The allocation of PhD enrolment quotas in China’s research-oriented universities based on equity and efficiency principles

ABSTRACT

PhD enrolment quota allocation proves the key concern for China’s universities to promote institutional reform and improve research level, and it is often characterized by the zero sum game among schools within a university. Therefore, this article develops a new indicator system for PhD enrolment quota allocation and efficiency evaluation in China, and then it reallocates the quotas considering the preferences of decision-makers and the efficiency based on the historical data during 2011–2015 in a research-oriented university in China. The results indicate that, first, the preferences of decision-makers in the university for article publications and research funds may significantly affect the allocation of PhD enrolment quotas among schools. Second, when the linear combination weighting method is used, the overall efficiency for PhD enrolment allocation proves the highest, among various weighting methods concerned. Finally, to improve the overall efficiency of the 19 schools, five social science schools and four engineering schools have to cut their PhD enrolment quotas; among them, three engineering schools should reduce the largest redundant quotas sharply. The methods and results in this article are conducive to the allocation of education resources which have the zero sum feature and are often accompanied with undesirable outputs.

KEYWORDS:

• Research-oriented university
• PhD enrolment quota
• education resource allocation
• zero sum gains data envelopment analysis (ZSG-DEA)

JEL CLASSIFICATION:

• I21
• D81
• A23

Acknowledgements

This work is supported by National Natural Science Foundation of China (no. 71704050), Education Science Planning Fund of Hunan Province of China (no. XJK016BGD01), Natural Science Foundation of Hunan Province of China, Humanities and Social Science Fund of Ministry of Education in China (no. 16YJC880117) and Postgraduate Education and Teaching Cultivation Project of Beijing Institute of Technology (no. 2017G-26).

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ http://news.xinhuanet.com/politics/2013-01/06/c_114269977.htm.

² On 24 October 2015, Chinese State Council issued the ‘Overall Plan for Promoting the Development of World-class Universities and First-class Disciplines’, which requires the establishment of a batch of first-class universities and disciplines in the world by the middle of this century, thus becoming a powerful nation in the global higher education system.

³ According to the definition of weakly disposable undesirable output, if the undesirable output is reduced, the desirable output must also be reduced. This method is widely used, but it does not conform to the actual situation of this article, because reducing the H33 cannot lead to the reduction of H1 and H2 in Table 1.

⁴ The ‘985 project’ was proposed by the central government of China in May 1998, which means the union of China’s top research-oriented universities and plays the dominant role in academic research and scientific innovation in China’s higher education system. In 2017, the ‘985 project’ was updated into the Double World-Class Project.

⁵ As for the indicator of invention patent mentioned by a reviewer, we have made a survey in several ‘985 project’ universities and find that none of them consider this indicator when the PhD enrolment quotas are allocated. The historic data show that in the case university we discussed in this article, among the 19 schools, only 9 schools have invention patents, while 8 schools are closely related with social science and have no outputs of invention patents, and other two schools are School of Architecture and College of Mathematics and Econometrics, which also have no invention patents. Under this circumstance, if the indicator of invention patents is considered, many schools will get the value of zero for this indicator, which is not appropriate and not fair for the allocation and efficiency evaluation. Even so, we also collected the data of invention patent numbers of all schools in the case university during 2011–2015 and re-calculated the results. We found that the central results still hold although the exact numbers have some small changes. The detailed results can be obtained upon request from the authors.

⁶ The reviewers also suggest the indicator of PhD dropout for the undesired output. We made a survey for this and found that as a common phenomenon in China’s top research-oriented universities, almost there were no PhD dropouts during their normal study period (such as four years or five years) and those PhD candidates who drop out ultimately would be deferred for graduation more than for two years (usually deferred for at most four or five years); in other words, the indicator of H₃₃ has covered these PhD dropouts.

⁷ The university makes a list and up to three key Chinese academic journals are selected for different disciplines, including philosophy, education, politics, law, sociology, theoretical economics, applied economics, management science, business administration, public management, information science, mathematics, physics, chemistry, optical engineering, mechanical engineering, material engineering, computer science, electrical engineering, electronic science, communication engineering, civil engineering, architecture and environmental science.

⁸ The Graduate School in the university is responsible for the allocation of PhD enrolment quotas among academic schools.

⁹ In fact, this view is also well recognized in other countries or regions, such as Romania (Bucur, Kifor, and Mărginean 2016) and Taiwan (Chou and Chan 2016).

¹⁰ We also set it as 1.5 times larger, and the central results do not change significantly.

¹¹ If they are the Low indicators, which are unfavourable to PhD enrolment quota allocations when their values are bigger, they can be normalized as follows.

$s_{ij}=\frac{max\left\{{s_{ij}}^{\prime }\right\}-{s_{ij}}^{\prime }}{max\left\{{s_{ij}}^{\prime }\right\}-min\left\{{s_{ij}}^{\prime }\right\}}\left(i=1,2,\dots ,19;j=1,2,3\right)$

.

¹² If they are the low indicators, which are unfavourable to PhD enrolment quota allocations when their values are bigger, they can be normalized as follows:

$s_{ij}=\frac{max\left\{{s_{ij}}^{\prime }\right\}-{s_{ij}}^{\prime }}{max\left\{{s_{ij}}^{\prime }\right\}-min\left\{{s_{ij}}^{\prime }\right\}}\left(i=1,2,\dots ,19;j=1,2,3\right)$

.

¹³ Generally speaking, when the MAPE value exceeds 10%, we can say that the difference is significant.

¹⁴ These five schools are the College of Civil Engineering, College of Mechanical and Vehicle Engineering, College of Electrical and Information Engineering, College of Chemistry and Chemical Engineering and School of Economy and Trade, respectively.

Additional information

Funding

This work is supported by National Natural Science Foundation of China (no. 71704050), Education Science Planning Fund of Hunan Province of China (no. XJK016BGD01), Natural Science Foundation of Hunan Province of China, Humanities and Social Science Fund of Ministry of Education in China (no. 16YJC880117) and Postgraduate Education and Teaching Cultivation Project of Beijing Institute of Technology (no. 2017G-26).