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.

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