IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i9p7545-d1139441.html
   My bibliography  Save this article

Assessment of Vulnerability Caused by Earthquake Disasters Based on DEA: A Case Study of County-Level Units in Chinese Mainland

Author

Listed:
  • Yuxin Gao

    (School of Economics and Management, Beihang University, Beijing 100191, China
    Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing 100191, China)

  • Xianrui Yu

    (School of Economics and Management, Beihang University, Beijing 100191, China
    Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing 100191, China)

  • Menghao Xi

    (School of Emergency Management, Institute of Disaster Prevention, Sanhe 065201, China)

  • Qiuhong Zhao

    (School of Economics and Management, Beihang University, Beijing 100191, China
    Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations, Beijing 100191, China)

Abstract

Earthquake activity can generate huge energy in a short period of time, bringing enormous risks to people’s lives and property safety. This poses a great challenge to regional sustainable development. Meanwhile, due to the complex mechanism, seismic activity is difficult to accurately predict. Therefore, it is of great significance to explore how to reduce earthquake disaster losses from the perspective of human society. In this study, we use vulnerability to reflect the relative impact of earthquake disasters on different counties. The vulnerability caused by earthquakes is calculated with the data envelopment analysis (DEA) method. We use CCR and BCC models to further decompose vulnerability into pure technology vulnerability and scale vulnerability. This study analyzes 69 earthquake disasters that occurred in the Chinese mainland from 2013 to 2020 and explores the influencing factors of pure technology vulnerability from both quantitative and qualitative perspectives. Three main conclusions are drawn. First, four factors, including the added value of the secondary industry, gross domestic product (GDP) per capita, investment density of fixed assets and energy released by earthquakes, have a significant impact on the pure technical vulnerability of counties caused by earthquake disasters. Second, in the samples under consideration, the average vulnerability of the regions with an earthquake magnitude below 5.0 is higher than that of the regions with an earthquake magnitude between 5.0 and 6.0. There are deficiencies in organization, management and facilities in regions with a small earthquake risk. Third, through qualitative analysis, it is shown that the seismic function of buildings affects the vulnerability of counties facing earthquake disasters. The results of the research can provide decision makers with new insights into earthquake prevention and disaster reduction management.

