Evaluation of China's High-Advanced Industrial Policy: A PMC Index Model Approach

5Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

High-advanced industries upgraded by digital empowerment have gradually become an important support industry. Therefore, various provinces in China have issued relevant policies to support the prosperous of the digital economy and high-advanced industries. The collection and analysis of high-advanced industrial policy help to scientifically evaluate industrial policies and formulate scientific policy optimization paths. Based on a total of 168 high-advanced industrial policy documents from 26 cities in the Yangtze River Delta region from 2009-2021, this study adopts the PMC-Index model to evaluate the high-advanced industry policies in the digitalization context quantitatively. 12 representative high-advanced industry policy texts were selected for specific analysis. In addition, this study visualizes the measurement results of the internal structure and policy effectiveness of policies by PMC-Surface diagrams and then concludes that the design of high-advanced industry policies was relatively reasonable overall, with 11 policies rated as "Good Consistency"and only one "Acceptable Consistency."The sample policies lack reasonable arrangements for different period plans, lack incentives, or have relatively single incentives. The policy influence among cities in the Yangtze River Delta urban agglomerations is small, and the integration trend is not apparent. There is a particular gap in the scores between Shanghai, Zhejiang, Jiangsu, and Anhui province. This study provides references and suggestions for formulating and revising high-advanced industrial policies.

Cite

CITATION STYLE

APA

Tian, Y., Zhang, K., Hong, J., & Meng, F. (2022). Evaluation of China’s High-Advanced Industrial Policy: A PMC Index Model Approach. Mathematical Problems in Engineering, 2022. https://doi.org/10.1155/2022/9963611

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free