Measurement and Dynamic Evolution Analysis of New Quality Productive Forces in Listed Companies within Western China’s Manufacturing Industry

西部地区制造业转型升级在不断推进,如何有效提升新质生产力已成为推动区域经济高质量发展的关键课题。本文依据新质生产力的理论内涵,尝试利用超效率EBM-GML模型测度2011~2022年西部地区134家A股制造业上市公司的新质生产力,揭示其动态演变规律。研究发现:西部制造业上市公司的新质生产力整体呈上升趋势,但增长过程中存在阶段性波动。其次,2019年前技术效率是新质生产力增长的主要动力,而2019年后技术进步成为核心驱动因素。Markov链分析表明,西部制造业企业新质生产力的动态演进呈现较强的稳定性,中等水平企业则更倾向于向更高水平迈进。提升西部地区制造业新质生产力的关键在于加强政策支持、优化效率与创新协同、建立企业梯度培育体系。The transformation and upgrading of the manufacturing industry in the western region of China are continuously advancing, and how to effectively enhance new quality productive forces (NQPF) has become a key issue in promoting high-quality regional economic development. Based on the theoretical connotation of NQPF, this paper attempts to measure the NQPF of 134 Chinese A-share listed manufacturing companies in the western region from 2011 to 2022 using the super-efficiency EBM-GML model, revealing their dynamic evolution patterns. The findings indicate that the NQPF of manufacturing listed companies in the western China generally show an upward trend, though with fluctuations during the growth process. Secondly, before 2019, technical efficiency was the main driver of the growth of NQPF, while technological progress became the core driving factor after 2019. Markov chain analysis reveals that the dynamic evolution of NQPF in western manufacturing enterprises exhibits strong stability, with mid-level enterprises more inclined to advance to higher levels. The key to enhancing NQPF in western China’s manufacturing industry lies in strengthening policy support, optimizing the synergy between efficiency and innovation, and establishing a gradient cultivation system for enterprises.

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Publication Details

Journal
Statistics and Applications
Published
2025-01-01
DOI
https://doi.org/10.12677/sa.2025.145131
Primary Topic
Industrial Technology and Control Systems
Type
article
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article

Measurement and Dynamic Evolution Analysis of New Quality Productive Forces in Listed Companies within Western China’s Manufacturing Industry

乙萍 蔡
Statistics and Applications
Industrial Technology and Control Systems
article

Measurement and Dynamic Evolution Analysis of New Quality Productive Forces in Listed Companies within Western China’s Manufacturing Industry

乙萍 蔡
article en

Abstract

西部地区制造业转型升级在不断推进,如何有效提升新质生产力已成为推动区域经济高质量发展的关键课题。本文依据新质生产力的理论内涵,尝试利用超效率EBM-GML模型测度2011~2022年西部地区134家A股制造业上市公司的新质生产力,揭示其动态演变规律。研究发现:西部制造业上市公司的新质生产力整体呈上升趋势,但增长过程中存在阶段性波动。其次,2019年前技术效率是新质生产力增长的主要动力,而2019年后技术进步成为核心驱动因素。Markov链分析表明,西部制造业企业新质生产力的动态演进呈现较强的稳定性,中等水平企业则更倾向于向更高水平迈进。提升西部地区制造业新质生产力的关键在于加强政策支持、优化效率与创新协同、建立企业梯度培育体系。The transformation and upgrading of the manufacturing industry in the western region of China are continuously advancing, and how to effectively enhance new quality productive forces (NQPF) has become a key issue in promoting high-quality regional economic development. Based on the theoretical connotation of NQPF, this paper attempts to measure the NQPF of 134 Chinese A-share listed manufacturing companies in the western region from 2011 to 2022 using the super-efficiency EBM-GML model, revealing their dynamic evolution patterns. The findings indicate that the NQPF of manufacturing listed companies in the western China generally show an upward trend, though with fluctuations during the growth process. Secondly, before 2019, technical efficiency was the main driver of the growth of NQPF, while technological progress became the core driving factor after 2019. Markov chain analysis reveals that the dynamic evolution of NQPF in western manufacturing enterprises exhibits strong stability, with mid-level enterprises more inclined to advance to higher levels. The key to enhancing NQPF in western China’s manufacturing industry lies in strengthening policy support, optimizing the synergy between efficiency and innovation, and establishing a gradient cultivation system for enterprises.

Statistics and ApplicationsVol. 14(05)
Decent work and economic growth
Openalex Percentile: Top 87%
Industrial Technology and Control Systems
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