand competitiveness of power enterprises based on the fuzzy comprehensive evaluation method. Fuzzy Syst. Data Min. Proc. FSDM 281, 17 (2016)

    Google Scholar 

  29. Wu, D.D., Olson, D.L.: Online banking efficiency and risk evaluation with principal component analysis. In: Enterprise Risk Management in Finance, pp. 99–107. Palgrave Macmillan, London (2015)

    Google Scholar 

  30. Mirhedayatian, S.M., Azadi, M., Saen, R.F.: A novel network data envelopment analysis model for evaluating green supply chain management. Int. J. Prod. Econ. 147, 544–554 (2014)

    Google Scholar 

  31. Grace, A.M., Williams, S.O.: Comparative analysis of neural network and fuzzy logic techniques in credit risk evaluation. Int. J. Intell. Inf. Technol. 12(1), 47–62 (2016)

    Google Scholar 

  32. Rahmani, S., Omidvari, M.: Assessing safety risk in electricity distribution processes using ET & BA improved technique and its ranking by VIKOR and TOPSIS models in fuzzy environment. Health Saf. Work 6(1), 1–12 (2016)

    Google Scholar 

  33. Opricovic, S., Tzeng, G.H.: Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res. 156(2), 445–455 (2004)

    MATH  Google Scholar 

  34. Fan, G., Zhong, D., Yan, F., et al.: A hybrid fuzzy evaluation method for curtain grouting efficiency assessment based on an AHP method extended by D numbers. Expert Syst. Appl. 44, 289–303 (2016)

    Google Scholar 

  35. Li, W., Zhu, Z., Jiang, F., et al.: Fault diagnosis of rotating machinery with a novel statistical feature extraction and evaluation method. Mech. Syst. Signal Process. 50, 414–426 (2015)

    Google Scholar 

  36. Tang, H.: A novel fuzzy soft set approach in decision making based on grey relational analysis and Dempster-Shafer theory of evidence. Appl. Soft Comput. 31, 317–325 (2015)

    Google Scholar 

  37. Jane, C.J.: A hybrid analytic network process with grey fuzzy model for large-scale project risk analysis. J. Grey Syst. 19(2), 73–82 (2016)

    Google Scholar 

  38. Rabbani, A., Zamani, M., Yazdani-Chamzini, A., et al.: Proposing a new integrated model based on sustainability balanced scorecard (SBSC) and MCDM approaches by using linguistic variables for the performance evaluation of oil producing companies. Expert Syst. Appl. 41(16), 7316–7327 (2014)

    Google Scholar 

  39. Zornoza, R., Acosta, J.A., Bastida, F., et al.: Identification of sensitive indicators to assess the interrelationship between soil quality, management practices and human health. Soil 1(1), 173 (2015)

    Google Scholar 

  40. Stewart, B.T., Gyedu, A., Quansah, R., et al.: District-level hospital trauma care audit filters: Delphi technique for defining context-appropriate indicators for quality improvement initiative evaluation in developing countries. Injury 47(1), 211–219 (2016)

    Google Scholar 

  41. Li, L., Liu, F., Li, C.: Customer satisfaction evaluation method for customized product development using entropy weight and analytic hierarchy process. Comput. Ind. Eng. 77, 80–87 (2014)

    Google Scholar 

  42. Aragonés-Beltrán, P., Chaparro-González, F., Pastor-Ferrando, J.P., et al.: An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects. Energy 66, 222–238 (2014)

    Google Scholar 

  43. Stebler, N., Schuepbach-Regula, G., Braam, P., et al.: Use of a modified Delphi panel to identify and weight criteria for prioritization of zoonotic diseases in Switzerland. Prev. Vet. Med. 121(1), 165–169 (2015)

    Google Scholar 

  44. Mei, Y., Ye, J., Zeng, Z.: Entropy-weighted ANP fuzzy comprehensive evaluation of interim product production schemes in one-of-a-kind production. Comput. Ind. Eng. 100, 144–152 (2016)

    Google Scholar 

  45. You, X.Y., You, J.X., Liu, H.C., et al.: Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information. Expert Syst. Appl. 42(4), 1906–1916 (2015)

