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. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    2. Contreras, I. & Lozano, S., 2020. "Allocating additional resources to public universities. A DEA bargaining approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    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. 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.
    2. 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.
    3. 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.
    4. Zanella, Andreia & Camanho, Ana S. & Dias, Teresa G., 2015. "Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(2), pages 517-530.
    5. 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.
    6. Toloo, Mehdi & Hančlová, Jana, 2020. "Multi-valued measures in DEA in the presence of undesirable outputs," Omega, Elsevier, vol. 94(C).
    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. 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.
    9. Jie Wu & Qingyuan Zhu & Pengzhen Yin & Malin Song, 2017. "Measuring energy and environmental performance for regions in China by using DEA-based Malmquist indices," Operational Research, Springer, vol. 17(3), pages 715-735, October.
    10. Guillen, Maria D. & Aparicio, Juan & Kapelko, Magdalena & Esteve, Miriam, 2025. "Measuring environmental inefficiency through machine learning: An approach based on efficiency analysis trees and by-production technology," European Journal of Operational Research, Elsevier, vol. 321(2), pages 529-542.
    11. Zou, Bo & Kafle, Nabin & Chang, Young-Tae & Park, Kevin, 2015. "US airport financial reform and its implications for airport efficiency: An exploratory investigation," Journal of Air Transport Management, Elsevier, vol. 47(C), pages 66-78.
    12. Xiang Ji & Jie Wu & Qingyuan Zhu & Jiasen Sun, 2019. "Using a hybrid heterogeneous DEA method to benchmark China’s sustainable urbanization: an empirical study," Annals of Operations Research, Springer, vol. 278(1), pages 281-335, July.
    13. Jie Wu & Zhixiang Zhou, 2015. "A mixed-objective integer DEA model," Annals of Operations Research, Springer, vol. 228(1), pages 81-95, May.
    14. Pourmahmoud, Jafar & Bagheri, Narges, 2023. "Uncertain Malmquist productivity index: An application to evaluate healthcare systems during COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    15. Li-Ling Kao, 2023. "ESG-Based Performance Assessment of the Operation and Management of Industrial Parks in Taiwan," Sustainability, MDPI, vol. 15(2), pages 1-27, January.
    16. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.
    17. 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.
    18. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    19. 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.
    20. Chang, Dong-Shang & Yang, Fu-Chiang, 2011. "Assessing the power generation, pollution control, and overall efficiencies of municipal solid waste incinerators in Taiwan," Energy Policy, Elsevier, vol. 39(2), pages 651-663, February.

    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.