نویسنده

استاد دانشکده روانشناسی و علوم تربیتی، دانشگاه تهران

چکیده

به ­منظور مقابله با فشار مالی مضاعفی که از ناحیه رشد چشمگیر تقاضا و کاهش نسبی حمایت‌های مالی دولت بر واحدهای آموزش عالی ایجاد شده، طی سال‌های اخیر به سازوکار تخصیص منابع عملکردمحور با فرض ایجاد انگیزه برای بهبود عملکرد، بسیار توجه شده است. اما مرور نتایج ارزیابی‌های تجربی نشان می‌دهد که در واقعیت تغییرات عملکردی مورد انتظار محقق نشده است. در مطالعه حاضر، با استفاده از روش شبیه‌سازی آماری مبتنی بر شاخص بهره‌وری مالم‌کوئیست و استفاده از هفت مجموعه‌ آماری مختلف، اثربخشی تغییر سازوکارهای تخصیص از نهاده‌محور به ستانده‌محور به‌صورت کاملاً علمی- فنی بازآزمایی شده است. نتایج به ­دست آمده نشان داد که تخصیص منابع نهاده‌محور با ناکارایی زیاد همراه است و بازتوزیع منابع بر مبنای سازوکار ستانده‌محور، کارایی را به سطح مطلوب افزایش و در مقابل، بهره‌وری را کاهش می‌دهد که درمجموع، تناقضی جدّی آشکار می‌شود. برآوردهای مربوط به اجزای شاخص بهره‌وری، یعنی تغییرات کارایی و تغییرات فناوری مؤید آن است که منشأ اصلی کاهش بهره‌وری جابه ­جایی مرز تولید به سمت پایین و تشدید استفاده نشدن از ظرفیت‌های تولید است که سبب می‌شود کارایی به‌صورت تصنعی بالا نشان داده شود. بدین ترتیب، دستاوردهای مطالعه حاضر و نتایج تحقیقات تجربی اخیر مشخص می‌کنند که مفروضات بنیادین سازوکار تخصیص منابع عملکردمحور (ستانده‌محور) با واقعیت‌ها انطباق ندارند و این سازوکار راه حل مؤثری برای بهبود عملکرد و مقابله با کمیابی نیست. از این رو، لازم است سازوکار تخصیص منابع جدید و متفاوتی شناسایی و جایگزین شود.

کلیدواژه‌ها

عنوان مقاله [English]

Performance-Based Resource Allocation in Higher Education: A Black Box Containing the Paradox of Increasing Efficiency and Decreasing Productivity

نویسنده [English]

  • Abolghasem Naderi

Faculty of Psychology and Educational Sciences, Tehran University, Tehran, Iran.

چکیده [English]

To cope with escalating financial resource limitations from both expanding demands for higher education and experiencing a relatively reduction in public support, higher education units have profoundly adopted a performance-based resource allocation mechanism in recent years. Nevertheless, empirical evaluation findings show that the presumed improvement in performance has not been fulfilled. Using seven sets of data and performing statistical simulations based on the Malmquist index, we evaluate the effectiveness of both input-based and performance-based resource allocation mechanisms. The findings show that input-based resource allocation faces massive inefficiency. In contrast, performance-based resource allocation is accompanied by complete efficiency as well as a substantial reduction in productivity. Hence, a critical paradox has emerged. The estimates of the components of the Malmquist index provide essential evidence on the fact that improvements in efficiency due to performance-based resource allocation are artificial rather than real, and productivity shrinks due to underutilization of production capacities. The results highlight the need for finding and adopting a superior resource allocation mechanism.

کلیدواژه‌ها [English]

