Regional economic imbalance is a longstanding challenge to the holistic economic and social progress. Although scholarly work has extensively analyzed the roots and consequences of these disparities, there is an unmet need for research that examines regional economic differences from the perspective of new quality productive forces. The integration of labor's core components—objects, materials, and tools—with regional economic variations remains underexplored. Additionally, current studies inadequately address how regional disparities in technological innovation, green development, and the digital economy influence the development of new quality productive forces and the mechanisms involved. This gap in research presents an opportunity for further exploration and understanding.
This study comprehensively evaluates China's new quality productive forces (NQP), focusing on regional disparities and the synergies among three critical components: new manufacturing, new services, and new business models. NQP is increasingly recognized as a crucial driver of modern economic development, encapsulating innovations across production and service sectors while reflecting the ongoing transformation of economic activities within the country.
To conduct this evaluation, a robust measurement system is established that incorporates advanced methodologies, including the entropy-weighted technique for order preference by similarity to ideal solution (TOPSIS) method and the full permutation polygon method. These techniques facilitate a nuanced understanding of NQP levels across various regions. Additionally, the Dagum Gini coefficient and complex system synergy models are utilized to analyze both regional differences in NQP and the overall synergy within the system, capturing the complexity of productive forces variations and their implications for regional economic policies.〖HJ*3〗
The findings indicate a steady increase in NQP across China, showcasing a clear gradient distribution characterized by "East > Central > West > Northeast". This gradient underscores significant regional disparities, with the eastern region exhibiting the highest NQP levels, driven primarily by robust technological innovation and proactive industrial upgrading. In stark contrast, the western and northeastern regions experience slower progress in their NQP trajectories, highlighting the urgent need for targeted policy interventions to address developmental gaps between regions. Overall performance of NQP across China fluctuates between "average" and "good," emphasizing the necessity for resilience amid global challenges, such as the COVID-19 pandemic, which has significantly impacted economic activities. Despite the pandemic's setbacks, there is a noticeable trend of reducing regional disparities, primarily driven by the economic disparities between the more developed eastern region and the less developed central, western, and northeastern regions.
The synergy analysis reveals an increasing level of coordination across the dimensions of NQP, with the eastern region demonstrating the highest degree of synergy, particularly in the integration of new manufacturing and new services. This synergy is crucial for fostering innovation and enhancing overall productive forces. Conversely, the central and western regions require substantial improvements in effectively combining new manufacturing with new services. The northeastern region must focus on optimizing the synergy between its manufacturing capabilities and new business models to enhance productive forces.
Significant gaps in NQP between the eastern region and both the western and northeastern regions are highlighted. The analysis using the Gini coefficient reveals a gradual reduction in regional inequality; however, inter-group disparities remain pronounced. This suggests that while progress is being made, targeted policies are essential for achieving more balanced development across regions, particularly to mitigate the disparities between the leading eastern region and the underdeveloped western and northeastern areas. Moreover, although the overall synergy of the composite NQP system is improving, disparities in synergy levels persist across different regions, underscoring the need for a more integrated approach to regional development. This approach should focus on fostering collaboration among new manufacturing, services, and business models, enhancing regional productive forces and contributing to a more cohesive national economic strategy.
In conclusion, this research provides a comprehensive framework for measuring and evaluating NQP in China, identifying regional disparities and highlighting opportunities for enhancing synergy within the economic system. As China transitions into a phase of high-quality development, strengthening the synergy among new manufacturing, services, and business models will be paramount for sustaining economic growth and enhancing national competitiveness. This study contributes to the ongoing discourse on regional economic disparities and underscores the importance of strategic policymaking in fostering fair economic growth nationwide.
Shi Xiongtian
,
Yu Zhengyong
. The Measurement of New Quality Productive Forces, Regional Difference and the Analysis of Synergy Degree of Complex System[J]. Science & Technology Progress and Policy, 2025
, 42(7)
: 9
-20
.
