Research on the Improvement of China’s Public Service Quality Management Level Based on the Background of Big Data
- DOI
- 10.2991/978-94-6463-016-9_6How to use a DOI?
- Keywords
- Big data; quality management of public service; service-oriented government
- Abstract
As socialism with Chinese characteristics has entered a new era and the economy and society has entered a stage of high-quality development, around adhering to the people-centered development idea, it is necessary to propose a public service quality management proposition that better meets the people’s growing demand for public services [1]. Therefore, through literature analysis and measurable analysis methods, this paper uses public service quality monitoring technology and compares the background and content of public service quality improvement at home and abroad, and then explores the development bottleneck existing in the process of improving public service quality management in China. This paper proposes countermeasures and suggestions to improve the quality management level of China’s public services, so as to achieve high-quality development of China’s public services.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiuhua Shi AU - Qiong Wu PY - 2022 DA - 2022/12/07 TI - Research on the Improvement of China’s Public Service Quality Management Level Based on the Background of Big Data BT - Proceedings of the 2022 2nd International Conference on Public Management and Intelligent Society (PMIS 2022) PB - Atlantis Press SP - 38 EP - 45 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-016-9_6 DO - 10.2991/978-94-6463-016-9_6 ID - Shi2022 ER -