Evaluation of Resource Allocation Efficiency in Innovation and Entrepreneurship Education at Undergraduate Institutions in Jiangsu Province
DOI: https://doi.org/10.62517/jhet.202615507
Author(s)
Fei Shi1, Fei Xia2,*, Yan Gong1, Quan Li1, Huimin Zhang3, Yifei Cheng1
Affiliation(s)
1School of Civil Engineering and Architecture, Suqian University, Suqian, Jiangsu, China
2School of Innovation and Entrepreneurship, Suqian University, Suqian, Jiangsu, China
3School of Biological and Materials Engineering, Suqian University, Suqian, Jiangsu, China
*Corresponding Author
Abstract
Improving the efficiency with which universities allocate resources to innovation and entrepreneurship education is central to converting expanded investment into educational outcomes. Drawing on an input-output framework, this study develops an evaluation system and examines 31 undergraduate institutions in Jiangsu Province. An input-oriented BCC model and a super-efficiency BCC model measure static efficiency in 2025, while the Malmquist index tracks productivity change between 2024 and 2025. The geometric mean of the 2025 super-efficiency scores is 1.174; 28 institutions are on or above the efficiency frontier, yet 64.5% operate under decreasing returns to scale, indicating a mismatch between resource input and output growth. Differences within institutional categories are more pronounced than differences between categories, and static efficiency does not form a stable north-central-south gradient. Total factor productivity increases by 4.1%, driven mainly by improved management and resource utilisation. Growth is faster in Southern Jiangsu, moderate in Central Jiangsu, and nearly flat in Northern Jiangsu. The findings support five policy directions: scale adjustment, resource coordination, pedagogical innovation, differentiated strategies, and dynamic feedback.
Keywords
Undergraduate Institutions; Innovation and Entrepreneurship Education; Resource Allocation Efficiency; Policy Implications; Jiangsu Province
References
[1] Wang, Z. R. The evolution and development trends of entrepreneurship education in China. Journal of East China Normal University (Educational Sciences), 2016, 34(2), 30-38.
[2] Hu, L. F., Ren, X. X. Evolution and development of research themes in innovation and entrepreneurship education: A bibliometric analysis of CSSCI journal literature from 1999 to 2025. Journal of Henan University (Social Science), 2025, 65(4), 108-114+155-156.
[3] Hanushek, E. A. The economics of schooling: Production and efficiency in public schools. Journal of Economic Literature, 1986, 24(3), 1141-1177.
[4] Charnes, A., Cooper, W. W., Rhodes, E. Measuring the efficiency of decision making units. European Journal of Operational Research, 1978, 2(6), 429-444.
[5] Banker, R. D., Charnes, A., Cooper, W. W. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 1984, 30(9), 1078-1092.
[6] Andersen, P., Petersen, N. C. A procedure for ranking efficient units in data envelopment analysis. Management Science, 1993, 39(10), 1261-1264.
[7] Parteka, A., Wolszczak-Derlacz, J. Dynamics of productivity in higher education: Cross-European evidence based on bootstrapped Malmquist indices. Journal of Productivity Analysis, 2013, 40(1), 67-82.
[8] Lin, Z. Y. A preliminary study of the economic efficiency of higher education. Journal of Anhui Normal University (Philosophy and Social Sciences), 1983, (4), 30-35.
[9] Chen, T., Bai, J. Y. Evaluation of the relative effectiveness of higher education inputs and outputs in Western China. Journal of Northwest A&F University (Social Science Edition), 2003, (2), 102-105.
[10] Liu, R. Z., Ma, Y. H. The status and trends of industry-education integration in professional postgraduate education: An empirical analysis based on the DEA-Malmquist index. China Education of Light Industry, 2024, 27(6), 32-40.
[11] Zhang, H. Q. Efficiency and determinants of human capital investment in higher education in western ethnic regions: Evidence from a DEA-Malmquist-Tobit model. Higher Education of Sciences, 2025, (2), 62-73.
[12] Guan, Y. G. Analysis of resource allocation efficiency in higher education based on a super-efficiency DEA model. Heilongjiang Researches on Higher Education, 2019, 37(2), 84-88.
[13] Li, A. L., Deng, X. B., Hu, Y. M. Efficiency of innovation and entrepreneurship education in undergraduate institutions in Central and Western China: Evidence from 15 universities in Hunan Province. Journal of Hunan Agricultural University (Social Sciences), 2018, 19(3), 98-102.
[14] Jiang, Y. C., Liu, S. Y., Hong, Y. G. Regional disparities in higher education resource allocation efficiency from the perspective of industrial labour productivity growth. Research in Educational Development, 2020, 40(11), 76-84.
[15] Song, X. D. Evaluation of resource allocation efficiency in university innovation and entrepreneurship education: Evidence from Jiangxi Province. Journal of Hubei Adult Education Institute, 2022, 28(6), 10-15, 31.
[16] You, L., Kong, Q. P. Evaluation and determinants of higher education resource allocation efficiency under the Double First-Class initiative: A super-efficiency DEA-Malmquist and Tobit analysis. Education & Economy, 2021, 37(6), 30-37.
[17] Xu, L. L. Evaluation of resource allocation efficiency in university scientific and technological innovation using relational network DEA. Shanxi Science and Technology, 2019, 34(1), 25-28.
[18] Xia, F., Shi, F., Gao, Y. Evaluation of resource allocation efficiency in innovation and entrepreneurship education at the school level: A case study of University S. Journal of Heilongjiang Vocational Institute of Ecological Engineering, 2026, 39(1), 89-94.
[19] Leontief, W. W. Quantitative input and output relations in the economic systems of the United States. The Review of Economics and Statistics, 1936, 18(3), 105-125.
[20] Wang, S. T., Liang, H., Zhao, Z. Q. Efficiency of knowledge production in philosophy and social sciences at universities and disciplinary differences: Evidence from a DEA-Malmquist index model. Hubei Social Sciences, 2026, (2), 99-110.