IDEAS home Printed from https://ideas.repec.org/a/eee/epplan/v94y2022ics0149718922000787.html
   My bibliography  Save this article

An alternative assessment approach to national higher education system evaluation

Author

Listed:
  • See, Kok Fong
  • Ng, Ying Chu
  • Yu, Ming-Miin

Abstract

While the assessment of higher education systems is informative to both policy makers and individuals, it is subjective and performed according to experts’ judgment. The present study proposes a relatively objective approach, hierarchical data envelopment analysis (H-DEA), to rank higher education systems. Unlike the subjective approach, H-DEA utilizes endogenous weight determination, allowing assessors to identify the relative importance of each attribute and subattribute. Utilizing the U21 Ranking of National Higher Education System 2020 data, our analysis indicates that the output attribute is a crucial factor influencing the overall performance of higher education systems, even considering countries’ stage of development and culture. The computed weights of the H-DEA framework show various attributes’ different contributions by group. Resources allocated to the higher education system are important for developing countries, while a high degree of internationalization and a strong link between academia and industry matter for advanced countries. Surprisingly, Asian and Western cultures experience similar performance in their higher education systems, reflecting the Asian higher education system’s development toward the Western style. The performance of countries with non-Asian–non-Western cultures, as expected, lags behind, and putting more resources into these countries’ higher education system is a way to enhance the overall performance.

Suggested Citation

  • See, Kok Fong & Ng, Ying Chu & Yu, Ming-Miin, 2022. "An alternative assessment approach to national higher education system evaluation," Evaluation and Program Planning, Elsevier, vol. 94(C).
  • Handle: RePEc:eee:epplan:v:94:y:2022:i:c:s0149718922000787
    DOI: 10.1016/j.evalprogplan.2022.102124
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0149718922000787
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.evalprogplan.2022.102124?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. Paolo Paruolo & Michaela Saisana & Andrea Saltelli, 2013. "Ratings and rankings: voodoo or science?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 609-634, June.
    2. Halme, Merja & Korhonen, Pekka, 2000. "Restricting weights in value efficiency analysis," European Journal of Operational Research, Elsevier, vol. 126(1), pages 175-188, October.
    3. Stéphane Blancard & Jean-François Hoarau, 2011. "Optimizing the new formulation of the United Nations' human development index: An empirical view from data envelopment analysis," Economics Bulletin, AccessEcon, vol. 31(1), pages 989-1003.
    4. 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.
    5. Russell G. Thompson & F. D. Singleton & Robert M. Thrall & Barton A. Smith, 1986. "Comparative Site Evaluations for Locating a High-Energy Physics Lab in Texas," Interfaces, INFORMS, vol. 16(6), pages 35-49, December.
    6. Jacek Pietrucha, 2018. "Country-specific determinants of world university rankings," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1129-1139, March.
    7. Pilar Murias & Fidel Martinez & Carlos Miguel, 2006. "An Economic Wellbeing Index for the Spanish Provinces: A Data Envelopment Analysis Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 77(3), pages 395-417, July.
    8. Roll, Y & Golany, B., 1993. "Alternate methods of treating factor weights in DEA," Omega, Elsevier, vol. 21(1), pages 99-109, January.
    9. Thompson, Russell G. & Langemeier, Larry N. & Lee, Chih-Tah & Lee, Euntaik & Thrall, Robert M., 1990. "The role of multiplier bounds in efficiency analysis with application to Kansas farming," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 93-108.
    10. Pilar Murias & José Miguel & David Rodríguez, 2008. "A Composite Indicator for University Quality Assesment: The Case of Spanish Higher Education System," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 89(1), pages 129-146, October.
    11. Meng, Wei & Zhang, Daqun & Qi, Li & Liu, Wenbin, 2008. "Two-level DEA approaches in research evaluation," Omega, Elsevier, vol. 36(6), pages 950-957, December.
    12. D K Despotis, 2005. "A reassessment of the human development index via data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(8), pages 969-980, August.
    13. Stéphane Blancard & Jean-François Hoarau, 2011. "Optimizing the new formulation of the United Nations' human development index: An empirical view from data envelopment analysis," Economics Bulletin, AccessEcon, vol. 31(1), pages 989-1003.
    14. Chen, Po-Chi & Yu, Ming-Miin & Shih, Jou-Chen & Chang, Ching-Cheng & Hsu, Shih-Hsun, 2019. "A reassessment of the Global Food Security Index by using a hierarchical data envelopment analysis approach," European Journal of Operational Research, Elsevier, vol. 272(2), pages 687-698.
    15. Castelli, Lorenzo & Pesenti, Raffaele & Ukovich, Walter, 2004. "DEA-like models for the efficiency evaluation of hierarchically structured units," European Journal of Operational Research, Elsevier, vol. 154(2), pages 465-476, April.
    16. Zilla Sinuany-Stern & Arthur Hirsh, 2021. "The Relative Efficiencies of Higher Education in OECD Countries," International Series in Operations Research & Management Science, in: Zilla Sinuany-Stern (ed.), Handbook of Operations Research and Management Science in Higher Education, chapter 0, pages 481-512, Springer.
    17. Ming-Miin Yu & Bo Hsiao, 2016. "Measuring the technology gap and logistics performance of individual countries by using a meta-DEA--AR model," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(1), pages 98-120, January.
    18. Raab, Raymond & Kotamraju, Pradeep & Haag, Stephen, 2000. "Efficient provision of child quality of life in less developed countries: conventional development indexes versus a programming approach to development indexes," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 51-67, March.
    19. Marie-Laure Bougnol & José Dulá, 2006. "Validating DEA as a ranking tool: An application of DEA to assess performance in higher education," Annals of Operations Research, Springer, vol. 145(1), pages 339-365, July.
    20. Benito, M. & Gil, P. & Romera, R., 2020. "Evaluating the influence of country characteristics on the Higher Education System Rankings’ progress," Journal of Informetrics, Elsevier, vol. 14(3).
    21. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Comparing aggregating methods for constructing the composite environmental index: An objective measure," Ecological Economics, Elsevier, vol. 59(3), pages 305-311, September.
    22. Kao, Chiang, 2015. "Efficiency measurement for hierarchical network systems," Omega, Elsevier, vol. 51(C), pages 121-127.
    23. M. Saisana & A. Saltelli & S. Tarantola, 2005. "Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 307-323, March.
    24. Thanassoulis, E. & Boussofiane, A. & Dyson, R. G., 1995. "Exploring output quality targets in the provision of perinatal care in England using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 80(3), pages 588-607, February.
    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. Shahari, Mohd Ridzwan & See, Kok Fong & Mohammed, Noor Syahireen & Yu, Ming-Miin, 2023. "Constructing the performance index of Malaysia’s district health centers using effectiveness-based hierarchical data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    2. Yan Xia & Jianxin You & Xiumeng Feng & Yingjie Xu & Hui Feng, 2023. "Clustering Analysis of Classified Performance Evaluation of Higher Education in Shanghai Based on Topsis Model," Sustainability, MDPI, vol. 15(8), pages 1-18, April.

