【摘要】 基于区位熵测度2009-2023年中国30个省份(不包括西藏、香港、澳门、台湾)的纺织产业集聚度，借助重心模型、标准差椭圆、 Dagum基尼系数、核密度估计等方法，结合棉花与纺织产业的关联特性及纺织产业对乡村振兴的带动作用，对中国纺织产业集聚的时空特征、区域差异和动态演化展开分析。结果表明：(1) 2009-2023年中国纺织产业集聚度保持在0.7左右，纺织产业集聚发展催生棉花需求持续增长，有效带动新疆、湖北、山东等棉花主产区农民增收，为乡村振兴提供产业支撑。华东地区集聚度最高，其次是华中、西北、华南、华北、东北、西南。华东地区(叠加市场与技术优势)和华中地区(棉花资源与劳动力结合)集聚度远高于全国平均水平，新疆(棉花主产区)所在的西北地区因棉花资源优势及政策扶持，集聚度波动上升趋势显著，且棉花种植与加工环节的就业吸纳能力持续增强，进一步拓宽了农民增收渠道。(2) 2009-2023年山东、浙江、江苏、福建、湖北和新疆是纺织产业的高值集聚省份。全国纺织产业集聚重心受棉花主产区产业布局影响拉动整体向西北迁移，空间覆盖范围持续拓展，东西向(棉花主产区与加工区联结方向)集聚趋势强化，空间分布不均衡性加剧。棉花主产区纺织产业集聚，带动当地棉花种植规模化、产业化发展，促进农民通过土地流转、务工就业等方式实现收入提升。(3) 2009-2023年7大地理区纺织产业集聚的总体差异在持续扩大，区域间差异(如棉花主产区与非主产区、加工区与贸易区差异)为总体差异的主要来源；区域内Dagum基尼系数的平均值从大到小依次为华北、西北、西南、华南、华东、华中、东北。不同区域纺织产业集聚的差异值，对应棉花需求及农民增收效应的区域不均衡性，棉花主产区依托纺织产业获得更显著的乡村振兴赋能效果。(4)中国纺织产业集聚存在显著的空间非均衡性，不同区域之间差异突出，异质性特征明显。这种异质性不仅体现在产业集聚水平上，更反映在纺织产业对棉花主产区乡村振兴的带动能力的差异上，产业集聚度高的区域能够高效地将棉花资源优势转化为农民增收和乡村发展动能。更多还原

【Abstract】 Based on the location entropy, thisstudy measured the agglomeration degree of 30 provinces(excluding Xizang, Hongkong, Macao and Taiwan) in China from 2009 to 2023. Using methods such as the center of gravity model, standard deviation ellipse, Dagum Gini coefficient, and kernel density estimation, combined with the correlation characteristics of the cotton and textile industries and the driving effect of the textile industry on rural revitalization, the spatiotemporal characteristics, regional differences and dynamic evolution of China’s textile industry agglomeration were systematically analyzed. The results showed that:(1) From 2009 to 2023, the agglomeration degree of China’s textile industry remained around 0. 7, and the agglomeration development of the textile industry continuously stimulated the growth of cotton demand, effectively driving an increase in farmers’ income in cotton-producing areas such as Xinjiang, Hubei and Shandong, and providing industrial support for rural revitalization. The agglomeration degree in the East China region was the highest, followed by the Central Chinaregion, Northwest China, South China, North China, Northeast China and Southwest China. The agglomeration degree in the East China region(with market and technological advantages) and the Central China region(with the combination of cotton resources and labor force) was much higher than the national average level. Xinjiang, located in the Northwest region(a major cotton-producing area), showed a significant upward trend in agglomeration degree due to its cotton resource advantages and policy support. The employment absorption capacity of cotton planting and processing links continued to strengthen, further broadening farmers’ income channels.(2) From 2009 to 2023, Shandong, Zhejiang, Jiangsu, Fujian, Hubei and Xinjiang were high-value agglomeration provinces of the textile industry. The agglomeration center of the national textile industry driven by the industrial layout of cotton-producing areas. Overall, it shifted northwest ward, with spatial coverage continuously expanding. The east-west(direction connecting cotton-producing areas and processing areas) agglomeration trend strengthened, and the spatial distribution imbalance intensified. The agglomeration of the textile industry in cotton-producing areashad driven the large-scale and industrialized development of cotton planting, promoting farmers’ income increase through land transfer, employment and other means.(3) From 2009 to 2023, the overall differences in textile industry agglomeration among the seven major geographical regions continued to expand. The regional differences(such as those between cotton-producing and non-producing areas, and between processing and trade areas) were the main source of overall differences. The average intra-regional Dagum Gini coefficient showed a distribution pattern of North China > Northwest China > Southwest China > South China > East China > Central China > Northeast China. The differences in textile industry agglomeration among different regions corresponded to the regional imbalance of cotton demand and farmers’ income increase effects, and the cotton-producing areas relied on the textile industry to achieve more significant rural revitalization empowerment effects.(4) There was a significant spatial non-equilibrium in China’s textile industry agglomeration, with prominent differences between regions and obvious heterogeneity characteristics. This heterogeneity was evident not only in the level of agglomeration but also in the varying capacity of the textile industry to drive rural revitalization in cotton-producing areas. Regions with higher agglomeration could more efficiently transform cotton resource advantages into momentum for farmers’ income growth and rural development.更多还原