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Are Brazilian Higher Education Institutions Efficient in Their Graduate Activities? A Two-Stage Dynamic Data-Envelopment-Analysis Cooperative Approach

Author

Listed:
  • Lívia Mariana Lopes de Souza Torres

    (Department of Production Engineering, Graduate Program in Management Engineering, Federal University of Pernambuco (UFPE), Architecture Avenue, s/n, Recife 50740-550, Brazil)

  • Francisco S. Ramos

    (Department of Production Engineering, Graduate Program in Management Engineering, Federal University of Pernambuco (UFPE), Architecture Avenue, s/n, Recife 50740-550, Brazil
    Department of Economics, Laboratory of Risk Management, Governance and Compliance—LabGRC, Federal University of Pernambuco (UFPE), Professor Moraes Rego, s/n, Recife 50670-901, Brazil)

Abstract

Higher education evaluation presents itself as a worldwide trend. It aims to improve performance due to its importance for economic and personal growth. Graduate activities are essential for Brazilian research and innovation systems. However, previous studies have disregarded the importance of this educational level and have evaluated efficiency by jointly considering teaching and research or only undergraduate courses. Therefore, this study contributes to Brazilian reality by proving a national graduate activities efficiency evaluation that considers them as a two-stage system (formative and scientific production stages). The study provides three main methodological contributions by presenting a new centralized two-stage dynamic network data envelopment analysis (DNDEA) model with shared resources. Besides measuring efficiency, an efficiency decomposition based on a leader–follower assumption shows managers how much efficiency can alter when one of the stages needs to be prioritized. Finally, a new framework based on modified virtual inputs and outputs provides a bi-dimensional representation of the efficiency frontier. Results indicate the usefulness of the approach for ranking universities, and the need to improve scientific production, highlighting the negative impacts of COVID-19 on the formative process efficiency and showing no significant regional discrepancies regarding performance.

Suggested Citation

  • Lívia Mariana Lopes de Souza Torres & Francisco S. Ramos, 2024. "Are Brazilian Higher Education Institutions Efficient in Their Graduate Activities? A Two-Stage Dynamic Data-Envelopment-Analysis Cooperative Approach," Mathematics, MDPI, vol. 12(6), pages 1-41, March.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:6:p:884-:d:1358577
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    References listed on IDEAS