    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. Shahari, Mohd Ridzwan & See, Kok Fong & Mohammed, Noor Syahireen & Yu, Ming-Miin, 2023. "Constructing the performance index of Malaysia’s district health centers using effectiveness-based hierarchical data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    2. Victoria Wojcik & Harald Dyckhoff & Marcel Clermont, 2019. "Is data envelopment analysis a suitable tool for performance measurement and benchmarking in non-production contexts?," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 559-595, December.
    3. 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.
    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. P. Zhou & B. Ang, 2009. "Comparing MCDA Aggregation Methods in Constructing Composite Indicators Using the Shannon-Spearman Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 94(1), pages 83-96, October.
    6. Sarrico, C. S. & Dyson, R. G., 2004. "Restricting virtual weights in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 159(1), pages 17-34, November.
    7. T Joro & E-J Viitala, 2004. "Weight-restricted DEA in action: from expert opinions to mathematical models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 814-821, August.
    8. Dimitrov, Stanko & Sutton, Warren, 2010. "Promoting symmetric weight selection in data envelopment analysis: A penalty function approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 281-288, January.
    9. Hatefi, S.M. & Torabi, S.A., 2010. "A common weight MCDA-DEA approach to construct composite indicators," Ecological Economics, Elsevier, vol. 70(1), pages 114-120, November.
    10. Zhou, P. & Ang, B.W. & Poh, K.L., 2007. "A mathematical programming approach to constructing composite indicators," Ecological Economics, Elsevier, vol. 62(2), pages 291-297, April.
    11. Roets, Bart & Verschelde, Marijn & Christiaens, Johan, 2018. "Multi-output efficiency and operational safety: An analysis of railway traffic control centre performance," European Journal of Operational Research, Elsevier, vol. 271(1), pages 224-237.
    12. Mariano, Enzo Barberio & Sobreiro, Vinicius Amorim & Rebelatto, Daisy Aparecida do Nascimento, 2015. "Human development and data envelopment analysis: A structured literature review," Omega, Elsevier, vol. 54(C), pages 33-49.
    13. Hosein Arman & Abdollah Hadi‐Vencheh, 2021. "Restricting the relative weights in data envelopment analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4127-4136, July.
    14. Pereira, Miguel Alves & Camanho, Ana Santos & Figueira, José Rui & Marques, Rui Cunha, 2021. "Incorporating preference information in a range directional composite indicator: The case of Portuguese public hospitals," European Journal of Operational Research, Elsevier, vol. 294(2), pages 633-650.
    15. Kremantzis, Marios Dominikos & Beullens, Patrick & Kyrgiakos, Leonidas Sotirios & Klein, Jonathan, 2022. "Measurement and evaluation of multi-function parallel network hierarchical DEA systems," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    16. Tavana, Madjid & Ebrahimnejad, Ali & Santos-Arteaga, Francisco J. & Mansourzadeh, Seyed Mehdi & Matin, Reza Kazemi, 2018. "A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 70-89.
    17. William W. Cooper & Kyung Sam Park & Gang Yu, 2001. "An Illustrative Application of Idea (Imprecise Data Envelopment Analysis) to a Korean Mobile Telecommunication Company," Operations Research, INFORMS, vol. 49(6), pages 807-820, December.
    18. Shimshak, Daniel G. & Lenard, Melanie L. & Klimberg, Ronald K., 2009. "Incorporating quality into data envelopment analysis of nursing home performance: A case study," Omega, Elsevier, vol. 37(3), pages 672-685, June.
    19. V V Podinovski, 2004. "Production trade-offs and weight restrictions in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1311-1322, December.
    20. C Kao & H-T Hung, 2005. "Data envelopment analysis with common weights: the compromise solution approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1196-1203, October.

    More about this item

    Keywords

    Evaluation; Education system; Hierarchical DEA; Assessment;
    All these keywords.

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • P46 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - Consumer Economics; Health; Education and Training; Welfare, Income, Wealth, and Poverty
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

    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:eee:epplan:v:94:y:2022:i:c:s0149718922000787. 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/evalprogplan .

    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.