Regression Analysis of the Job Burnout of Street-Level Bureaucracy under the Background of Applied Statistics

DOI

10.2991/978-94-6463-042-8_190How to use a DOI?

Keywords

Applied statistics; Regression analysis; Street-level bureaucracy; Job burnout; Occupational stress

Abstract

With the continuous improvement of the efficiency and effect of big data on grassroots government participation in social governance, government digitization has become an important measure to improve the government's grassroots social governance ability. The purpose of this paper is to explore the causes of job burnout of grassroots government personnel under the background of digital government and to explore the relationship and influence mechanism between job burnout and job tension of grassroots government personnel based on a regression analysis model. Using the OSI-R scale and the MBI-HSS scale, it is found that the heavy work task of street-level bureaucracy will significantly impact the emotional exhaustion of job burnout, and the task ambiguity will also have a significant impact on the emotional exhaustion of job burnout. In addition, role stress plays an intermediary role in the relationship between occupational stress and job burnout of street-level bureaucracy. Therefore, the grassroots government should be aware of street-level bureaucracy's social and psychological needs, reasonably set up posts and personnel arrangements, reduce the burden of heavy government work for street-level bureaucracy, and implement a sustainable digital government personnel resource management scheme.

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.

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TY  - CONF
AU  - Wei Geng
AU  - Kaiqiao Yang
AU  - He Wang
PY  - 2022
DA  - 2022/12/29
TI  - Regression Analysis of the Job Burnout of Street-Level Bureaucracy under the Background of Applied Statistics
BT  - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)
PB  - Atlantis Press
SP  - 1316
EP  - 1320
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-042-8_190
DO  - 10.2991/978-94-6463-042-8_190
ID  - Geng2022
ER  -