The spatial distribution of high-tech textile firms directly affects the effectiveness of industrial agglomeration, technological diffusion, and competitiveness enhancement. Using provincial panel data (2011–2023), this study adopts centroid migration analysis, Gini coefficient decomposition, and spatial Durbin modeling to systematically explore the spatiotemporal evolution and underlying determinants of China’s high-tech textile firms. Reportedly, there is a pronounced two-stage growth trajectory, characterised by rapid expansion from 2012 to 2017 and a marked slowdown after 2018, including negative growth during and following the COVID-19 pandemic. Further econometric evidence from the spatial Durbin model highlights land prices, industrial scale, market potential, human capital, and technological innovation capacity as key factors exerting significant spatial spillover effects. Conversely, wage levels and regional economic development also affect enterprise location decisions but exhibit comparatively weaker spatial spillovers. This study contributes to the interdisciplinary discourse bridging economic geography and business management by clarifying the multifaceted drivers of industrial spatial distribution. Thus, the findings offer actionable insights and policy guidance for optimising textile industry layouts and regional economic coordination under China’s dual-circulation development framework, with broader implications for emerging economies.
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