The Multidimensional Quantitative Evaluation of Local Policies for Promoting the Development of New Quality Productive Forces: Based on the "Theme-Tool-Effectiveness" Framework

Authors

• Jing PAN, 1.School of Foreign Languages, Changsha Social Work College, Changsha 410004 2.School of Educational Science, Hunan Normal University, Changsha 410081
• Hongjun YI, School of Foreign Languages, Changsha Social Work College, Changsha 410004
• Yu LU, School of Business, Hunan Women's University, Changsha 410004

Keywords

new quality productive forces; local policy texts; theme-tool-effectiveness; multidimensional quantitative evaluation; LDA topic model; poliey tools; PMC index model

Abstract

[Purpose/significance] The development of new quality productive forces is a crucial strategic goal for national progress, with local policies serving as important conduits for conveying and implementing national strategies. Researching local policies that promote the development of new quality productive forces is significant for the implementation of the national strategy in different regions and for further policy evaluation.

[Method/process] By constructing a theme-tool-effectiveness analysis framework and employing LDA topic model, policy tools, and PMC index model, this study conducts a multidimensional quantitative evaluation of local policy texts related to the development of new quality productive forces.

[Result/conclusion] The study finds that the distribution of policy quantity follows the trend of East China > Central China > South China > North China/Southwest China > Northeast China > Northwest China. Policy themes comprehensively reflect the main actions of local governments in promoting new quality productive forces, with East China primarily supporting specialized and innovative small and medium-sized enterprises, while Central China focuses on supporting industrial transformation and upgrading. Across the seven major regions, there is a general tendency to use environmental policy tools more than supply-side and demand-side policy tools. The average PMC index for policy effectiveness is above good, with East China having the highest overall PMC score. However, certain issues merit attention: there are significant differences in the use of policy tools across themes, and there is an imbalance between internal and external use of policy tools. Policy effectiveness is still relatively weak in terms of policy content, policy areas, policy targets, and localization. It is recommended that local strengthen the diversity of policy themes, governments enhance the balance of policy tools and improve the comprehensiveness of policy effectiveness during policy formulation.

First Page

111

Last Page

121

Submission Date

February 2025

Revision Date

March 2025

Acceptance Date

April 2025

Publication Date

October 2025

Digital Object Identifier (DOI)

ꎺ 10.19809/j.cnki.kjqbyj.2025.04.011

Recommended Citation

PAN, Jing; YI, Hongjun; and LU, Yu (2025) "The Multidimensional Quantitative Evaluation of Local Policies for Promoting the Development of New Quality Productive Forces: Based on the "Theme-Tool-Effectiveness" Framework," Journal of Scientific Information Research: Vol. 7: Iss. 4, Article 11.
DOI: ꎺ 10.19809/j.cnki.kjqbyj.2025.04.011
Available at: https://eng.kjqbyj.com/journal/vol7/iss4/11