  • Efficiency
  • productivity
  • Performance-based resource allocation
  • Malmquist Index
  • Higher Education
  • Statistical simulation
1. Amirkhani, T. (2010). A model for initializing performance based budgeting in Iran. (Ph.D. Thesis). University of Alame Tabatabaee (in Persian).
2. Azar, A., Amini, M., & Ahmadi, P. (2013). Performance based budgeting model using fuzzy goal programming approach to manage risk in resource allocation. Management Research in Iran, 17(4), 65-96 (in Persian).
3. Azar, A., Amini, M., & Ahmadi, P. (2014). Applying fuzzy goal programming in university budgeting. Quarterly Journal of Research and Planning in Higher Education, 20(2), 1-24 (in Persian).
4. Azar, A., Mostafaee, K., & Ahmadi, P. (2011). Designing operational budgeting model by combining cognitive mapping technique with hierarchical techniques: The case of Statistical Center of Iran. J. of Planning and Budget, 16(3, Autumn), 3-22 (in Persian).
5. Beasley, J. (1990). Comparing university departments. Omega, 18, 171-183.
6. Beasley, J.E. (2003). Allocating fixed costs and resources via data envelopment analysis. European Journal of Operational Research, 147, 198-216.
7. Bell, E. (2018). Why performance-based funding fails to improve college graduation rates - and how states can do better. Scholars Strategy Network, JULY 5, 2018.
8. Bell, E., Fryar, A., Hillman, N., & Tandberg, D. (2018). When intuition misfires: A meta-analysis of performance-based funding. In: Ellen Hazelkorn, Alexander McCormick, and Hamish Coates (eds.). Research handbook on quality, performance and accountability in higher education. Edward Elgar Publishing.
9. Casper, Ch.A., & Henry, M.S. (2001). Developing performance-oriented models for university resource allocation. Research in Higher Education, 42(3, Jun.), 353-376.
10. Cibulka, J.G. (1987). Theories of education budgeting; Lessons from the management of decline. Educational Administration Quarterly, 23(1, February), 7-40.
11. Crain, W.M., & O’Roark, J.B. (2004). The impact of performance-based budgeting on state fiscal performance. Economics of Governance, 5, 167-186.
12. Dabagh, R., & Javaherian, L. (2016). Productivity of educational and research units at public comprehensive universities in Iran. Quarterly Journal of Research and Planning in Higher Education, 22(2), 99-123 (in Persian).
13. Dougherty, K.J., Sosanya, M.J., Lahr, H., Natow, R.S., Pheatt, L., & Reddy, V. (2014). Performance funding for higher education: Forms, origins, impacts, and futures. The Annals of the American Academy of Political and Social Science, 655(The Role of State Policy in Promoting College Access and Success, September), 163-184.
14. Entezari, Y., & Mahjoob, H. (2013). Choosing appropriate allocation mechanism and approach for allocating public funds to higher education. Quarterly Journal of Research and Planning in Higher Education, 68, 49-69 (in Persian).
15. Ezati, M., & Naderi, A. (2009). Impact of financial resource allocation mechanisms on performance of academic departments: The case of Tehran University. Quarterly Journal of Research and Planning in Higher Education, 15(2), 23-54 (in Persian).
16. Făre, R., Grosskopf, S., Lindgren, B., & Roos, P. (1992). Productivity changes in Swedish Pharamacies 1980-1989: A non-parametric malmquist approach. Journal of Productivity Analysis, 3, 85-101.
17. Guedes, E.E., Freitas, G.M., Avellar, J.V.G., & Milioni, A.Z. (2009). On the allocation of new inputs and outputs with DEA. Engevista, 11, 4-7.
18. Hillman, N. (2016). Why performance-based college funding doesn’t work. The Century Foundation. MAY 25, 2016.
19. Hillman, N., & Corral, D. (2018). The equity implications of paying for performance in higher education. American Behavioral Scientist, 61(14), 1757–1772.
20. Hillman, N.W., Fryar, A.H., & Crespin-Trujillo, V. (2018). Evaluating the impact of performance funding in Ohio and Tennessee. American Educational Research Journal, 55(1), 144-170.
21. Jonkers, K., & Zacharewicz, T. (2016). Research performance based funding systems: A comparative assessment; EUR 27837 EN; Report No JRC101043 EU.
22. Kaikkonen, D. (2016). Shifting from enrollment-to performance-based funding in higher education what can we learn from Washington's experience. Education Finance and Policy, 11(4, Fall), 482-498.
23. Kao, Ch., & Hung, H.T. (2008). Efficiency analysis of university departments: An empirical study. Omega, 36, 653 - 664.
24. Khaleghi Sorush, F., Abolghasemi, M., Geraeenejad, G., & Develoo, M. (2017). Designing a higher education resources allocation model for Iran. J. of Financial Economics, 11(34), 147-170 (in Persian).
25. Kong, D. (2005). Performance-based budgeting: The U.S. experience. Public Organization Review: A Global Journal, (5), 91-107.
26. Kordbache, M. (2006). Performance based budgeting. Plan and Budget Bulletin, 101, 3-31, (in Persian).
27. Korhonen, P., & Syrjänen, M. (2004). Resource allocation based on efficiency analysis. Management Science, 50(8, Aug.), 1134-1144.
28. Liefner, I. (2003). Funding, resource allocation, and performance in higher education systems. Higher Education, 46, 469-489.
29. Naderi, A. (2003). Multilevel models and evaluating inequality and efficiency in budget among selective universities. Quarterly Journal of Research and Planning in Higher Education, 9(4), 1-42 (in Persian).
30. Naderi, A. (2015). Education finance. Tehran: University of Tehran Press (in Persian).
31. Naderi, A. (2017). Measuring Malmquist productivity index of university units using multilevel approach. Research Project Report. University of Tehran (in Persian).
32. Naderi, A. (2018). Evaluating the efficiency of resource allocation at selective universities using multilevel approach. Mimeo (in Persian).
33. Naderi, A., Kharazi, K., Entezari, Y., & Majoob, H. (2013). Resource allocation mechanism in higher education. J. of Human Resources Studies, 10(Winter), 91-120 (in Persian).
34. OECD (2010). Performance-based funding for public research in tertiary education institutions: Workshop proceedings. OECD Publishing.
35. Rasuli, M. (2010). Feasibility of implementing result based budgeting: The case of public universities in Iran. (MA Dissertation). Tarbiyat Modares University (in Persian).
36. Salmi, J., & Hauptman, A.M. (2006). Resource allocation mechanisms in tertiary education: A typology and an assessment. In: Higher Education in the World 2006.
37. Wang, D.D. (2019). Performance-based resource allocation for higher education institutions in China. Socio-Economic Planning Sciences, 65, 66-75.