IDEAS home Printed from https://ideas.repec.org/a/eee/teinso/v68y2022ics0160791x22000562.html
   My bibliography  Save this article

Spreading knowledge and technology: Research efficiency at universities based on the three-stage MCDM-NRSDEA method with bootstrapping

Author

Listed:
  • Zhang, Chonghui
  • Jiang, Nanyue
  • Su, Tiantian
  • Chen, Ji
  • Streimikiene, Dalia
  • Balezentis, Tomas

Abstract

Consequent to increasing higher education attainment and the expansion of higher education institutions, many countries have embarked on assessing discipline efficiency to track performance, promote competition, and ensure reasonable resource allocation. Therefore, measuring scientific-research efficiency is a crucial part of evaluating a discipline's development. This paper proposes the three-stage multi-criteria decision-making (MCDM) non-radial super-efficiency data envelopment analysis (NRSDEA) method with bootstrapping to study a discipline's scientific research efficiency from the university-level perspective. To ensure robust analysis, the proposed model incorporates the contextual variables describing the external environment and the random error. The data envelopment analysis (DEA) model is a non-oriented one. The three-stage DEA approach is applied, including contextual variables such as economic growth, innovation, infrastructure, and the natural environment. In addition, the bootstrap method is applied to correct for measurement errors. Finally, the research efficiency measurement of the statistics discipline at Chinese universities is taken as an example to verify the method's validity.

