<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>At present, due to the limitations of technology and resources, the comprehensive budget management generally has problems such as imperfect foundation of establishment, weak binding force of execution, and lack of performance appraisal system. These problems become more prominent in the context of the era of big data. The use of big data technology, such as large capacity, real-time control, intelligent Settings and other characteristics, will be able to improve the current many problems. Therefore, this paper focuses on how to combine big data with comprehensive budget management. This paper holds that it is not enough for comprehensive budget management to stay in the current stage, but also need to use big data technology, which is a higher level of information stage. Therefore, this paper adopts the method of double subordination fuzzy support vector machine to study the effect of budget management of scientific research projects in Chinese universities. Based on the construction of comprehensive budget management performance evaluation index system throughout the whole process of college budget cycle, taking S university as an example, this paper analyzes the performance of comprehensive budget management in S university, and points out that big data can optimize and innovate the budget management mode, which has great significance for college budget management.</p>
</abstract>

At present, due to the limitations of technology and resources, the comprehensive budget management generally has problems such as imperfect foundation of establishment, weak binding force of execution, and lack of performance appraisal system. These problems become more prominent in the context of the era of big data. The use of big data technology, such as large capacity, real-time control, intelligent Settings and other characteristics, will be able to improve the current many problems. Therefore, this paper focuses on how to combine big data with comprehensive budget management. This paper holds that it is not enough for comprehensive budget management to stay in the current stage, but also need to use big data technology, which is a higher level of information stage. Therefore, this paper adopts the method of double subordination fuzzy support vector machine to study the effect of budget management of scientific research projects in Chinese universities. Based on the construction of comprehensive budget management performance evaluation index system throughout the whole process of college budget cycle, taking S university as an example, this paper analyzes the performance of comprehensive budget management in S university, and points out that big data can optimize and innovate the budget management mode, which has great significance for college budget management.

Research on performance evaluation and optimization of college budget management under the background of big data

Shandong Youth University of Political Science

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

At present, due to the limitations of technology and resources, the comprehensive budget management generally has problems such as imperfect foundation of...

Research on performance evaluation and optimization of college budget management under the background of big data

Online veröffentlicht: 02. Juni 2023

Seitenbereich: -

Eingereicht: 06. Mai 2022

Akzeptiert: 13. Okt. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00157

Schlüsselwörter
Big data, Colleges and universities, Budget management, Performance evaluation, Support vector machine method

© 2023 Wei Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on performance evaluation and optimization of college budget management under the background of big data

Online veröffentlicht: 02. Juni 2023

Seitenbereich: -

Eingereicht: 06. Mai 2022

Akzeptiert: 13. Okt. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00157

SchlüsselwörterBig data, Colleges and universities, Budget management, Performance evaluation, Support vector machine method

© 2023 Wei Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Big data, Colleges and universities, Budget management, Performance evaluation, Support vector machine method