IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v97y2025ics003801212400301x.html
   My bibliography  Save this article

Performance evaluation of child welfare departments using Data Envelopment Analysis: A comparative study across US states

Author

Listed:
  • Sedghi, Sepideh
  • Azizi, Shima
  • Canada, Katherine
  • Charles, Vincent
  • Trapp, Andrew C.

Abstract

Public child welfare agencies play a pivotal role in safeguarding the well-being of children and thus, the future of our society. While the performance of child welfare agencies is of critical importance, limited previous research relying on operations research and advanced analytics appears to exist in the analysis of their performance. We conduct a multi-criteria analysis for benchmarking the performance of the United States child welfare system, using Data Envelopment Analysis (DEA) to evaluate the performance of public child welfare agencies across different US states. We select as outputs various statewide data indicators from the Child and Family Services Review (CFSR), while our inputs include the total annual expenditure by each state on the child welfare system. We use clustering to differentiate agencies based on the presence of the “Alternative Response” policy, which provides for preventive and support options for families, and apply DEA to each homogeneous cluster. We identify best-practice agencies and provide benchmarks for the remaining agencies to enhance their performance. Our study offers data-driven directions for child welfare agencies to improve safety and permanency outcomes for children.

Suggested Citation

  • Sedghi, Sepideh & Azizi, Shima & Canada, Katherine & Charles, Vincent & Trapp, Andrew C., 2025. "Performance evaluation of child welfare departments using Data Envelopment Analysis: A comparative study across US states," Socio-Economic Planning Sciences, Elsevier, vol. 97(C).
  • Handle: RePEc:eee:soceps:v:97:y:2025:i:c:s003801212400301x
    DOI: 10.1016/j.seps.2024.102101
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S003801212400301X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.seps.2024.102101?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. Contreras, I. & Lozano, S., 2020. "Allocating additional resources to public universities. A DEA bargaining approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    2. Bonasia, Mariangela & Kounetas, Konstantinos & Oreste, Napolitano, 2020. "Assessment of regional productive performance of European health systems under a metatechnology framework," Economic Modelling, Elsevier, vol. 84(C), pages 234-248.
    3. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    4. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min & Lin, Bruce J.Y., 2013. "A survey of DEA applications," Omega, Elsevier, vol. 41(5), pages 893-902.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. Andrew Johnson & John Ruggiero, 2014. "Nonparametric measurement of productivity and efficiency in education," Annals of Operations Research, Springer, vol. 221(1), pages 197-210, October.
    7. Fare, Rolf, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    8. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    9. Charles, Vincent & Aparicio, Juan & Zhu, Joe, 2019. "The curse of dimensionality of decision-making units: A simple approach to increase the discriminatory power of data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 279(3), pages 929-940.
    10. Apergis, Nicholas & Aye, Goodness C. & Barros, Carlos Pestana & Gupta, Rangan & Wanke, Peter, 2015. "Energy efficiency of selected OECD countries: A slacks based model with undesirable outputs," Energy Economics, Elsevier, vol. 51(C), pages 45-53.
    11. Haas, David A. & Murphy, Frederic H., 2003. "Compensating for non-homogeneity in decision-making units in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 144(3), pages 530-544, February.
    12. A Medina-Borja & K S Pasupathy & K Triantis, 2007. "Large-scale data envelopment analysis (DEA) implementation: a strategic performance management approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(8), pages 1084-1098, August.
    13. 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.
    14. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    15. Giulia Garavaglia & Emanuele Lettieri & Tommaso Agasisti & Silvano Lopez, 2011. "Efficiency and quality of care in nursing homes: an Italian case study," Health Care Management Science, Springer, vol. 14(1), pages 22-35, March.
    16. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    17. Iparraguirre, José Luis & Ma, Ruosi, 2015. "Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 33-46.
    Full references (including those not matched with items on IDEAS)

    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. Arsen Benga & Glediana Zeneli (Foto) & María Jesús Delgado‑Rodríguez & Sonia Lucas Santos, 2025. "Company efforts and environmental efficiency: evidence from European railways considering market-based emissions," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(5), pages 9977-10012, May.
    2. 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.
    3. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    4. Wen-Min Lu & Qian Long Kweh & Kai-Chu Yang, 2022. "Multiplicative efficiency aggregation to evaluate Taiwanese local auditing institutions performance," Annals of Operations Research, Springer, vol. 315(2), pages 1243-1262, August.
    5. Guillen, Maria D. & Charles, Vincent & Aparicio, Juan, 2025. "Enhanced efficiency assessment in manufacturing: Leveraging machine learning for improved performance analysis," Omega, Elsevier, vol. 134(C).
    6. César Salazar & Roberto Cárdenas-Retamal & Marcela Jaime, 2023. "Environmental efficiency in the salmon industry—an exploratory analysis around the 2007 ISA virus outbreak and subsequent regulations in Chile," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8107-8135, August.
    7. Taleb, Mushtaq & Khalid, Ruzelan & Ramli, Razamin & Ghasemi, Mohammad Reza & Ignatius, Joshua, 2022. "An integrated bi-objective data envelopment analysis model for measuring returns to scale," European Journal of Operational Research, Elsevier, vol. 296(3), pages 967-979.
    8. Yuanxiang Zhou & Shan Wang & Shuqi Xu & Qingyuan Zhu, 2025. "Big data in data envelopment analysis with undesirable outputs based on simulation and environmental-health matching data of Chinese industrial enterprises," Annals of Operations Research, Springer, vol. 348(1), pages 279-298, May.
    9. Hsiao-Yen Mao & Wen-Min Lu & Hsin-Yen Shieh, 2023. "Exploring the Influence of Environmental Investment on Multinational Enterprises’ Performance from the Sustainability and Marketability Efficiency Perspectives," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    10. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    11. Zhiqiang Zhu & Xuechi Zhang & Mengqing Xue & Yaoyao Song, 2023. "Eco-Efficiency and Its Evolutionary Change under Regulatory Constraints: A Case Study of Chinese Transportation Industry," Sustainability, MDPI, vol. 15(9), pages 1-18, April.
    12. Lin, Ruiyue & Peng, Yudan, 2024. "A new cross-efficiency meta-frontier analysis method with good ability to identify technology gaps," European Journal of Operational Research, Elsevier, vol. 314(2), pages 735-746.
    13. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    14. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    15. Fang, Tao & Fang, Debin & Yu, Bolin, 2022. "Carbon emission efficiency of thermal power generation in China: Empirical evidence from the micro-perspective of power plants," Energy Policy, Elsevier, vol. 165(C).
    16. Chih-Ching Yang, 2014. "An enhanced DEA model for decomposition of technical efficiency in banking," Annals of Operations Research, Springer, vol. 214(1), pages 167-185, March.
    17. Li Xie & Chunlin Chen & Yihua Yu, 2019. "Dynamic Assessment of Environmental Efficiency in Chinese Industry: A Multiple DEA Model with a Gini Criterion Approach," Sustainability, MDPI, vol. 11(8), pages 1-22, April.
    18. Fang Zhang & Hong Fang & Junjie Wu & Damian Ward, 2016. "Environmental Efficiency Analysis of Listed Cement Enterprises in China," Sustainability, MDPI, vol. 8(5), pages 1-19, May.
    19. Bretholt, Abraham & Pan, Jeh-Nan, 2013. "Evolving the latent variable model as an environmental DEA technology," Omega, Elsevier, vol. 41(2), pages 315-325.
    20. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.

    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:eee:soceps:v:97:y:2025:i:c:s003801212400301x. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    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.