IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v73y2021ics0038012119301818.html
   My bibliography  Save this article

Best-Worst PROMETHEE method for evaluating school performance in the OECD's PISA project

Author

Listed:
  • Ishizaka, Alessio
  • Resce, Giuliano

Abstract

This paper introduces the Best-Worst PROMETHEE method, which avoids the rank reversal problem of other PROMETHEE methods. We use this new technique to rank schools in the Programme for International Student Assessment (PISA). We consider three separate outputs, provided by average student attainments in mathematics, language, and sciences. Our sample comprises 16,500 schools in 66 countries, and our results show significant differences between school performance both within and between countries. The top half of the ranking mainly comprises European and Asian countries, while the bottom half includes many North African, Middle Eastern, and South American countries. We find no strong association between inequality between schools and the country-level performance, suggesting the absence of a trade-off between equity and performance in education. The Best-Worst PROMETHEE is a generic method that can be used to support decisions in strategic sectors with multidimensional outcomes.

Suggested Citation

  • Ishizaka, Alessio & Resce, Giuliano, 2021. "Best-Worst PROMETHEE method for evaluating school performance in the OECD's PISA project," Socio-Economic Planning Sciences, Elsevier, vol. 73(C).
    • Handle: RePEc:eee:soceps:v:73:y:2021:i:c:s0038012119301818
    DOI: 10.1016/j.seps.2020.100799
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012119301818
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2020.100799?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. Antonio Villar, 2016. "Educational poverty as a welfare loss: Low performance in the OECD according to PISA 2012," Working Papers 16.04, Universidad Pablo de Olavide, Department of Economics.
    2. De Keyser, Wim & Peeters, Peter, 1996. "A note on the use of PROMETHEE multicriteria methods," European Journal of Operational Research, Elsevier, vol. 89(3), pages 457-461, March.
    3. Eric A. Hanushek & Ludger Wössmann, 2006. "Does Educational Tracking Affect Performance and Inequality? Differences- in-Differences Evidence Across Countries," Economic Journal, Royal Economic Society, vol. 116(510), pages 63-76, March.
    4. Giuseppe Munda, 2012. "Choosing Aggregation Rules for Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 109(3), pages 337-354, December.
    5. Nicholas Bloom & Renata Lemos & Raffaella Sadun & John Van Reenen, 2015. "Does Management Matter in schools?," Economic Journal, Royal Economic Society, vol. 0(584), pages 647-674, May.
    6. Entorf Horst & Minoiu Nicoleta, 2005. "What a Difference Immigration Policy Makes: A Comparison of PISA Scores in Europe and Traditional Countries of Immigration," German Economic Review, De Gruyter, vol. 6(3), pages 355-376, August.
    7. Agasisti, Tommaso & Longobardi, Sergio, 2014. "Inequality in education: Can Italian disadvantaged students close the gap?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 52(C), pages 8-20.
    8. Michele Raitano & Francesco Vona, 2016. "Assessing students’ equality of opportunity in OECD countries: the role of national- and school-level policies," Applied Economics, Taylor & Francis Journals, vol. 48(33), pages 3148-3163, July.
    9. 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.
    10. Koen Decancq & María Ana Lugo, 2013. "Weights in Multidimensional Indices of Wellbeing: An Overview," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 7-34, January.
    11. Aparicio, Juan & Cordero, Jose M. & Pastor, Jesus T., 2017. "The determination of the least distance to the strongly efficient frontier in Data Envelopment Analysis oriented models: Modelling and computational aspects," Omega, Elsevier, vol. 71(C), pages 1-10.
    12. F Ruiz & J M Cabello & M Luque, 2011. "An application of reference point techniques to the calculation of synthetic sustainability indicators," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(1), pages 189-197, January.
    13. Lai, Young-Jou & Liu, Ting-Yun & Hwang, Ching-Lai, 1994. "TOPSIS for MODM," European Journal of Operational Research, Elsevier, vol. 76(3), pages 486-500, August.
    14. Herrero, Carmen & Mendez, Ildefonso & Villar, Antonio, 2014. "Analysis of group performance with categorical data when agents are heterogeneous: The evaluation of scholastic performance in the OECD through PISA," Economics of Education Review, Elsevier, vol. 40(C), pages 140-151.
    15. J. P. Brans & Ph. Vincke, 1985. "Note---A Preference Ranking Organisation Method," Management Science, INFORMS, vol. 31(6), pages 647-656, June.
    16. Raj Chetty & Nathaniel Hendren & Lawrence F. Katz, 2016. "The Effects of Exposure to Better Neighborhoods on Children: New Evidence from the Moving to Opportunity Experiment," American Economic Review, American Economic Association, vol. 106(4), pages 855-902, April.
    17. Lagravinese, Raffaele & Liberati, Paolo & Resce, Giuliano, 2019. "Exploring health outcomes by stochastic multicriteria acceptability analysis: An application to Italian regions," European Journal of Operational Research, Elsevier, vol. 274(3), pages 1168-1179.
    18. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    19. Behzadian, Majid & Kazemzadeh, R.B. & Albadvi, A. & Aghdasi, M., 2010. "PROMETHEE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 200(1), pages 198-215, January.
    20. De Witte, Kristof & Schiltz, Fritz, 2018. "Measuring and explaining organizational effectiveness of school districts: Evidence from a robust and conditional Benefit-of-the-Doubt approach," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1172-1181.
    21. Salvatore Greco & Alessio Ishizaka & Benedetto Matarazzo & Gianpiero Torrisi, 2018. "Stochastic multi-attribute acceptability analysis (SMAA): an application to the ranking of Italian regions," Regional Studies, Taylor & Francis Journals, vol. 52(4), pages 585-600, April.
    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. Pranith Kumar Roy & Krishnendu Shaw & Alessio Ishizaka, 2023. "Developing an integrated fuzzy credit rating system for SMEs using fuzzy-BWM and fuzzy-TOPSIS-Sort-C," Annals of Operations Research, Springer, vol. 325(2), pages 1197-1229, June.
    2. František Zapletal, 2022. "Revised PROMETHEE algorithm with reference values," 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. 30(2), pages 521-545, June.
    3. Zhang, Jingshun & Hu, Jiayi & Wang, Xitong & Fang, Lien & Jin, Yi & Li, Muyang & Liu, Yangqing & Wu, Anna & Wang, Libin & Liu, Ruining & Zhang, Yi & Chen, Faan, 2023. "Quantifying transport safety success at the regional level: A guide to policy and practice on investment for G20," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    4. Pranith Kumar Roy & Krishnendu Shaw, 2021. "A multicriteria credit scoring model for SMEs using hybrid BWM and TOPSIS," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    5. Gul, Muhammet & Yucesan, Melih, 2022. "Performance evaluation of Turkish Universities by an integrated Bayesian BWM-TOPSIS model," Socio-Economic Planning Sciences, Elsevier, vol. 80(C).