Suggested Citation

  • Zhang, Chonghui & Jiang, Nanyue & Su, Tiantian & Chen, Ji & Streimikiene, Dalia & Balezentis, Tomas, 2022. "Spreading knowledge and technology: Research efficiency at universities based on the three-stage MCDM-NRSDEA method with bootstrapping," Technology in Society, Elsevier, vol. 68(C).
  • Handle: RePEc:eee:teinso:v:68:y:2022:i:c:s0160791x22000562
    DOI: 10.1016/j.techsoc.2022.101915
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160791X22000562
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techsoc.2022.101915?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. Cristian Barra & Roberto Zotti, 2016. "Measuring Efficiency in Higher Education: An Empirical Study Using a Bootstrapped Data Envelopment Analysis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(1), pages 11-33, February.
    2. Zeng, Shouzhen & Zhang, Na & Zhang, Chonghui & Su, Weihua & Carlos, Llopis-Albert, 2022. "Social network multiple-criteria decision-making approach for evaluating unmanned ground delivery vehicles under the Pythagorean fuzzy environment," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    3. Amara, Nabil & Rhaiem, Mehdi & Halilem, Norrin, 2020. "Assessing the research efficiency of Canadian scholars in the management field: Evidence from the DEA and fsQCA," Journal of Business Research, Elsevier, vol. 115(C), pages 296-306.
    4. Chen, Yao & Sherman, H. David, 2004. "The benefits of non-radial vs. radial super-efficiency DEA: an application to burden-sharing amongst NATO member nations," Socio-Economic Planning Sciences, Elsevier, vol. 38(4), pages 307-320, December.
    5. Cherchye, L. & Abeele, P. Vanden, 2005. "On research efficiency: A micro-analysis of Dutch university research in Economics and Business Management," Research Policy, Elsevier, vol. 34(4), pages 495-516, May.
    6. Lee, Hsuan-Shih & Chu, Ching-Wu & Zhu, Joe, 2011. "Super-efficiency DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 212(1), pages 141-147, July.
    7. Léopold Simar & Paul W. Wilson, 2011. "Performance of the Bootstrap for DEA Estimators and Iterating the Principle," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 241-271, Springer.
    8. 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.
    9. Shihong Zeng & Mimi Hu & Bin Su, 2016. "Research on Investment Efficiency and Policy Recommendations for the Culture Industry of China Based on a Three-Stage DEA," Sustainability, MDPI, vol. 8(4), pages 1-15, March.
    10. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    11. Zhimin Dai & Lu Guo & Zhengyi Jiang, 2016. "Study on the industrial Eco-Efficiency in East China based on the Super Efficiency DEA Model: an example of the 2003–2013 panel data," Applied Economics, Taylor & Francis Journals, vol. 48(59), pages 5779-5785, December.
    12. Stepan Zemtsov & Maxim Kotsemir, 2019. "An assessment of regional innovation system efficiency in Russia: the application of the DEA approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 375-404, August.
    13. Banal-Estañol, Albert & Macho-Stadler, Inés & Pérez-Castrillo, David, 2019. "Evaluation in research funding agencies: Are structurally diverse teams biased against?," Research Policy, Elsevier, vol. 48(7), pages 1823-1840.
    14. Anne-Wil Harzing & Satu Alakangas, 2016. "Google Scholar, Scopus and the Web of Science: a longitudinal and cross-disciplinary comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 787-804, February.
    15. Mehdi Rhaiem, 2017. "Measurement and determinants of academic research efficiency: a systematic review of the evidence," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 581-615, February.
    16. Bai, Xuejie & Sun, Xianzhen & Chiu, Yung-Ho, 2020. "Does China's higher education investment play a role in industrial growth?," Technology in Society, Elsevier, vol. 63(C).
    17. George E. Halkos & Nickolaos G. Tzeremes & Stavros A. Kourtzidis, 2012. "Measuring Public Owned University Departments' Efficiency: A Bootstrapped DEA Approach," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 55(2), pages 1-24.
    18. Wei, Quanling & Zhang, Jianzhong & Zhang, Xiangsun, 2000. "An inverse DEA model for inputs/outputs estimate," European Journal of Operational Research, Elsevier, vol. 121(1), pages 151-163, February.
    19. Çelikbilek, Yakup & Tüysüz, Fatih, 2016. "An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources," Energy, Elsevier, vol. 115(P1), pages 1246-1258.
    20. Ming-Miin Yu & Nan-Hsing Hsiung & Li-Hsueh Chen, 2020. "Determinants of banks’ Nerlovian economic efficiency: a DEA-bootstrap approach," Applied Economics, Taylor & Francis Journals, vol. 52(47), pages 5169-5187, October.
    21. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    22. Mary da Silva Quintino, Heliana & Rodrigues Holanda, Francisco Sandro & Rodrigues Moura, Fabio & Ricardo de Santana, Jose & Vidal, Luiz Diego, 2021. "World efficiency in the potential production of new technologies under intellectual property assets," Technology in Society, Elsevier, vol. 65(C).
    23. Liu, Yong & Liu, Zhi-yang & Li, Jian, 2020. "Research on efficiency and differences of regional industry-university-research synergetic innovation in China," Technology in Society, Elsevier, vol. 63(C).