    as
    1. Kao, Chiang, 2009. "Efficiency decomposition in network data envelopment analysis: A relational model," European Journal of Operational Research, Elsevier, vol. 192(3), pages 949-962, February.
    2. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2005. "Returns to scale in dynamic DEA," European Journal of Operational Research, Elsevier, vol. 161(2), pages 536-544, March.
    3. John S. Liu & Louis Y. Y. Lu & Wen-Min Lu, 2016. "Research Fronts and Prevailing Applications in Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, chapter 0, pages 543-574, Springer.
    4. Kristof De Witte & Laura López-Torres, 2017. "Efficiency in education: a review of literature and a way forward," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 339-363, April.
    5. Dovile Stumbriene & Ana S. Camanho & Audrone Jakaitiene, 2020. "The performance of education systems in the light of Europe 2020 strategy," Annals of Operations Research, Springer, vol. 288(2), pages 577-608, May.
    6. Ding, Tao & Zhang, Yun & Zhang, Danlu & Li, Feng, 2023. "Performance evaluation of Chinese research universities: A parallel interactive network DEA approach with shared and fixed sum inputs," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    7. Chuang-Min Chao & Ming-Miin Yu & Hsiao-Ning Wu, 2015. "An Application of the Dynamic Network DEA Model: The Case of Banks in Taiwan," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 51(S1), pages 133-151, January.
    8. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    9. Zoghbi, Ana Carolina & Rocha, Fabiana & Mattos, Enlinson, 2013. "Education production efficiency: Evidence from Brazilian universities," Economic Modelling, Elsevier, vol. 31(C), pages 94-103.
    10. 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.
    11. Kao, Chiang & Hwang, Shiuh-Nan, 2008. "Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan," European Journal of Operational Research, Elsevier, vol. 185(1), pages 418-429, February.
    12. Philipp Geymueller, 2009. "Static versus dynamic DEA in electricity regulation: the case of US transmission system operators," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 17(4), pages 397-413, December.
    13. José França & João Figueiredo & Jair Lapa, 2010. "A DEA methodology to evaluate the impact of information asymmetry on the efficiency of not-for-profit organizations with an application to higher education in Brazil," Annals of Operations Research, Springer, vol. 173(1), pages 39-56, January.
    14. Cook, Wade D. & Seiford, Larry M., 2009. "Data envelopment analysis (DEA) - Thirty years on," European Journal of Operational Research, Elsevier, vol. 192(1), pages 1-17, January.
    15. El-Mahgary, Sami & Lahdelma, Risto, 1995. "Data envelopment analysis: Visualizing the results," European Journal of Operational Research, Elsevier, vol. 83(3), pages 700-710, June.
    16. Marcus Porembski & Kristina Breitenstein & Paul Alpar, 2005. "Visualizing Efficiency and Reference Relations in Data Envelopment Analysis with an Application to the Branches of a German Bank," Journal of Productivity Analysis, Springer, vol. 23(2), pages 203-221, May.
    17. Hiroyuki Kawaguchi & Kaoru Tone & Miki Tsutsui, 2014. "Estimation of the efficiency of Japanese hospitals using a dynamic and network data envelopment analysis model," Health Care Management Science, Springer, vol. 17(2), pages 101-112, June.
    18. Anup Kumar & Rajiv R. Thakur, 2019. "Objectivity in performance ranking of higher education institutions using dynamic data envelopment analysis," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 68(4), pages 774-796, January.
    19. Sebastián Lozano, 2017. "Technical and environmental efficiency of a two-stage production and abatement system," Annals of Operations Research, Springer, vol. 255(1), pages 199-219, August.
    20. Chen, Yao & Du, Juan & David Sherman, H. & Zhu, Joe, 2010. "DEA model with shared resources and efficiency decomposition," European Journal of Operational Research, Elsevier, vol. 207(1), pages 339-349, November.
    21. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    22. Jiro Nemoto & Mika Goto, 2003. "Measurement of Dynamic Efficiency in Production: An Application of Data Envelopment Analysis to Japanese Electric Utilities," Journal of Productivity Analysis, Springer, vol. 19(2), pages 191-210, April.
    23. Samira Foladi & Maghsud Solimanpur & Mustafa Jahangoshai Rezaee, 2020. "Inverse Dynamic Data Envelopment Analysis for Evaluating Faculties of University with Quasi-Fixed Inputs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(1), pages 323-347, February.
    24. Nemoto, Jiro & Goto, Mika, 1999. "Dynamic data envelopment analysis: modeling intertemporal behavior of a firm in the presence of productive inefficiencies," Economics Letters, Elsevier, vol. 64(1), pages 51-56, July.
    25. Davood Gharakhani & Abbas Toloie Eshlaghy & Kiamars Fathi Hafshejani & Reza Kiani Mavi & Farhad Hosseinzadeh Lotfi, 2018. "Common weights in dynamic network DEA with goal programming approach for performance assessment of insurance companies in Iran," Management Research Review, Emerald Group Publishing Limited, vol. 41(8), pages 920-938, April.
    26. Dimitris Despotis & Gregory Koronakos & Dimitris Sotiros, 2016. "Composition versus decomposition in two-stage network DEA: a reverse approach," Journal of Productivity Analysis, Springer, vol. 45(1), pages 71-87, February.
    27. Liang Liang & Wade D. Cook & Joe Zhu, 2008. "DEA models for two‐stage processes: Game approach and efficiency decomposition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 643-653, October.
    28. Fukuyama, Hirofumi & Weber, William L. & Xia, Yin, 2016. "Time substitution and network effects with an application to nanobiotechnology policy for US universities," Omega, Elsevier, vol. 60(C), pages 34-44.
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