    MathSciNet  Google Scholar 

  46. Biswas, P., Pramanik, S., Giri, B.C.: TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment. Neural Comput. Appl. 27(3), 727–737 (2016)

    Google Scholar 

  47. Biswas, P., Pramanik, S., Giri, B.C.: Entropy based grey relational analysis method for multi-attribute decision making under single valued neutrosophic assessments. Neutrosophic Sets Syst 2, 102–110 (2014)

    Google Scholar 

  48. Li, H., Lu, Z., Qiao, Y., et al.: The comprehensive evaluation method of high wind power penetration transmission grid based on maximum entropy criterion. In: Power and Energy: Proceedings of the International Conference on Power and Energy (CPE 2014), Shanghai, China, 29–30 November 2014, pp. 29. CRC Press, Boca Raton (2015)

    Google Scholar 

  49. Li, H., Dong, K., Jiang, H., et al.: Risk assessment of China’s overseas oil refining investment using a fuzzy-grey comprehensive evaluation method. Sustainability 9(5), 696 (2017)

    Google Scholar 

  50. Kusi-Sarpong, S., Bai, C., Sarkis, J., et al.: Green supply chain practices evaluation in the mining industry using a joint rough sets and fuzzy TOPSIS methodology. Resour. Policy 46, 86–100 (2015)

    Google Scholar 

  51. Tian, Z., Zhang, H., Wang, J., et al.: Multi-criteria decision-making method based on a cross-entropy with interval neutrosophic sets. Int. J. Syst. Sci. 47(15), 3598–3608 (2016)

    MATH  Google Scholar 

  52. Dalkey, N., Helmer, O.: An experimental application of the Delphi method to the use of experts. Manag. Sci. 9(3), 458–467 (1963)

    Google Scholar 

  53. Di Zio, S., Maretti, M.: Acceptability of energy sources using an integration of the Delphi method and the analytic hierarchy process. Qual. Quant. 48(6), 2973–2991 (2014)

    Google Scholar 

  54. Chang, I.S., Tsujimura, Y., Gen, M., et al.: An efficient approach for large scale project planning based on fuzzy Delphi method. Fuzzy Sets Syst. 76(3), 277–288 (1995)

    Google Scholar 

  55. Kuo, Y.F., Chen, P.C.: Constructing performance appraisal indicators for mobility of the service industries using Fuzzy Delphi Method. Expert Syst. Appl. 35(4), 1930–1939 (2008)

    Google Scholar 

  56. Jafari, A., Jafarian, M., Zareei, A., et al.: Using fuzzy Delphi method in maintenance strategy selection problem. J. Uncertain Syst. 2(4), 289–298 (2008)

    Google Scholar 

  57. Cui, J., Dang, Y.G., Liu, S.F.: An improved approach for determining weights of attributes in decision making based on grey incidence. Chin. J. Manag. Sci. 16(5), 141–145 (2008)

    Google Scholar 

  58. Guo, Y.: Comprehensive Evaluation Theory and Method, pp. 41–46. Press of Science and Technology, Beijing (2002)

    Google Scholar 

Download references

Acknowledgements

This paper is supported by China State Grid International Development CO., LTD.

Author information

Authors and Affiliations

  1. School of Economy and Management, North China Electric Power University, Changping District, Beijing, 102206, China

    Hongze Li & Bingkang Li

  2. State Grid International Development Co., Ltd., Xicheng District, Beijing, 100031, China

    Guang Yang, Cheng Chen, Yuanzi Chen & Chunzhang Zhao

Authors
  1. Hongze Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bingkang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cheng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yuanzi Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Chunzhang Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

HL and BL conceived and designed the research method used in this paper; GY, CC, YC, and CZ collected the data we need for empirical analysis; BL performed the empirical analysis and wrote the paper.

Corresponding author

Correspondence to Bingkang Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, H., Li, B., Yang, G. et al. Evaluating the Regulatory Environment of Overseas Electric Power Market Based on a Hybrid Evaluation Model. Int. J. Fuzzy Syst. 22, 138–155 (2020). https://doi.org/10.1007/s40815-019-00774-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-019-00774-z

Keywords

Search

Navigation