Reference

[1] 金碚. 论“新质生产力”的国家方略政策取向[J]. 北京工业大学学报 (社会科学版), 2024, 24 (2): 1-8.
[2] 宋潇, 钟易霖, 张龙鹏, 等．推动基础研究发展的地方政策研究: 基于路径—工具—评价框架的PMC分析[J]．科学学与科学技术管理, 2021, 42 (12): 79-98.
[3] 计金标, 李震. 税收政策推动新质生产力发展: 基于技术创新视角[J]. 税务研究, 2024 (11): 106-111.
[4] 李建森, 冯一鸣. 构建促进新质生产力发展的高水平开放体制机制: 理论逻辑与核心维度[J]. 当代经济研究, 2024 (11): 5-16.
[5] 李晓天, 庄雷. 绿色金融赋能新质生产力发展的路径创新与监管策略[J]. 南京社会科学, 2024 (11): 37-46.
[6] 李存芳, 庄甲荣, 王文虎, 等. 绿色信贷政策对资源型企业新质生产力形成的系统效应[J]. 资源科学, 2024, 46 (10): 1930-1943.
[7] 尹聪慧, 纪佳敏, 严飞. 构建动态演化的颠覆性技术政策保护空间: 以2001—2023年新能源汽车政策扶持实践为例[J]. 中国软科学, 2024 (12): 154-163.
[8] 王小林, 金冉. 未来产业: 政策扩散与路径选择[J]. 社会科学战线, 2024 (5): 63-75, 294.
[9] 宋雨薇, 汪雨鑫, 刘纪达, 等. 军民科技政策的供给与协调: 基于“工具—对象—目标”框架的政策文本量化研究[J/OL]. 世界科技研究与发展, 2025: 1-16[2025-03-11]. https://doi.org/10.16507/j.issn.1006-6055.2024.12.007
[10] 张涛, 张博雅, 马海群. 我国央地政府数据安全政策扩散特征及主题转移研究[J/OL]. 情报理论与实践, 2024: 1-13[2024-12-31]. https://link.cnki.net/urlid/11.1762.G3.
20241231. 0833. 002.
[11] 翟燕霞, 石培华. 文旅融合政策结构体系、演进规律及话语生成机制: 基于1993—2024年政策文本的扎根分析[J]. 云南民族大学学报 (哲学社会科学版), 2024, 41 (5): 45-53.
[12] 张亚明, 赵科, 宋雯婕, 等. 区域科技成果转化政策工具的配置与优化分析: 基于河北省的政策文本计量[J]. 软科学, 2024, 38 (1): 23-30.
[13] 胡峰, 李加陈, 翟婧. 政策文本计量视角下科技人才政策分析与评价: 基于“工具—效力”的二维框架[J]. 情报科学, 2024, 42 (6): 99-112.
[14] 何代欣, 郑淼云, 周赟媞, 等. 充实完善因地制宜发展新质生产力的税收政策工具箱[J]. 国际税收, 2025 (1): 14-28.
[15] 廖恒, 魏海玉, 肖艺璇, 等. 新质生产力的形成机制与金融政策优化[J]. 财经科学, 2024 (6): 77-86.
[16] 凌永辉, 刘志彪, 孙瑞东. 因地制宜发展新质生产力的产业政策转型研究: 以江苏为例[J]. 苏州大学学报 (哲学社会科学版), 2025, 46 (1): 33-43.
[17] 王明姬, 查梓琰. 发展新质生产力的人才政策[J]. 宏观经济管理, 2024 (9): 62-67, 76.
[18] ROTHWELL R. Reindustrialization and technology: Towards a national policy framework[J]. Science and Public Policy, 1985, 12: 113-130.
[19] 赵需要, 姬祥飞, 张杰妮. 政策工具视角下数据要素市场政策文本的结构特征与优化路径[J]. 信息资源管理学报, 2024, 14 (6): 73-84.
[20] 蒋祖存, 徐双敏. 中国数字政府建设的政策工具选择与策略优化[J]. 学术论坛, 2024, 47 (6): 134-145.
[21] 杨佳雯, 赵志耘, 高芳, 等. 基于文本量化分析的中国省级人工智能政策布局研究[J]. 现代情报, 2022, 42 (7): 125-135.
[22] 任越, 李泊泳, 谭科铭. 基于“主题—工具—效力”三维框架的我国传统村落保护政策研究[J/OL]. 情报科学: 1-31[2024-10-24]. http://kns.cnki.net/kcms/detail/22.1264.G2.20241023.1729.012.html.
[23] 谭淋露, 董馨妮, 熊兴旺, 等. 政策工具视角下中国省属科研院所改革发展政策文本研究: 以江西省为例[J]. 科技管理研究, 2024, 44 (23): 28-37.
[24] 刘泽,邵波. 政策工具视角下我国文献信息资源保障政策文本量化研究[J]. 图书情报工作, 2024, 68 (20): 26-36.
[25] ESTRADA M A R. Policy modeling: Definition, classification and evaluation[J]. Journal of Policy Modeling, 2011, 33 (4): 523-536.
[26] ESTRADA M A R, Donghyun Park. The past, present and future of policy modeling[J]. Journal of Policy Modeling, 2018, 40: 1-15.
[27] 吴松强, 王鹏程, 马硕, 等. 新发展格局下中国集成电路产业政策的特征挖掘与量化评价研究[J]. 科技管理研究, 2024, 44 (16): 1-13.
[28] 钱小龙, 朱家莹, 黄蓓蓓. 基于PMC指数模型的“十四五”基础教育数字化转型政策评价: 以江浙沪地区为例[J]. 远程教育杂志, 2024, 42 (1): 50-60.
[29] 张倩, 马海群, 牛晓宏. 基于PMC指数模型的我国数据安全政策评价研究[J]. 现代情报, 2024, 44 (8): 13-27, 136.
[30] 张永安, 郄海拓. “大众创业、万众创新”政策量化评价研究: 以2017年10项双创政策情报为例[J]. 情报杂志, 2018, 37 (3): 158-164, 186.
[31] 王思, 张洪铭. 基于PMC指数模型的我国大模型产业政策文本量化研究[J/OL]. 情报科学, 2024: 1-20[2024-10-24]. https://link.cnki.net/urlid/22.1264.G2.20241023.1931.018.
[32] 张少峰, 陈昕, 魏玖长. 中国高质量发展政策评价研究: 基于政策文本的量化分析[J]. 华东经济管理, 2024, 38 (9): 61-72.
[33] 杜宝贵, 张芳祯. 职务科技成果赋权改革试点政策的量化评价[J]. 科技管理研究, 2024, 44 (18): 19-27.
[34] 杨瑾, 罗笑月. 装备制造业颠覆性创新生态系统构建政策评价研究[J]. 软科学, 2024, 38 (6): 67-74.