    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. Giuseppe Coco & Raffaele Lagravinese & Giuliano Resce, 2020. "Beyond the weights: a multicriteria approach to evaluate inequality in education," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(4), pages 469-489, December.
    2. Paolo Liberati & Raffaele Lagravinese & Giuliano Resce, 2017. "How Does Economic Social And Cultural Status Affect The Efficiency Of Educational Attainments? A Comparative Analysis On Pisa Results," Departmental Working Papers of Economics - University 'Roma Tre' 0217, Department of Economics - University Roma Tre.
    3. Giuliano Resce & Fritz Schiltz, 2021. "Sustainable Development in Europe: A Multicriteria Decision Analysis," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(2), pages 509-529, June.
    4. Salvatore Greco & Alessio Ishizaka & Menelaos Tasiou & Gianpiero Torrisi, 2019. "On the Methodological Framework of Composite Indices: A Review of the Issues of Weighting, Aggregation, and Robustness," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(1), pages 61-94, January.
    5. Lagravinese, Raffaele & Liberati, Paolo & Resce, Giuliano, 2020. "The impact of economic, social and cultural conditions on educational attainments," Journal of Policy Modeling, Elsevier, vol. 42(1), pages 112-132.
    6. Khatab Alqararah, 2023. "Assessing the robustness of composite indicators: the case of the Global Innovation Index," Journal of Innovation and Entrepreneurship, Springer, vol. 12(1), pages 1-22, December.
    7. Sulis, Isabella & Giambona, Francesca & Porcu, Mariano, 2020. "Adjusted indicators of quality and equity for monitoring the education systems over time. Insights on EU15 countries from PISA surveys," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    8. R. Pelissari & M. C. Oliveira & S. Ben Amor & A. Kandakoglu & A. L. Helleno, 2020. "SMAA methods and their applications: a literature review and future research directions," Annals of Operations Research, Springer, vol. 293(2), pages 433-493, October.
    9. Alessio Ishizaka & Philippe Nemery, 2013. "A Multi-Criteria Group Decision Framework for Partner Grouping When Sharing Facilities," Group Decision and Negotiation, Springer, vol. 22(4), pages 773-799, July.
    10. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2019. "Sigma-Mu efficiency analysis: A methodology for evaluating units through composite indicators," European Journal of Operational Research, Elsevier, vol. 278(3), pages 942-960.
    11. Arcidiacono, Sally Giuseppe & Corrente, Salvatore & Greco, Salvatore, 2021. "Robust stochastic sorting with interacting criteria hierarchically structured," European Journal of Operational Research, Elsevier, vol. 292(2), pages 735-754.
    12. Ana Garcia-Bernabeu & Adolfo Hilario-Caballero, 2021. "Monitoring multidimensional phenomena with a multicriteria composite performance interval approach," Papers 2107.08393, arXiv.org.
    13. Paolo Liberati & Giuliano Resce, 2022. "Regional Well-Being and its Inequality in the OECD Member Countries," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(3), pages 671-700, September.
    14. Milica Maricic & Jose A. Egea & Veljko Jeremic, 2019. "A Hybrid Enhanced Scatter Search—Composite I-Distance Indicator (eSS-CIDI) Optimization Approach for Determining Weights Within Composite Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 497-537, July.
    15. Su, Weihua & Chen, Sibo & Zhang, Chonghui & Li, Kevin W., 2023. "A subgroup dominance-based benefit of the doubt method for addressing rank reversals: A case study of the human development index in Europe," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1299-1317.
    16. Raffaele Lagravinese & Paolo Liberati & Giuliano Resce, 2020. "Measuring Health Inequality in US: A Composite Index Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(3), pages 921-946, February.
    17. Mustafa Hamurcu & Tamer Eren, 2020. "Strategic Planning Based on Sustainability for Urban Transportation: An Application to Decision-Making," Sustainability, MDPI, vol. 12(9), pages 1-24, April.
    18. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2021. "The ordinal input for cardinal output approach of non-compensatory composite indicators: the PROMETHEE scoring method," European Journal of Operational Research, Elsevier, vol. 288(1), pages 225-246.
    19. Camanho, Ana S. & Varriale, Luisa & Barbosa, Flávia & Sobral, Thiago, 2021. "Performance assessment of upper secondary schools in Italian regions using a circular pseudo-Malmquist index," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1188-1208.
    20. Atwood, Joseph & Shaik, Saleem, 2020. "Theory and statistical properties of Quantile Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 286(2), pages 649-661.

    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:73:y:2021:i:c:s0038012119301818. 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.