Skip to main content
Log in

Evaluation models of insurers’ risk management based on large system theory

  • Original Paper
  • Published:
Stochastic Environmental Research and Risk Assessment Aims and scope Submit manuscript

Abstract

The financial supply chain is increasingly recognized as an area offering significant potential for generating bottom-line improvements and creating competitive advantage. Insurers’ appraisal is one of the basic decisions for a company, and the choosing course has always many criterions. Considering the stability of the financial supply chain, the coordination evaluation and fuzzy multi-objective evaluation model of insurers’ risk management are firstly studied in this paper by using large system theory and methods. The corresponding coordination evaluation index model is then established to evaluate, forecast and control the actuality and the future of risk coordination management, and to improve the durative development for a combination pension model. The evaluation standards of numerous insurers are established to constitute a set of vectors. By presenting a dimensional point to each insurer, the optimal or the worst insurer is decided. Finally, the distances of each insurer to the optimal or the worst insurer on the basis of the Euclidean distance are counted, and the insurers’ ordering according to the value of distances is sorted out. The financial supply chain and large system theory and methods are combined to contribute new evaluation models that revise the deficiency of intrinsic model and improve the financial stability.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  • Agulnik P, Cardarelti R, Sefton J (2004) The pensions green paper: a generational accounting perspective. Econ J 110:598–610

    Article  Google Scholar 

  • Albareto G (2004) Monetary policy and banking stability: a survey. University Genova Working Paper (5)

  • Alicia G, Pedro R (2003) Financial stability and the design of monetary policy. The American University of Paris Working Paper (17)

  • Banal EA, Ottaviani M (2006) Mergers with product market risk. J Econ Manage Strategy 15(3):577–608

    Article  Google Scholar 

  • Blundell R, Meghir C, Smith S (2002) Pension incentives and the pattern of early retirement. Econ J 112:153–170

    Article  Google Scholar 

  • Celen BC, Ozerturk S (2007) Implications of executive hedge markets for firm value maximization. J Econ Manage Strategy 16(2):319–349

    Article  Google Scholar 

  • Wang FK, Norma F, Hubele Frederick P (2000) Lawrence comparison of three multivariate process capability indices. J Qual Technol 32(3):263–275

    Google Scholar 

  • Fairbank JF, Labianca GJ, Steensma HK et al (2006) Information processing design choices, strategy, and risk management performance. J Manage Inf Syst 23(1):293–319

    Google Scholar 

  • Hall MJ (2002) The american customer satisfaction index. Public Manager 31(1):23–27

    Google Scholar 

  • Hannah R (2002) A brief history and possibilities for the future, management decision. Control Pensions 40(10):938–946

    Google Scholar 

  • Henry S (1999) Steel baron Andrew Carnegie pioneered pension funding. Pensions Invest 27(26):26–34

    Google Scholar 

  • International Foundation of Employee Benefit Plans (2000) Historical perspective of multi-employer defined contribution plans. Employee Benefit Basics, pp 1–12

  • Issing O (2003) Monetary and financial stability: is there a trade-off. Conference on Monetary Stability, Financial stability and the business cycle, March 28–29

  • Jamshid M (1987) Large systems modeling and control. Science Press, Beijing

    Google Scholar 

  • Sameer K, Thomas R, Mark A (2005) Systems thinking, a consilience of values and logic. Hum Syst Manage 24(4):259–274

    Google Scholar 

  • Lall S (2001) An economic evaluation of the global competitiveness report. World Dev 29(9):1501–1525

    Article  Google Scholar 

  • Liang XB, Tang, BY (2004) Research on the risk management control models of the portfolio pension pattern. J Basic Sci Eng, Suppl, pp 276–279

  • Lin HF, Lee GG (2005) Impact of organizational learning and knowledge management factors on e-business adoption. Manage Decis 43(2):171–188

    Article  CAS  Google Scholar 

  • Mackay P, Moeller SB (2007) The value of corporate risk management. J Finance 62(3):1379–1419

    Article  Google Scholar 

  • Mark SR, Tamar S (2004) Public employee pension funds and social investments: recent performance and a policy option for changing investment strategies. J Urban Affairs 26(3):325–337

    Article  Google Scholar 

  • Padoa-Schioppa T (2003) Central banks and financial stability: exploring a land in between. The Transformation of the European Financial System, ECB, Frankfurt, pp 269–3l0

  • Pamela P (2003) The significance of integrated plans. Benefits Q Second Quarter 19(2):36–50

    Google Scholar 

  • Sass S (1997) The promise of private pensions, the first 100 years. Harvard University Press, Cambridge

    Google Scholar 

  • Scheytt T, Soin K, Sahlin AK et al (2006) Organizations, risk and regulation. J Manage Stud 43(6):1331–1337

    Article  Google Scholar 

  • Skalka C, Wang XS, Chapin P (2007) Risk management for distributed authorization. J Comput Secur 15(4):447–489

    Google Scholar 

  • Xi YG (1988) Introduction of dynamic large systems method. National Defence Industry Press, Beijing

    Google Scholar 

  • Zachary G (2002) Process capability indices: overview and extensions. Nonlinear Anal Real World Appl 3(2):191–210

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by grant 05ZR14091 of the Shanghai Natural Science Foundation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiaobei Liang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liang, X., Chen, D., Ruan, D. et al. Evaluation models of insurers’ risk management based on large system theory. Stoch Environ Res Risk Assess 23, 415–423 (2009). https://doi.org/10.1007/s00477-008-0228-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00477-008-0228-4

Keywords

Navigation