新质生产力驱动纺织服装企业高质量发展组态效应研究OA

In the context of intensifying global manufacturing competition and economic restructuring,China's textile and apparel industry,a traditional pillar of the national economy,faces severe challenges in upgrading and transforming.Although previous studies focused on the drivers of high-quality development in the industry,they mostly limited themselves to single-factor analysis or linear causal evolution,failing to fully reveal the complexity of multi-factor interactions during industrial transformation.In this context,exploring the innovative theory of new quality productive forces becomes an urgent need and a key path to overcome development bottlenecks and lead the industry to achieve high-quality advancement. The article constructed a theoretical framework based on the technology-factor-industry(TFI)dimension to systematically deconstruct new quality productive forces and employed dynamic QCA using 51 listed textile and apparel enterprises from 2020 to 2024 as a sample.It adopted total factor productivity as a measure of high-quality development and tested the TFI framework using six antecedent variables:knowledge intensity,R&D capability,digital elements,resource allocation capability,enterprise transformation,and value chain upgrading.Necessity analysis showed that no single factor could constitute a necessary condition for high-quality development.Subsequent configurational analysis identified three different paths driving high-quality development:knowledge-driven,digital-empowered,and resource-optimized types.Further inter-and intra-group analysis showed that the three configurational paths had no significant time effects.The overall consistency fluctuations in 2022-2023 were related to policy changes and public health events.Notably,the textile and apparel industry exhibited an evolutionary trend from knowledge-driven to digital-empowered types between 2020 and 2024.Additionally,no significant case effects were observed,indicating that these paths apply to most enterprises in different sub-sectors within the industry. The systematic empirical research on how new quality productive forces drive high-quality development in the textile and apparel industry reveals unique high-quality development paths distinct from those in strategic emerging industries and the broader manufacturing sector.By combining dynamic QCA with panel data,it captures the complex nonlinear relationships among multiple factors,providing a more detailed understanding than traditional linear regression methods.The research findings differ from the traditional assumption that traditional manufacturing sectors must have high R&D investment,demonstrating how textile and apparel enterprises achieve high-quality development through diverse combinations of knowledge,digital elements,and resource allocation.In practical implications,enterprises should choose development paths matching their resource endowments,and governments should consider data element institutional frameworks,industry-specific support strategies,and enhancing industry-academia-research cooperation mechanisms.