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Quantitative Evaluation of High-Tech Industry Policies Based on the PMC-Index Model: A Case Study of China’s Beijing-Tianjin-Hebei Region

Author

Listed:
  • Yiwen Liu

    (School of Management, Tianjin University of Technology, Tianjin 300384, China)

  • Jian Li

    (School of Management, Tianjin University of Technology, Tianjin 300384, China
    College of Management and Economics, Tianjin University, Tianjin 300072, China)

  • Yi Xu

    (School of Management, Tianjin University of Technology, Tianjin 300384, China)

Abstract

High-tech industrial agglomeration plays a significant role in regional sustainable development. Local governments have issued many industrial policies to accelerate the development of high-tech industries in China. Evaluating high-tech industry policies from the perspective of regional industrial synergy can prevent problems in policy implementation and promote the industrial synergy in a region. For this purpose, taking China’s Beijing-Tianjin-Hebei (BTH) region as a case, we evaluate seven policies governing the high-tech industry in this region by using the approach which integrates the policy modeling consistency index (PMC-Index) model and text mining. We propose an evaluation system with consideration of regional industrial synergy, which is based on the PMC-Index model. The results show that the lowest PMC-Index value of the seven policies is 5.30, the highest is 8.17, and the average is 6.67. Among the policies, four are of excellent or perfect grade and relatively comprehensive; three are of acceptable grade and relatively insufficient. The overall designs of the high-tech industrial policies are reasonable but there is still much room for improvement. According to the average scores of the main indicators, the policies function relatively poorly in terms of policy release agency, policy timeliness, policy type and policy receptor. The optimizations for the shortcomings of each policy are also suggested. This study may not only provide some enlightenment to policymakers, but also provide a supplement for the policy evaluation field.

Suggested Citation

  • Yiwen Liu & Jian Li & Yi Xu, 2022. "Quantitative Evaluation of High-Tech Industry Policies Based on the PMC-Index Model: A Case Study of China’s Beijing-Tianjin-Hebei Region," Sustainability, MDPI, vol. 14(15), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9338-:d:875779
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    2. Boyao Zhang & Liping Xu, 2025. "Research on Policy Optimization for Coordinated Development of Digital Content Industry in China’s Yangtze River Delta Region—Based on the PMC-Index Model," SAGE Open, , vol. 15(3), pages 21582440251, September.
    3. Shuigen Hu & Xianbo Wang, 2025. "A Text-Mining-Based Evaluation of Data Element Policies in China: Integrating the LDA and PMC Models in the Context of Green Development," Sustainability, MDPI, vol. 17(15), pages 1-36, July.
    4. Song, Chenchen & Zhao, Ziwen & Liu, Zhengguang, 2025. "Evaluation of regional and temporal dynamics in CCUS-hydrogen development policy pathways: A data-driven framework," Renewable Energy, Elsevier, vol. 239(C).
    5. Gaofei Wang & Yi Yang, 2024. "Quantitative Evaluation of Digital Economy Policy in Heilongjiang Province of China Based on the PMC-AE Index Model," SAGE Open, , vol. 14(1), pages 21582440241, March.
    6. Riya Kumbukattu Alex & Preetha Sadasivan & Thomas Maes & Suja Purushothaman Devipriya, 2026. "Quantitative evaluation of global microbead policies: a PMC index approach towards microplastic pollution," Policy Sciences, Springer;Society of Policy Sciences, vol. 59(1), pages 53-76, March.
    7. Ziyi Wang & Pu Han & Wenqi Chen, 2025. "Unravelling the combination of medical and elderly care in China: a comprehensive policy analysis," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 12(1), pages 1-17, December.

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