Exploring Optimal Pathways for University Fee Management in the Context of Digital Intelligence

DOI: https://doi.org/10.62517/jhet.202515419

Author(s)

Jianrui Rong

Affiliation(s)

Guilin University of Aerospace Technology, Guilin, Guangxi, China

Abstract

With the continuous advancement of technology, big data and artificial intelligence are increasingly permeating daily life and work. The digital transformation of university tuition management is an important component of building smart campuses. This paper, based on the digital transformation context, conducts an in-depth analysis of the current state and existing issues in university tuition management, in the context of digital transformation, explores strategies for optimizing university tuition management pathways, and provides references for universities to build efficient, intelligent, and secure tuition management systems, thereby enhancing the overall level and efficiency of university financial management.

Keywords

Digital Intelligence; University Fee Management; Optimization Path; Financial Security; Tuition Management

References

[1] Leocádio, D., Guedes, L., Oliveira, J., Reis, J., & Melão, N. (2024). Servitization in Digital Age: A Systematic Literature Review. Procedia Computer Science, 232, 2531-2539. [2] Sun, S., De Widt, D. and Andrews, R. (2025), Knowledge Commercialization and University Audit Fees: A UK-Based Study. Financial Acc & Man. https://doi.org/10.1111/faam.12434 [3] O. Ben Rhaiem, M. Amara, R. Zaghdoud, L. Chaari, and M. M. Alshammari, “Blockchain-based System Towards Data Security Against Smart Contract Vulnerabilities: Electronic Toll Collection Context,” international journal of advanced computer science and applications, vol. 15, no. 6, pp. 1524–1538, Jun. 2024. [4] Z. Ma, M. Jiang, H. Gao, and Z. Wang, “Blockchain for digital rights management,” future generation computer systems-the international journal of escience, vol. 89, pp. 746–764, Dec. 2018, doi: 10.1016/j.future.2018.07.029. [5] A. Ahmad, M. Hasan, and M. Ghorbanpour, “Education cost as a new fickle in higher education for students learning via quantitively multinomial logistic regression,” scientific reports, vol. 14, no. 1, Dec. 2024, doi: 10.1038/s41598-024-81074-x. [6] Y. Wu, Y. Zhu, and J. Zhao, “The Propulsion Path of Synergy and Linkage Based on Artificial Intelligence and Digital Economy,” frontiers in psychology, vol. 13, May 2022, doi: 10.3389/fpsyg.2022.854542. [7] L. Zhigong and W. Linjing, “Research on Management of Auxiliary Fees in Residential Areas,” in proceedings of the 2016 international conference on economy, management and education technology, z. Jiang and Y. Xue, Eds., in Advances in Social Science Education and Humanities Research, vol. 62. 2016, pp. 1227–1230. [8] Buckeye, K. R., Berrens, C., & Baker, R. T. (2022). Minnesota Distance-Based Fee Project: Charting a Path Forward. Transportation Research Record, 2677(3), 609-619. https://doi-org.mpu.idm.oclc.org/10.1177/03611981221116371. [9] Monzón, N.S., Jadán-Guerrero, J., Cáceres Mesa, M.L., Andrade, M.V.A. (2021). Digital Transformation of Education: Technology Strengthens Creative Methodological Productions in Master's Programs in Education. In: Russo, D., Ahram, T., Karwowski, W., Di Bucchianico, G., Taiar, R. (eds) Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing, vol 1322. Springer, Cham. https://doi-org.mpu.idm.oclc.org/10.1007/978-3-030-68017-6_98.