Skip to main content
Log in

Evaluating İstanbul’s disaster resilience capacity by data envelopment analysis

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

Abstract

İstanbul is one of the most important commercial, cultural, industrial, and educational centers in the world. However, İstanbul is also an earthquake-prone city, and it has experienced many of them throughout history. It is likely to be threatened by a huge, destructive earthquake in the next few years. In this study, the earthquake resilience capacity of İstanbul and her districts is evaluated by data envelopment analysis (DEA) models and returns to scale analysis. The efficient and inefficient districts are determined and discussed, for possible improvements of inefficient units in input and output values. The classification of İstanbul’s districts is applied according to vulnerabilities representing the potential losses from casualties, damage, destruction, and/or business interruption in a possible earthquake by DEA and returns to scale analysis.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Al-Shammari M (1999) A multi-criteria data envelopment analysis model for measuring the productive efficiency of hospitals. Int J Oper Prod Manag 19(9):879–891

    Article  Google Scholar 

  • Ambraseys NN, Finkel CF (1991) Long-term Seismicity of İstanbul and of the Marmara Sea Region. Terra Nova 3(1991):527–539

    Article  Google Scholar 

  • Azadeh A, Armin R-G, Mohsen M (2014) Location optimization of wind power generation–transmission systems under uncertainty using hierarchical fuzzy DEA: a case study. Renew Sustain Energy Rev 30:877–885

    Article  Google Scholar 

  • Balamir M (1999) Reproducing the fatalist society: an evaluation of the ‘disasters’ and ‘development’ laws and regulations in Turkey. In: Urban settlements and natural disasters. Proceedings of UIA region II workshop, Chamber of Architects of Turkey

  • Banker RD, Charnes A, Cooper WW (1984) Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag Sci 30:1078–1092

    Article  Google Scholar 

  • Barr RS, Siems TF (1997) Bank failure prediction using DEA to measure management quality. Interfaces in computer science and operations research. Springer, New York, pp 341–365

    Chapter  Google Scholar 

  • Castelli L, Pesenti R (2014) Network, shared flow and multi-level DEA models: a critical review. Data envelopment analysis. Springer, New York, pp 329–376

    Chapter  Google Scholar 

  • Chang YC, Yu MM (2014) Measuring production and consumption efficiencies using the slack-based measure network data envelopment analysis approach: the case of low-cost carriers. J Adv Transp 48(1):15–31

    Article  Google Scholar 

  • Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444

    Article  Google Scholar 

  • Charnes A, Cooper WW, Golany B, Seiford LM, Stutz J (1985) Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. J Econom 30:91–107

    Article  Google Scholar 

  • Charnes A, Cooper WW, Huang ZM, Sun DB (1990) Polyhedral cone-ratio DEA models with an illustrative application to large commercial banks. J Econ 30:91–107

    Article  Google Scholar 

  • Cook WD, Zhu J (2006) Modeling performance measurement: applications and implementation issues in DEA, vol 566. Springer, Berlin

    Google Scholar 

  • Cooper WW, Seiford LM, Tone K (2000) Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software. Kluwer Academic Publisher, Dordrecht

    Google Scholar 

  • Cooper WW, Seiford LM, Tone K (2006) Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software. Kluwer Academic Publisher, Dordrecht

    Google Scholar 

  • Cooper WW, Seiford LM, Zhu J (2011) Handbook on data envelopment analysis, vol 164. Springer, Berlin

    Google Scholar 

  • Dash U, Vaishnavi SD, Muraleedharan VR, Acharya D (2007) Benchmarking the performance of public hospitals in Tamil Nadu: an application of data envelopment analysis. J Health Manag 9:59. doi:10.1177/097206340700900104

    Article  Google Scholar 

  • Dyckhoff H, Mbock E, Gutgesell S (2014) Distance‐based measures of specialization and balance in multi‐criteria: a DEA‐integrated method. J Multi-Crit Decis Anal. doi:10.1002/mcda.1532

    Google Scholar 

  • Dyson RG, Thanassoulis E (1988) Reducing weight flexibility in data envelopment analysis. J Oper Res Soc 39:563–576

    Article  Google Scholar 

  • Efficiency Measurement System (EMS). http://www.microtheory.unijena.de/download/ems.pdf

  • Erdik M, Aydinoglu N, Fahjan K, Demircioglu M, Siyahi B, Durukal E, Ozbey C, Biro Y, Akman H, Yuzugulu O (2003) Earthquake risk assessment for İstanbul metropolitan area. Earth Eng Vib 2(1):1–25

    Article  Google Scholar 

  • Ergunay O (1999) A perspective of disaster in Turkey: issues and prospects. In: Urban settlements and natural disasters. Proceedings of UIA region II workshop, Chamber of Architects of Turkey

  • Färe R, Grosskopf S, Logan J, Lovell CK (1985) Measuring efficiency in production: with an application to electric utilities. Managerial Issues in Productivity Analysis. Springer, Berlin, pp 185–214

    Chapter  Google Scholar 

  • Gulkan P (2000) Code enforcement at municipal level in Turkey: failure of public policy for effective building hazard mitigation. In: Proceedings of the 6th international conference on seismic zoning, no. 21. Earthquake Engineering Research Institute

  • ISMEP (2014) İstanbul Seismic Risk Mitigation and Emergency Preparedness Project (ISMEP) conducted by Governorship of İstanbul, İstanbul Project Coordination Unit (IPCU) ISMEP Guide Books, Beyaz Gemi Social Project Agency

  • Japan International Cooperation Agency (JICA) (2002) The study on a disaster prevention/mitigation basic plan in İstanbul including Seismic Microzonation in the Republic of Turkey

