IDEAS home Printed from https://ideas.repec.org/a/spr/anresc/v66y2021i2d10.1007_s00168-020-01025-y.html
   My bibliography  Save this article

China’s regional public safety efficiency: a data envelopment analysis approach

Author

Listed:
  • Yongguang Zou

    (Huaqiao University
    Center of Tourism Safety and Security Research of China Tourism Academy)

  • Yuemei He

    (College of History Cultrue and Tourism, Yulin Normal University)

  • Weiling Lin

    (Fujian Agriculture and Forestry University)

  • Sha Fang

    (City University of Macau)

Abstract

This study develops a comprehensive public safety efficiency index that includes the inputs and outputs of regional public safety. The DEA-BC2 model was used to measure the technical efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) of public safety at 31 province-level administrative divisions (regions) in China from 2014 to 2018, and to analyze the effectiveness of public safety in each year. The findings indicate that the average TE, PTE, and SE of all regions from 2014 and 2018 were mostly redundant and ineffective. The average Malmquist index continued to decline, with the lack of technological progress identified as the main hindering factor. The public safety efficiency of 31 regions was affected by the technical progress change, pure technical efficiency change, and scale efficiency change at different periods. The findings suggest that all regions should improve the public safety inputs, better allocate various input elements and utilize public safety resources more effectively.

Suggested Citation

  • Yongguang Zou & Yuemei He & Weiling Lin & Sha Fang, 2021. "China’s regional public safety efficiency: a data envelopment analysis approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 66(2), pages 409-438, April.
  • Handle: RePEc:spr:anresc:v:66:y:2021:i:2:d:10.1007_s00168-020-01025-y
    DOI: 10.1007/s00168-020-01025-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00168-020-01025-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00168-020-01025-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tsai, Wen-Hsien & Yang, Chih-Hao & Chang, Jui-Chu & Lee, Hsiu-Li, 2014. "An Activity-Based Costing decision model for life cycle assessment in green building projects," European Journal of Operational Research, Elsevier, vol. 238(2), pages 607-619.
    2. Caves, Douglas W. & Christensen, Laurits R. & Herriges, Joseph A., 1984. "Consistency of residential customer response in time-of-use electricity pricing experiments," Journal of Econometrics, Elsevier, vol. 26(1-2), pages 179-203.
    3. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    4. S. L. Tang & H. K. Lee & K. Wong, 1997. "Safety cost optimization of building projects in Hong Kong," Construction Management and Economics, Taylor & Francis Journals, vol. 15(2), pages 177-186.
    5. Paradi, Joseph C. & Zhu, Haiyan, 2013. "A survey on bank branch efficiency and performance research with data envelopment analysis," Omega, Elsevier, vol. 41(1), pages 61-79.
    6. Aven, Terje & Hiriart, Yolande, 2011. "The use of a basic safety investment model in a practical risk management context," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1421-1425.
    7. Schmitz, Patrick W., 2000. "On the joint use of liability and safety regulation," International Review of Law and Economics, Elsevier, vol. 20(3), pages 371-382, September.
    8. Sato, Yuji, 2012. "Optimal budget planning for investment in safety measures of a chemical company," International Journal of Production Economics, Elsevier, vol. 140(2), pages 579-585.
    9. Saeed Al-Muharrami, 2008. "An examination of technical, pure technical and scale efficiencies in GCC banking," American Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 1(2), pages 152-166.
    10. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
    11. Herbert Lewis & Thomas Sexton, 2004. "Data Envelopment Analysis with Reverse Inputs and Outputs," Journal of Productivity Analysis, Springer, vol. 21(2), pages 113-132, March.
    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. Dingjun Chang & Shuling Tang, 2024. "Research on Low-Carbon Building Development and Carbon Emission Control Based on Mathematical Models: A Case Study of Jiangsu Province," Energies, MDPI, vol. 17(18), pages 1-22, September.