    24. Lu, Louis Y.Y. & Liu, John S., 2016. "A novel approach to identify the major research themes and development trajectory: The case of patenting research," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 71-82.
    25. Bonaccorsi, Andrea & Cicero, Tindaro, 2016. "Nondeterministic ranking of university departments," Journal of Informetrics, Elsevier, vol. 10(1), pages 224-237.
    26. Lim, Sungmook & Zhu, Joe, 2019. "Primal-dual correspondence and frontier projections in two-stage network DEA models," Omega, Elsevier, vol. 83(C), pages 236-248.
    27. Shamohammadi, Mehdi & Oh, Dong-hyun, 2019. "Measuring the efficiency changes of private universities of Korea: A two-stage network data envelopment analysis," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    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. Puertas, Rosa & Guaita-Martinez, José M. & Carracedo, Patricia & Ribeiro-Soriano, Domingo, 2022. "Analysis of European environmental policies: Improving decision making through eco-efficiency," Technology in Society, Elsevier, vol. 70(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. Amara, Nabil & Rhaiem, Mehdi & Halilem, Norrin, 2020. "Assessing the research efficiency of Canadian scholars in the management field: Evidence from the DEA and fsQCA," Journal of Business Research, Elsevier, vol. 115(C), pages 296-306.
    2. Mehdi Rhaiem & Nabil Amara, 2020. "Determinants of research efficiency in Canadian business schools: evidence from scholar-level data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 53-99, October.
    3. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    4. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    5. Bornmann, Lutz & Gralka, Sabine & Anegón, Félix de Moya & Wohlrabe, Klaus, 2023. "Efficiency of universities and research-focused institutions worldwide: The introduction of a new input indicator reflecting institutional staff numbers," Journal of Informetrics, Elsevier, vol. 17(2).
    6. Manuel Salas-Velasco, 2020. "Measuring and explaining the production efficiency of Spanish universities using a non-parametric approach and a bootstrapped-truncated regression," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 825-846, February.
    7. Mehdi Rhaiem, 2017. "Measurement and determinants of academic research efficiency: a systematic review of the evidence," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 581-615, February.
    8. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, April.
    9. Kerstin Enflo & Per Hjertstrand, 2009. "Relative Sources of European Regional Productivity Convergence: A Bootstrap Frontier Approach," Regional Studies, Taylor & Francis Journals, vol. 43(5), pages 643-659.
    10. Agasisti, Tommaso & de Oliveira Ribeiro, Celma & Montemor, Daniel Sanches, 2022. "The efficiency of Brazilian elementary public schools," International Journal of Educational Development, Elsevier, vol. 93(C).
    11. Nolwenn Roudaut & Anne Vanhems, 2012. "Explaining firms efficiency in the Ivorian manufacturing sector: a robust nonparametric approach," Journal of Productivity Analysis, Springer, vol. 37(2), pages 155-169, April.
    12. Pengyu Ren & Zhaoxia Liu, 2021. "Efficiency Evaluation of China’s Public Sports Services: A Three-Stage DEA Model," IJERPH, MDPI, vol. 18(20), pages 1-12, October.
    13. Jonek-Kowalska, Izabela & Musioł-Urbańczyk, Anna & Podgórska, Marzena & Wolny, Maciej, 2021. "Does motivation matter in evaluation of research institutions? Evidence from Polish public universities," Technology in Society, Elsevier, vol. 67(C).
    14. Zervopoulos, Panagiotis & Emrouznejad, Ali & Sklavos, Sokratis, 2019. "A Bayesian approach for correcting bias of data envelopment analysis estimators," MPRA Paper 91886, University Library of Munich, Germany.
    15. Andreas Dellnitz & Elmar Reucher & Andreas Kleine, 2021. "Efficiency evaluation in data envelopment analysis using strong defining hyperplanes," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(2), pages 441-465, June.
    16. Gnewuch, Matthias & Wohlrabe, Klaus, 2018. "Super-efficiency of education institutions: an application to economics departments," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 26, pages 610-623.
    17. Cristian Barra & Roberto Zotti, 2016. "Measuring Efficiency in Higher Education: An Empirical Study Using a Bootstrapped Data Envelopment Analysis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 22(1), pages 11-33, February.
    18. Laurens Cherchye & Bram De Rock & Frederic Vermeulen, 2008. "Analyzing Cost-Efficient Production Behavior Under Economies of Scope: A Nonparametric Methodology," Operations Research, INFORMS, vol. 56(1), pages 204-221, February.
    19. Wu, Yunna & Ke, Yiming & Zhang, Ting & Liu, Fangtong & Wang, Jing, 2018. "Performance efficiency assessment of photovoltaic poverty alleviation projects in China: A three-phase data envelopment analysis model," Energy, Elsevier, vol. 159(C), pages 599-610.
    20. Wang, Derek D., 2019. "Performance-based resource allocation for higher education institutions in China," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 66-75.

    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:teinso:v:68:y:2022:i:c:s0160791x22000562. 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: https://www.journals.elsevier.com/technology-in-society .

    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.