Suggested Citation

  • Yuxin Gao & Xianrui Yu & Menghao Xi & Qiuhong Zhao, 2023. "Assessment of Vulnerability Caused by Earthquake Disasters Based on DEA: A Case Study of County-Level Units in Chinese Mainland," Sustainability, MDPI, vol. 15(9), pages 1-15, May.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7545-:d:1139441
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/9/7545/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/9/7545/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jianyi Huang & Yi Liu & Li Ma & Fei Su, 2013. "Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 65(1), pages 115-134, January.
    2. Li Peng & Jing Tan & Lei Lin & Dingde Xu, 2019. "Understanding sustainable disaster mitigation of stakeholder engagement: Risk perception, trust in public institutions, and disaster insurance," Sustainable Development, John Wiley & Sons, Ltd., vol. 27(5), pages 885-897, September.
    3. Seth Stein & Mian Liu, 2009. "Long aftershock sequences within continents and implications for earthquake hazard assessment," Nature, Nature, vol. 462(7269), pages 87-89, November.
    4. Yi Peng, 2015. "Regional earthquake vulnerability assessment using a combination of MCDM methods," Annals of Operations Research, Springer, vol. 234(1), pages 95-110, November.
    5. Mohsen Alizadeh & Esmaeil Alizadeh & Sara Asadollahpour Kotenaee & Himan Shahabi & Amin Beiranvand Pour & Mahdi Panahi & Baharin Bin Ahmad & Lee Saro, 2018. "Social Vulnerability Assessment Using Artificial Neural Network (ANN) Model for Earthquake Hazard in Tabriz City, Iran," Sustainability, MDPI, vol. 10(10), pages 1-23, September.
    6. Xiaolu Gao & Jue Ji, 2014. "Analysis of the seismic vulnerability and the structural characteristics of houses in Chinese rural areas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(2), pages 1099-1114, January.
    7. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    8. Blake Walker & Cameron Taylor-Noonan & Alan Tabbernor & T’Brenn McKinnon & Harsimran Bal & Dan Bradley & Nadine Schuurman & John Clague, 2014. "A multi-criteria evaluation model of earthquake vulnerability in Victoria, British Columbia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 1209-1222, November.
    9. Toya, Hideki & Skidmore, Mark, 2007. "Economic development and the impacts of natural disasters," Economics Letters, Elsevier, vol. 94(1), pages 20-25, January.
    10. Mingze Li & Jun Lv & Xin Chen & Nan Jiang, 2015. "Provincial evaluation of vulnerability to geological disaster in China and its influencing factors: a three-stage DEA-based analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1649-1662, December.
    11. Dingde Xu & Wenfeng Zhou & Xin Deng & Zhixing Ma & Zhuolin Yong & Cheng Qin, 2020. "Information credibility, disaster risk perception and evacuation willingness of rural households in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2865-2882, September.
    12. Rajiv D. Banker & Richard C. Morey, 1986. "Efficiency Analysis for Exogenously Fixed Inputs and Outputs," Operations Research, INFORMS, vol. 34(4), pages 513-521, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lihui Wu & Da Ma & Jinling Li, 2023. "Assessment of the Regional Vulnerability to Natural Disasters in China Based on DEA Model," Sustainability, MDPI, vol. 15(14), pages 1-12, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, March.
    2. Fethi, Meryem Duygun & Pasiouras, Fotios, 2010. "Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey," European Journal of Operational Research, Elsevier, vol. 204(2), pages 189-198, July.
    3. Avkiran, Necmi K., 2001. "Investigating technical and scale efficiencies of Australian Universities through data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 35(1), pages 57-80, March.
    4. Valentina Bosetti & Mariaester Cassinelli & Alessandro Lanza, 2007. "Benchmarking in Tourism Destinations; Keeping in Mind the Sustainable Paradigm," Springer Books, in: Álvaro Matias & Peter Nijkamp & Paulo Neto (ed.), Advances in Modern Tourism Research, chapter 0, pages 165-180, Springer.
    5. Peyrache, Antonio & Rose, Christiern & Sicilia, Gabriela, 2020. "Variable selection in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 282(2), pages 644-659.
    6. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    7. Alexandre Marinho & Simone de Souza Cardoso & Vivian Vicente de Almeida, 2009. "Avaliação da Eficiência Técnica dos Países nos Jogos Olímpicos de Pequim – 2008," Discussion Papers 1394, Instituto de Pesquisa Econômica Aplicada - IPEA.
    8. Ane Elixabete Ripoll-Zarraga & Sebastián Lozano, 2020. "A centralised DEA approach to resource reallocation in Spanish airports," Annals of Operations Research, Springer, vol. 288(2), pages 701-732, May.
    9. Mehdiloo, Mahmood & Podinovski, Victor V., 2019. "Selective strong and weak disposability in efficiency analysis," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1154-1169.
    10. Zhixing Ma & Shili Guo & Xin Deng & Dingde Xu, 2021. "Community resilience and resident's disaster preparedness: evidence from China's earthquake-stricken areas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 567-591, August.
    11. Ole Bent Olesen & Niels Christian Petersen & Victor V. Podinovski, 2022. "Scale characteristics of variable returns-to-scale production technologies with ratio inputs and outputs," Annals of Operations Research, Springer, vol. 318(1), pages 383-423, November.
    12. Tumaniants, Karen A. (Туманянц, Карэн) & Sesina, Julia E. (Сесина, Юлия), 2017. "Social Expenditures of Russian Regions in Terms of “Input-Output” [Расходы На Социальную Политику Российских Регионов В Координатах «Затраты — Результат»]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 128-149, October.
    13. Sampaio, Breno Ramos & Neto, Oswaldo Lima & Sampaio, Yony, 2008. "Efficiency analysis of public transport systems: Lessons for institutional planning," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(3), pages 445-454, March.
    14. Ali, Agha Iqbal & Lerme, Catherine S. & Seiford, Lawrence M., 1995. "Components of efficiency evaluation in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 80(3), pages 462-473, February.
    15. Avkiran, Necmi K. & Rowlands, Terry, 2008. "How to better identify the true managerial performance: State of the art using DEA," Omega, Elsevier, vol. 36(2), pages 317-324, April.
    16. Karima Kourtit & Peter Nijkamp & Soushi Suzuki, 2023. "Quantitative performance assessment of Asian stellar cities by a DEA cascade system: a capability interpretation," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 70(1), pages 259-286, February.
    17. Zhang, Linjia & Botti, Laurent & Petit, Sylvain, 2016. "Destination performance: Introducing the utility function in the mean-variance space," Tourism Management, Elsevier, vol. 52(C), pages 123-132.
    18. Habibov, Nazim N. & Fan, Lida, 2010. "Comparing and contrasting poverty reduction performance of social welfare programs across jurisdictions in Canada using Data Envelopment Analysis (DEA): An exploratory study of the era of devolution," Evaluation and Program Planning, Elsevier, vol. 33(4), pages 457-467, November.
    19. Amirteimoori, Alireza & Cezar, Asunur & Zadmirzaei, Majid & Susaeta, Andres, 2024. "Environmental performance evaluation in the forest sector: An extended stochastic data envelopment analysis approach," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    20. Fernández, David & Pozo, Carlos & Folgado, Rubén & Jiménez, Laureano & Guillén-Gosálbez, Gonzalo, 2018. "Productivity and energy efficiency assessment of existing industrial gases facilities via data envelopment analysis and the Malmquist index," Applied Energy, Elsevier, vol. 212(C), pages 1563-1577.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7545-:d:1139441. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.