Skip to main content
SpringerLink
Log in

Hazard management and risk design by optimal statistical analysis

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

Elicitation methods are used in decision making with respect to risk hazards to allow a researcher to infer the subjective utilities of outcomes from the observed preferences of an individual. A questionnaire method is presented, in this study, which takes into account the inevitable distortion of preferences by random errors and minimizes the effect of such errors. Under mild assumptions, the method for eliciting the utilities of many outcomes is a three-stage procedure. First, the questionnaire is utilized to elicit responses from which a subjective score is defined. Second, individual risk factors are discussed. Finally, the regression model presents individual risk preferences given the overall organizational risk culture, risk management policy, risk identification, and risk analysis. This paper addresses how company managers face risk and their tolerance of risk with respect to risk management.

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

Similar content being viewed by others

References

  • Accorsi R, Zio E, Apostolakis GE (1999) Developing utility functions for environmental decision-making. Prog Nucl Energy 34(4):387–411

    Article  Google Scholar 

  • Chen CW (2004) Stability analysis of T-S fuzzy models for nonlinear multiple time-delay interconnected systems. Mathematics and Computers in Simulation 66:523–537

    Google Scholar 

  • Chen CW (2006) Stability conditions of fuzzy systems and its application to structural and mechanical systems. Advances in Engineering Software 37:624–629

    Google Scholar 

  • Chen CY (2010) Fuzzy control for an oceanic structure: A case study in time-delay TLP system. Journal of Vibration and Control 16:147–160

    Google Scholar 

  • Chen CY (2012a) Assessment of the major hazard potential of interfacial solitary waves moving over a trapezoidal obstacle on a horizontal plateau. Natural Hazards, 62(3):841–852

    Google Scholar 

  • Chen CY (2012b) Disaster prevention and reduction for exploring teachers’ technology acceptance using a virtual reality system and partial least squares techniques. Natural Hazards 62(3):1217–1231

    Google Scholar 

  • Chen TH, Chen CW (2010) Application of data mining to the spatial heterogeneity of foreclosed mortgages. Expert Syst Appl 37(2):993–997

    Article  Google Scholar 

  • El-Gayar OF, Fritz BD (2010) A web-based multi-perspective decision support system for information security planning. Decis Support Syst 50:43–54

    Article  Google Scholar 

  • Hoecht A, Trott P (2006) Innovation risks of strategic outsourcing. Technovation 26:672–681

    Article  Google Scholar 

  • Hsiao FH, Chen CW, Liang YW, Xu SD and Chiang WL (2005a) T-S fuzzy controllers for nonlinear interconnected systems with multiple time delays. IEEE Trans Circuits Syst I Regul Pap 52:1883–1893

  • Hsiao FH, Hwang, JD, Chen CW and Tsai ZR (2005b) Robust stabilization of nonlinear multiple time-delay large-scale systems via decentralized fuzzy control. IEEE Trans Fuzzy Syst 13:152–163

    Google Scholar 

  • Hsu WK (2011) An integrated flood risk assessment model for property insurance industry in Taiwan. Nat Hazards 58(3):1295–1309

    Google Scholar 

  • Hsu WK (2012) Risk and uncertainty analysis in the planning stages of a risk decision-making process. Nat Hazards 61(3):1355–1365

    Google Scholar 

  • Kumar S, Budin EM (2006) Prevention and management of product recalls in the processed food industry: a case study based on an exporter’s perspective. Technovation 26:739–750

    Article  Google Scholar 

  • Lauras M, Marques G, Gourc D (2010) Towards a multi-dimensional project performance measurement system. Decis Support Syst 48:342–353

    Article  Google Scholar 

  • Lin JW (2012a) Kalman filter decision systems for debris flow hazard assessment. Nat Hazards 60(3):1255–1266

    Google Scholar 

  • Lin JW (2012b) Modeling and assessment of bridge structure for seismic hazard prevention. Nat Hazards 61(3):1115–1126

    Google Scholar 

  • Lin JW (2012c) Potential hazard analysis and risk assessment of debris flow by fuzzy modeling. Nat Hazards. doi: 10.1007/s11069-012-0236-z

  • Lin ML (2011) Using GIS-based spatial geocomputation from remotely sensed data for drought risk-sensitive assessment. International Journal of Innovative Computing, Information and Control 7(2): 657-668

    Google Scholar 

  • Lin JW, Chen CW, Peng CY (2012) Kalman filter decision systems for debris flow hazard assessment. Nat Hazards 60(3):1255–1266

