IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i9p7418-d1136942.html
   My bibliography  Save this article

Do Financial Investment, Disciplinary Differences, and Level of Development Impact on the Efficiency of Resource Allocation in Higher Education: Evidence from China

Author

Listed:
  • Biao Chen

    (School of Education, China University of Geosciences, Wuhan 430074, China
    School of Public Administration, China University of Geosciences, Wuhan 430074, China)

  • Yan Chen

    (School of Education, China University of Geosciences, Wuhan 430074, China)

  • Xianghua Qu

    (School of Education, China University of Geosciences, Wuhan 430074, China)

  • Wanyu Huang

    (School of Education, China University of Geosciences, Wuhan 430074, China)

  • Panyu Wang

    (School of Education, China University of Geosciences, Wuhan 430074, China)

Abstract

Optimizing the allocation of university resources to improve the efficiency of inputs and outputs is an important issue for the high-quality development of universities. In recent years, China has become an important growth pole for the development of global higher education. In particular, Chinese agricultural universities, with their distinctive disciplinary characteristics and outstanding professional advantages, have made important contributions to the sustainable development of agricultural education around the world. In contrast, academic research on the efficiency of resource allocation in Chinese agricultural universities is very limited. To fill this gap, this study was guided by econometrics and took high-level agricultural universities in China as the research object to measure the effects of financial investment, disciplinary differences, and development level on the level of resource allocation efficiency of universities. With the help of a data envelopment model (DEA) and a Malmquist index decomposition model, we found that the overall level of resource allocation efficiency in the sample universities was high, but there were great disparities in resource input–output effectiveness between universities. In many universities, marginal inputs exceeded marginal outputs, resulting in input redundancy and resource wastage. In addition, this study shows that for high-level agricultural universities, the regression of capital input technology is preventing a sustained increase in productivity, which places the total factor productivity of resource allocation in a diminishing state.

