Evaluation of Digital Transformation in Chinese Government from Data Mining Perspective

DOI

10.2991/978-94-6463-064-0_15How to use a DOI?

Keywords

Digital transformation; Clustering; Data mining

Abstract

Currently, science and technology are changing rapidly, digitalization and intelligence are developing deeply, profoundly affecting economic development trends and social operation laws, and the digital era is coming. Governments around China are in full swing in the process of digital transformation of government. However, few studies have been conducted to evaluate the results of digital transformation of local governments. In order to solve the above problems and gain practical insights about the digital transformation of governments, this paper firstly constructs a government digital transformation evaluation system containing six evaluation indicators. Second, this paper uses a clustering algorithm called K-Means++ to evaluate the digital transformation outcomes of 31 provincial local governments in China. Based on the panel data obtained in 2020, we find that the optimal number of clusters is 4 (the silhouette coefficient is 0.372). This results in four levels of government digital transformation evaluation: high, medium-high, medium-low, and low. The results of this paper provide meaningful theoretical insights for local governments at all levels to enact digital transformation policies and develop relevant government strategies.

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.

Download article (PDF)

TY  - CONF
AU  - Ping Lan
PY  - 2022
DA  - 2022/12/27
TI  - Evaluation of Digital Transformation in Chinese Government from Data Mining Perspective
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 134
EP  - 144
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_15
DO  - 10.2991/978-94-6463-064-0_15
ID  - Lan2022
ER  -