    Article  Google Scholar 

  • Power DJ, Sohal AS, Rahman S (2001) Critical success factors in agile natural disaster risk management: an empirical study. Int J Phys Distrib Logist 31(4):247–265

    Article  Google Scholar 

  • Prater E, Biehl M, Smith MA (2001) International natural disaster risk control tradeoffs between flexibility and uncertainty. Int J Oper Prod Manag 21(5/6):823–839

    Article  Google Scholar 

  • Raviv A (1979) The design of an optimal insurance policy. Am Econ Rev 69:84–96

    Google Scholar 

  • Shih BY (2012) Using Lego NXT to explore scientific literacy in disaster prevention and rescue systems. Nat Hazards. doi: 10.1007/s11069-012-0233-2

  • Tsai CH (2010) An earthquake disaster management mechanism based on risk assessment information for the tourism industry—a case study from the island of Taiwan. Tour Manag 31(4):470–481

    Google Scholar 

  • Tsai CH (2011a) Development of a mechanism for typhoon and flood risk assessment and disaster management in the hotel industry—a case study of the Hualien area. Scandinavian J Hosp Tour 11(3):324–341

    Google Scholar 

  • Tsai CH (2011b) The establishment of a rapid natural disaster risk assessment model for the tourism industry. Tour Manag 32(1):158–171

    Google Scholar 

  • Tseng CP (2011) A new viewpoint on risk control decision models for natural disasters. Nat Hazards 59(3):1715–1733

    Google Scholar 

  • Tseng CP (2012) Default risk-based probabilistic decision model for risk management and control. Nat Hazards. doi: 10.1007/s11069-012-0183-8.

  • Tseng CP, Chen CW (2012) Natural disaster management mechanisms for probabilistic earthquake loss. Nat Hazards 60(3):1055–1063

    Article  Google Scholar 

  • Tseng CP, Chen CW and Liu FR (2012) Risk control allocation model for pressure vessels and piping project. J Vib Control 18(3):385–394

    Google Scholar 

  • Wang JT, Lin W, Huang YH (2010) A performance-oriented risk management framework for innovative R&D projects. Technovation 30:601–611

    Article  Google Scholar 

  • Yang HC (2012) Potential hazard analysis from the viewpoint of flow measurement in large open-channel junctions. Nat Hazards 61(2):803–813

    Google Scholar 

  • Yi CS, Lee JH, Shim MP (2010) GIS-based distributed technique for assessing economic loss from flood damage: pre-feasibility study for the Anyang Stream Basin in Korea. Nat Hazards 55(2):251–272

    Google Scholar 

  • Yusuf YY, Gunasekaran A, Adeleye EO, Sivayoganathan K (2004) Agile natural disaster risk capabilities: determinants of competitive objectives. Eur J Oper Res 159:379–392

    Article  Google Scholar 

  • Zhou HJ, Wang JA, Wan JH et al (2010) Resilience to natural hazards: a geographic perspective. Nat Hazards 53(1):21–41

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the National Science Council of the Republic of China, Taiwan, for their financial support of this research under Contract Nos. NSC 100-2221-E-022-013-MY2 and NSC 100-2628-E-022-002-MY2.

Author information

Authors and Affiliations

  1. Institute of Maritime Information and Technology, National Kaohsiung Marine University, Kaohsiung, 80543, Taiwan

    Cheng-Wu Chen

  2. Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, New Taipei City, 24301, Taiwan, ROC

    Kevin Fong-Rey Liu

  3. Chung Shan Institute of Science and Technology, Armaments Bureau, Taoyuan, Taiwan

    Chun-Pin Tseng

  4. Research Center for Hazard Mitigation and Prevention, National Central University, Jhung-li, Taoyuan, Taiwan

    Wen-Ko Hsu

  5. Department of Civil Engineering, National Central University, Jhung-li, Taoyuan, Taiwan, ROC

    Wei-Ling Chiang

Authors
  1. Cheng-Wu Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kevin Fong-Rey Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chun-Pin Tseng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wen-Ko Hsu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wei-Ling Chiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cheng-Wu Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chen, CW., Liu , K.FR., Tseng, CP. et al. Hazard management and risk design by optimal statistical analysis. Nat Hazards 64, 1707–1716 (2012). https://doi.org/10.1007/s11069-012-0329-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-012-0329-8

Keywords

Search

Navigation