Natural Hazards

, Volume 91, Issue 2, pp 587–609 | Cite as

Evaluation of the moderate earthquake resilience of counties in China based on a three-stage DEA model

Original Paper


China has been struck by earthquakes at all scales, and such quakes have resulted in enormous human and property losses. Previous studies have mainly focused on large-scale earthquakes. However, small-scale quakes can also have long-term impacts. This study sheds light on moderate earthquakes with magnitudes ranging from 5.0 to 7.0. It aims to evaluate county resilience to moderate earthquakes based on 102 moderate quakes that occurred in Mainland China during 2002–2014. To overcome the shortcomings of traditional data envelopment analysis (DEA) evaluation methods, this study adopts a three-stage super-efficient DEA model to evaluate the resilience of counties that have been struck by moderate earthquakes. Moreover, it identifies socioeconomic factors that can effectively affect county resilience. Results suggest that most counties in China that have been struck by moderate earthquakes exhibit low efficiency and resilience. The research uses Tobit regression to demonstrate that insurance intensity, hospital beds, teledensity, government financial expenditure, and disaster experience can efficiently improve county resilience to moderate earthquakes, which indicates the future improvement direction of local resilience. Moreover, a region with a high frequency of moderate quakes displays relatively low efficiency and resilience. Considerable attention and effort should be afforded to these areas.


Seismic hazard Resilience Three-stage DEA Moderate earthquake China 



This research was funded by the National Natural Science Foundation of China (71522013, 71373250, and 71490735).