    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. Wijesiri, Mahinda & Yaron, Jacob & Meoli, Michele, 2017. "Assessing the financial and outreach efficiency of microfinance institutions: Do age and size matter?," Journal of Multinational Financial Management, Elsevier, vol. 40(C), pages 63-76.
    2. Toloo, Mehdi & Hančlová, Jana, 2020. "Multi-valued measures in DEA in the presence of undesirable outputs," Omega, Elsevier, vol. 94(C).
    3. Barros, Carlos Pestana, 2008. "Airports in Argentina: Technical efficiency in the context of an economic crisis," Journal of Air Transport Management, Elsevier, vol. 14(6), pages 315-319.
    4. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    5. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
    6. Imad Bou-Hamad & Abdel Latef Anouze & Ibrahim H. Osman, 2022. "A cognitive analytics management framework to select input and output variables for data envelopment analysis modeling of performance efficiency of banks using random forest and entropy of information," Annals of Operations Research, Springer, vol. 308(1), pages 63-92, January.
    7. Xiaopeng Yang & Hiroshi Morita, 2012. "A DEA model with identical weight assignment based on multiple perspectives," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 4(1), pages 18-35.
    8. Lee, Boon L. & Worthington, Andrew C., 2014. "Technical efficiency of mainstream airlines and low-cost carriers: New evidence using bootstrap data envelopment analysis truncated regression," Journal of Air Transport Management, Elsevier, vol. 38(C), pages 15-20.
    9. Bortoluzzi, Mirian & Furlan, Marcelo & dos Reis Neto, José Francisco, 2022. "Assessing the impact of hydropower projects in Brazil through data envelopment analysis and machine learning," Renewable Energy, Elsevier, vol. 200(C), pages 1316-1326.
    10. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    11. Chilingerian, Jon A., 1995. "Evaluating physician efficiency in hospitals: A multivariate analysis of best practices," European Journal of Operational Research, Elsevier, vol. 80(3), pages 548-574, February.
    12. Boon Lee & Andrew Worthington, 2011. "Operational performance of low-cost carriers and international airlines: New evidence using a bootstrap truncated regression," School of Economics and Finance Discussion Papers and Working Papers Series 271, School of Economics and Finance, Queensland University of Technology.
    13. Reuben Elan & Verma Bharat Bhushan & Bhat Ramesh, 2001. "Hospital Efficiency: An Empirical Analysis of District and Grant-in-Aid Hospitals in Gujarat," IIMA Working Papers WP2001-07-05, Indian Institute of Management Ahmedabad, Research and Publication Department.
    14. Wen-Chih Chen & Andrew Johnson, 2010. "The dynamics of performance space of Major League Baseball pitchers 1871–2006," Annals of Operations Research, Springer, vol. 181(1), pages 287-302, December.
    15. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    16. Wijesiri, Mahinda & Yaron, Jacob & Meoli, Michele, 2015. "Performance of microfinance institutions in achieving the poverty outreach and financial sustainability: When age and size matter?," MPRA Paper 69821, University Library of Munich, Germany.
    17. LaPlante, A.E. & Paradi, J.C., 2015. "Evaluation of bank branch growth potential using data envelopment analysis," Omega, Elsevier, vol. 52(C), pages 33-41.
    18. Fallahi, Alireza & Ebrahimi, Reza & Ghaderi, S.F., 2011. "Measuring efficiency and productivity change in power electric generation management companies by using data envelopment analysis: A case study," Energy, Elsevier, vol. 36(11), pages 6398-6405.
    19. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    20. Kristiaan Kerstens & Jafar Sadeghi & Ignace Van de Woestyne, 2020. "Plant capacity notions in a non-parametric framework: a brief review and new graph or non-oriented plant capacities," Annals of Operations Research, Springer, vol. 288(2), pages 837-860, May.

    More about this item

    JEL classification:

    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

    Statistics

    Access and download statistics

    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:spr:anresc:v:66:y:2021:i:2:d:10.1007_s00168-020-01025-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.