DOI: 10.6049/kjjbydc.L2024XZ198
[1] 张姣玉,徐政.中国式现代化视域下新质生产力的理论审视、逻辑透析与实践路径[J].新疆社会科学,2024,44(1):34-45.
[2] 黄奇帆,李金波.试论发展新质生产力的内涵逻辑和战略路径[J].人民论坛,2024,33(14):6-11.
[3] 郑永年.如何科学地理解“新质生产力”[J].中国科学院院刊,2024,39(5):797-803.
[4] 孙艺.人工智能赋能新质生产力:理论逻辑、实践基础与政策路径[J].西南民族大学学报(人文社会科学版),2024,45(2):108-115.
[5] 孙亚男,刘燕伟,傅念豪,等.中国新质生产力的增长模式、区域差异与协调发展[J].财经研究,2024,50(6):4-18,33.
[6] 杨丹辉.“三新”经济赋能高质量发展[J].人民论坛,2022,31(22):90-93.
[7] 焦勇,高月鹏.数据要素赋能新质生产力涌现:供给创新与需求牵引的解释[J].新疆社会科学,2024,44(4):38-51,173.
[8] 王廷惠,李娜.新质生产力催生机制与发展路径——“技术—要素—产业”分析框架[J].广东社会科学,2024,41(4):14-25,284.
[9] 戚聿东,沈天洋.人工智能赋能新质生产力:逻辑、模式及路径[J].经济与管理研究,2024,45(7):3-17.
[10] 乔晓楠,马飞越.新质生产力发展的分析框架:理论机理、测度方法与经验证据[J].经济纵横,2024,40(4):12-28.
[11] 卢江,郭子昂,王煜萍.新质生产力发展水平、区域差异与提升路径[J].重庆大学学报(社会科学版),2024,30(3):1-17.
[12] 高帆.系统集成:发展新质生产力的基本方法论[J].改革,2024,37(7):21-32.
[13] 范晓韵,潘爱民,袁永发.算法基建赋能产业智能化发展:何以可能与何以可行[J].经济学家,2024,36(4):88-97.
[14] 孙亚男,刘燕伟,傅念豪,等.中国新质生产力的增长模式、区域差异与协调发展[J].财经研究,2024,50(6):4-18,33.
[15] 王水兴,刘勇.智能生产力:一种新质生产力[J].当代经济研究,2024,35(1):36-45.
[16] 樊胜根.发展农业领域新质生产力助力农业现代化[J].人民论坛·学术前沿,2024,13(13):87-94.
[17] 林毅夫,黄奇帆,郑永年,等.新质生产力[M].北京:中国出版集团,2023:52-69.
[18] 孙祁祥,周新发.科技创新与经济高质量发展[J].北京大学学报(哲学社会科学版),2020,57(3):140-149.
[19] 张长全,严长勇.基于“互联网+”与“工业4.0”联动机制的实证研究[J].北京工业大学学报(社会科学版),2017,17(2):58-67.
[20] 中国社会科学院工业经济研究所课题组.工业稳增长:国际经验、现实挑战与政策导向[J].中国工业经济,2022,36(2):5-26.
[21] 王凤彬,杨京雨.企业裂变式发展过程的质性元分析研究[J].管理世界,2024,40(3):180-215.
[22] 周绍森,胡德龙.保罗·罗默的新增长理论及其在分析中国经济增长因素中的应用[J].南昌大学学报(人文社会科学版),2019,50(4):71-81.
[23] 仵凤清,施雄天.我国区域高技术产业高质量发展水平测度及区域差异分析[J].科技管理研究,2023,43(18):79-89.
[24] 马才学,金莹,柯新利,等.基于全排列多边形图示法的湖北省耕地多功能强度与协调度典型模式探究[J].中国土地科学,2018,32(4):51-58.
[25] 李鹏,李美娟,陈维花.企业RD投入与产学研协同创新绩效分析[J].统计与决策,2019,35(2):183-185.