  1. Adger WN, Hughes TP, Folke C, Carpenter SR, Rockstrom J (2005) Social–ecological resilience to coastal disasters. Science 309(5737):1036–1039CrossRefGoogle Scholar
  2. Adger WN, Brown K, Conway D (2010) Progress in global environmental change. Glob Environ Change 20(4):547–549CrossRefGoogle Scholar
  3. Andersen P, Petersen NC (1993) A procedure for ranking efficient units in data envelopment analysis. Manage Sci 39(10):1261–1264CrossRefGoogle Scholar
  4. Artzner P, Delbaen F (1995) Default risk insurance and incomplete markets. Math Finance 5(3):187–195CrossRefGoogle Scholar
  5. Bruneau M, Chang SE, Eguchi RT, Lee GC, O’Rourke TD, Reinhorn AM, Von Winterfeldt D (2003) A framework to quantitatively assess and enhance the seismic resilience of communities. Earthq Spectra 19(4):733–752CrossRefGoogle Scholar
  6. Chang SE, Shinozuka M (2004) Measuring improvements in the disaster resilience of communities. Earthq Spectra 20(3):739–755CrossRefGoogle Scholar
  7. Cheng Y, Cheng Q (2003) Earthquakes and seismic hazard in China. In: Science progress in China, pp 387–400Google Scholar
  8. China Earthquake Administration (2016)
  9. Cimellaro GP, Reinhorn AM, Bruneau M (2006) Quantification of seismic resilience. In: Proceedings of the 8th US National conference on Earthquake Engineering, pp 18–22Google Scholar
  10. Comfort L (2005) Risk, security, and disaster management. Annu Rev Polit Sci 8:335–356CrossRefGoogle Scholar
  11. Cutter, S. L., Boruff, B. J., & Shirley, W. L. (2003). Social vulnerability to environmental hazards. Soc Sci Quart 84(2):242–261CrossRefGoogle Scholar
  12. Cutter SL, Barnes L, Berry M, Burton C, Evans E, Tate E, Webb J (2008) A place-based model for understanding community resilience to natural disasters. Glob Environ Change 18(4):598–606CrossRefGoogle Scholar
  13. Cutter SL, Burton CG, Emrich CT (2010) Disaster resilience indicators for benchmarking baseline conditions. J Homel Secur Emerg Manag 7(1):1–22Google Scholar
  14. Dooley D, Catalano R, Mishra S, Serxner S (1992) Earthquake preparedness: predictors in a community survey. J Appl Soc Psychol 22:451–470CrossRefGoogle Scholar
  15. Douglas R (2014) Insuring resilience-employing approaches from the re/insurance sector to encourage sustainable design & operations against natural hazards. In: AGU fall meeting abstracts 1:8Google Scholar
  16. Feldman R, Dowd B, Leitz S, Blewett LA (1997) The effect of premiums on the small firm’s decision to offer health insurance. J Hum Resour 32:635–658CrossRefGoogle Scholar
  17. Fried HO, Lovell CK, Schmidt SS, Yaisawarng S (2002) Accounting for environmental effects and statistical noise in data envelopment analysis. J Prod Anal 17(1):157–174CrossRefGoogle Scholar
  18. Ganor M, Ben-Lavy YULI (2003) Community resilience: lessons derived from Gilo under fire. J Jew Communal Serv 79(2/3):105–108Google Scholar
  19. Goodman R, Speers M, McLeroy K, Fawcett S, Kegler M, Parker E et al (1998) Identifying and defining the dimensions of community capacity to provide a basis for measurement. Health Educ Behav 25:258–278CrossRefGoogle Scholar
  20. Gorman MF, Ruggiero J (2008) Evaluating US state police performance using data envelopment analysis. Int J Prod Econ 113(2):1031–1037CrossRefGoogle Scholar
  21. Holling CS (1996) Engineering resilience versus ecological resilience. In: Schulze PC (ed) Engineering within ecological constraints. National Academy Press, Washington, pp 31–44Google Scholar
  22. Horwich G (2000) Economic lessons from the Kobe earthquake. Econ Dev Cult Change 48:521–542CrossRefGoogle Scholar
  23. Jacques CC, McIntosh J, Giovinazzi S, Kirsch TD, Wilson T, Mitrani-Reiser J (2014) Resilience of the Canterbury hospital system to the 2011 Christchurch earthquake. Earthq Spectra 30(1):533–554CrossRefGoogle Scholar
  24. John Heinz H III, Center for Science, Economics, and the Environment (2000) The Hidden costs of coastal hazards: implications for risk assessment and mitigation. Island Press, WashingtonGoogle Scholar
  25. Kahn ME (2005) The death toll from natural disasters: the role of income, geography, and institutions. Rev Econ Stat 87(2):271–284CrossRefGoogle Scholar
  26. Lam NSN, Reams M, Li K, Li C, Mata LP (2015) Measuring community resilience to coastal hazards along the Northern Gulf of Mexico. Natural Hazards Rev 17(1):04015013CrossRefGoogle Scholar
  27. Lee JY (2008) Application of the three-stage DEA in measuring efficiency—an empirical evidence. Appl Econ Lett 15(1):49–52CrossRefGoogle Scholar
  28. Li M, Lv J, Chen X, Jiang N (2015) Provincial evaluation of vulnerability to geological disaster in China and its influencing factors: a three-stage DEA-based analysis. Nat Hazards 79(3):1649–1662CrossRefGoogle Scholar
  29. Li X, Wang L, Liu S (2016) Geographical analysis of community resilience to seismic hazard in Southwest China. Int J Disaster Risk Sci 7(3):257–276CrossRefGoogle Scholar
  30. Lindell MK, Perry RW (2000) Household adjustment to earthquake hazard a review of research. Environ Behav 32(4):461–501CrossRefGoogle Scholar
  31. Liu J, Wang S (2014) Analysis of the differentiation in human vulnerability to earthquake hazard between rural and urban areas: case studies in 5.12 Wenchuan Earthquake (2008) and 4.20 Ya’an Earthquake (2013), China. J Housing Built Environ 1–21Google Scholar
  32. Manyena SB (2006) The concept of resilience revisited. Disasters 30(4):434–450CrossRefGoogle Scholar
  33. Nahra TA, Mendez D, Alexander JA (2009) Employing super-efficiency analysis as an alternative to DEA: an application in outpatient substance abuse treatment. Eur J Oper Res 196(3):1097–1106CrossRefGoogle Scholar
  34. Norris FH, Hamblen JL, Watson PJ, Ruzek JI, Gibson LE, Pfefferbaum BJ, Friedman MJ (2006) Toward understanding and creating systems of postdisaster care. Interventions Following Mass Violence and Disasters: Strategies for Mental Health Practice 343Google Scholar
  35. Norris FH, Stevens SP, Pfefferbaum B, Wyche KF, Pfefferbaum RL (2008) Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. Am J Community Psychol 41(1–2):127–150CrossRefGoogle Scholar
  36. NRC (National Research Council) (2012) Disaster resilience: a national imperative. The National Academies Press, WashingtonGoogle Scholar
  37. Olson DL, Wu DD (2010) Earthquakes and risk management in China. Human Ecol Risk Assess 16(3):478–493CrossRefGoogle Scholar
  38. Paton D, Johnston D (2017) Disaster resilience: an integrated approach. Charles C Thomas Publisher, SpringfieldGoogle Scholar
  39. Raschky PA (2008) Institutions and the losses from natural disasters. Nat Hazards Earth Syst Sci 8(4):627–634CrossRefGoogle Scholar
  40. Russell LA, Goltz JD, Bourque LB (1995) Preparedness and hazard mitigation actions before and after two earthquakes. Environ Behav 27(6):744–770CrossRefGoogle Scholar
  41. Shepherd RW (2015) Theory of cost and production functions. Princeton University Press, PrincetonCrossRefGoogle Scholar
  42. Shrestha MK, York AM, Boone CG, Zhang S (2012) Land fragmentation due to rapid urbanization in the Phoenix Metropolitan Area: analyzing the spatiotemporal patterns and drivers. Appl Geogr 32(2):522–531CrossRefGoogle Scholar
  43. State Council office (2007) National earthquake prevention and disaster mitigation plan (2006–2020).
  44. Tapsell SM, Penning-Rowsell EC, Tunstall SM, Wilson TL (2002) Vulnerability to flooding: health and social dimensions. Philos Trans R Soc Lond A Math Phys Eng Sci 360(1796):1511–1525CrossRefGoogle Scholar
  45. Turner BL, Kasperson RE, Matson PA, McCarthy JJ, Corell RW, Christensen L, Eckley N, Kasperson JX, Luers A, Martello ML, Polsky C, Pulsipher A, Schiller A (2003) A framework for vulnerability analysis in sustainability science. Proc Natl Acad Sci 100(14):8074–8079CrossRefGoogle Scholar
  46. United States Geological Survey (USGS) (2013) Earthquake facts and statistics.
  47. Üstün AK (2016) Evaluating İstanbul’s disaster resilience capacity by data envelopment analysis. Nat Hazards 80(3):1603–1623CrossRefGoogle Scholar
  48. Wei J, Xia W (2014) Evaluation of industrial-accidents management performance in China. Human Ecol Risk Assess Int J 20(2):537–558CrossRefGoogle Scholar
  49. Wei YM, Fan Y, Lu C, Tsai HT (2004) The assessment of vulnerability to natural disasters in China by using the DEA method. Environ Impact Assess Rev 24(4):427–439CrossRefGoogle Scholar
  50. Zhu J (2001) Super-efficiency and DEA sensitivity analysis. Eur J Oper Res 129(2):443–455CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of ManagementUniversity of Science and Technology of ChinaHefeiPeople’s Republic of China
  2. 2.Department of Business AdministrationNanjing University of Finance and EconomicsNanjing, JiangsuPeople’s Republic of China

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