Based on Text Mining and Analysis of Beijing’s Achievement Transformation Policy Research

DOI

10.2991/978-94-6463-368-9_56How to use a DOI?

Keywords

technology transfer policies; text mining; word frequency analysis; semantic network analysis

Abstract

This study utilizes text mining to analyze Beijing’s technology transfer policies from 2006–2023. Frequency and semantic network analysis provide an in-depth investigation of the regional policy landscape.

The study found frequent keywords like innovation, development, enterprise, reflecting policies aim to support enterprise innovation. Network shows continuous promotion across financial support, tax incentives, IP protection to integrate R&D with economic and social development.

Beijing’s policies have achieved remarkable results and exemplify nationwide leadership. Suggestions proposed to further improve policies include increasing fiscal support, establishing evaluation incentives, simplifying approvals, strengthening industry-academia ties, and cultivating intermediaries.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zihao Cao
AU  - Xinfeng Wang
AU  - Jian Ma
PY  - 2024
DA  - 2024/02/14
TI  - Based on Text Mining and Analysis of Beijing’s Achievement Transformation Policy Research
BT  - Proceedings of the 2023 5th International Conference on Economic Management and Cultural Industry (ICEMCI 2023)
PB  - Atlantis Press
SP  - 480
EP  - 485
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-368-9_56
DO  - 10.2991/978-94-6463-368-9_56
ID  - Cao2024
ER  -