Evaluation of Digital Transformation in Chinese Government from Data Mining Perspective
- 10.2991/978-94-6463-064-0_15How to use a DOI?
- Digital transformation; Clustering; Data mining
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.
- © 2023 The Author(s)
- Open Access
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Cite this article
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 -