Research on the evaluation of China’s provincial public data policies based on the PMC index model

Tang, Qiong; Chen, Xiying

Permalink

https://hdl.handle.net/2142/132981 Copy

Description

Title

Research on the evaluation of China’s provincial public data policies based on the PMC index model

Author(s)

• Tang, Qiong
• Chen, Xiying

Issue Date

2026-03-12

Keyword(s)

• Public open data
• Open data policies
• Policy modeling consistency index

Abstract

Introduction. This paper aims to evaluate provincial-level policies on the development and utilization of public data in China, assess the effectiveness of policy formulation, and explore their weaknesses, so as to provide a basis for optimizing policy design and enhance the effectiveness of policy implementation. Method. This study constructs a PMC index model with 9 primary variables and 49 secondary variables. A multi-input-output table is created to track the performance of various policies. Ten representative policies are selected for empirical analysis, with PMC index calculations and evaluation grading performed. PMC surface plots are constructed. Results. The 10 policy samples selected for this study achieved an average PMC Index score of 6.26, demonstrating overall good performance in terms of timeliness, coverage, and targeting. The score distribution showed that three policies received an Excellent rating, five received a Good rating, and two received a Pass rating. Conclusion(s). The study found that the 10 sample policies require improvement primarily in policy instruments, policy timeliness, policy content, and policy targets. Consequently, the study proposes recommendations for optimizing policy formulation and adjustments, focusing on four key areas: enhancing short-term policy adjustments, expanding the types of policy instruments, broadening policy content, and encouraging deeper enterprise participation.

Publisher

iSchools

Series/Report Name or Number

iConference 2026 Proceedings

Type of Resource

Other

Genre of Resource

Conference Poster

Language

eng

Permalink

https://hdl.handle.net/2142/132981

Copyright and License Information

Copyright 2026 is held by Qiong Tang and Xiying Chen. Copyright permissions, when appropriate, must be obtained directly from the authors.

Owning Collections