Suggested Citation

  • Biao Chen & Yan Chen & Xianghua Qu & Wanyu Huang & Panyu Wang, 2023. "Do Financial Investment, Disciplinary Differences, and Level of Development Impact on the Efficiency of Resource Allocation in Higher Education: Evidence from China," Sustainability, MDPI, vol. 15(9), pages 1-23, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7418-:d:1136942
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/9/7418/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/9/7418/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Contreras, I. & Lozano, S., 2020. "Allocating additional resources to public universities. A DEA bargaining approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    2. Laureti, Tiziana & Secondi, Luca & Biggeri, Luigi, 2014. "Measuring the efficiency of teaching activities in Italian universities: An information theoretic approach," Economics of Education Review, Elsevier, vol. 42(C), pages 147-164.
    3. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2018. "Measuring the inefficiency of Chinese research universities based on a two-stage network DEA model," Journal of Informetrics, Elsevier, vol. 12(1), pages 10-30.
    4. Lee, Boon L. & Worthington, Andrew C., 2016. "A network DEA quantity and quality-orientated production model: An application to Australian university research services," Omega, Elsevier, vol. 60(C), pages 26-33.
    5. Welch, F, 1970. "Education in Production," Journal of Political Economy, University of Chicago Press, vol. 78(1), pages 35-59, Jan.-Feb..
    6. Jacob Mincer, 1962. "On-the-Job Training: Costs, Returns, and Some Implications," NBER Chapters, in: Investment in Human Beings, pages 50-79, National Bureau of Economic Research, Inc.
    7. Marvin A. Titus & Adriana Vamosiu & Shannon Hayes Buenaflor & Casey Maliszewski Lukszo, 2021. "Persistent Cost Efficiency at Public Community Colleges in the US: A Stochastic Frontier Analysis," Research in Higher Education, Springer;Association for Institutional Research, vol. 62(8), pages 1168-1197, December.
    8. Tavares, Rafael Santos & Angulo-Meza, Lidia & Sant'Anna, Annibal Parracho, 2021. "A proposed multistage evaluation approach for Higher Education Institutions based on network Data envelopment analysis: A Brazilian experience," Evaluation and Program Planning, Elsevier, vol. 89(C).
    9. Johnes, Jill, 2006. "Data envelopment analysis and its application to the measurement of efficiency in higher education," Economics of Education Review, Elsevier, vol. 25(3), pages 273-288, June.
    10. Brennan, Shae & Haelermans, Carla & Ruggiero, John, 2014. "Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools," European Journal of Operational Research, Elsevier, vol. 234(3), pages 809-818.
    11. Tommaso Agasisti & Sabine Gralka, 2019. "The transient and persistent efficiency of Italian and German universities: a stochastic frontier analysis," Applied Economics, Taylor & Francis Journals, vol. 51(46), pages 5012-5030, October.
    12. Auranen, Otto & Nieminen, Mika, 2010. "University research funding and publication performance--An international comparison," Research Policy, Elsevier, vol. 39(6), pages 822-834, July.
    13. Gerhard Kempkes & Carsten Pohl, 2010. "The efficiency of German universities-some evidence from nonparametric and parametric methods," Applied Economics, Taylor & Francis Journals, vol. 42(16), pages 2063-2079.
    14. Abbott, M. & Doucouliagos, C., 2003. "The efficiency of Australian universities: a data envelopment analysis," Economics of Education Review, Elsevier, vol. 22(1), pages 89-97, February.
    15. Caballero, Rafael & Galache, Teodoro & Gomez, Trinidad & Molina, Julian & Torrico, Angel, 2004. "Budgetary allocations and efficiency in the human resources policy of a university following multiple criteria," Economics of Education Review, Elsevier, vol. 23(1), pages 67-74, February.
    16. 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.
    17. Berbegal-Mirabent, Jasmina & Lafuente, Esteban & Solé, Francesc, 2013. "The pursuit of knowledge transfer activities: An efficiency analysis of Spanish universities," Journal of Business Research, Elsevier, vol. 66(10), pages 2051-2059.
    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. Contreras, I. & Lozano, S., 2020. "Allocating additional resources to public universities. A DEA bargaining approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    2. Zihong Liu & Haitao Xiong & Ying Sun, 2023. "Will Online MOOCs Improve the Efficiency of Chinese Higher Education Institutions? An Empirical Study Based on DEA," Sustainability, MDPI, vol. 15(7), pages 1-21, March.
    3. Calogero Guccio & Marco Ferdinando Martorana & Isidoro Mazza, 2016. "Efficiency assessment and convergence in teaching and research in Italian public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1063-1094, June.
    4. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2018. "Measuring the inefficiency of Chinese research universities based on a two-stage network DEA model," Journal of Informetrics, Elsevier, vol. 12(1), pages 10-30.
    5. Cui, Yuan & Ren, Xian-tong & He, Xi-jie & Yang, Guo-liang, 2023. "Is human and financial investment in Chinese universities effective?," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    6. Vanesa D’Elia & Gustavo Ferro, 2019. "Empirical Efficiency Measurement in Higher Education: An Overview," CEMA Working Papers: Serie Documentos de Trabajo. 708, Universidad del CEMA.
    7. Chen, Zhuo & Yang, Zhenbing & Yang, Lili, 2020. "How to optimize the allocation of research resources? An empirical study based on output and substitution elasticities of universities in Chinese provincial level," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    8. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).
    9. Berbegal-Mirabent, Jasmina & Gil-Doménech, Dolors & de la Torre, Rocío, 2019. "Dealing with heterogeneity: An analysis of Spanish universities," TEC Empresarial, School of Business, Costa Rica Institute of Technology (ITCR), vol. 13(3), pages 58-77.
    10. 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.
    11. Sabine Gralka & Klaus Wohlrabe & Lutz Bornmann, 2018. "How to Measure Research Efficiency in Higher Education? Research Grants vs. Publication Output," CESifo Working Paper Series 7055, CESifo.
    12. Xi Xiong & Guo-liang Yang & Kai-di Liu & De-qun Zhou, 2022. "A proposed fixed-sum carryovers reallocation DEA approach for social scientific resources of Chinese public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4097-4121, July.
    13. 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).
    14. Yaisawarng, Suthathip & Ng, Ying Chu, 2014. "The impact of higher education reform on research performance of Chinese universities," China Economic Review, Elsevier, vol. 31(C), pages 94-105.
    15. Samira El Gibari & Trinidad Gómez & Francisco Ruiz, 2022. "Combining reference point based composite indicators with data envelopment analysis: application to the assessment of universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4363-4395, August.
    16. Tommaso Agasisti & Guo-liang Yang & Yao-yao Song & Carolyn-Thi Thanh Dung Tran, 2021. "Evaluating the higher education productivity of Chinese and European “elite” universities using a meta-frontier approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5819-5853, July.
    17. 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.
    18. Fu, Tsu-Tan & See, Kok Fong, 2022. "An integrated analysis of quality and productivity growth in China’s and Taiwan’s higher education institutions," Economic Analysis and Policy, Elsevier, vol. 74(C), pages 234-249.
    19. Xianmei Wang & Hanhui Hu, 2017. "Sustainability in Chinese Higher Educational Institutions’ Social Science Research: A Performance Interface toward Efficiency," Sustainability, MDPI, vol. 9(11), pages 1-18, October.
    20. José Manuel Pastor & Lorenzo Serrano, 2016. "The determinants of the research output of universities: specialization, quality and inefficiencies," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1255-1281, November.

    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:gam:jsusta:v:15:y:2023:i:9:p:7418-:d:1136942. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.