  • Jin J, Zhou D, Zhou P (2014) Measuring environmental performance with stochastic environmental DEA: the case of APEC economies. Econ Model 38:80–86

    Article  Google Scholar 

  • Kacak H, Ozcan YA, Kavuncubasi S (2014) A new examination of hospital performance after healthcare reform in Turkey: sensitivity and quality comparisons. Int J Public Policy 10(4):178–194

    Article  Google Scholar 

  • Khodabakhshi M, Asgharian M, Gregoriou GN (2010) An input-oriented super-efficiency measure in stochastic data envelopment analysis: evaluating chief executive officers of US public banks and thrifts. Expert Syst Appl 37(3):2092–2097

    Article  Google Scholar 

  • Köksalan M, Tuncer C (2009) A DEA-based approach to ranking multi-criteria alternatives. Int J Inf Technol Decis Mak 8(01):29–54

    Article  Google Scholar 

  • Korkmaz KA (2010) Integrated seismic hazard evaluation and disaster management approach for Turkey. Environ Earth Sci 61(3):467–476

    Article  Google Scholar 

  • Lewis HF (2014) Performance measurement of major league baseball teams using network DEA. Data envelopment analysis. Springer, Berlin, pp 475–535

    Chapter  Google Scholar 

  • Li S, Gholam RJ, Khodabakhshi M (2007) A super-efficiency model for ranking efficient units in data envelopment analysis. Appl Math Comput 184(2):638–648

    Article  Google Scholar 

  • Montoneri B, Lin TT, Lee CC, Huang SL (2012) Application of data envelopment analysis on the indicators contributing to learning and teaching performance. Teach Teach Educ 28(3):382–395

    Article  Google Scholar 

  • Ouenniche J, Xu B, Tone K (2014) Relative performance evaluation of competing crude oil prices’ volatility forecasting models: a slacks-based super-efficiency DEA model. Am J Oper Res. doi:10.4236/ajor.2014.44023

    Google Scholar 

  • Özerdem A, Barakat S (2000) After the Marmara earthquake: lessons for avoiding short cuts to disasters. Third World Q 21(3):425–439

    Article  Google Scholar 

  • Ozgen H, Şahin İ (2010) Measurement of efficiency of the dialysis sector in Turkey using data envelopment analysis. Health Policy 95(2–3):185–193

    Article  Google Scholar 

  • Parsons T, Toda S, Stein RS, Barka A, Dietrich JH (2000) Heightened odds of a large earthquake near İstanbul: an interaction-based probability calculation. Science 288(5466):661–665

    Article  Google Scholar 

  • Puri J, Yadav SP (2014) A fuzzy DEA model with undesirable fuzzy outputs and its application to the banking sector in India. Expert Syst Appl 41(14):6419–6432

    Article  Google Scholar 

  • Saein AF, Saen RF (2012) Assessment of the site effect vulnerability within urban regions by data envelopment analysis: a case study in Iran. Comput Geosci 48:280–288

    Article  Google Scholar 

  • Sharma G, Kataria A (2014) Efficiency of software development projects: a case study on an information technology company in India. Managing service productivity. Springer, Berlin, pp 263–285

    Google Scholar 

  • Sherman HD, Zhu J (2006) Service productivity management: improving service performance using data envelopment analysis (DEA). Springer, Berlin

    Google Scholar 

  • Staub RB, Souza G, Tabak BM (2010) Evolution of bank efficiency in Brazil: a DEA approach. Eur J Oper Res 202:204–213

    Article  Google Scholar 

  • Thompson RG, Langemeier LN, Lee CT, Thrall R (1990) The role of multiplier bounds efficiency analysis with application to Kansas farming. J Econ 46:93–108

    Article  Google Scholar 

  • Ural A, Firat FK (2015) Evaluation of masonry minarets collapsed by a strong wind under uncertainty. Nat Hazards. doi:10.1007/s11069-014-1531-7

    Google Scholar 

  • Üstün AK, Barbarosoğlu G (2015) Performance evaluation of Turkish disaster relief management system in 1999 earthquakes using data envelopment analysis. Nat Hazards 75(2):1977–1996. doi:10.1007/s11069-014-1407-x

    Article  Google Scholar 

  • Vijayakumar A (2012) Evaluating performance of banks through camel model: a case study of State Bank of India and its associates. Online Int Interdiscip Res J 2(4):104–124

    Google Scholar 

  • Wang W-K, Wen-Min L, Pei-Yi L (2014) A fuzzy multi-objective two-stage DEA model for evaluating the performance of US bank holding companies. Expert Syst Appl 41(9):4290–4297

    Article  Google Scholar 

  • 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):427–439

    Article  Google Scholar 

  • Wei G, Chen J, Wang J (2014) Stochastic efficiency analysis with a reliability consideration. Omega 48:1–9

    Article  Google Scholar 

  • Wong Y, Beasley JE (1990) Restricting weight flexibility in data envelopment analysis. J Oper Res Soc 41:829–835

    Article  Google Scholar 

  • Zhao M, Wu WB (2014) Study on the evaluation of rural logistics service providers’ performance based on DEA model. In: 2014 international conference on management science and engineering (ICMSE). IEEE, pp 387–394

  • Zhu J (1996) DEA/AR analysis of the 1988–1989 performance of the Nanjing Textiles Corporation. Ann Oper Res 66(5):311–335

    Article  Google Scholar 

  • Zhu J (2003) Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spreadsheets and DEA excel solver, vol 51. Springer, Berlin

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Abdullah Korkut Üstün.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Üstün, A.K. Evaluating İstanbul’s disaster resilience capacity by data envelopment analysis. Nat Hazards 80, 1603–1623 (2016). https://doi.org/10.1007/s11069-015-2041-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-015-2041-y

Keywords