Policy Evolution of Government Procurement of Public Services in China: A Text-Mining Perspective
Dongdan Zhu,
Yuting Zhang,
Zhengnan Lu and
Guilherme Ferraz de Arruda
Complexity, 2023, vol. 2023, 1-15
Abstract:
The in-depth mining of policy text of Government Procurement of Public Services (GPPS) is helpful to distinguish stage characteristics and evolution logic of the policy. Through text-mining technology, the current research analyzes the policy text of GPPS from 1995 to 2021 in China. Firstly, the GPPS policy is divided into three stages according to the key policy nodes. Secondly, the TF-IDF algorithm is adopted to obtain keywords at each stage, and the static stage characteristics are summarized by constructing the complex network of the extracted keywords. Finally, the policy is clustered into several categories with the help of K-means cluster analysis, and the characteristic of each category is achieved through secondary word segmentation, so as to figure out the dynamic evolution logic of each policy category at divided stages. Results show that the development of the GPPS policy in China presents a point-to-face change feature, manifested in the evolution logic of “government purchase—government procurement of public service—all-round supporting policy.†And policy priorities at different stages, namely, policy tools, will change according to the development of economy and variation of demands.
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/complexity/2023/3139117.pdf (application/pdf)
http://downloads.hindawi.com/journals/complexity/2023/3139117.xml (application/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:3139117
DOI: 10.1155/2023/3139117
Access Statistics for this article
More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().